diff --git a/src/target/source/codegen_cuda.cc b/src/target/source/codegen_cuda.cc
index 4454dd319768..defc94efa28f 100644
--- a/src/target/source/codegen_cuda.cc
+++ b/src/target/source/codegen_cuda.cc
@@ -1615,13 +1615,17 @@ inline void PrintConst(const FloatImmNode* op, std::ostream& os, CodeGenCUDA* p)
   // Type code is kBFloat
   if (op->dtype.is_bfloat16()) {
     os << "__float2bfloat16_rn";
-    os << '(' << std::scientific << op->value << 'f' << ')';
+    os << '(' << std::hexfloat << op->value << 'f';
+    os << "/*" << std::scientific << op->value << "*/";
+    os << ')';
     return;
   }
   // Type code is kFloat8_e5m2 or kE4M4Float
   if (op->dtype.is_float8() || op->dtype.is_float4()) {
     p->PrintType(op->dtype, os);
-    os << '(' << std::scientific << op->value << 'f' << ')';
+    os << '(' << std::hexfloat << op->value << 'f';
+    os << "/*" << std::scientific << op->value << "*/";
+    os << ')';
     return;
   }
   // Type code is kFloat
@@ -1656,7 +1660,8 @@ inline void PrintConst(const FloatImmNode* op, std::ostream& os, CodeGenCUDA* p)
         temp << "CUDART_NAN_F";
         p->need_math_constants_h_ = true;
       } else {
-        temp << std::scientific << op->value << 'f';
+        temp << std::hexfloat << op->value << 'f';
+        temp << "/*" << std::scientific << op->value << "*/";
       }
       p->MarkConst(temp.str());
       os << temp.str();
diff --git a/tests/python/codegen/test_target_codegen_cuda.py b/tests/python/codegen/test_target_codegen_cuda.py
index db49f56045ad..0841d0f54562 100644
--- a/tests/python/codegen/test_target_codegen_cuda.py
+++ b/tests/python/codegen/test_target_codegen_cuda.py
@@ -801,6 +801,25 @@ def main(
     assert 'extern "C" __device__ float add(float a, float b) {\n  return (a + b);\n}' in cuda_code
 
 
+@tvm.testing.requires_cuda
+def test_cuda_float_const_hex_format():
+    """Test that float constants are emitted in hexadecimal format for precision"""
+
+    @I.ir_module
+    class Module:
+        @T.prim_func
+        def main(
+            A: T.Buffer((1024, 1024), "float32"),
+        ):
+            for bx in T.thread_binding(1024, "blockIdx.x"):
+                for tx in T.thread_binding(1024, "threadIdx.x"):
+                    A[bx, tx] = T.float32(1 / 27)
+
+    lib = tvm.compile(Module, target="cuda")
+    cuda_code = lib.mod.imports[0].inspect_source()
+    assert "0x1.2f684bda12f68p-5f" in cuda_code
+
+
 @tvm.testing.requires_cuda
 def test_device_host_call_same_func():
     @I.ir_module
diff --git a/tests/python/tir-transform/test_tir_transform_inject_ptx_async_copy.py b/tests/python/tir-transform/test_tir_transform_inject_ptx_async_copy.py
index 67598b0ba04f..aa4f5138a17f 100644
--- a/tests/python/tir-transform/test_tir_transform_inject_ptx_async_copy.py
+++ b/tests/python/tir-transform/test_tir_transform_inject_ptx_async_copy.py
@@ -264,8 +264,8 @@ def test_inject_async_copy_barrier():
 extern "C" __global__ void __launch_bounds__(16) main_kernel(float* __restrict__ A, float* __restrict__ B, float* __restrict__ C) {
   __shared__ float A_shared[64];
   __shared__ float B_shared[64];
-  A_shared[((int)threadIdx.x)] = 0.000000e+00f;
-  B_shared[((int)threadIdx.x)] = 0.000000e+00f;
+  A_shared[((int)threadIdx.x)] = 0x0p+0f/*0.000000e+00*/;
+  B_shared[((int)threadIdx.x)] = 0x0p+0f/*0.000000e+00*/;
 __asm__ __volatile__("cp.async.commit_group;");