[
  {
    "model": "mlx-8bit",
    "prompt": "Say hello in one short sentence.",
    "returncode": 0,
    "repetition_flag": false,
    "output_tail": "==========\n<think>\nThe user asks: \"Say hello in one short sentence.\" So we need to respond with a single short sentence that says hello. For example: \"Hello!\" or \"Greetings!\" That's one short sentence. Must not add extra commentary. So answer: Hello! Or \"Greetings!\" The instruction: \"Say hello in one short sentence.\" So we can say \"Hello!\" That's a short sentence. Provide that. No extra formatting. So just\n==========\nPrompt: 16 tokens, 127.925 tokens-per-sec\nGeneration: 96 tokens, 174.506 tokens-per-sec\nPeak memory: 9.016 GB\n"
  },
  {
    "model": "mlx-8bit",
    "prompt": "What tools would you use to check the weather in Austin, TX?",
    "returncode": 0,
    "repetition_flag": false,
    "output_tail": "==========\n<think>\nOkay, the user is asking about tools to check the weather in Austin, TX. Let me think about the different options available. First, I should consider both free and paid tools. For real-time data, maybe the National Weather Service is a reliable source. Then there are weather apps like Weather.com, AccuWeather, and the built-in Weather app on iPhones. Also, Google Weather and Apple Weather are options. \n\nI should also mention hyperlocal tools\n==========\nPrompt: 23 tokens, 174.392 tokens-per-sec\nGeneration: 96 tokens, 175.492 tokens-per-sec\nPeak memory: 9.039 GB\n"
  },
  {
    "model": "mlx-8bit",
    "prompt": "Write a native LFM tool call to open https://example.com using browser_navigate.",
    "returncode": 0,
    "repetition_flag": false,
    "output_tail": "==========\n<think>\nThe user asks: \"Write a native LFM tool call to open https://example.com using browser_navigate.\"\n\nWe need to interpret: LFM is likely \"Language Model Framework\"? Or maybe \"LFM\" is a tool name. However, the user likely wants a tool call in the LFM format (like a JSON with name and arguments). They want to open a URL using a browser. The tool name is \"browser_navigate\". So\n==========\nPrompt: 28 tokens, 204.063 tokens-per-sec\nGeneration: 96 tokens, 172.892 tokens-per-sec\nPeak memory: 9.047 GB\n"
  },
  {
    "model": "mlx-8bit",
    "prompt": "After <tool_response>{\"status\":\"ok\"}</tool_response>, give a short final answer.",
    "returncode": 0,
    "repetition_flag": false,
    "output_tail": "==========\n<think>\nThe user says: \"After <tool_response>{\"status\":\"ok\"}</tool_response>, give a short final answer.\"\n\nWe need to respond with a short final answer. However we have no context of what the tool response was. The system says we are a helpful assistant. The user didn't ask a new question. They just gave a previous tool response and asked to give a short final answer. Possibly they want a confirmation that the tool executed successfully?\n==========\nPrompt: 29 tokens, 219.543 tokens-per-sec\nGeneration: 96 tokens, 175.284 tokens-per-sec\nPeak memory: 9.049 GB\n"
  },
  {
    "model": "mlx-8bit",
    "prompt": "Do not use tools: explain what a router does in a MoE model in one sentence.",
    "returncode": 0,
    "repetition_flag": false,
    "output_tail": "==========\n<think>\nThe user asks: \"Do not use tools: explain what a router does in a MoE model in one sentence.\" So we need to produce a single sentence, no tools, no extra commentary. Must not use markdown unless asked. So just one sentence. The router in Mixture of Experts (MoE) selects which expert to route each input to. So one sentence: \"A router in a MoE model decides which expert to forward each input to based on\n==========\nPrompt: 28 tokens, 201.548 tokens-per-sec\nGeneration: 96 tokens, 175.009 tokens-per-sec\nPeak memory: 9.047 GB\n"
  },
  {
    "model": "mlx-6bit",
    "prompt": "Say hello in one short sentence.",
    "returncode": 0,
    "repetition_flag": false,
    "output_tail": "==========\n<think>\nThe user asks: \"Say hello in one short sentence.\" So we need to respond with a single short sentence that says hello. For example: \"Hello!\" or \"Greetings!\" That's one short sentence. Must not add extra commentary. So answer: Hello! Or \"Greetings!\" The instruction: \"Say hello in one short sentence.\" So we can say \"Hello!\" That's a short sentence. Provide that. No extra formatting. So just\n==========\nPrompt: 16 tokens, 136.991 tokens-per-sec\nGeneration: 96 tokens, 185.245 tokens-per-sec\nPeak memory: 8.837 GB\n"
  },
  {
    "model": "mlx-6bit",
    "prompt": "What tools would you use to check the weather in Austin, TX?",
    "returncode": 0,
    "repetition_flag": false,
    "output_tail": "==========\n<think>\nOkay, the user is asking about tools to check the weather in Austin, TX. Let me think about the different options available. First, I should consider both free and paid tools. Weather apps are a common choice, like the built-in Weather app on smartphones. Then there are dedicated weather websites like Weather.com or AccuWeather. Maybe also mention the National Weather Service for official forecasts.\n\nI should also think about real-time tools. Weather radios or smart home devices like\n==========\nPrompt: 23 tokens, 193.694 tokens-per-sec\nGeneration: 96 tokens, 185.414 tokens-per-sec\nPeak memory: 8.860 GB\n"
  },
  {
    "model": "mlx-6bit",
    "prompt": "Write a native LFM tool call to open https://example.com using browser_navigate.",
    "returncode": 0,
    "repetition_flag": false,
    "output_tail": "==========\n<think>\nThe user asks: \"Write a native LFM tool call to open https://example.com using browser_navigate.\"\n\nWe need to interpret: LFM is likely \"Language Model Framework\"? Or maybe \"LFM\" is a tool naming. However, the user likely wants a tool call in the LFM format (like a JSON with name of tool and arguments). They want to open a URL using a browser. The tool name is \"browser_navigate\n==========\nPrompt: 28 tokens, 222.563 tokens-per-sec\nGeneration: 96 tokens, 185.543 tokens-per-sec\nPeak memory: 8.869 GB\n"
  },
  {
    "model": "mlx-6bit",
    "prompt": "After <tool_response>{\"status\":\"ok\"}</tool_response>, give a short final answer.",
    "returncode": 0,
    "repetition_flag": false,
    "output_tail": "==========\n<think>\nThe user says: \"After <tool_response>{\"status\":\"ok\"}</tool_response>, give a short final answer.\"\n\nWe need to respond with a short final answer. However we have no context of what the tool response was. The system says we are a helpful assistant. The user didn't ask a new question; they just gave a previous tool response and ask to give a short final answer. Possibly they want a concise answer summarizing something? But\n==========\nPrompt: 29 tokens, 226.877 tokens-per-sec\nGeneration: 96 tokens, 185.389 tokens-per-sec\nPeak memory: 8.870 GB\n"
  },
  {
    "model": "mlx-6bit",
    "prompt": "Do not use tools: explain what a router does in a MoE model in one sentence.",
    "returncode": 0,
    "repetition_flag": false,
    "output_tail": "==========\n<think>\nThe user asks: \"Do not use tools: explain what a router does in a MoE model in one sentence.\" So we need to produce a single sentence, no tools, no extra formatting. Provide a concise explanation: In a Mixture of Experts (MoE) model, the router (or gating network) decides which expert to forward each input to. So one sentence: \"A router in a MoE model assigns each input to the most appropriate expert\n==========\nPrompt: 28 tokens, 215.728 tokens-per-sec\nGeneration: 96 tokens, 185.453 tokens-per-sec\nPeak memory: 8.869 GB\n"
  }
]