diff --git a/db.py b/db.py
index 0816c17..9a96ca2 100644
--- a/db.py
+++ b/db.py
@@ -132,3 +132,17 @@ class TokenDatabase:
                         'total_tokens': row[4],
                         'timestamp': row[5]
                     }
+
+    async def get_token_counts_for_model(self, model):
+        """Get token counts for a specific model."""
+        async with aiosqlite.connect(self.db_path) as db:
+            async with db.execute('SELECT endpoint, model, input_tokens, output_tokens, total_tokens FROM token_counts WHERE model = ?', (model,)) as cursor:
+                async for row in cursor:
+                    return {
+                        'endpoint': row[0],
+                        'model': row[1],
+                        'input_tokens': row[2],
+                        'output_tokens': row[3],
+                        'total_tokens': row[4]
+                    }
+            return None
diff --git a/router.py b/router.py
index 1b0af1c..94831f9 100644
--- a/router.py
+++ b/router.py
@@ -797,7 +797,8 @@ async def proxy(request: Request):
                         chunk = rechunk.openai_completion2ollama(chunk, stream, start_ts)
                     prompt_tok = chunk.prompt_eval_count or 0
                     comp_tok   = chunk.eval_count or 0
-                    await token_queue.put((endpoint, model, prompt_tok, comp_tok))
+                    if prompt_tok != 0 or comp_tok != 0:
+                        await token_queue.put((endpoint, model, prompt_tok, comp_tok))
                     if hasattr(chunk, "model_dump_json"):
                         json_line = chunk.model_dump_json()
                     else:
@@ -811,7 +812,8 @@ async def proxy(request: Request):
                     response = async_gen.model_dump_json()
                     prompt_tok = async_gen.prompt_eval_count or 0
                     comp_tok   = async_gen.eval_count or 0
-                    await token_queue.put((endpoint, model, prompt_tok, comp_tok))
+                    if prompt_tok != 0 or comp_tok != 0:
+                        await token_queue.put((endpoint, model, prompt_tok, comp_tok))
                 json_line = (
                     response
                     if hasattr(async_gen, "model_dump_json")
@@ -913,7 +915,8 @@ async def chat_proxy(request: Request):
                     # `chunk` can be a dict or a pydantic model – dump to JSON safely
                     prompt_tok = chunk.prompt_eval_count or 0
                     comp_tok   = chunk.eval_count or 0
-                    await token_queue.put((endpoint, model, prompt_tok, comp_tok))
+                    if prompt_tok != 0 or comp_tok != 0:
+                        await token_queue.put((endpoint, model, prompt_tok, comp_tok))
                     if hasattr(chunk, "model_dump_json"):
                         json_line = chunk.model_dump_json()
                     else:
@@ -927,7 +930,8 @@ async def chat_proxy(request: Request):
                     response = async_gen.model_dump_json()
                     prompt_tok = async_gen.prompt_eval_count or 0
                     comp_tok   = async_gen.eval_count or 0
-                    await token_queue.put((endpoint, model, prompt_tok, comp_tok))
+                    if prompt_tok != 0 or comp_tok != 0:
+                        await token_queue.put((endpoint, model, prompt_tok, comp_tok))
                 json_line = (
                     response
                     if hasattr(async_gen, "model_dump_json")
@@ -1140,7 +1144,7 @@ async def show_proxy(request: Request, model: Optional[str] = None):
         if not model:
             payload = orjson.loads(body_bytes.decode("utf-8"))
             model = payload.get("model")
-        
+
         if not model:
             raise HTTPException(
                 status_code=400, detail="Missing required field 'model'"
@@ -1159,6 +1163,55 @@ async def show_proxy(request: Request, model: Optional[str] = None):
     # 4. Return ShowResponse
     return show
 
+# -------------------------------------------------------------
+# 12. API route – Stats
+# -------------------------------------------------------------
+@app.post("/api/stats")
+async def stats_proxy(request: Request, model: Optional[str] = None):
+    """
+    Return token usage statistics for a specific model.
+    """
+    try:
+        body_bytes = await request.body()
+
+        if not model:
+            payload = orjson.loads(body_bytes.decode("utf-8"))
+            model = payload.get("model")
+
+        if not model:
+            raise HTTPException(
+                status_code=400, detail="Missing required field 'model'"
+            )
+    except orjson.JSONDecodeError as e:
+        raise HTTPException(status_code=400, detail=f"Invalid JSON: {e}") from e
+
+    # Get token counts from database
+    token_data = await db.get_token_counts_for_model(model)
+
+    if not token_data:
+        raise HTTPException(
+            status_code=404, detail="No token data found for this model"
+        )
+
+    # Get time series data
+    time_series = []
+    async for entry in db.get_latest_time_series(limit=10):
+        if entry['model'] == model:
+            time_series.append({
+                'timestamp': entry['timestamp'],
+                'input_tokens': entry['input_tokens'],
+                'output_tokens': entry['output_tokens'],
+                'total_tokens': entry['total_tokens']
+            })
+
+    return {
+        'model': model,
+        'input_tokens': token_data['input_tokens'],
+        'output_tokens': token_data['output_tokens'],
+        'total_tokens': token_data['total_tokens'],
+        'time_series': time_series
+    }
+
 # -------------------------------------------------------------
 # 12. API route – Copy
 # -------------------------------------------------------------
@@ -1584,7 +1637,8 @@ async def openai_chat_completions_proxy(request: Request):
             else:
                 prompt_tok = async_gen.usage.prompt_tokens or 0
                 comp_tok   = async_gen.usage.completion_tokens or 0
-                await token_queue.put((endpoint, model, prompt_tok, comp_tok))
+                if prompt_tok != 0 or comp_tok != 0:
+                    await token_queue.put((endpoint, model, prompt_tok, comp_tok))
                 json_line = (
                     async_gen.model_dump_json()
                     if hasattr(async_gen, "model_dump_json")
@@ -1690,7 +1744,8 @@ async def openai_completions_proxy(request: Request):
             else:
                 prompt_tok = async_gen.usage.prompt_tokens or 0
                 comp_tok   = async_gen.usage.completion_tokens or 0
-                await token_queue.put((endpoint, model, prompt_tok, comp_tok))
+                if prompt_tok != 0 or comp_tok != 0:
+                    await token_queue.put((endpoint, model, prompt_tok, comp_tok))
                 json_line = (
                     async_gen.model_dump_json()
                     if hasattr(async_gen, "model_dump_json")
diff --git a/static/index.html b/static/index.html
index b4f5466..0ecbf7d 100644
--- a/static/index.html
+++ b/static/index.html
@@ -447,7 +447,7 @@
                                 ? `${digest.slice(0, 12)}...${digest.slice(-12)}`
                                 : digest;
                             return `<tr data-model="${m.name}">
-                                <td class="model">${m.name}</td>
+                                <td class="model">${m.name} <a href="#" class="stats-link" data-model="${m.name}">stats</a></td>
                                 <td>${m.details.parameter_size}</td>
                                 <td>${m.details.quantization_level}</td>
                                 <td>${m.context_length}</td>
@@ -636,6 +636,56 @@
                         modal.style.display = "none";
                     }
                 });
+
+                /* stats logic */
+                document.body.addEventListener("click", async (e) => {
+                    if (!e.target.matches(".stats-link")) return;
+                    e.preventDefault();
+                    const model = e.target.dataset.model;
+                    try {
+                        const resp = await fetch(
+                            `/api/stats?model=${encodeURIComponent(model)}`,
+                            { method: "POST" },
+                        );
+                        if (!resp.ok)
+                            throw new Error(`Status ${resp.status}`);
+                        const data = await resp.json();
+                        const content = document.getElementById("stats-content");
+                        content.innerHTML = `
+                            <h3>Token Usage</h3>
+                            <p>Input tokens: ${data.input_tokens}</p>
+                            <p>Output tokens: ${data.output_tokens}</p>
+                            <p>Total tokens: ${data.total_tokens}</p>
+                            <h3>Usage Over Time</h3>
+                            <div id="time-series-chart">
+                                ${data.time_series.length > 0 ?
+                                    data.time_series.map(ts => `
+                                        <div>
+                                            <strong>${new Date(ts.timestamp * 1000).toLocaleString()}</strong>
+                                            <p>Input: ${ts.input_tokens}, Output: ${ts.output_tokens}, Total: ${ts.total_tokens}</p>
+                                        </div>
+                                    `).join('') :
+                                    '<p>No time series data available</p>'
+                                }
+                            </div>
+                        `;
+                        document.getElementById("stats-modal").style.display = "flex";
+                    } catch (err) {
+                        console.error(err);
+                        alert(`Could not load model stats: ${err.message}`);
+                    }
+                });
+
+                /* stats modal close */
+                const statsModal = document.getElementById("stats-modal");
+                statsModal.addEventListener("click", (e) => {
+                    if (
+                        e.target === statsModal ||
+                        e.target.matches(".close-btn")
+                    ) {
+                        statsModal.style.display = "none";
+                    }
+                });
             });
         </script>
 
@@ -646,5 +696,15 @@
                 <pre id="json-output"></pre>
             </div>
         </div>
+
+        <div id="stats-modal" class="modal">
+            <div class="modal-content">
+                <span class="close-btn">&times;</span>
+                <h2>Model Stats</h2>
+                <div id="stats-content">
+                    <p>Loading stats...</p>
+                </div>
+            </div>
+        </div>
     </body>
 </html>