{
  "format": "6bit",
  "strict_reload": true,
  "finite_prefill_decode_logits": true,
  "cache_offsets_correct": true,
  "source_sidecars_identical": true,
  "native_thinking_template_preserved": true,
  "temperature": 0.0,
  "max_tokens": 512,
  "smoke_tests": [
    {
      "task": "arithmetic",
      "prompt": "What is 17 multiplied by 23? Give the answer.",
      "text": "<think>We need answer simple multiplication. Need maybe just answer. 17*23=391. Ensure no extra? User asks \"What is 17 multiplied by 23? Give the answer.\" So final maybe 391.</think>391",
      "answer": "391",
      "checks": {
        "expected_391": true
      },
      "generated_tokens": 48,
      "seconds": 0.5709626669995487
    },
    {
      "task": "retrieval",
      "prompt": "The passcode is 941731. Repeat the passcode exactly.",
      "text": "<think>The user is asking me to repeat a passcode exactly. This is a simple request. I should just repeat it back exactly as given.\n\nThe passcode is 941731.\n\nI should repeat it exactly. No need for extra commentary unless helpful. The instruction says \"Repeat the passcode exactly.\" So I should just output the passcode.</think>941731",
      "answer": "941731",
      "checks": {
        "expected_passcode": true
      },
      "generated_tokens": 70,
      "seconds": 0.7855458341073245
    },
    {
      "task": "code",
      "prompt": "Write a Python function add(a, b) that returns a + b.",
      "text": "<think>We need to write a Python function add(a, b) that returns a + b. This is straightforward. The user likely expects a simple implementation.\n\nWe should provide the code, maybe with a brief explanation.\n\nThe instruction: \"Write a Python function add(a, b) that returns a + b.\"\n\nSo we can just output:\n\ndef add(a, b):\n    return a + b\n\nWe might also include a docstring or example usage, but the core is simple.\n\nSince the user asked to write the function, we should just provide the code. Possibly in a code block.\n\nLet's respond with the function definition and maybe a quick test.</think>Here's a simple Python function that adds two numbers:\n\n```python\ndef add(a, b):\n    \"\"\"Return the sum of a and b.\"\"\"\n    return a + b\n```\n\nYou can use it like this:\n\n```python\nresult = add(3, 5)  # result will be 8\n```",
      "answer": "Here's a simple Python function that adds two numbers:\n\n```python\ndef add(a, b):\n    \"\"\"Return the sum of a and b.\"\"\"\n    return a + b\n```\n\nYou can use it like this:\n\n```python\nresult = add(3, 5)  # result will be 8\n```",
      "checks": {
        "add_function": true
      },
      "generated_tokens": 196,
      "seconds": 2.3982239169999957
    }
  ],
  "all_smoke_checks_pass": true,
  "device": {
    "device_name": "Apple M5 Max",
    "max_recommended_working_set_size": 115448725504,
    "memory_size": 137438953472,
    "architecture": "applegpu_g17s",
    "max_buffer_length": 86586540032,
    "resource_limit": 499000
  },
  "mlx_version": "0.32.4",
  "mlx_vlm_version": "0.7.10",
  "converter_revision": "6d9ba328abbd6129c7461eda86280aa9fbfd9986",
  "python": "3.12.15",
  "peak_active_gb": 32.405607624,
  "seconds": 8.617207458009943,
  "swap_before": "vm.swapusage: total = 10240.00M  used = 8736.50M  free = 1503.50M  (encrypted)",
  "swap_after": "vm.swapusage: total = 10240.00M  used = 8736.50M  free = 1503.50M  (encrypted)",
  "limits": "Three synthetic smoke prompts and finite/cache checks; not a quality benchmark or proof of parity to BF16/Transformers."
}