diff --git a/vllm_mlx/engine/simple.py b/vllm_mlx/engine/simple.py
index e96317ef..da3ccfc1 100644
--- a/vllm_mlx/engine/simple.py
+++ b/vllm_mlx/engine/simple.py
@@ -369,7 +369,7 @@ async def stream_generate(
             ):
                 prompt_tokens = (
                     chunk.prompt_tokens
-                    if hasattr(chunk, "prompt_tokens")
+                    if hasattr(chunk, "prompt_tokens") and chunk.prompt_tokens
                     else prompt_tokens
                 )
                 completion_tokens += 1
@@ -472,9 +472,20 @@ async def chat(
                     **kwargs,
                 )
                 text = clean_output_text(output.text)
+                # Count prompt tokens from the full templated prompt
+                tokenizer = self._model.tokenizer
+                template_kwargs = {
+                    "tokenize": True,
+                    "add_generation_prompt": True,
+                }
+                if template_tools:
+                    template_kwargs["tools"] = template_tools
+                prompt_ids = tokenizer.apply_chat_template(messages, **template_kwargs)
+                prompt_token_count = len(prompt_ids)
                 return GenerationOutput(
                     text=text,
                     tokens=output.tokens,
+                    prompt_tokens=prompt_token_count,
                     completion_tokens=len(output.tokens),
                     finish_reason=output.finish_reason,
                 )
diff --git a/vllm_mlx/models/llm.py b/vllm_mlx/models/llm.py
index 72182037..75bbab85 100644
--- a/vllm_mlx/models/llm.py
+++ b/vllm_mlx/models/llm.py
@@ -30,6 +30,7 @@ class StreamingOutput:
     token: int
     finished: bool = False
     finish_reason: str | None = None
+    prompt_tokens: int = 0
 
 
 class MLXLanguageModel:
@@ -203,6 +204,9 @@ def stream_generate(
         # Create sampler with parameters
         sampler = self._create_sampler(temperature, top_p)
 
+        # Count prompt tokens once upfront
+        num_prompt_tokens = len(self.tokenizer.encode(prompt))
+
         token_count = 0
         accumulated_text = ""
 
@@ -241,6 +245,7 @@ def stream_generate(
                 token=response.token if hasattr(response, "token") else 0,
                 finished=finished,
                 finish_reason=finish_reason,
+                prompt_tokens=num_prompt_tokens,
             )
 
             if finished: