diff --git a/ddtrace/internal/datadog/profiling/stack_v2/src/stack_v2.cpp b/ddtrace/internal/datadog/profiling/stack_v2/src/stack_v2.cpp
index 62fa4b38b77..b5cd8a81312 100644
--- a/ddtrace/internal/datadog/profiling/stack_v2/src/stack_v2.cpp
+++ b/ddtrace/internal/datadog/profiling/stack_v2/src/stack_v2.cpp
@@ -91,7 +91,7 @@ _stack_v2_link_span(PyObject* self, PyObject* args, PyObject* kwargs)
     uint64_t thread_id;
     uint64_t span_id;
     uint64_t local_root_span_id;
-    const char* span_type;
+    const char* span_type = nullptr;
 
     PyThreadState* state = PyThreadState_Get();
 
@@ -104,10 +104,16 @@ _stack_v2_link_span(PyObject* self, PyObject* args, PyObject* kwargs)
     static const char* const_kwlist[] = { "span_id", "local_root_span_id", "span_type", NULL };
     static char** kwlist = const_cast<char**>(const_kwlist);
 
-    if (!PyArg_ParseTupleAndKeywords(args, kwargs, "KKs", kwlist, &span_id, &local_root_span_id, &span_type)) {
+    if (!PyArg_ParseTupleAndKeywords(args, kwargs, "KKz", kwlist, &span_id, &local_root_span_id, &span_type)) {
         return NULL;
     }
 
+    // From Python, span_type is a string or None, and when given None, it is passed as a nullptr.
+    static const std::string empty_string = "";
+    if (span_type == nullptr) {
+        span_type = empty_string.c_str();
+    }
+
     ThreadSpanLinks::get_instance().link_span(thread_id, span_id, local_root_span_id, std::string(span_type));
 
     Py_RETURN_NONE;
diff --git a/ddtrace/llmobs/_llmobs.py b/ddtrace/llmobs/_llmobs.py
index c76f90f7782..f25adb3bff0 100644
--- a/ddtrace/llmobs/_llmobs.py
+++ b/ddtrace/llmobs/_llmobs.py
@@ -508,7 +508,7 @@ def annotate(
         if parameters is not None:
             log.warning("Setting parameters is deprecated, please set parameters and other metadata as tags instead.")
             cls._tag_params(span, parameters)
-        if input_data or output_data:
+        if input_data is not None or output_data is not None:
             if span_kind == "llm":
                 cls._tag_llm_io(span, input_messages=input_data, output_messages=output_data)
             elif span_kind == "embedding":
@@ -598,9 +598,9 @@ def _tag_text_io(cls, span, input_value=None, output_value=None):
         """Tags input/output values for non-LLM kind spans.
         Will be mapped to span's `meta.{input,output}.values` fields.
         """
-        if input_value:
+        if input_value is not None:
             span.set_tag_str(INPUT_VALUE, safe_json(input_value))
-        if output_value:
+        if output_value is not None:
             span.set_tag_str(OUTPUT_VALUE, safe_json(output_value))
 
     @staticmethod
diff --git a/releasenotes/notes/fix-numeric-annotations-7cf06b5ceb615282.yaml b/releasenotes/notes/fix-numeric-annotations-7cf06b5ceb615282.yaml
new file mode 100644
index 00000000000..05ed3ddb964
--- /dev/null
+++ b/releasenotes/notes/fix-numeric-annotations-7cf06b5ceb615282.yaml
@@ -0,0 +1,5 @@
+---
+fixes:
+  - |
+    LLM Observability: This fix resolves an issue where input and output values equal to zero were not being annotated
+    on workflow, task, agent and tool spans when using `LLMObs.annotate`.
diff --git a/releasenotes/notes/profiling-stack-v2-endpoint-span-type-none-48a1196296be3742.yaml b/releasenotes/notes/profiling-stack-v2-endpoint-span-type-none-48a1196296be3742.yaml
new file mode 100644
index 00000000000..1e4fea09afe
--- /dev/null
+++ b/releasenotes/notes/profiling-stack-v2-endpoint-span-type-none-48a1196296be3742.yaml
@@ -0,0 +1,5 @@
+---
+fixes:
+  - |
+    profiling: resolves an issue where endpoint profiling for stack v2 throws
+    ``TypeError`` exception when it is given a ``Span`` with ``None`` span_type.
diff --git a/tests/llmobs/test_llmobs_service.py b/tests/llmobs/test_llmobs_service.py
index 7c51705853d..9f0f4e44710 100644
--- a/tests/llmobs/test_llmobs_service.py
+++ b/tests/llmobs/test_llmobs_service.py
@@ -471,6 +471,17 @@ def test_annotate_input_string(LLMObs):
         assert retrieval_span.get_tag(INPUT_VALUE) == "test_input"
 
 
+def test_annotate_numeric_io(LLMObs):
+    with LLMObs.task() as task_span:
+        LLMObs.annotate(span=task_span, input_data=0, output_data=0)
+        assert task_span.get_tag(INPUT_VALUE) == "0"
+        assert task_span.get_tag(OUTPUT_VALUE) == "0"
+    with LLMObs.task() as task_span:
+        LLMObs.annotate(span=task_span, input_data=1.23, output_data=1.23)
+        assert task_span.get_tag(INPUT_VALUE) == "1.23"
+        assert task_span.get_tag(OUTPUT_VALUE) == "1.23"
+
+
 def test_annotate_input_serializable_value(LLMObs):
     with LLMObs.task() as task_span:
         LLMObs.annotate(span=task_span, input_data=["test_input"])