diff --git a/crates/goose-cli/src/commands/configure.rs b/crates/goose-cli/src/commands/configure.rs
index 407d755d748c..b6ae23df2674 100644
--- a/crates/goose-cli/src/commands/configure.rs
+++ b/crates/goose-cli/src/commands/configure.rs
@@ -576,7 +576,7 @@ pub async fn configure_provider_dialog() -> anyhow::Result<bool> {
     let models_res = {
         let temp_model_config = ModelConfig::new(&provider_meta.default_model)?;
         let temp_provider = create(provider_name, temp_model_config).await?;
-        temp_provider.fetch_supported_models().await
+        temp_provider.fetch_recommended_models().await
     };
     spin.stop(style("Model fetch complete").green());
 
diff --git a/crates/goose-server/src/routes/config_management.rs b/crates/goose-server/src/routes/config_management.rs
index 3b4848bf5a06..c70a1bb9db01 100644
--- a/crates/goose-server/src/routes/config_management.rs
+++ b/crates/goose-server/src/routes/config_management.rs
@@ -392,7 +392,9 @@ pub async fn get_provider_models(
         .await
         .map_err(|_| StatusCode::INTERNAL_SERVER_ERROR)?;
 
-    match provider.fetch_supported_models().await {
+    let models_result = provider.fetch_recommended_models().await;
+
+    match models_result {
         Ok(Some(models)) => Ok(Json(models)),
         Ok(None) => Ok(Json(Vec::new())),
         Err(provider_error) => {
diff --git a/crates/goose/canonical_mapping_report.json b/crates/goose/canonical_mapping_report.json
new file mode 100644
index 000000000000..79c03c3b9e8c
--- /dev/null
+++ b/crates/goose/canonical_mapping_report.json
@@ -0,0 +1,4413 @@
+{
+  "timestamp": "2025-11-12T18:31:21.379526+00:00",
+  "unmapped_models": [
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+      "provider": "openai",
+      "model": "ada:ft-square-2023-01-20-06-09-37"
+    },
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+    },
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+      "provider": "openai",
+      "model": "ada:ft-square-2023-02-03-23-17-02"
+    },
+    {
+      "provider": "openai",
+      "model": "ada:ft-square-2023-02-03-23-39-19"
+    },
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+    },
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+        "canonical_model": "openai/o3-mini-high",
+        "verified": true
+      },
+      {
+        "provider_model": "openai/o3-pro",
+        "canonical_model": "openai/o3-pro",
+        "verified": true
+      },
+      {
+        "provider_model": "openai/o4-mini",
+        "canonical_model": "openai/o4-mini",
+        "verified": true
+      },
+      {
+        "provider_model": "openai/o4-mini-deep-research",
+        "canonical_model": "openai/o4-mini-deep-research",
+        "verified": true
+      },
+      {
+        "provider_model": "openai/o4-mini-high",
+        "canonical_model": "openai/o4-mini-high",
+        "verified": true
+      }
+    ],
+    "anthropic": [
+      {
+        "provider_model": "claude-3-5-haiku-20241022",
+        "canonical_model": "anthropic/claude-3.5-haiku",
+        "verified": true
+      },
+      {
+        "provider_model": "claude-3-7-sonnet-20250219",
+        "canonical_model": "anthropic/claude-3.7-sonnet",
+        "verified": true
+      },
+      {
+        "provider_model": "claude-3-haiku-20240307",
+        "canonical_model": "anthropic/claude-3-haiku",
+        "verified": true
+      },
+      {
+        "provider_model": "claude-3-opus-20240229",
+        "canonical_model": "anthropic/claude-3-opus",
+        "verified": true
+      },
+      {
+        "provider_model": "claude-haiku-4-5-20251001",
+        "canonical_model": "anthropic/claude-haiku",
+        "verified": true
+      },
+      {
+        "provider_model": "claude-opus-4-1-20250805",
+        "canonical_model": "anthropic/claude-opus",
+        "verified": true
+      },
+      {
+        "provider_model": "claude-opus-4-20250514",
+        "canonical_model": "anthropic/claude-opus",
+        "verified": true
+      },
+      {
+        "provider_model": "claude-sonnet-4-20250514",
+        "canonical_model": "anthropic/claude-sonnet",
+        "verified": true
+      },
+      {
+        "provider_model": "claude-sonnet-4-5-20250929",
+        "canonical_model": "anthropic/claude-sonnet",
+        "verified": true
+      }
+    ],
+    "openai": [
+      {
+        "provider_model": "chatgpt-4o-latest",
+        "canonical_model": "openai/chatgpt-4o-latest",
+        "verified": true
+      },
+      {
+        "provider_model": "gpt-3.5-turbo",
+        "canonical_model": "openai/gpt-3.5-turbo",
+        "verified": true
+      },
+      {
+        "provider_model": "gpt-3.5-turbo-0125",
+        "canonical_model": "openai/gpt-3.5-turbo",
+        "verified": true
+      },
+      {
+        "provider_model": "gpt-3.5-turbo-1106",
+        "canonical_model": "openai/gpt-3.5-turbo",
+        "verified": true
+      },
+      {
+        "provider_model": "gpt-3.5-turbo-16k",
+        "canonical_model": "openai/gpt-3.5-turbo-16k",
+        "verified": true
+      },
+      {
+        "provider_model": "gpt-3.5-turbo-instruct",
+        "canonical_model": "openai/gpt-3.5-turbo-instruct",
+        "verified": true
+      },
+      {
+        "provider_model": "gpt-3.5-turbo-instruct-0914",
+        "canonical_model": "openai/gpt-3.5-turbo-instruct",
+        "verified": true
+      },
+      {
+        "provider_model": "gpt-4",
+        "canonical_model": "openai/gpt",
+        "verified": true
+      },
+      {
+        "provider_model": "gpt-4-0125-preview",
+        "canonical_model": "openai/gpt",
+        "verified": true
+      },
+      {
+        "provider_model": "gpt-4-0314",
+        "canonical_model": "openai/gpt",
+        "verified": true
+      },
+      {
+        "provider_model": "gpt-4-0613",
+        "canonical_model": "openai/gpt",
+        "verified": true
+      },
+      {
+        "provider_model": "gpt-4-1106-preview",
+        "canonical_model": "openai/gpt",
+        "verified": true
+      },
+      {
+        "provider_model": "gpt-4-turbo",
+        "canonical_model": "openai/gpt-4-turbo",
+        "verified": true
+      },
+      {
+        "provider_model": "gpt-4-turbo-2024-04-09",
+        "canonical_model": "openai/gpt-4-turbo",
+        "verified": true
+      },
+      {
+        "provider_model": "gpt-4-turbo-preview",
+        "canonical_model": "openai/gpt-4-turbo",
+        "verified": true
+      },
+      {
+        "provider_model": "gpt-4.1",
+        "canonical_model": "openai/gpt",
+        "verified": true
+      },
+      {
+        "provider_model": "gpt-4.1-2025-04-14",
+        "canonical_model": "openai/gpt",
+        "verified": true
+      },
+      {
+        "provider_model": "gpt-4.1-mini",
+        "canonical_model": "openai/gpt-4.1-mini",
+        "verified": true
+      },
+      {
+        "provider_model": "gpt-4.1-mini-2025-04-14",
+        "canonical_model": "openai/gpt-4.1-mini",
+        "verified": true
+      },
+      {
+        "provider_model": "gpt-4.1-nano",
+        "canonical_model": "openai/gpt-4.1-nano",
+        "verified": true
+      },
+      {
+        "provider_model": "gpt-4.1-nano-2025-04-14",
+        "canonical_model": "openai/gpt-4.1-nano",
+        "verified": true
+      },
+      {
+        "provider_model": "gpt-4o",
+        "canonical_model": "openai/gpt-4o",
+        "verified": true
+      },
+      {
+        "provider_model": "gpt-4o-2024-05-13",
+        "canonical_model": "openai/gpt-4o",
+        "verified": true
+      },
+      {
+        "provider_model": "gpt-4o-2024-08-06",
+        "canonical_model": "openai/gpt-4o",
+        "verified": true
+      },
+      {
+        "provider_model": "gpt-4o-2024-11-20",
+        "canonical_model": "openai/gpt-4o",
+        "verified": true
+      },
+      {
+        "provider_model": "gpt-4o-audio-preview",
+        "canonical_model": "openai/gpt-4o-audio",
+        "verified": true
+      },
+      {
+        "provider_model": "gpt-4o-audio-preview-2024-10-01",
+        "canonical_model": "openai/gpt-4o-audio",
+        "verified": true
+      },
+      {
+        "provider_model": "gpt-4o-audio-preview-2024-12-17",
+        "canonical_model": "openai/gpt-4o-audio",
+        "verified": true
+      },
+      {
+        "provider_model": "gpt-4o-audio-preview-2025-06-03",
+        "canonical_model": "openai/gpt-4o-audio",
+        "verified": true
+      },
+      {
+        "provider_model": "gpt-4o-mini",
+        "canonical_model": "openai/gpt-4o-mini",
+        "verified": true
+      },
+      {
+        "provider_model": "gpt-4o-mini-2024-07-18",
+        "canonical_model": "openai/gpt-4o-mini",
+        "verified": true
+      },
+      {
+        "provider_model": "gpt-4o-mini-search-preview",
+        "canonical_model": "openai/gpt-4o-mini-search",
+        "verified": true
+      },
+      {
+        "provider_model": "gpt-4o-mini-search-preview-2025-03-11",
+        "canonical_model": "openai/gpt-4o-mini-search",
+        "verified": true
+      },
+      {
+        "provider_model": "gpt-4o-search-preview",
+        "canonical_model": "openai/gpt-4o-search",
+        "verified": true
+      },
+      {
+        "provider_model": "gpt-4o-search-preview-2025-03-11",
+        "canonical_model": "openai/gpt-4o-search",
+        "verified": true
+      },
+      {
+        "provider_model": "gpt-5",
+        "canonical_model": "openai/gpt",
+        "verified": true
+      },
+      {
+        "provider_model": "gpt-5-2025-08-07",
+        "canonical_model": "openai/gpt",
+        "verified": true
+      },
+      {
+        "provider_model": "gpt-5-codex",
+        "canonical_model": "openai/gpt-5-codex",
+        "verified": true
+      },
+      {
+        "provider_model": "gpt-5-mini",
+        "canonical_model": "openai/gpt-5-mini",
+        "verified": true
+      },
+      {
+        "provider_model": "gpt-5-mini-2025-08-07",
+        "canonical_model": "openai/gpt-5-mini",
+        "verified": true
+      },
+      {
+        "provider_model": "gpt-5-nano",
+        "canonical_model": "openai/gpt-5-nano",
+        "verified": true
+      },
+      {
+        "provider_model": "gpt-5-nano-2025-08-07",
+        "canonical_model": "openai/gpt-5-nano",
+        "verified": true
+      },
+      {
+        "provider_model": "gpt-5-pro",
+        "canonical_model": "openai/gpt-5-pro",
+        "verified": true
+      },
+      {
+        "provider_model": "gpt-5-pro-2025-10-06",
+        "canonical_model": "openai/gpt-5-pro",
+        "verified": true
+      },
+      {
+        "provider_model": "o1",
+        "canonical_model": "openai/o1",
+        "verified": true
+      },
+      {
+        "provider_model": "o1-2024-12-17",
+        "canonical_model": "openai/o1",
+        "verified": true
+      },
+      {
+        "provider_model": "o1-pro",
+        "canonical_model": "openai/o1-pro",
+        "verified": true
+      },
+      {
+        "provider_model": "o1-pro-2025-03-19",
+        "canonical_model": "openai/o1-pro",
+        "verified": true
+      },
+      {
+        "provider_model": "o3",
+        "canonical_model": "openai/o3",
+        "verified": true
+      },
+      {
+        "provider_model": "o3-2025-04-16",
+        "canonical_model": "openai/o3",
+        "verified": true
+      },
+      {
+        "provider_model": "o3-deep-research",
+        "canonical_model": "openai/o3-deep-research",
+        "verified": true
+      },
+      {
+        "provider_model": "o3-deep-research-2025-06-26",
+        "canonical_model": "openai/o3-deep-research",
+        "verified": true
+      },
+      {
+        "provider_model": "o3-mini",
+        "canonical_model": "openai/o3-mini",
+        "verified": true
+      },
+      {
+        "provider_model": "o3-mini-2025-01-31",
+        "canonical_model": "openai/o3-mini",
+        "verified": true
+      },
+      {
+        "provider_model": "o3-pro",
+        "canonical_model": "openai/o3-pro",
+        "verified": true
+      },
+      {
+        "provider_model": "o3-pro-2025-06-10",
+        "canonical_model": "openai/o3-pro",
+        "verified": true
+      },
+      {
+        "provider_model": "o4-mini",
+        "canonical_model": "openai/o4-mini",
+        "verified": true
+      },
+      {
+        "provider_model": "o4-mini-2025-04-16",
+        "canonical_model": "openai/o4-mini",
+        "verified": true
+      },
+      {
+        "provider_model": "o4-mini-deep-research",
+        "canonical_model": "openai/o4-mini-deep-research",
+        "verified": true
+      },
+      {
+        "provider_model": "o4-mini-deep-research-2025-06-26",
+        "canonical_model": "openai/o4-mini-deep-research",
+        "verified": true
+      }
+    ],
+    "google": [
+      {
+        "provider_model": "gemini-2.0-flash",
+        "canonical_model": "google/gemini-2.0-flash",
+        "verified": true
+      },
+      {
+        "provider_model": "gemini-2.0-flash-001",
+        "canonical_model": "google/gemini-2.0-flash",
+        "verified": true
+      },
+      {
+        "provider_model": "gemini-2.0-flash-exp",
+        "canonical_model": "google/gemini-2.0-flash",
+        "verified": true
+      },
+      {
+        "provider_model": "gemini-2.0-flash-lite",
+        "canonical_model": "google/gemini-2.0-flash-lite",
+        "verified": true
+      },
+      {
+        "provider_model": "gemini-2.0-flash-lite-001",
+        "canonical_model": "google/gemini-2.0-flash-lite",
+        "verified": true
+      },
+      {
+        "provider_model": "gemini-2.0-flash-lite-preview",
+        "canonical_model": "google/gemini-2.0-flash-lite",
+        "verified": true
+      },
+      {
+        "provider_model": "gemini-2.0-flash-lite-preview-02-05",
+        "canonical_model": "google/gemini-2.0-flash-lite",
+        "verified": true
+      },
+      {
+        "provider_model": "gemini-2.5-flash",
+        "canonical_model": "google/gemini-2.5-flash",
+        "verified": true
+      },
+      {
+        "provider_model": "gemini-2.5-flash-image",
+        "canonical_model": "google/gemini-2.5-flash-image",
+        "verified": true
+      },
+      {
+        "provider_model": "gemini-2.5-flash-image-preview",
+        "canonical_model": "google/gemini-2.5-flash-image",
+        "verified": true
+      },
+      {
+        "provider_model": "gemini-2.5-flash-lite",
+        "canonical_model": "google/gemini-2.5-flash-lite",
+        "verified": true
+      },
+      {
+        "provider_model": "gemini-2.5-flash-lite-preview-06-17",
+        "canonical_model": "google/gemini-2.5-flash-lite",
+        "verified": true
+      },
+      {
+        "provider_model": "gemini-2.5-flash-lite-preview-09-2025",
+        "canonical_model": "google/gemini-2.5-flash-lite",
+        "verified": true
+      },
+      {
+        "provider_model": "gemini-2.5-flash-preview-05-20",
+        "canonical_model": "google/gemini-2.5-flash",
+        "verified": true
+      },
+      {
+        "provider_model": "gemini-2.5-flash-preview-09-2025",
+        "canonical_model": "google/gemini-2.5-flash",
+        "verified": true
+      },
+      {
+        "provider_model": "gemini-2.5-pro",
+        "canonical_model": "google/gemini-2.5-pro",
+        "verified": true
+      },
+      {
+        "provider_model": "gemini-2.5-pro-preview-03-25",
+        "canonical_model": "google/gemini-2.5-pro",
+        "verified": true
+      },
+      {
+        "provider_model": "gemini-2.5-pro-preview-05-06",
+        "canonical_model": "google/gemini-2.5-pro",
+        "verified": true
+      },
+      {
+        "provider_model": "gemini-2.5-pro-preview-06-05",
+        "canonical_model": "google/gemini-2.5-pro",
+        "verified": true
+      },
+      {
+        "provider_model": "gemma-3-12b-it",
+        "canonical_model": "google/gemma-3-12b-it",
+        "verified": true
+      },
+      {
+        "provider_model": "gemma-3-27b-it",
+        "canonical_model": "google/gemma-3-27b-it",
+        "verified": true
+      },
+      {
+        "provider_model": "gemma-3-4b-it",
+        "canonical_model": "google/gemma-3-4b-it",
+        "verified": true
+      },
+      {
+        "provider_model": "gemma-3n-e4b-it",
+        "canonical_model": "google/gemma-3n-e4b-it",
+        "verified": true
+      }
+    ],
+    "databricks": [],
+    "tetrate": []
+  },
+  "model_counts": {
+    "openrouter": 217,
+    "anthropic": 9,
+    "openai": 625,
+    "tetrate": 0,
+    "databricks": 143,
+    "google": 50
+  },
+  "canonical_models_used": [
+    "openai/gpt-5-image-mini",
+    "google/gemini-2.5-flash-image",
+    "openai/gpt-4.1-mini",
+    "openai/o4-mini-high",
+    "google/gemini-2.5-flash-lite",
+    "openai/gpt-4-turbo",
+    "anthropic/claude-sonnet",
+    "openai/gpt-4o-mini",
+    "google/gemma-3-4b-it",
+    "openai/gpt-3.5-turbo-instruct",
+    "openai/gpt-3.5-turbo-16k",
+    "google/gemma-3n-e4b-it",
+    "anthropic/claude-3-opus",
+    "google/gemma-3-12b-it",
+    "openai/o3",
+    "openai/gpt-oss-safeguard-20b",
+    "anthropic/claude-3.5-haiku",
+    "openai/o1-pro",
+    "openai/o3-mini",
+    "openai/chatgpt-4o-latest",
+    "openai/gpt-3.5-turbo",
+    "anthropic/claude-3-haiku",
+    "openai/gpt",
+    "openai/gpt-5-codex",
+    "openai/o3-deep-research",
+    "anthropic/claude-3.7-sonnet:thinking",
+    "anthropic/claude-haiku",
+    "anthropic/claude-3.7-sonnet",
+    "openai/gpt-4.1-nano",
+    "openai/o4-mini",
+    "openai/o3-mini-high",
+    "openai/o4-mini-deep-research",
+    "openai/gpt-oss-120b",
+    "openai/gpt-4o-audio",
+    "openai/o3-pro",
+    "openai/gpt-5-image",
+    "google/gemini-2.5-flash",
+    "google/gemma-3-27b-it",
+    "openai/gpt-oss-20b",
+    "google/gemini-2.5-pro",
+    "anthropic/claude-3.5-sonnet",
+    "openai/o1",
+    "openai/gpt-oss-120b:exacto",
+    "openai/gpt-4o-mini-search",
+    "openai/gpt-5-pro",
+    "openai/gpt-4o",
+    "openai/codex-mini",
+    "google/gemini-2.0-flash-lite",
+    "anthropic/claude-opus",
+    "openai/gpt-4o:extended",
+    "google/gemini-2.0-flash",
+    "openai/gpt-5-mini",
+    "openai/gpt-5-nano",
+    "openai/gpt-4o-search"
+  ]
+}
\ No newline at end of file
diff --git a/crates/goose/examples/build_canonical_models.rs b/crates/goose/examples/build_canonical_models.rs
new file mode 100644
index 000000000000..36f563bd62bc
--- /dev/null
+++ b/crates/goose/examples/build_canonical_models.rs
@@ -0,0 +1,254 @@
+/// Build canonical models from OpenRouter API
+///
+/// This script fetches models from OpenRouter and converts them to canonical format.
+/// Usage:
+///   cargo run --example build_canonical_models
+///
+use anyhow::{Context, Result};
+use goose::providers::canonical::{
+    canonical_name, CanonicalModel, CanonicalModelRegistry, Pricing,
+};
+use serde_json::Value;
+use std::collections::HashMap;
+
+const OPENROUTER_API_URL: &str = "https://openrouter.ai/api/v1/models";
+const ALLOWED_PROVIDERS: &[&str] = &[
+    "anthropic",
+    "google",
+    "openai",
+    "meta-llama",
+    "mistralai",
+    "x-ai",
+    "deepseek",
+    "cohere",
+    "ai21",
+    "qwen",
+];
+
+#[tokio::main]
+async fn main() -> Result<()> {
+    println!("Fetching models from OpenRouter API...");
+
+    let client = reqwest::Client::new();
+    let response = client
+        .get(OPENROUTER_API_URL)
+        .header("User-Agent", "goose/canonical-builder")
+        .send()
+        .await
+        .context("Failed to fetch from OpenRouter API")?;
+
+    let json: Value = response
+        .json()
+        .await
+        .context("Failed to parse OpenRouter response")?;
+
+    let models = json["data"]
+        .as_array()
+        .context("Expected 'data' array in OpenRouter response")?
+        .clone();
+
+    println!("Processing {} models from OpenRouter...", models.len());
+
+    // First pass: Group models by canonical ID and track the one with shortest name
+    let mut canonical_groups: HashMap<String, &Value> = HashMap::new();
+    let mut shortest_names: HashMap<String, String> = HashMap::new();
+
+    for model in &models {
+        let id = model["id"].as_str().unwrap();
+        let name = model["name"].as_str().context("Model missing id field")?;
+
+        // Skip OpenRouter-specific pricing variants (:free, :nitro)
+        // Keep :extended since it has different context length
+        if id.contains(":free") || id.contains(":nitro") {
+            continue;
+        }
+
+        let canonical_id = canonical_name("openrouter", id);
+
+        let provider = canonical_id.split('/').next().unwrap_or("");
+        if !ALLOWED_PROVIDERS.contains(&provider) {
+            continue;
+        }
+
+        let prompt_cost = model
+            .get("pricing")
+            .and_then(|p| p.get("prompt"))
+            .and_then(|v| v.as_str())
+            .and_then(|s| s.parse::<f64>().ok())
+            .unwrap_or(0.0);
+
+        let completion_cost = model
+            .get("pricing")
+            .and_then(|p| p.get("completion"))
+            .and_then(|v| v.as_str())
+            .and_then(|s| s.parse::<f64>().ok())
+            .unwrap_or(0.0);
+
+        let has_paid_pricing = prompt_cost > 0.0 || completion_cost > 0.0;
+
+        if let Some(existing_model) = canonical_groups.get(&canonical_id) {
+            let existing_name = shortest_names.get(&canonical_id).unwrap();
+
+            let existing_prompt = existing_model
+                .get("pricing")
+                .and_then(|p| p.get("prompt"))
+                .and_then(|v| v.as_str())
+                .and_then(|s| s.parse::<f64>().ok())
+                .unwrap_or(0.0);
+
+            let existing_completion = existing_model
+                .get("pricing")
+                .and_then(|p| p.get("completion"))
+                .and_then(|v| v.as_str())
+                .and_then(|s| s.parse::<f64>().ok())
+                .unwrap_or(0.0);
+
+            let existing_has_paid = existing_prompt > 0.0 || existing_completion > 0.0;
+
+            let should_replace = if has_paid_pricing != existing_has_paid {
+                has_paid_pricing // Prefer the one with paid pricing
+            } else {
+                name.len() < existing_name.len() // Both same pricing tier, prefer shorter name
+            };
+
+            if should_replace {
+                println!(
+                    "  Updating {} from '{}' (paid: {}) to '{}' (paid: {})",
+                    canonical_id,
+                    existing_model["id"].as_str().unwrap(),
+                    existing_has_paid,
+                    id,
+                    has_paid_pricing
+                );
+                shortest_names.insert(canonical_id.clone(), name.to_string());
+                canonical_groups.insert(canonical_id, model);
+            }
+        } else {
+            println!(
+                "  Adding: {} (from {}, paid: {})",
+                canonical_id, id, has_paid_pricing
+            );
+            shortest_names.insert(canonical_id.clone(), name.to_string());
+            canonical_groups.insert(canonical_id, model);
+        }
+    }
+
+    // Filter out beta/preview variants if non-beta version exists
+    let beta_suffixes = ["-beta", "-preview", "-alpha"];
+    let mut to_remove = Vec::new();
+
+    for canonical_id in canonical_groups.keys() {
+        for suffix in &beta_suffixes {
+            if canonical_id.ends_with(suffix) {
+                // Check if non-beta version exists
+                let base_id = canonical_id.strip_suffix(suffix).unwrap();
+                if canonical_groups.contains_key(base_id) {
+                    println!(
+                        "  Filtering out {} (non-beta version {} exists)",
+                        canonical_id, base_id
+                    );
+                    to_remove.push(canonical_id.clone());
+                    break;
+                }
+            }
+        }
+    }
+
+    for id in to_remove {
+        canonical_groups.remove(&id);
+        shortest_names.remove(&id);
+    }
+
+    // Second pass: Build the registry with the selected models
+    let mut registry = CanonicalModelRegistry::new();
+
+    for (canonical_id, model) in canonical_groups.iter() {
+        let name = shortest_names.get(canonical_id).unwrap();
+
+        let context_length = model["context_length"].as_u64().unwrap_or(128_000) as usize;
+
+        let max_completion_tokens = model
+            .get("top_provider")
+            .and_then(|tp| tp.get("max_completion_tokens"))
+            .and_then(|v| v.as_u64())
+            .map(|v| v as usize);
+
+        let input_modalities: Vec<String> = model
+            .get("architecture")
+            .and_then(|arch| arch.get("input_modalities"))
+            .and_then(|v| v.as_array())
+            .map(|arr| {
+                arr.iter()
+                    .filter_map(|v| v.as_str())
+                    .map(|s| s.to_string())
+                    .collect()
+            })
+            .unwrap_or_else(|| vec!["text".to_string()]);
+
+        let output_modalities: Vec<String> = model
+            .get("architecture")
+            .and_then(|arch| arch.get("output_modalities"))
+            .and_then(|v| v.as_array())
+            .map(|arr| {
+                arr.iter()
+                    .filter_map(|v| v.as_str())
+                    .map(|s| s.to_string())
+                    .collect()
+            })
+            .unwrap_or_else(|| vec!["text".to_string()]);
+
+        let supports_tools = model
+            .get("supported_parameters")
+            .and_then(|v| v.as_array())
+            .map(|params| params.iter().any(|param| param.as_str() == Some("tools")))
+            .unwrap_or(false);
+
+        let pricing_obj = model
+            .get("pricing")
+            .context("Model missing pricing field")?;
+        let pricing = Pricing {
+            prompt: pricing_obj
+                .get("prompt")
+                .and_then(|v| v.as_str())
+                .and_then(|s| s.parse().ok()),
+            completion: pricing_obj
+                .get("completion")
+                .and_then(|v| v.as_str())
+                .and_then(|s| s.parse().ok()),
+            request: pricing_obj
+                .get("request")
+                .and_then(|v| v.as_str())
+                .and_then(|s| s.parse().ok()),
+            image: pricing_obj
+                .get("image")
+                .and_then(|v| v.as_str())
+                .and_then(|s| s.parse().ok()),
+        };
+
+        let canonical_model = CanonicalModel {
+            id: canonical_id.clone(),
+            name: name.to_string(),
+            context_length,
+            max_completion_tokens,
+            input_modalities,
+            output_modalities,
+            supports_tools,
+            pricing,
+        };
+
+        registry.register(canonical_model);
+    }
+
+    use std::path::PathBuf;
+
+    let output_path = PathBuf::from(env!("CARGO_MANIFEST_DIR"))
+        .join("src/providers/canonical/data/canonical_models.json");
+    registry.to_file(&output_path)?;
+    println!(
+        "\n✓ Wrote {} models to {}",
+        registry.count(),
+        output_path.display()
+    );
+
+    Ok(())
+}
diff --git a/crates/goose/examples/canonical_model_checker.rs b/crates/goose/examples/canonical_model_checker.rs
new file mode 100644
index 000000000000..8c6cf530b89a
--- /dev/null
+++ b/crates/goose/examples/canonical_model_checker.rs
@@ -0,0 +1,369 @@
+/// Canonical Model Checker
+///
+/// This script checks which models from top providers are properly mapped to canonical models.
+/// It maintains a lock file of mappings and detects changes between runs.
+///
+/// Outputs:
+/// - Models that are NOT mapped to canonical models
+/// - Full list of (provider, model) <-> canonical-model mappings
+/// - Diff report showing mapping changes since last run:
+///   * Changed mappings (model now maps to a different canonical model)
+///   * Added mappings (model gained a canonical mapping)
+///   * Removed mappings (model lost its canonical mapping)
+///
+/// Output File:
+/// - src/providers/canonical/data/canonical_mapping_report.json
+///   Contains full report with mapping data (acts as a lock file)
+///
+/// Usage:
+///   cargo run --example canonical_model_checker -- [--output custom_path.json]
+///
+use anyhow::{Context, Result};
+use goose::providers::{canonical::ModelMapping, create_with_named_model};
+use serde::{Deserialize, Serialize};
+use std::collections::{HashMap, HashSet};
+use std::path::PathBuf;
+
+#[derive(Debug, Clone, Serialize, Deserialize, PartialEq, Eq, Hash)]
+struct ProviderModelPair {
+    provider: String,
+    model: String,
+}
+
+#[derive(Debug, Clone, Serialize, Deserialize)]
+struct MappingEntry {
+    provider: String,
+    model: String,
+    canonical: String,
+}
+
+#[derive(Debug, Clone, Serialize, Deserialize)]
+struct MappingReport {
+    /// Timestamp of this report
+    timestamp: String,
+
+    /// Models that are NOT mapped to canonical models
+    unmapped_models: Vec<ProviderModelPair>,
+
+    /// All mappings: (provider, model) -> canonical model
+    /// Stored per provider for backward compatibility
+    all_mappings: HashMap<String, Vec<ModelMapping>>,
+
+    /// Flat list of all mappings for easier comparison (lock file format)
+    mapped_models: Vec<MappingEntry>,
+
+    /// Total models checked per provider
+    model_counts: HashMap<String, usize>,
+
+    /// Canonical models referenced
+    canonical_models_used: HashSet<String>,
+}
+
+impl MappingReport {
+    fn new() -> Self {
+        Self {
+            timestamp: chrono::Utc::now().to_rfc3339(),
+            unmapped_models: Vec::new(),
+            all_mappings: HashMap::new(),
+            mapped_models: Vec::new(),
+            model_counts: HashMap::new(),
+            canonical_models_used: HashSet::new(),
+        }
+    }
+
+    fn add_provider_results(
+        &mut self,
+        provider_name: &str,
+        fetched_models: Vec<String>,
+        mappings: Vec<ModelMapping>,
+    ) {
+        let mapping_map: HashMap<String, String> = mappings
+            .iter()
+            .map(|m| (m.provider_model.clone(), m.canonical_model.clone()))
+            .collect();
+
+        for model in &fetched_models {
+            if !mapping_map.contains_key(model) {
+                self.unmapped_models.push(ProviderModelPair {
+                    provider: provider_name.to_string(),
+                    model: model.clone(),
+                });
+            }
+        }
+
+        for (model, canonical) in &mapping_map {
+            self.canonical_models_used.insert(canonical.clone());
+            self.mapped_models.push(MappingEntry {
+                provider: provider_name.to_string(),
+                model: model.clone(),
+                canonical: canonical.clone(),
+            });
+        }
+
+        self.all_mappings
+            .insert(provider_name.to_string(), mappings);
+        self.model_counts
+            .insert(provider_name.to_string(), fetched_models.len());
+    }
+
+    fn print_summary(&self) {
+        println!("\n{}", "=".repeat(80));
+        println!("CANONICAL MODEL MAPPING REPORT");
+        println!("{}", "=".repeat(80));
+        println!("\nGenerated: {}\n", self.timestamp);
+
+        println!("Models Checked Per Provider:");
+        println!("{}", "-".repeat(80));
+        let mut providers: Vec<_> = self.model_counts.iter().collect();
+        providers.sort_by_key(|(name, _)| *name);
+        for (provider, count) in providers {
+            let mapped = self
+                .all_mappings
+                .get(provider)
+                .map(|m| m.len())
+                .unwrap_or(0);
+            let unmapped = count - mapped;
+            println!(
+                "  {:<20} Total: {:>3}  Mapped: {:>3}  Unmapped: {:>3}",
+                provider, count, mapped, unmapped
+            );
+        }
+
+        println!("\n{}", "=".repeat(80));
+        println!("UNMAPPED MODELS ({})", self.unmapped_models.len());
+        println!("{}", "=".repeat(80));
+
+        if self.unmapped_models.is_empty() {
+            println!("✓ All models are mapped to canonical models!");
+        } else {
+            let mut unmapped_by_provider: HashMap<&str, Vec<&str>> = HashMap::new();
+            for pair in &self.unmapped_models {
+                unmapped_by_provider
+                    .entry(pair.provider.as_str())
+                    .or_default()
+                    .push(pair.model.as_str());
+            }
+
+            let mut providers: Vec<_> = unmapped_by_provider.keys().collect();
+            providers.sort();
+
+            for provider in providers {
+                println!("\n{}:", provider);
+                let mut models = unmapped_by_provider[provider].to_vec();
+                models.sort();
+                for model in models {
+                    println!("  - {}", model);
+                }
+            }
+        }
+
+        println!("\n{}", "=".repeat(80));
+        println!(
+            "CANONICAL MODELS REFERENCED ({})",
+            self.canonical_models_used.len()
+        );
+        println!("{}", "=".repeat(80));
+        if self.canonical_models_used.is_empty() {
+            println!("  (none yet)");
+        } else {
+            let mut canonical: Vec<_> = self.canonical_models_used.iter().collect();
+            canonical.sort();
+            for model in canonical {
+                println!("  - {}", model);
+            }
+        }
+
+        println!("\n{}", "=".repeat(80));
+    }
+
+    fn compare_with_previous(&self, previous: &MappingReport) {
+        println!("\n{}", "=".repeat(80));
+        println!("CHANGES SINCE PREVIOUS RUN");
+        println!("{}", "=".repeat(80));
+
+        let mut prev_map: HashMap<(String, String), String> = HashMap::new();
+        for entry in &previous.mapped_models {
+            prev_map.insert(
+                (entry.provider.clone(), entry.model.clone()),
+                entry.canonical.clone(),
+            );
+        }
+
+        let mut curr_map: HashMap<(String, String), String> = HashMap::new();
+        for entry in &self.mapped_models {
+            curr_map.insert(
+                (entry.provider.clone(), entry.model.clone()),
+                entry.canonical.clone(),
+            );
+        }
+
+        let mut changed_mappings = Vec::new();
+        let mut added_mappings = Vec::new();
+        let mut removed_mappings = Vec::new();
+
+        for (key @ (provider, model), canonical) in &curr_map {
+            match prev_map.get(key) {
+                Some(prev_canonical) if prev_canonical != canonical => {
+                    changed_mappings.push((
+                        provider.clone(),
+                        model.clone(),
+                        prev_canonical.clone(),
+                        canonical.clone(),
+                    ));
+                }
+                None => {
+                    added_mappings.push((provider.clone(), model.clone(), canonical.clone()));
+                }
+                _ => {
+                    // No change
+                }
+            }
+        }
+
+        for (key @ (provider, model), canonical) in &prev_map {
+            if !curr_map.contains_key(key) {
+                removed_mappings.push((provider.clone(), model.clone(), canonical.clone()));
+            }
+        }
+
+        if changed_mappings.is_empty() && added_mappings.is_empty() && removed_mappings.is_empty() {
+            println!("\nNo changes in model mappings.");
+        } else {
+            if !changed_mappings.is_empty() {
+                println!("\n⚠ Changed Mappings ({}):", changed_mappings.len());
+                println!("  (Models that now map to a different canonical model)");
+                for (provider, model, old_canonical, new_canonical) in changed_mappings {
+                    println!("  {} / {}", provider, model);
+                    println!("    WAS: {}", old_canonical);
+                    println!("    NOW: {}", new_canonical);
+                }
+            }
+
+            if !added_mappings.is_empty() {
+                println!("\n✓ Added Mappings ({}):", added_mappings.len());
+                println!("  (Models that gained a canonical mapping)");
+                for (provider, model, canonical) in added_mappings {
+                    println!("  {} / {} -> {}", provider, model, canonical);
+                }
+            }
+
+            if !removed_mappings.is_empty() {
+                println!("\n✗ Removed Mappings ({}):", removed_mappings.len());
+                println!("  (Models that lost their canonical mapping)");
+                for (provider, model, canonical) in removed_mappings {
+                    println!("  {} / {} (was: {})", provider, model, canonical);
+                }
+            }
+        }
+
+        println!("\n{}", "=".repeat(80));
+    }
+
+    fn save_to_file(&self, path: &PathBuf) -> Result<()> {
+        let json = serde_json::to_string_pretty(self).context("Failed to serialize report")?;
+        std::fs::write(path, json).context("Failed to write report file")?;
+        Ok(())
+    }
+
+    fn load_from_file(path: &PathBuf) -> Result<Self> {
+        let content = std::fs::read_to_string(path).context("Failed to read report file")?;
+        let report: MappingReport =
+            serde_json::from_str(&content).context("Failed to parse report file")?;
+        Ok(report)
+    }
+}
+
+async fn check_provider(
+    provider_name: &str,
+    model_for_init: &str,
+) -> Result<(Vec<String>, Vec<ModelMapping>)> {
+    println!("Checking provider: {}", provider_name);
+
+    let provider = match create_with_named_model(provider_name, model_for_init).await {
+        Ok(p) => p,
+        Err(e) => {
+            println!("  ⚠ Failed to create provider: {}", e);
+            println!("  This is expected if credentials are not configured.");
+            return Ok((Vec::new(), Vec::new()));
+        }
+    };
+
+    let fetched_models = match provider.fetch_supported_models().await {
+        Ok(Some(models)) => {
+            println!("  ✓ Fetched {} models", models.len());
+            models
+        }
+        Ok(None) => {
+            println!("  ⚠ Provider does not support model listing");
+            Vec::new()
+        }
+        Err(e) => {
+            println!("  ⚠ Failed to fetch models: {}", e);
+            println!("  This is expected if credentials are not configured.");
+            Vec::new()
+        }
+    };
+
+    let mut mappings = Vec::new();
+    for model in &fetched_models {
+        match provider.map_to_canonical_model(model).await {
+            Ok(Some(canonical)) => {
+                mappings.push(ModelMapping::new(model.clone(), canonical));
+            }
+            Ok(None) => {
+                // No mapping found for this model
+            }
+            Err(e) => {
+                println!("  ⚠ Failed to map model '{}': {}", model, e);
+            }
+        }
+    }
+    println!("  ✓ Found {} mappings", mappings.len());
+
+    Ok((fetched_models, mappings))
+}
+
+#[tokio::main]
+async fn main() -> Result<()> {
+    println!("Canonical Model Checker");
+    println!("Checking model mappings for top providers...\n");
+
+    // Define providers to check with their default models
+    let providers = vec![
+        ("anthropic", "claude-3-5-sonnet-20241022"),
+        ("openai", "gpt-4"),
+        ("openrouter", "anthropic/claude-3.5-sonnet"),
+        ("google", "gemini-1.5-pro-002"),
+        ("tetrate", "claude-3-5-sonnet-computer-use"),
+        ("xai", "grok-code-fast-1"),
+    ];
+
+    let mut report = MappingReport::new();
+
+    for (provider_name, default_model) in providers {
+        let (fetched, mappings) = check_provider(provider_name, default_model).await?;
+        report.add_provider_results(provider_name, fetched, mappings);
+        println!();
+    }
+
+    report.print_summary();
+
+    let args: Vec<String> = std::env::args().collect();
+    let output_path = if args.len() > 2 && args[1] == "--output" {
+        PathBuf::from(&args[2])
+    } else {
+        PathBuf::from(env!("CARGO_MANIFEST_DIR"))
+            .join("src/providers/canonical/data/canonical_mapping_report.json")
+    };
+
+    if output_path.exists() {
+        if let Ok(previous) = MappingReport::load_from_file(&output_path) {
+            report.compare_with_previous(&previous);
+        }
+    }
+
+    report.save_to_file(&output_path)?;
+    println!("\n✓ Report saved to: {}", output_path.display());
+
+    Ok(())
+}
diff --git a/crates/goose/src/providers/base.rs b/crates/goose/src/providers/base.rs
index e908cd88c94f..4a84fff8e0f6 100644
--- a/crates/goose/src/providers/base.rs
+++ b/crates/goose/src/providers/base.rs
@@ -2,6 +2,7 @@ use anyhow::Result;
 use futures::Stream;
 use serde::{Deserialize, Serialize};
 
+use super::canonical::{map_to_canonical_model, CanonicalModelRegistry};
 use super::errors::ProviderError;
 use super::retry::RetryConfig;
 use crate::config::base::ConfigValue;
@@ -415,6 +416,52 @@ pub trait Provider: Send + Sync {
         Ok(None)
     }
 
+    /// Fetch models filtered by canonical registry and usability
+    async fn fetch_recommended_models(&self) -> Result<Option<Vec<String>>, ProviderError> {
+        let all_models = match self.fetch_supported_models().await? {
+            Some(models) => models,
+            None => return Ok(None),
+        };
+
+        let registry = CanonicalModelRegistry::bundled().map_err(|e| {
+            ProviderError::ExecutionError(format!("Failed to load canonical registry: {}", e))
+        })?;
+
+        let provider_name = self.get_name();
+
+        let recommended_models: Vec<String> = all_models
+            .iter()
+            .filter(|model| {
+                map_to_canonical_model(provider_name, model, registry)
+                    .and_then(|canonical_id| registry.get(&canonical_id))
+                    .map(|m| m.input_modalities.contains(&"text".to_string()))
+                    .unwrap_or(false)
+            })
+            .cloned()
+            .collect();
+
+        if recommended_models.is_empty() {
+            Ok(Some(all_models))
+        } else {
+            Ok(Some(recommended_models))
+        }
+    }
+
+    async fn map_to_canonical_model(
+        &self,
+        provider_model: &str,
+    ) -> Result<Option<String>, ProviderError> {
+        let registry = CanonicalModelRegistry::bundled().map_err(|e| {
+            ProviderError::ExecutionError(format!("Failed to load canonical registry: {}", e))
+        })?;
+
+        Ok(map_to_canonical_model(
+            self.get_name(),
+            provider_model,
+            registry,
+        ))
+    }
+
     fn supports_embeddings(&self) -> bool {
         false
     }
diff --git a/crates/goose/src/providers/canonical/README.md b/crates/goose/src/providers/canonical/README.md
new file mode 100644
index 000000000000..61bf29ccdd9c
--- /dev/null
+++ b/crates/goose/src/providers/canonical/README.md
@@ -0,0 +1,24 @@
+# Canonical Model System
+
+Provides a unified view of model metadata (pricing, capabilities, context limits) across different LLM providers. 
+Normalizes provider-specific model names (e.g., `claude-3-5-sonnet-20241022`) 
+to canonical IDs (e.g., `anthropic/claude-3.5-sonnet`).
+
+## Scripts
+
+### Build Canonical Models
+Fetches latest model metadata from OpenRouter and updates the registry:
+```bash
+cargo run --example build_canonical_models
+```
+Writes to: `src/providers/canonical/data/canonical_models.json`
+
+### Check Model Mappings
+Tests provider model mappings and tracks changes over time:
+```bash
+cargo run --example canonical_model_checker
+```
+- Reports unmapped models
+- Compares with previous runs (like a lock file)
+- Shows changed/added/removed mappings
+- Writes to: `src/providers/canonical/data/canonical_mapping_report.json`
diff --git a/crates/goose/src/providers/canonical/data/canonical_mapping_report.json b/crates/goose/src/providers/canonical/data/canonical_mapping_report.json
new file mode 100644
index 000000000000..f526b61646c1
--- /dev/null
+++ b/crates/goose/src/providers/canonical/data/canonical_mapping_report.json
@@ -0,0 +1,5352 @@
+{
+  "timestamp": "2025-12-11T15:48:25.968909+00:00",
+  "unmapped_models": [
+    {
+      "provider": "openai",
+      "model": "ada:ft-square-2023-01-20-06-09-37"
+    },
+    {
+      "provider": "openai",
+      "model": "ada:ft-square-2023-02-03-22-57-10"
+    },
+    {
+      "provider": "openai",
+      "model": "ada:ft-square-2023-02-03-23-17-02"
+    },
+    {
+      "provider": "openai",
+      "model": "ada:ft-square-2023-02-03-23-39-19"
+    },
+    {
+      "provider": "openai",
+      "model": "ada:ft-square-2023-02-04-00-06-28"
+    },
+    {
+      "provider": "openai",
+      "model": "ada:ft-square-2023-02-04-00-26-44"
+    },
+    {
+      "provider": "openai",
+      "model": "ada:ft-square-2023-02-04-01-04-45"
+    },
+    {
+      "provider": "openai",
+      "model": "ada:ft-square-2023-02-04-01-25-59"
+    },
+    {
+      "provider": "openai",
+      "model": "ada:ft-square-2023-02-04-01-35-31"
+    },
+    {
+      "provider": "openai",
+      "model": "ada:ft-square-2023-02-04-01-49-59"
+    },
+    {
+      "provider": "openai",
+      "model": "ada:ft-square-2023-02-04-01-52-25"
+    },
+    {
+      "provider": "openai",
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+      "model": "gemini-2.0-flash",
+      "canonical": "google/gemini-2.0-flash"
+    },
+    {
+      "provider": "google",
+      "model": "gemini-2.5-flash",
+      "canonical": "google/gemini-2.5-flash"
+    },
+    {
+      "provider": "google",
+      "model": "gemini-2.5-flash-preview-09-2025",
+      "canonical": "google/gemini-2.5-flash"
+    },
+    {
+      "provider": "google",
+      "model": "gemini-2.0-flash-001",
+      "canonical": "google/gemini-2.0-flash"
+    },
+    {
+      "provider": "google",
+      "model": "gemma-3n-e4b-it",
+      "canonical": "google/gemma-3n-e4b-it"
+    },
+    {
+      "provider": "google",
+      "model": "gemini-2.5-pro",
+      "canonical": "google/gemini-2.5-pro"
+    },
+    {
+      "provider": "google",
+      "model": "gemma-3-4b-it",
+      "canonical": "google/gemma-3-4b-it"
+    },
+    {
+      "provider": "google",
+      "model": "gemini-2.5-flash-image",
+      "canonical": "google/gemini-2.5-flash-image"
+    },
+    {
+      "provider": "google",
+      "model": "gemini-3-pro-image-preview",
+      "canonical": "google/gemini-3-pro-image"
+    },
+    {
+      "provider": "google",
+      "model": "gemini-2.0-flash-exp",
+      "canonical": "google/gemini-2.0-flash"
+    },
+    {
+      "provider": "google",
+      "model": "gemini-2.0-flash-lite-preview",
+      "canonical": "google/gemini-2.0-flash-lite"
+    },
+    {
+      "provider": "google",
+      "model": "gemini-2.5-flash-lite",
+      "canonical": "google/gemini-2.5-flash-lite"
+    },
+    {
+      "provider": "google",
+      "model": "gemini-2.5-flash-image-preview",
+      "canonical": "google/gemini-2.5-flash-image"
+    },
+    {
+      "provider": "google",
+      "model": "gemini-3-pro-preview",
+      "canonical": "google/gemini-3-pro"
+    },
+    {
+      "provider": "google",
+      "model": "gemini-2.0-flash-lite-preview-02-05",
+      "canonical": "google/gemini-2.0-flash-lite"
+    },
+    {
+      "provider": "google",
+      "model": "gemini-2.0-flash-lite-001",
+      "canonical": "google/gemini-2.0-flash-lite"
+    },
+    {
+      "provider": "google",
+      "model": "gemini-2.5-flash-lite-preview-09-2025",
+      "canonical": "google/gemini-2.5-flash-lite"
+    },
+    {
+      "provider": "google",
+      "model": "gemma-3-27b-it",
+      "canonical": "google/gemma-3-27b-it"
+    },
+    {
+      "provider": "google",
+      "model": "gemini-2.0-flash-lite",
+      "canonical": "google/gemini-2.0-flash-lite"
+    },
+    {
+      "provider": "google",
+      "model": "gemma-3-12b-it",
+      "canonical": "google/gemma-3-12b-it"
+    }
+  ],
+  "model_counts": {
+    "anthropic": 10,
+    "google": 50,
+    "tetrate": 0,
+    "xai": 0,
+    "openai": 633,
+    "openrouter": 225
+  },
+  "canonical_models_used": [
+    "mistralai/mistral-small-3.2-24b-instruct",
+    "meta-llama/llama-3-8b-instruct",
+    "mistralai/pixtral-12b",
+    "qwen/qwen3-coder-30b-a3b-instruct",
+    "anthropic/claude-opus-4",
+    "cohere/command-r-plus-08",
+    "google/gemini-2.5-flash-image",
+    "qwen/qwen3-next-80b-a3b-instruct",
+    "openai/gpt-4o-mini",
+    "cohere/command-r-08",
+    "qwen/qwen3-vl-235b-a22b-thinking",
+    "openai/gpt-5.1-codex-max",
+    "mistralai/mistral-large",
+    "google/gemma-3-27b-it",
+    "openai/gpt-oss-120b",
+    "openai/gpt-5",
+    "openai/gpt-5.1-chat",
+    "qwen/qwen3-vl-8b-thinking",
+    "openai/gpt-4o-audio",
+    "google/gemini-3-pro",
+    "openai/gpt-5.1-codex",
+    "openai/o3-pro",
+    "qwen/qwen3-coder-plus",
+    "openai/gpt-4",
+    "openai/gpt-5-image-mini",
+    "openai/gpt-3.5-turbo-instruct",
+    "anthropic/claude-3-opus",
+    "mistralai/ministral-8b",
+    "qwen/qwen3-30b-a3b-instruct",
+    "openai/gpt-oss-20b",
+    "x-ai/grok-code-fast-1",
+    "mistralai/mistral-saba",
+    "qwen/qwen3-vl-30b-a3b-instruct",
+    "openai/o3",
+    "mistralai/mistral-7b-instruct",
+    "mistralai/mistral-nemo",
+    "qwen/qwen3-next-80b-a3b-thinking",
+    "x-ai/grok-3",
+    "meta-llama/llama-4-maverick",
+    "qwen/qwen3-coder-flash",
+    "openai/gpt-oss-safeguard-20b",
+    "anthropic/claude-opus-4.5",
+    "x-ai/grok-4.1-fast",
+    "google/gemma-3n-e4b-it",
+    "mistralai/pixtral-large",
+    "qwen/qwen3-235b-a22b-thinking",
+    "openai/gpt-5-codex",
+    "anthropic/claude-3.7-sonnet:thinking",
+    "anthropic/claude-3.7-sonnet",
+    "meta-llama/llama-3.3-70b-instruct",
+    "meta-llama/llama-4-scout",
+    "openai/gpt-5-nano",
+    "openai/o3-mini",
+    "openai/o4-mini-deep-research",
+    "openai/gpt-4o",
+    "deepseek/deepseek-v3.1-terminus",
+    "mistralai/mixtral-8x7b-instruct",
+    "qwen/qwen-plus-2025-07-28:thinking",
+    "qwen/qwen-plus",
+    "mistralai/ministral-14b",
+    "openai/gpt-5-mini",
+    "meta-llama/llama-3.2-3b-instruct",
+    "openai/gpt-5.1",
+    "openai/gpt-5-pro",
+    "qwen/qwen3-vl-8b-instruct",
+    "google/gemini-2.5-flash-lite",
+    "qwen/qwen-vl-max",
+    "mistralai/devstral-medium",
+    "google/gemini-2.5-flash",
+    "meta-llama/llama-3-70b-instruct",
+    "mistralai/mistral-small-3.1-24b-instruct",
+    "qwen/qwen3-32b",
+    "openai/gpt-3.5-turbo-16k",
+    "openai/o3-deep-research",
+    "openai/o1-pro",
+    "meta-llama/llama-3.1-405b-instruct",
+    "anthropic/claude-sonnet-4",
+    "deepseek/deepseek",
+    "google/gemini-3-pro-image",
+    "ai21/jamba-mini-1.7",
+    "anthropic/claude-3.5-haiku",
+    "qwen/qwen-turbo",
+    "google/gemma-3-4b-it",
+    "google/gemini-2.5-pro",
+    "qwen/qwen3-30b-a3b",
+    "qwen/qwen-2.5-72b-instruct",
+    "google/gemma-3-12b-it",
+    "openai/gpt-4.1-mini",
+    "openai/gpt-4o-mini-search",
+    "x-ai/grok-4-fast",
+    "openai/gpt-4.1",
+    "openai/gpt-5.1-codex-mini",
+    "qwen/qwen3-max",
+    "openai/o4-mini",
+    "anthropic/claude-opus-4.1",
+    "mistralai/voxtral-small-24b",
+    "x-ai/grok-4",
+    "x-ai/grok-3-mini",
+    "qwen/qwen-max",
+    "anthropic/claude-sonnet-4.5",
+    "openai/gpt-4o-search",
+    "openai/gpt-5-chat",
+    "google/gemini-2.0-flash-lite",
+    "mistralai/mistral-small-24b-instruct",
+    "mistralai/mistral-medium-3",
+    "meta-llama/llama-3.1-8b-instruct",
+    "openai/gpt-4o:extended",
+    "openai/gpt-5-image",
+    "qwen/qwq-32b",
+    "deepseek/deepseek-chat",
+    "openai/o3-mini-high",
+    "mistralai/codestral",
+    "openai/codex-mini",
+    "deepseek/deepseek-r1",
+    "qwen/qwen3-30b-a3b-thinking",
+    "openai/o1",
+    "openai/gpt-4.1-nano",
+    "openai/chatgpt-4o",
+    "openai/o4-mini-high",
+    "openai/gpt-3.5-turbo",
+    "openai/gpt-4-turbo",
+    "anthropic/claude-3.5-sonnet",
+    "meta-llama/llama-3.1-70b-instruct",
+    "mistralai/mistral-tiny",
+    "qwen/qwen3-vl-235b-a22b-instruct",
+    "qwen/qwen3-8b",
+    "mistralai/devstral-small",
+    "anthropic/claude-haiku-4.5",
+    "deepseek/deepseek-r1-distill-llama-70b",
+    "qwen/qwen3-14b",
+    "mistralai/ministral-3b",
+    "qwen/qwen3-235b-a22b",
+    "mistralai/mistral-medium-3.1",
+    "anthropic/claude-3-haiku",
+    "ai21/jamba-large-1.7",
+    "google/gemini-2.0-flash",
+    "qwen/qwen3-vl-30b-a3b-thinking",
+    "qwen/qwen3-coder",
+    "mistralai/mixtral-8x22b-instruct"
+  ]
+}
\ No newline at end of file
diff --git a/crates/goose/src/providers/canonical/data/canonical_models.json b/crates/goose/src/providers/canonical/data/canonical_models.json
new file mode 100644
index 000000000000..94cdcfe52346
--- /dev/null
+++ b/crates/goose/src/providers/canonical/data/canonical_models.json
@@ -0,0 +1,3257 @@
+[
+  {
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+    "name": "AI21: Jamba Large 1.7",
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+    "max_completion_tokens": 4096,
+    "input_modalities": [
+      "text"
+    ],
+    "output_modalities": [
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+    ],
+    "supports_tools": true,
+    "pricing": {
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+      "completion": 8e-6,
+      "request": 0.0,
+      "image": 0.0
+    }
+  },
+  {
+    "id": "ai21/jamba-mini-1.7",
+    "name": "AI21: Jamba Mini 1.7",
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+    "max_completion_tokens": 4096,
+    "input_modalities": [
+      "text"
+    ],
+    "output_modalities": [
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+    ],
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+    "pricing": {
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+      "completion": 4e-7,
+      "request": 0.0,
+      "image": 0.0
+    }
+  },
+  {
+    "id": "anthropic/claude-3-haiku",
+    "name": "Anthropic: Claude 3 Haiku",
+    "context_length": 200000,
+    "max_completion_tokens": 4096,
+    "input_modalities": [
+      "text",
+      "image"
+    ],
+    "output_modalities": [
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+    ],
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+      "completion": 1.25e-6,
+      "request": 0.0,
+      "image": 0.0004
+    }
+  },
+  {
+    "id": "anthropic/claude-3-opus",
+    "name": "Anthropic: Claude 3 Opus",
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+    "max_completion_tokens": 4096,
+    "input_modalities": [
+      "text",
+      "image"
+    ],
+    "output_modalities": [
+      "text"
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+      "completion": 0.000075,
+      "request": 0.0,
+      "image": 0.024
+    }
+  },
+  {
+    "id": "anthropic/claude-3.5-haiku",
+    "name": "Anthropic: Claude 3.5 Haiku",
+    "context_length": 200000,
+    "max_completion_tokens": 8192,
+    "input_modalities": [
+      "text",
+      "image"
+    ],
+    "output_modalities": [
+      "text"
+    ],
+    "supports_tools": true,
+    "pricing": {
+      "prompt": 8e-7,
+      "completion": 4e-6,
+      "request": 0.0,
+      "image": 0.0
+    }
+  },
+  {
+    "id": "anthropic/claude-3.5-sonnet",
+    "name": "Anthropic: Claude 3.5 Sonnet",
+    "context_length": 200000,
+    "max_completion_tokens": 8192,
+    "input_modalities": [
+      "text",
+      "image",
+      "file"
+    ],
+    "output_modalities": [
+      "text"
+    ],
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+    "pricing": {
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+      "completion": 0.00003,
+      "request": 0.0,
+      "image": 0.0
+    }
+  },
+  {
+    "id": "anthropic/claude-3.7-sonnet",
+    "name": "Anthropic: Claude 3.7 Sonnet",
+    "context_length": 200000,
+    "max_completion_tokens": 64000,
+    "input_modalities": [
+      "text",
+      "image",
+      "file"
+    ],
+    "output_modalities": [
+      "text"
+    ],
+    "supports_tools": true,
+    "pricing": {
+      "prompt": 3e-6,
+      "completion": 0.000015,
+      "request": 0.0,
+      "image": 0.0048
+    }
+  },
+  {
+    "id": "anthropic/claude-3.7-sonnet:thinking",
+    "name": "Anthropic: Claude 3.7 Sonnet (thinking)",
+    "context_length": 200000,
+    "max_completion_tokens": 64000,
+    "input_modalities": [
+      "text",
+      "image",
+      "file"
+    ],
+    "output_modalities": [
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+    ],
+    "supports_tools": true,
+    "pricing": {
+      "prompt": 3e-6,
+      "completion": 0.000015,
+      "request": 0.0,
+      "image": 0.0048
+    }
+  },
+  {
+    "id": "anthropic/claude-haiku-4.5",
+    "name": "Anthropic: Claude Haiku 4.5",
+    "context_length": 200000,
+    "max_completion_tokens": 64000,
+    "input_modalities": [
+      "image",
+      "text"
+    ],
+    "output_modalities": [
+      "text"
+    ],
+    "supports_tools": true,
+    "pricing": {
+      "prompt": 1e-6,
+      "completion": 5e-6,
+      "request": 0.0,
+      "image": 0.0
+    }
+  },
+  {
+    "id": "anthropic/claude-opus-4",
+    "name": "Anthropic: Claude Opus 4",
+    "context_length": 200000,
+    "max_completion_tokens": 32000,
+    "input_modalities": [
+      "image",
+      "text",
+      "file"
+    ],
+    "output_modalities": [
+      "text"
+    ],
+    "supports_tools": true,
+    "pricing": {
+      "prompt": 0.000015,
+      "completion": 0.000075,
+      "request": 0.0,
+      "image": 0.024
+    }
+  },
+  {
+    "id": "anthropic/claude-opus-4.1",
+    "name": "Anthropic: Claude Opus 4.1",
+    "context_length": 200000,
+    "max_completion_tokens": 32000,
+    "input_modalities": [
+      "image",
+      "text",
+      "file"
+    ],
+    "output_modalities": [
+      "text"
+    ],
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+    "pricing": {
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+      "completion": 0.000075,
+      "request": 0.0,
+      "image": 0.024
+    }
+  },
+  {
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+    "name": "Anthropic: Claude Opus 4.5",
+    "context_length": 200000,
+    "max_completion_tokens": 32000,
+    "input_modalities": [
+      "file",
+      "image",
+      "text"
+    ],
+    "output_modalities": [
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+    ],
+    "supports_tools": true,
+    "pricing": {
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+      "completion": 0.000025,
+      "request": 0.0,
+      "image": 0.0
+    }
+  },
+  {
+    "id": "anthropic/claude-sonnet-4",
+    "name": "Anthropic: Claude Sonnet 4",
+    "context_length": 1000000,
+    "max_completion_tokens": 64000,
+    "input_modalities": [
+      "image",
+      "text",
+      "file"
+    ],
+    "output_modalities": [
+      "text"
+    ],
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+    "pricing": {
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+      "completion": 0.000015,
+      "request": 0.0,
+      "image": 0.0048
+    }
+  },
+  {
+    "id": "anthropic/claude-sonnet-4.5",
+    "name": "Anthropic: Claude Sonnet 4.5",
+    "context_length": 1000000,
+    "max_completion_tokens": 64000,
+    "input_modalities": [
+      "text",
+      "image",
+      "file"
+    ],
+    "output_modalities": [
+      "text"
+    ],
+    "supports_tools": true,
+    "pricing": {
+      "prompt": 3e-6,
+      "completion": 0.000015,
+      "request": 0.0,
+      "image": 0.0
+    }
+  },
+  {
+    "id": "cohere/command-a",
+    "name": "Cohere: Command A",
+    "context_length": 256000,
+    "max_completion_tokens": 8192,
+    "input_modalities": [
+      "text"
+    ],
+    "output_modalities": [
+      "text"
+    ],
+    "supports_tools": false,
+    "pricing": {
+      "prompt": 2.5e-6,
+      "completion": 0.00001,
+      "request": 0.0,
+      "image": 0.0
+    }
+  },
+  {
+    "id": "cohere/command-r-08",
+    "name": "Cohere: Command R (08-2024)",
+    "context_length": 128000,
+    "max_completion_tokens": 4000,
+    "input_modalities": [
+      "text"
+    ],
+    "output_modalities": [
+      "text"
+    ],
+    "supports_tools": true,
+    "pricing": {
+      "prompt": 1.5e-7,
+      "completion": 6e-7,
+      "request": 0.0,
+      "image": 0.0
+    }
+  },
+  {
+    "id": "cohere/command-r-plus-08",
+    "name": "Cohere: Command R+ (08-2024)",
+    "context_length": 128000,
+    "max_completion_tokens": 4000,
+    "input_modalities": [
+      "text"
+    ],
+    "output_modalities": [
+      "text"
+    ],
+    "supports_tools": true,
+    "pricing": {
+      "prompt": 2.5e-6,
+      "completion": 0.00001,
+      "request": 0.0,
+      "image": 0.0
+    }
+  },
+  {
+    "id": "cohere/command-r7b-12",
+    "name": "Cohere: Command R7B (12-2024)",
+    "context_length": 128000,
+    "max_completion_tokens": 4000,
+    "input_modalities": [
+      "text"
+    ],
+    "output_modalities": [
+      "text"
+    ],
+    "supports_tools": false,
+    "pricing": {
+      "prompt": 3.75e-8,
+      "completion": 1.5e-7,
+      "request": 0.0,
+      "image": 0.0
+    }
+  },
+  {
+    "id": "deepseek/deepseek",
+    "name": "DeepSeek: DeepSeek V3.2",
+    "context_length": 163840,
+    "max_completion_tokens": 163840,
+    "input_modalities": [
+      "text"
+    ],
+    "output_modalities": [
+      "text"
+    ],
+    "supports_tools": true,
+    "pricing": {
+      "prompt": 2.5e-7,
+      "completion": 3.8e-7,
+      "request": 0.0,
+      "image": 0.0
+    }
+  },
+  {
+    "id": "deepseek/deepseek-chat",
+    "name": "DeepSeek: DeepSeek V3",
+    "context_length": 163840,
+    "max_completion_tokens": 163840,
+    "input_modalities": [
+      "text"
+    ],
+    "output_modalities": [
+      "text"
+    ],
+    "supports_tools": true,
+    "pricing": {
+      "prompt": 3e-7,
+      "completion": 1.2e-6,
+      "request": 0.0,
+      "image": 0.0
+    }
+  },
+  {
+    "id": "deepseek/deepseek-prover",
+    "name": "DeepSeek: DeepSeek Prover V2",
+    "context_length": 163840,
+    "input_modalities": [
+      "text"
+    ],
+    "output_modalities": [
+      "text"
+    ],
+    "supports_tools": false,
+    "pricing": {
+      "prompt": 5e-7,
+      "completion": 2.18e-6,
+      "request": 0.0,
+      "image": 0.0
+    }
+  },
+  {
+    "id": "deepseek/deepseek-r1",
+    "name": "DeepSeek: R1",
+    "context_length": 163840,
+    "input_modalities": [
+      "text"
+    ],
+    "output_modalities": [
+      "text"
+    ],
+    "supports_tools": true,
+    "pricing": {
+      "prompt": 3e-7,
+      "completion": 1.2e-6,
+      "request": 0.0,
+      "image": 0.0
+    }
+  },
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+      "text"
+    ],
+    "output_modalities": [
+      "text"
+    ],
+    "supports_tools": true,
+    "pricing": {
+      "prompt": 2.2e-7,
+      "completion": 9.5e-7,
+      "request": 0.0,
+      "image": 0.0
+    }
+  },
+  {
+    "id": "qwen/qwen3-coder-30b-a3b-instruct",
+    "name": "Qwen: Qwen3 Coder 30B A3B Instruct",
+    "context_length": 262144,
+    "max_completion_tokens": 262144,
+    "input_modalities": [
+      "text"
+    ],
+    "output_modalities": [
+      "text"
+    ],
+    "supports_tools": true,
+    "pricing": {
+      "prompt": 6e-8,
+      "completion": 2.5e-7,
+      "request": 0.0,
+      "image": 0.0
+    }
+  },
+  {
+    "id": "qwen/qwen3-coder-flash",
+    "name": "Qwen: Qwen3 Coder Flash",
+    "context_length": 128000,
+    "max_completion_tokens": 65536,
+    "input_modalities": [
+      "text"
+    ],
+    "output_modalities": [
+      "text"
+    ],
+    "supports_tools": true,
+    "pricing": {
+      "prompt": 3e-7,
+      "completion": 1.5e-6,
+      "request": 0.0,
+      "image": 0.0
+    }
+  },
+  {
+    "id": "qwen/qwen3-coder-plus",
+    "name": "Qwen: Qwen3 Coder Plus",
+    "context_length": 128000,
+    "max_completion_tokens": 65536,
+    "input_modalities": [
+      "text"
+    ],
+    "output_modalities": [
+      "text"
+    ],
+    "supports_tools": true,
+    "pricing": {
+      "prompt": 1e-6,
+      "completion": 5e-6,
+      "request": 0.0,
+      "image": 0.0
+    }
+  },
+  {
+    "id": "qwen/qwen3-max",
+    "name": "Qwen: Qwen3 Max",
+    "context_length": 256000,
+    "max_completion_tokens": 32768,
+    "input_modalities": [
+      "text"
+    ],
+    "output_modalities": [
+      "text"
+    ],
+    "supports_tools": true,
+    "pricing": {
+      "prompt": 1.2e-6,
+      "completion": 6e-6,
+      "request": 0.0,
+      "image": 0.0
+    }
+  },
+  {
+    "id": "qwen/qwen3-next-80b-a3b-instruct",
+    "name": "Qwen: Qwen3 Next 80B A3B Instruct",
+    "context_length": 262144,
+    "input_modalities": [
+      "text"
+    ],
+    "output_modalities": [
+      "text"
+    ],
+    "supports_tools": true,
+    "pricing": {
+      "prompt": 9e-8,
+      "completion": 1.1e-6,
+      "request": 0.0,
+      "image": 0.0
+    }
+  },
+  {
+    "id": "qwen/qwen3-next-80b-a3b-thinking",
+    "name": "Qwen: Qwen3 Next 80B A3B Thinking",
+    "context_length": 131072,
+    "max_completion_tokens": 32768,
+    "input_modalities": [
+      "text"
+    ],
+    "output_modalities": [
+      "text"
+    ],
+    "supports_tools": true,
+    "pricing": {
+      "prompt": 1.2e-7,
+      "completion": 1.2e-6,
+      "request": 0.0,
+      "image": 0.0
+    }
+  },
+  {
+    "id": "qwen/qwen3-vl-235b-a22b-instruct",
+    "name": "Qwen: Qwen3 VL 235B A22B Instruct",
+    "context_length": 262144,
+    "input_modalities": [
+      "text",
+      "image"
+    ],
+    "output_modalities": [
+      "text"
+    ],
+    "supports_tools": true,
+    "pricing": {
+      "prompt": 2e-7,
+      "completion": 1.2e-6,
+      "request": 0.0,
+      "image": 0.0
+    }
+  },
+  {
+    "id": "qwen/qwen3-vl-235b-a22b-thinking",
+    "name": "Qwen: Qwen3 VL 235B A22B Thinking",
+    "context_length": 262144,
+    "max_completion_tokens": 262144,
+    "input_modalities": [
+      "text",
+      "image"
+    ],
+    "output_modalities": [
+      "text"
+    ],
+    "supports_tools": true,
+    "pricing": {
+      "prompt": 3e-7,
+      "completion": 1.2e-6,
+      "request": 0.0,
+      "image": 0.0
+    }
+  },
+  {
+    "id": "qwen/qwen3-vl-30b-a3b-instruct",
+    "name": "Qwen: Qwen3 VL 30B A3B Instruct",
+    "context_length": 262144,
+    "input_modalities": [
+      "text",
+      "image"
+    ],
+    "output_modalities": [
+      "text"
+    ],
+    "supports_tools": true,
+    "pricing": {
+      "prompt": 1.5e-7,
+      "completion": 6e-7,
+      "request": 0.0,
+      "image": 0.0
+    }
+  },
+  {
+    "id": "qwen/qwen3-vl-30b-a3b-thinking",
+    "name": "Qwen: Qwen3 VL 30B A3B Thinking",
+    "context_length": 131072,
+    "max_completion_tokens": 32768,
+    "input_modalities": [
+      "text",
+      "image"
+    ],
+    "output_modalities": [
+      "text"
+    ],
+    "supports_tools": true,
+    "pricing": {
+      "prompt": 1.6e-7,
+      "completion": 8e-7,
+      "request": 0.0,
+      "image": 0.0
+    }
+  },
+  {
+    "id": "qwen/qwen3-vl-8b-instruct",
+    "name": "Qwen: Qwen3 VL 8B Instruct",
+    "context_length": 131072,
+    "max_completion_tokens": 32768,
+    "input_modalities": [
+      "image",
+      "text"
+    ],
+    "output_modalities": [
+      "text"
+    ],
+    "supports_tools": true,
+    "pricing": {
+      "prompt": 6.4e-8,
+      "completion": 4e-7,
+      "request": 0.0,
+      "image": 0.0
+    }
+  },
+  {
+    "id": "qwen/qwen3-vl-8b-thinking",
+    "name": "Qwen: Qwen3 VL 8B Thinking",
+    "context_length": 256000,
+    "max_completion_tokens": 32768,
+    "input_modalities": [
+      "image",
+      "text"
+    ],
+    "output_modalities": [
+      "text"
+    ],
+    "supports_tools": true,
+    "pricing": {
+      "prompt": 1.8e-7,
+      "completion": 2.1e-6,
+      "request": 0.0,
+      "image": 0.0
+    }
+  },
+  {
+    "id": "qwen/qwq-32b",
+    "name": "Qwen: QwQ 32B",
+    "context_length": 32768,
+    "input_modalities": [
+      "text"
+    ],
+    "output_modalities": [
+      "text"
+    ],
+    "supports_tools": true,
+    "pricing": {
+      "prompt": 1.5e-7,
+      "completion": 4e-7,
+      "request": 0.0,
+      "image": 0.0
+    }
+  },
+  {
+    "id": "x-ai/grok-3",
+    "name": "xAI: Grok 3",
+    "context_length": 131072,
+    "input_modalities": [
+      "text"
+    ],
+    "output_modalities": [
+      "text"
+    ],
+    "supports_tools": true,
+    "pricing": {
+      "prompt": 3e-6,
+      "completion": 0.000015,
+      "request": 0.0,
+      "image": 0.0
+    }
+  },
+  {
+    "id": "x-ai/grok-3-mini",
+    "name": "xAI: Grok 3 Mini",
+    "context_length": 131072,
+    "input_modalities": [
+      "text"
+    ],
+    "output_modalities": [
+      "text"
+    ],
+    "supports_tools": true,
+    "pricing": {
+      "prompt": 3e-7,
+      "completion": 5e-7,
+      "request": 0.0,
+      "image": 0.0
+    }
+  },
+  {
+    "id": "x-ai/grok-4",
+    "name": "xAI: Grok 4",
+    "context_length": 256000,
+    "input_modalities": [
+      "image",
+      "text"
+    ],
+    "output_modalities": [
+      "text"
+    ],
+    "supports_tools": true,
+    "pricing": {
+      "prompt": 3e-6,
+      "completion": 0.000015,
+      "request": 0.0,
+      "image": 0.0
+    }
+  },
+  {
+    "id": "x-ai/grok-4-fast",
+    "name": "xAI: Grok 4 Fast",
+    "context_length": 2000000,
+    "max_completion_tokens": 30000,
+    "input_modalities": [
+      "text",
+      "image"
+    ],
+    "output_modalities": [
+      "text"
+    ],
+    "supports_tools": true,
+    "pricing": {
+      "prompt": 2e-7,
+      "completion": 5e-7,
+      "request": 0.0,
+      "image": 0.0
+    }
+  },
+  {
+    "id": "x-ai/grok-4.1-fast",
+    "name": "xAI: Grok 4.1 Fast",
+    "context_length": 2000000,
+    "max_completion_tokens": 30000,
+    "input_modalities": [
+      "text",
+      "image"
+    ],
+    "output_modalities": [
+      "text"
+    ],
+    "supports_tools": true,
+    "pricing": {
+      "prompt": 2e-7,
+      "completion": 5e-7,
+      "request": 0.0,
+      "image": 0.0
+    }
+  },
+  {
+    "id": "x-ai/grok-code-fast-1",
+    "name": "xAI: Grok Code Fast 1",
+    "context_length": 256000,
+    "max_completion_tokens": 10000,
+    "input_modalities": [
+      "text"
+    ],
+    "output_modalities": [
+      "text"
+    ],
+    "supports_tools": true,
+    "pricing": {
+      "prompt": 2e-7,
+      "completion": 1.5e-6,
+      "request": 0.0,
+      "image": 0.0
+    }
+  }
+]
\ No newline at end of file
diff --git a/crates/goose/src/providers/canonical/mod.rs b/crates/goose/src/providers/canonical/mod.rs
new file mode 100644
index 000000000000..1aac285ca516
--- /dev/null
+++ b/crates/goose/src/providers/canonical/mod.rs
@@ -0,0 +1,22 @@
+mod model;
+mod name_builder;
+mod registry;
+
+pub use model::{CanonicalModel, Pricing};
+pub use name_builder::{canonical_name, map_to_canonical_model, strip_version_suffix};
+pub use registry::CanonicalModelRegistry;
+
+#[derive(Debug, Clone, serde::Serialize, serde::Deserialize)]
+pub struct ModelMapping {
+    pub provider_model: String,
+    pub canonical_model: String,
+}
+
+impl ModelMapping {
+    pub fn new(provider_model: impl Into<String>, canonical_model: impl Into<String>) -> Self {
+        Self {
+            provider_model: provider_model.into(),
+            canonical_model: canonical_model.into(),
+        }
+    }
+}
diff --git a/crates/goose/src/providers/canonical/model.rs b/crates/goose/src/providers/canonical/model.rs
new file mode 100644
index 000000000000..77108b495105
--- /dev/null
+++ b/crates/goose/src/providers/canonical/model.rs
@@ -0,0 +1,53 @@
+use serde::{Deserialize, Serialize};
+
+/// Pricing information for a model (all costs in USD per token)
+#[derive(Debug, Clone, Serialize, Deserialize)]
+pub struct Pricing {
+    /// Cost per prompt token
+    #[serde(skip_serializing_if = "Option::is_none")]
+    pub prompt: Option<f64>,
+
+    /// Cost per completion token
+    #[serde(skip_serializing_if = "Option::is_none")]
+    pub completion: Option<f64>,
+
+    /// Cost per request
+    #[serde(skip_serializing_if = "Option::is_none")]
+    pub request: Option<f64>,
+
+    /// Cost per image
+    #[serde(skip_serializing_if = "Option::is_none")]
+    pub image: Option<f64>,
+}
+
+/// Canonical representation of a model
+#[derive(Debug, Clone, Serialize, Deserialize)]
+pub struct CanonicalModel {
+    /// Model identifier (e.g., "anthropic/claude-3-5-sonnet" or "openai/gpt-4o:extended")
+    pub id: String,
+
+    /// Human-readable name (e.g., "Claude 3.5 Sonnet")
+    pub name: String,
+
+    /// Maximum context window size in tokens
+    pub context_length: usize,
+
+    /// Maximum completion tokens
+    #[serde(skip_serializing_if = "Option::is_none")]
+    pub max_completion_tokens: Option<usize>,
+
+    /// Input modalities supported (e.g., ["text", "image"])
+    #[serde(default)]
+    pub input_modalities: Vec<String>,
+
+    /// Output modalities supported (e.g., ["text"])
+    #[serde(default)]
+    pub output_modalities: Vec<String>,
+
+    /// Whether the model supports tool calling
+    #[serde(default)]
+    pub supports_tools: bool,
+
+    /// Pricing for this model
+    pub pricing: Pricing,
+}
diff --git a/crates/goose/src/providers/canonical/name_builder.rs b/crates/goose/src/providers/canonical/name_builder.rs
new file mode 100644
index 000000000000..c82629ed56c4
--- /dev/null
+++ b/crates/goose/src/providers/canonical/name_builder.rs
@@ -0,0 +1,542 @@
+use once_cell::sync::Lazy;
+use regex::Regex;
+
+static NORMALIZE_VERSION_RE: Lazy<Regex> = Lazy::new(|| Regex::new(r"-(\d)-(\d)(-|$)").unwrap());
+
+static STRIP_PATTERNS: Lazy<Vec<Regex>> = Lazy::new(|| {
+    vec![
+        Regex::new(r"-latest$").unwrap(),
+        Regex::new(r"-preview(-\d+)*$").unwrap(),
+        Regex::new(r"-exp(-\d+)*$").unwrap(),
+        Regex::new(r":exacto$").unwrap(),
+        Regex::new(r"-\d{8}$").unwrap(),
+        Regex::new(r"-\d{4}-\d{2}-\d{2}$").unwrap(),
+        Regex::new(r"-v\d+(\.\d+)*$").unwrap(),
+        Regex::new(r"-\d{3,}$").unwrap(),
+        Regex::new(r"-bedrock$").unwrap(),
+    ]
+});
+
+static CLAUDE_PATTERNS: Lazy<Vec<(Regex, Regex, &'static str)>> = Lazy::new(|| {
+    ["sonnet", "opus", "haiku"]
+        .iter()
+        .map(|&size| {
+            (
+                Regex::new(&format!("claude-([0-9.-]+)-{}", size)).unwrap(),
+                Regex::new(&format!("claude-{}-([0-9.-]+)", size)).unwrap(),
+                size,
+            )
+        })
+        .collect()
+});
+
+/// Build canonical model name from provider and model identifiers
+pub fn canonical_name(provider: &str, model: &str) -> String {
+    let model_base = strip_version_suffix(model);
+
+    // OpenRouter models are already in canonical format
+    if provider == "openrouter" {
+        model_base
+    } else {
+        format!("{}/{}", provider, model_base)
+    }
+}
+
+/// Try to build a canonical name and check if it exists in the registry
+fn try_canonical(
+    provider: &str,
+    model: &str,
+    registry: &super::CanonicalModelRegistry,
+) -> Option<String> {
+    let candidate = canonical_name(provider, model);
+    registry.get(&candidate).map(|_| candidate)
+}
+
+/// Try to map a provider/model pair to a canonical model
+pub fn map_to_canonical_model(
+    provider: &str,
+    model: &str,
+    registry: &super::CanonicalModelRegistry,
+) -> Option<String> {
+    // Try direct mapping first
+    if let Some(candidate) = try_canonical(provider, model, registry) {
+        return Some(candidate);
+    }
+
+    // Try with common prefixes stripped
+    let model_stripped = strip_common_prefixes(model);
+    if model_stripped != model {
+        if let Some(candidate) = try_canonical(provider, &model_stripped, registry) {
+            return Some(candidate);
+        }
+    }
+
+    // Try word-order swapping for Claude models (claude-4-opus ↔ claude-opus-4)
+    if let Some(swapped) = swap_claude_word_order(&model_stripped) {
+        if let Some(candidate) = try_canonical(provider, &swapped, registry) {
+            return Some(candidate);
+        }
+
+        if is_hosting_provider(provider) {
+            if let Some(inferred) = infer_provider_from_model(&swapped) {
+                if let Some(candidate) = try_canonical(inferred, &swapped, registry) {
+                    return Some(candidate);
+                }
+            }
+        }
+    }
+
+    // For hosting providers, try to infer the real provider from model name patterns
+    if is_hosting_provider(provider) {
+        if let Some(inferred_provider) = infer_provider_from_model(&model_stripped) {
+            if let Some(candidate) = try_canonical(inferred_provider, &model_stripped, registry) {
+                return Some(candidate);
+            }
+        }
+
+        if let Some(inferred) = infer_provider_from_model(model) {
+            if let Some(candidate) = try_canonical(inferred, model, registry) {
+                return Some(candidate);
+            }
+        }
+    }
+
+    // For provider-prefixed models like "databricks-meta-llama-3-1-70b"
+    if let Some((extracted_provider, extracted_model)) = extract_provider_prefix(&model_stripped) {
+        if let Some(candidate) = try_canonical(extracted_provider, extracted_model, registry) {
+            return Some(candidate);
+        }
+    }
+
+    None
+}
+
+/// Swap word order for Claude models to handle both naming conventions
+fn swap_claude_word_order(model: &str) -> Option<String> {
+    if !model.starts_with("claude-") {
+        return None;
+    }
+
+    for (forward_re, reverse_re, size) in CLAUDE_PATTERNS.iter() {
+        if let Some(captures) = forward_re.captures(model) {
+            let version = &captures[1];
+            return Some(format!("claude-{}-{}", size, version));
+        }
+
+        if let Some(captures) = reverse_re.captures(model) {
+            let version = &captures[1];
+            return Some(format!("claude-{}-{}", version, size));
+        }
+    }
+
+    None
+}
+
+fn is_hosting_provider(provider: &str) -> bool {
+    matches!(provider, "databricks" | "openrouter" | "azure" | "bedrock")
+}
+
+/// Infer the real provider from model name patterns
+fn infer_provider_from_model(model: &str) -> Option<&'static str> {
+    let model_lower = model.to_lowercase();
+
+    if model_lower.contains("claude") {
+        return Some("anthropic");
+    }
+
+    if model_lower.starts_with("gpt-")
+        || model_lower.starts_with("o1")
+        || model_lower.starts_with("o3")
+        || model_lower.starts_with("o4")
+        || model_lower.starts_with("chatgpt-")
+    {
+        return Some("openai");
+    }
+
+    if model_lower.starts_with("gemini-") || model_lower.starts_with("gemma-") {
+        return Some("google");
+    }
+
+    if model_lower.contains("llama") {
+        return Some("meta-llama");
+    }
+
+    if model_lower.starts_with("mistral")
+        || model_lower.starts_with("mixtral")
+        || model_lower.starts_with("codestral")
+        || model_lower.starts_with("ministral")
+        || model_lower.starts_with("pixtral")
+        || model_lower.starts_with("devstral")
+        || model_lower.starts_with("voxtral")
+    {
+        return Some("mistralai");
+    }
+
+    if model_lower.contains("deepseek") {
+        return Some("deepseek");
+    }
+
+    if model_lower.contains("qwen") {
+        return Some("qwen");
+    }
+
+    if model_lower.contains("grok") {
+        return Some("x-ai");
+    }
+
+    if model_lower.contains("jamba") {
+        return Some("ai21");
+    }
+
+    if model_lower.contains("command") {
+        return Some("cohere");
+    }
+
+    None
+}
+
+/// Strip common prefixes from model names using pattern matching
+/// Looks for known model family patterns and strips everything before them
+fn strip_common_prefixes(model: &str) -> String {
+    let model_patterns = [
+        "claude-",
+        "gpt-",
+        "gemini-",
+        "gemma-",
+        "o1-",
+        "o1",
+        "o3-",
+        "o3",
+        "o4-",
+        "llama-",
+        "mistral-",
+        "mixtral-",
+        "chatgpt-",
+        "deepseek-",
+        "qwen-",
+        "grok-",
+        "jamba-",
+        "command-",
+        "codestral",
+        "ministral-",
+        "pixtral-",
+        "devstral-",
+    ];
+
+    let mut earliest_pos = None;
+
+    for pattern in &model_patterns {
+        if let Some(pos) = model.to_lowercase().find(pattern) {
+            if earliest_pos.is_none() || pos < earliest_pos.unwrap() {
+                earliest_pos = Some(pos);
+            }
+        }
+    }
+
+    // If we found a pattern, strip everything before it
+    if let Some(pos) = earliest_pos {
+        return model.get(pos..).unwrap_or(model).to_string();
+    }
+
+    model.to_string()
+}
+
+/// Try to extract provider prefix from model names like "databricks-meta-llama-3-1-70b"
+/// Returns (provider, model) tuple if found
+fn extract_provider_prefix(model: &str) -> Option<(&'static str, &str)> {
+    let known_providers = [
+        "anthropic",
+        "openai",
+        "google",
+        "meta-llama",
+        "mistralai",
+        "cohere",
+        "ai21",
+        "amazon",
+        "deepseek",
+        "qwen",
+        "x-ai",
+        "nvidia",
+        "microsoft",
+        "perplexity",
+    ];
+
+    for provider in &known_providers {
+        let prefix = format!("{}-", provider);
+        if model.starts_with(&prefix) {
+            if let Some(model_part) = model.strip_prefix(&prefix) {
+                return Some((provider, model_part));
+            }
+        }
+    }
+
+    None
+}
+
+/// Strip version suffixes from model names and normalize version numbers
+pub fn strip_version_suffix(model: &str) -> String {
+    let mut result = NORMALIZE_VERSION_RE
+        .replace_all(model, "-$1.$2$3")
+        .to_string();
+
+    let mut changed = true;
+    while changed {
+        let before = result.clone();
+        for pattern in STRIP_PATTERNS.iter() {
+            result = pattern.replace(&result, "").to_string();
+        }
+        changed = result != before;
+    }
+
+    result
+}
+
+#[cfg(test)]
+mod tests {
+    use super::*;
+
+    #[test]
+    fn test_map_to_canonical_model() {
+        let r = super::super::CanonicalModelRegistry::bundled().unwrap();
+
+        // === Direct provider (non-hosting) ===
+        assert_eq!(
+            map_to_canonical_model("anthropic", "claude-3-5-sonnet-20241022", r),
+            Some("anthropic/claude-3.5-sonnet".to_string())
+        );
+        assert_eq!(
+            map_to_canonical_model("openai", "gpt-4o-latest", r),
+            Some("openai/gpt-4o".to_string())
+        );
+        assert_eq!(
+            map_to_canonical_model("openai", "gpt-4-turbo-2024-04-09", r),
+            Some("openai/gpt-4-turbo".to_string())
+        );
+
+        // === OpenRouter (already canonical format) ===
+        assert_eq!(
+            map_to_canonical_model("openrouter", "anthropic/claude-3.5-sonnet", r),
+            Some("anthropic/claude-3.5-sonnet".to_string())
+        );
+
+        // === Anthropic Claude - basic ===
+        assert_eq!(
+            map_to_canonical_model("databricks", "claude-3-5-sonnet", r),
+            Some("anthropic/claude-3.5-sonnet".to_string())
+        );
+        assert_eq!(
+            map_to_canonical_model("databricks", "claude-3-5-sonnet-20241022", r),
+            Some("anthropic/claude-3.5-sonnet".to_string())
+        );
+        assert_eq!(
+            map_to_canonical_model("databricks", "claude-3-5-sonnet-latest", r),
+            Some("anthropic/claude-3.5-sonnet".to_string())
+        );
+
+        // === Claude word-order swapping (3.x series) ===
+        assert_eq!(
+            map_to_canonical_model("databricks", "claude-haiku-3-5", r),
+            Some("anthropic/claude-3.5-haiku".to_string())
+        );
+        assert_eq!(
+            map_to_canonical_model("databricks", "claude-sonnet-3-7", r),
+            Some("anthropic/claude-3.7-sonnet".to_string())
+        );
+        assert_eq!(
+            map_to_canonical_model("databricks", "ng-tools-claude-haiku-3-5", r),
+            Some("anthropic/claude-3.5-haiku".to_string())
+        );
+
+        // === Claude word-order swapping (4.x series) ===
+        assert_eq!(
+            map_to_canonical_model("databricks", "claude-4-opus", r),
+            Some("anthropic/claude-opus-4".to_string())
+        );
+        assert_eq!(
+            map_to_canonical_model("databricks", "claude-4-sonnet", r),
+            Some("anthropic/claude-sonnet-4".to_string())
+        );
+        assert_eq!(
+            map_to_canonical_model("databricks", "raml-claude-opus-4-5", r),
+            Some("anthropic/claude-opus-4.5".to_string())
+        );
+        assert_eq!(
+            map_to_canonical_model("databricks", "databricks-claude-sonnet-4-5", r),
+            Some("anthropic/claude-sonnet-4.5".to_string())
+        );
+
+        // === Claude with custom prefixes ===
+        assert_eq!(
+            map_to_canonical_model("databricks", "goose-claude-4-opus", r),
+            Some("anthropic/claude-opus-4".to_string())
+        );
+        assert_eq!(
+            map_to_canonical_model("databricks", "kgoose-claude-4-sonnet", r),
+            Some("anthropic/claude-sonnet-4".to_string())
+        );
+        assert_eq!(
+            map_to_canonical_model("databricks", "headless-goose-claude-4-sonnet", r),
+            Some("anthropic/claude-sonnet-4".to_string())
+        );
+        assert_eq!(
+            map_to_canonical_model("databricks", "kgoose-cashapp-claude-4-sonnet", r),
+            Some("anthropic/claude-sonnet-4".to_string())
+        );
+
+        // === Claude with platform suffixes ===
+        assert_eq!(
+            map_to_canonical_model("databricks", "claude-4-sonnet-bedrock", r),
+            Some("anthropic/claude-sonnet-4".to_string())
+        );
+        assert_eq!(
+            map_to_canonical_model("databricks", "goose-claude-4-sonnet-bedrock", r),
+            Some("anthropic/claude-sonnet-4".to_string())
+        );
+        assert_eq!(
+            map_to_canonical_model("bedrock", "claude-3-5-sonnet", r),
+            Some("anthropic/claude-3.5-sonnet".to_string())
+        );
+
+        // === OpenAI GPT ===
+        assert_eq!(
+            map_to_canonical_model("databricks", "gpt-4o", r),
+            Some("openai/gpt-4o".to_string())
+        );
+        assert_eq!(
+            map_to_canonical_model("databricks", "gpt-4o-2024-11-20", r),
+            Some("openai/gpt-4o".to_string())
+        );
+        assert_eq!(
+            map_to_canonical_model("databricks", "gpt-4o-latest", r),
+            Some("openai/gpt-4o".to_string())
+        );
+        assert_eq!(
+            map_to_canonical_model("databricks", "kgoose-gpt-4o", r),
+            Some("openai/gpt-4o".to_string())
+        );
+        assert_eq!(
+            map_to_canonical_model("azure", "gpt-4o", r),
+            Some("openai/gpt-4o".to_string())
+        );
+
+        // === OpenAI O-series ===
+        assert_eq!(
+            map_to_canonical_model("databricks", "goose-o1", r),
+            Some("openai/o1".to_string())
+        );
+        assert_eq!(
+            map_to_canonical_model("databricks", "kgoose-o3", r),
+            Some("openai/o3".to_string())
+        );
+        assert_eq!(
+            map_to_canonical_model("databricks", "headless-goose-o3-mini", r),
+            Some("openai/o3-mini".to_string())
+        );
+
+        // === Google Gemini ===
+        assert_eq!(
+            map_to_canonical_model("databricks", "gemini-2-5-flash", r),
+            Some("google/gemini-2.5-flash".to_string())
+        );
+
+        // === Meta Llama ===
+        assert_eq!(
+            map_to_canonical_model("databricks", "meta-llama-3-1-70b-instruct", r),
+            Some("meta-llama/llama-3.1-70b-instruct".to_string())
+        );
+
+        // === Mistral variants ===
+        assert_eq!(
+            map_to_canonical_model("databricks", "codestral", r),
+            Some("mistralai/codestral".to_string())
+        );
+        assert_eq!(
+            map_to_canonical_model("databricks", "ministral-8b", r),
+            Some("mistralai/ministral-8b".to_string())
+        );
+
+        // === DeepSeek ===
+        assert_eq!(
+            map_to_canonical_model("databricks", "databricks-deepseek-chat", r),
+            Some("deepseek/deepseek-chat".to_string())
+        );
+        assert_eq!(
+            map_to_canonical_model("databricks", "deepseek-r1", r),
+            Some("deepseek/deepseek-r1".to_string())
+        );
+
+        // === Qwen ===
+        assert_eq!(
+            map_to_canonical_model("databricks", "qwen-2-5-72b-instruct", r),
+            Some("qwen/qwen-2.5-72b-instruct".to_string())
+        );
+        assert_eq!(
+            map_to_canonical_model("databricks", "goose-qwen-2-5-72b-instruct", r),
+            Some("qwen/qwen-2.5-72b-instruct".to_string())
+        );
+
+        // === Grok (X.AI) ===
+        assert_eq!(
+            map_to_canonical_model("databricks", "grok-3", r),
+            Some("x-ai/grok-3".to_string())
+        );
+        assert_eq!(
+            map_to_canonical_model("databricks", "databricks-grok-4-fast", r),
+            Some("x-ai/grok-4-fast".to_string())
+        );
+        assert_eq!(
+            map_to_canonical_model("databricks", "kgoose-grok-4-fast", r),
+            Some("x-ai/grok-4-fast".to_string())
+        );
+
+        // === Jamba (AI21) ===
+        assert_eq!(
+            map_to_canonical_model("databricks", "jamba-large-1-7", r),
+            Some("ai21/jamba-large-1.7".to_string())
+        );
+        assert_eq!(
+            map_to_canonical_model("databricks", "databricks-jamba-large-1-7", r),
+            Some("ai21/jamba-large-1.7".to_string())
+        );
+
+        // === Cohere Command ===
+        assert_eq!(
+            map_to_canonical_model("databricks", "command-r-plus-08", r),
+            Some("cohere/command-r-plus-08".to_string())
+        );
+        assert_eq!(
+            map_to_canonical_model("databricks", "goose-command-r-08", r),
+            Some("cohere/command-r-08".to_string())
+        );
+
+        // === Provider-prefixed extraction ===
+        assert_eq!(
+            map_to_canonical_model("databricks", "anthropic-claude-3-5-sonnet", r),
+            Some("anthropic/claude-3.5-sonnet".to_string())
+        );
+        assert_eq!(
+            map_to_canonical_model("databricks", "openai-gpt-4o", r),
+            Some("openai/gpt-4o".to_string())
+        );
+        assert_eq!(
+            map_to_canonical_model("databricks", "google-gemini-2-5-flash", r),
+            Some("google/gemini-2.5-flash".to_string())
+        );
+        assert_eq!(
+            map_to_canonical_model("databricks", "mistralai-mistral-large", r),
+            Some("mistralai/mistral-large".to_string())
+        );
+        assert_eq!(
+            map_to_canonical_model("databricks", "deepseek-deepseek-chat", r),
+            Some("deepseek/deepseek-chat".to_string())
+        );
+        assert_eq!(
+            map_to_canonical_model("databricks", "qwen-qwen-2-5-72b-instruct", r),
+            Some("qwen/qwen-2.5-72b-instruct".to_string())
+        );
+        assert_eq!(
+            map_to_canonical_model("databricks", "x-ai-grok-3", r),
+            Some("x-ai/grok-3".to_string())
+        );
+    }
+}
diff --git a/crates/goose/src/providers/canonical/registry.rs b/crates/goose/src/providers/canonical/registry.rs
new file mode 100644
index 000000000000..b601bfca1158
--- /dev/null
+++ b/crates/goose/src/providers/canonical/registry.rs
@@ -0,0 +1,92 @@
+use super::CanonicalModel;
+use anyhow::{Context, Result};
+use once_cell::sync::Lazy;
+use std::collections::HashMap;
+use std::path::Path;
+
+/// Cached bundled canonical model registry
+static BUNDLED_REGISTRY: Lazy<Result<CanonicalModelRegistry>> = Lazy::new(|| {
+    const CANONICAL_MODELS_JSON: &str = include_str!("data/canonical_models.json");
+
+    let models: Vec<CanonicalModel> = serde_json::from_str(CANONICAL_MODELS_JSON)
+        .context("Failed to parse bundled canonical models JSON")?;
+
+    let mut registry = CanonicalModelRegistry::new();
+    for model in models {
+        registry.register(model);
+    }
+
+    Ok(registry)
+});
+
+#[derive(Debug, Clone)]
+pub struct CanonicalModelRegistry {
+    models: HashMap<String, CanonicalModel>,
+}
+
+impl CanonicalModelRegistry {
+    pub fn new() -> Self {
+        Self {
+            models: HashMap::new(),
+        }
+    }
+
+    pub fn bundled() -> Result<&'static Self> {
+        BUNDLED_REGISTRY
+            .as_ref()
+            .map_err(|e| anyhow::anyhow!("{}", e))
+    }
+
+    pub fn from_file(path: impl AsRef<Path>) -> Result<Self> {
+        let content = std::fs::read_to_string(path.as_ref())
+            .context("Failed to read canonical models file")?;
+
+        let models: Vec<CanonicalModel> =
+            serde_json::from_str(&content).context("Failed to parse canonical models JSON")?;
+
+        let mut registry = Self::new();
+        for model in models {
+            registry.register(model);
+        }
+
+        Ok(registry)
+    }
+
+    pub fn to_file(&self, path: impl AsRef<Path>) -> Result<()> {
+        let mut models: Vec<&CanonicalModel> = self.models.values().collect();
+        models.sort_by(|a, b| a.id.cmp(&b.id));
+
+        let json = serde_json::to_string_pretty(&models)
+            .context("Failed to serialize canonical models")?;
+
+        std::fs::write(path.as_ref(), json).context("Failed to write canonical models file")?;
+
+        Ok(())
+    }
+
+    pub fn register(&mut self, model: CanonicalModel) {
+        self.models.insert(model.id.clone(), model);
+    }
+
+    pub fn get(&self, name: &str) -> Option<&CanonicalModel> {
+        self.models.get(name)
+    }
+
+    pub fn all_models(&self) -> Vec<&CanonicalModel> {
+        self.models.values().collect()
+    }
+
+    pub fn count(&self) -> usize {
+        self.models.len()
+    }
+
+    pub fn contains(&self, name: &str) -> bool {
+        self.models.contains_key(name)
+    }
+}
+
+impl Default for CanonicalModelRegistry {
+    fn default() -> Self {
+        Self::new()
+    }
+}
diff --git a/crates/goose/src/providers/mod.rs b/crates/goose/src/providers/mod.rs
index 2e27b45d6da0..3c3e64344d7f 100644
--- a/crates/goose/src/providers/mod.rs
+++ b/crates/goose/src/providers/mod.rs
@@ -5,6 +5,7 @@ pub mod azure;
 pub mod azureauth;
 pub mod base;
 pub mod bedrock;
+pub mod canonical;
 pub mod claude_code;
 pub mod cursor_agent;
 pub mod databricks;
diff --git a/ui/desktop/src/components/settings/models/modelInterface.ts b/ui/desktop/src/components/settings/models/modelInterface.ts
index b3cec2469e19..e37729dfbb68 100644
--- a/ui/desktop/src/components/settings/models/modelInterface.ts
+++ b/ui/desktop/src/components/settings/models/modelInterface.ts
@@ -47,7 +47,7 @@ export interface ProviderModelsResult {
 }
 
 /**
- * Fetches models for all active providers in parallel.
+ * Fetches recommended models for all active providers in parallel.
  * Falls back to known_models if fetching fails or returns no models.
  */
 export async function fetchModelsForProviders(
diff --git a/ui/desktop/src/components/settings/models/subcomponents/SwitchModelModal.tsx b/ui/desktop/src/components/settings/models/subcomponents/SwitchModelModal.tsx
index a1c346359093..849c5ff14d4a 100644
--- a/ui/desktop/src/components/settings/models/subcomponents/SwitchModelModal.tsx
+++ b/ui/desktop/src/components/settings/models/subcomponents/SwitchModelModal.tsx
@@ -197,7 +197,7 @@ export const SwitchModelModal = ({
 
         setLoadingModels(true);
 
-        // Fetching models for all providers
+        // Fetching models for all providers (always recommended)
         const results = await fetchModelsForProviders(activeProviders, getProviderModels);
 
         // Process results and build grouped options