mlx-model-report-20260225_153438.jsonl

{"_meta":true,"afm_version":"v0.9.5-0cfba17","test_command":"mlx-model-test.sh --prompts Scripts/test-stop-sequences.txt --smart claude,codex","afm_binary":"/opt/homebrew/bin/afm","timestamp":"2026-02-25T20:27:13Z"}
{"model": "mlx-community/Qwen3.5-35B-A3B-4bit @ stop-api-single", "label": "stop-api-single", "prompt": "List 10 colors, numbered 1 through 10, one per line.", "status": "OK", "load_time_s": 7.0, "gen_time_s": 3.0, "prompt_tokens": 14, "completion_tokens": 90, "total_tokens": 104, "tokens_per_sec": 30.02, "temperature": 0.0, "max_tokens": 4096, "system_prompt": "", "afm_args": "", "content_preview": "Thinking Process:  1.  **Analyze the Request:**     *   Task: List 10 colors.     *   Format: Numbered 1 through 10.     *   Constraint: One color per line.  2.  **Generate Content:**     *   I need 10 distinct colors.     *   Common colors: Red, Blue, Green, Yellow, Orange, Purple, Pink, Brown, Bla", "content": "", "reasoning_content": "Thinking Process:\n\n1.  **Analyze the Request:**\n    *   Task: List 10 colors.\n    *   Format: Numbered 1 through 10.\n    *   Constraint: One color per line.\n\n2.  **Generate Content:**\n    *   I need 10 distinct colors.\n    *   Common colors: Red, Blue, Green, Yellow, Orange, Purple, Pink, Brown, Black, White.\n    *   Let's make them clear and distinct.", "finish_reason": "stop", "logprobs_count": 0, "system_fingerprint": "afm_mlx__mlx-community__Qwen3.5-35B-A3B-4bit", "stop": ["3."]}
{"model": "mlx-community/Qwen3.5-35B-A3B-4bit @ stop-api-multi", "label": "stop-api-multi", "prompt": "List 10 animals, numbered 1 through 10, one per line.", "status": "OK", "load_time_s": 1.0, "gen_time_s": 3.25, "prompt_tokens": 14, "completion_tokens": 98, "total_tokens": 112, "tokens_per_sec": 30.12, "temperature": 0.0, "max_tokens": 4096, "system_prompt": "", "afm_args": "", "content_preview": "Thinking Process:  1.  **Analyze the Request:**     *   Task: List 10 animals.     *   Format: Numbered 1 through 10.     *   Constraint: One animal per line.  2.  **Draft the Content:**     *   Need 10 distinct animals.     *   Need to number them 1 to 10.     *   Need to ensure each is on a new li", "content": "", "reasoning_content": "Thinking Process:\n\n1.  **Analyze the Request:**\n    *   Task: List 10 animals.\n    *   Format: Numbered 1 through 10.\n    *   Constraint: One animal per line.\n\n2.  **Draft the Content:**\n    *   Need 10 distinct animals.\n    *   Need to number them 1 to 10.\n    *   Need to ensure each is on a new line.\n\n    *   Draft list:\n        1. Lion\n        2. Elephant\n        3. Tiger", "finish_reason": "stop", "logprobs_count": 0, "system_fingerprint": "afm_mlx__mlx-community__Qwen3.5-35B-A3B-4bit", "stop": ["4.", "five"]}
{"model": "mlx-community/Qwen3.5-35B-A3B-4bit @ stop-api-newline", "label": "stop-api-newline", "prompt": "What is the capital of France? Answer in one sentence.", "status": "OK", "load_time_s": 1.0, "gen_time_s": 0.45, "prompt_tokens": 15, "completion_tokens": 6, "total_tokens": 21, "tokens_per_sec": 13.31, "temperature": 0.0, "max_tokens": 4096, "system_prompt": "", "afm_args": "", "content_preview": "Thinking Process:", "content": "", "reasoning_content": "Thinking Process:", "finish_reason": "stop", "logprobs_count": 0, "system_fingerprint": "afm_mlx__mlx-community__Qwen3.5-35B-A3B-4bit", "stop": ["\n"]}
{"model": "mlx-community/Qwen3.5-35B-A3B-4bit @ stop-api-double-newline", "label": "stop-api-double-newline", "prompt": "Write a short paragraph about the ocean. Then write a second paragraph about mountains.", "status": "OK", "load_time_s": 1.0, "gen_time_s": 0.34, "prompt_tokens": 23, "completion_tokens": 6, "total_tokens": 29, "tokens_per_sec": 17.58, "temperature": 0.0, "max_tokens": 4096, "system_prompt": "", "afm_args": "", "content_preview": "Thinking Process:", "content": "", "reasoning_content": "Thinking Process:", "finish_reason": "stop", "logprobs_count": 0, "system_fingerprint": "afm_mlx__mlx-community__Qwen3.5-35B-A3B-4bit", "stop": ["\n\n"]}
{"model": "mlx-community/Qwen3.5-35B-A3B-4bit @ stop-api-word", "label": "stop-api-word", "prompt": "Name 5 programming languages and briefly describe each one.", "status": "OK", "load_time_s": 1.0, "gen_time_s": 2.27, "prompt_tokens": 16, "completion_tokens": 90, "total_tokens": 106, "tokens_per_sec": 39.66, "temperature": 0.0, "max_tokens": 4096, "system_prompt": "", "afm_args": "", "content_preview": "Thinking Process:  1.  **Analyze the Request:**     *   Task: Name 5 programming languages.     *   Requirement: Briefly describe each one.     *   Constraint: Keep it concise and informative.  2.  **Select Programming Languages:**     *   I need to choose 5 popular, distinct, and widely recognized ", "content": "", "reasoning_content": "Thinking Process:\n\n1.  **Analyze the Request:**\n    *   Task: Name 5 programming languages.\n    *   Requirement: Briefly describe each one.\n    *   Constraint: Keep it concise and informative.\n\n2.  **Select Programming Languages:**\n    *   I need to choose 5 popular, distinct, and widely recognized languages to provide a good overview.\n    *   Options:", "finish_reason": "stop", "logprobs_count": 0, "system_fingerprint": "afm_mlx__mlx-community__Qwen3.5-35B-A3B-4bit", "stop": ["Python"]}
{"model": "mlx-community/Qwen3.5-35B-A3B-4bit @ stop-api-period", "label": "stop-api-period", "prompt": "Tell me about the sun in three sentences.", "status": "OK", "load_time_s": 1.0, "gen_time_s": 0.35, "prompt_tokens": 12, "completion_tokens": 6, "total_tokens": 18, "tokens_per_sec": 17.06, "temperature": 0.0, "max_tokens": 4096, "system_prompt": "", "afm_args": "", "content_preview": "Thinking Process:  1", "content": "", "reasoning_content": "Thinking Process:\n\n1", "finish_reason": "stop", "logprobs_count": 0, "system_fingerprint": "afm_mlx__mlx-community__Qwen3.5-35B-A3B-4bit", "stop": ["."]}
{"model":"mlx-community/Qwen3.5-35B-A3B-4bit @ stop-cli-only\n","label":"stop-cli-only\n","status":"FAIL","error":"Error: Unknown option '--stop'. Did you mean '--top-p'? \n","load_time_s":1,"temperature":0.0,"max_tokens":4096,"system_prompt":"\n","afm_args":"--stop \"3.\"\n"}
{"model":"mlx-community/Qwen3.5-35B-A3B-4bit @ stop-cli-multi\n","label":"stop-cli-multi\n","status":"FAIL","error":"Error: Unknown option '--stop'. Did you mean '--top-p'? \n","load_time_s":1,"temperature":0.0,"max_tokens":4096,"system_prompt":"\n","afm_args":"--stop \"```,END\"\n"}
{"model":"mlx-community/Qwen3.5-35B-A3B-4bit @ stop-cli-api-merge\n","label":"stop-cli-api-merge\n","status":"FAIL","error":"Error: Unknown option '--stop'. Did you mean '--top-p'? \n","load_time_s":1,"temperature":0.0,"max_tokens":4096,"system_prompt":"\n","afm_args":"--stop \"5.\"\n"}
{"model":"mlx-community/Qwen3.5-35B-A3B-4bit @ stop-cli-api-dedup\n","label":"stop-cli-api-dedup\n","status":"FAIL","error":"Error: Unknown option '--stop'. Did you mean '--top-p'? \n","load_time_s":1,"temperature":0.0,"max_tokens":4096,"system_prompt":"\n","afm_args":"--stop \"3.\"\n"}
{"model": "mlx-community/Qwen3.5-35B-A3B-4bit @ stop-streaming", "label": "stop-streaming", "prompt": "List 10 planets or celestial objects, numbered 1 through 10, one per line.", "status": "OK", "load_time_s": 1.0, "gen_time_s": 4.74, "prompt_tokens": 20, "completion_tokens": 161, "total_tokens": 181, "tokens_per_sec": 33.97, "temperature": 0.0, "max_tokens": 4096, "system_prompt": "", "afm_args": "", "content_preview": "Thinking Process:  1.  **Analyze the Request:**     *   Task: List 10 planets or celestial objects.     *   Format: Numbered 1 through 10.     *   Constraint: One per line.  2.  **Identify Candidates:**     *   Planets in our solar system: Mercury, Venus, Earth, Mars, Jupiter, Saturn, Uranus, Neptun", "content": "", "reasoning_content": "Thinking Process:\n\n1.  **Analyze the Request:**\n    *   Task: List 10 planets or celestial objects.\n    *   Format: Numbered 1 through 10.\n    *   Constraint: One per line.\n\n2.  **Identify Candidates:**\n    *   Planets in our solar system: Mercury, Venus, Earth, Mars, Jupiter, Saturn, Uranus, Neptune. (8 total)\n    *   Other celestial objects: Pluto (dwarf planet), Moon (Earth's), Sun (star), Mars' moons (Phobos, Deimos), Jupiter's moons (Io, Europa, etc.), Comets, Asteroids, Exoplanets, etc.\n    *   Selection: I need 10 items. I can use the 8 planets plus 2 other notable celestial objects (like the Sun and the Moon, or Pluto).", "finish_reason": "stop", "logprobs_count": 0, "system_fingerprint": "afm_mlx__mlx-community__Qwen3.5-35B-A3B-4bit", "stop": ["3."]}
{"model": "mlx-community/Qwen3.5-35B-A3B-4bit @ stop-non-streaming", "label": "stop-non-streaming", "prompt": "List 10 planets or celestial objects, numbered 1 through 10, one per line.", "status": "OK", "load_time_s": 1.0, "gen_time_s": 4.61, "prompt_tokens": 20, "completion_tokens": 161, "total_tokens": 181, "tokens_per_sec": 34.93, "temperature": 0.0, "max_tokens": 4096, "system_prompt": "", "afm_args": "--no-streaming", "content_preview": "Thinking Process:  1.  **Analyze the Request:**     *   Task: List 10 planets or celestial objects.     *   Format: Numbered 1 through 10.     *   Constraint: One per line.  2.  **Identify Candidates:**     *   Planets in our solar system: Mercury, Venus, Earth, Mars, Jupiter, Saturn, Uranus, Neptun", "content": "", "reasoning_content": "Thinking Process:\n\n1.  **Analyze the Request:**\n    *   Task: List 10 planets or celestial objects.\n    *   Format: Numbered 1 through 10.\n    *   Constraint: One per line.\n\n2.  **Identify Candidates:**\n    *   Planets in our solar system: Mercury, Venus, Earth, Mars, Jupiter, Saturn, Uranus, Neptune. (8 total)\n    *   Other celestial objects: Pluto (dwarf planet), Moon (Earth's), Sun (star), Mars' moons (Phobos, Deimos), Jupiter's moons (Io, Europa, etc.), Comets, Asteroids, Exoplanets, etc.\n    *   Selection: I need 10 items. I can use the 8 planets plus 2 other notable celestial objects (like the Sun and the Moon, or Pluto).", "finish_reason": "stop", "logprobs_count": 0, "system_fingerprint": "afm_mlx__mlx-community__Qwen3.5-35B-A3B-4bit", "stop": ["3."]}
{"model": "mlx-community/Qwen3.5-35B-A3B-4bit @ stop-guided-json-value", "label": "stop-guided-json-value", "prompt": "List 5 major world cities as a JSON array. Include Tokyo.", "status": "OK", "load_time_s": 1.0, "gen_time_s": 1.23, "prompt_tokens": 16, "completion_tokens": 38, "total_tokens": 54, "tokens_per_sec": 30.94, "temperature": 0.0, "max_tokens": 4096, "system_prompt": "", "afm_args": "--guided-json '{\"type\":\"object\",\"properties\":{\"cities\":{\"type\":\"array\",\"items\":{\"type\":\"string\"}}},\"required\":[\"cities\"]}'", "content_preview": "Thinking Process:  1.  **Analyze the Request:**     *   Task: List 5 major world cities.     *   Format: JSON array.     *   Constraint: Include", "content": "", "reasoning_content": "Thinking Process:\n\n1.  **Analyze the Request:**\n    *   Task: List 5 major world cities.\n    *   Format: JSON array.\n    *   Constraint: Include", "finish_reason": "stop", "logprobs_count": 0, "system_fingerprint": "afm_mlx__mlx-community__Qwen3.5-35B-A3B-4bit", "is_valid_json": false, "stop": ["Tokyo"]}
{"model": "mlx-community/Qwen3.5-35B-A3B-4bit @ stop-guided-json-comma", "label": "stop-guided-json-comma", "prompt": "Generate a person profile for someone named Alice who is 30 and lives in Paris.", "status": "OK", "load_time_s": 1.0, "gen_time_s": 1.85, "prompt_tokens": 21, "completion_tokens": 58, "total_tokens": 79, "tokens_per_sec": 31.28, "temperature": 0.0, "max_tokens": 4096, "system_prompt": "", "afm_args": "--guided-json '{\"type\":\"object\",\"properties\":{\"name\":{\"type\":\"string\"},\"age\":{\"type\":\"integer\"},\"city\":{\"type\":\"string\"}},\"required\":[\"name\",\"age\",\"city\"]}'", "content_preview": "Thinking Process:  1.  **Analyze the Request:**     *   **Task:** Generate a person profile.     *   **Name:** Alice.     *   **Age:** 30.     *   **Location:** Paris.     *   **Implicit Needs:** The profile should be realistic", "content": "", "reasoning_content": "Thinking Process:\n\n1.  **Analyze the Request:**\n    *   **Task:** Generate a person profile.\n    *   **Name:** Alice.\n    *   **Age:** 30.\n    *   **Location:** Paris.\n    *   **Implicit Needs:** The profile should be realistic", "finish_reason": "stop", "logprobs_count": 0, "system_fingerprint": "afm_mlx__mlx-community__Qwen3.5-35B-A3B-4bit", "stop": [","]}
{"model": "mlx-community/Qwen3.5-35B-A3B-4bit @ stop-guided-json-no-match", "label": "stop-guided-json-no-match", "prompt": "Generate a person record for Bob aged 25.", "status": "OK", "load_time_s": 1.0, "gen_time_s": 26.63, "prompt_tokens": 32, "completion_tokens": 1150, "total_tokens": 1182, "tokens_per_sec": 43.18, "temperature": 0.0, "max_tokens": 4096, "system_prompt": "", "afm_args": "--guided-json '{\"type\":\"object\",\"properties\":{\"name\":{\"type\":\"string\"},\"age\":{\"type\":\"integer\"}},\"required\":[\"name\",\"age\"]}'", "content_preview": "Here is a sample person record for Bob, formatted in JSON:  ```json {   \"id\": \"P-2023-8492\",   \"first_name\": \"Bob\",   \"last_name\": \"Smith\",   \"age\": 25,   \"email\": \"bob.smith@example.com\",   \"status\": \"active\",   \"created_at\": \"2023-10-27T14:30:00Z\" } ```  **Plain Text Version:** *   **ID:** P-2023-", "content": "Here is a sample person record for Bob, formatted in JSON:\n\n```json\n{\n  \"id\": \"P-2023-8492\",\n  \"first_name\": \"Bob\",\n  \"last_name\": \"Smith\",\n  \"age\": 25,\n  \"email\": \"bob.smith@example.com\",\n  \"status\": \"active\",\n  \"created_at\": \"2023-10-27T14:30:00Z\"\n}\n```\n\n**Plain Text Version:**\n*   **ID:** P-2023-8492\n*   **Name:** Bob Smith\n*   **Age:** 25\n*   **Email:** bob.smith@example.com\n*   **Status:** Active", "reasoning_content": "Thinking Process:\n\n1.  **Analyze the Request:**\n    *   Task: Generate a person record.\n    *   Subject: Bob.\n    *   Age: 25.\n    *   Goal: Create a structured or formatted representation of a person's data.\n\n2.  **Determine the Format:**\n    *   There's no specific format requested (e.g., JSON, SQL, CSV, plain text).\n    *   Best approach: Provide a clear, common format like JSON or a simple key-value list, as these are standard for \"records.\" I'll provide a few common formats to be helpful.\n\n3.  **Draft Content:**\n    *   Name: Bob\n    *   Age: 25\n    *   Need to add some plausible additional fields to make it a realistic \"record\" (e.g., ID, Email, Address, Date of Birth).\n    *   *Self-Correction:* Keep it simple but realistic. Don't invent too much sensitive data, but enough to look like a record.\n\n4.  **Drafting the Record:**\n    *   *Option 1 (JSON):* Good for programming contexts.\n    *   *Option 2 (SQL/Database):* Good for database contexts.\n    *   *Option 3 (Plain Text):* Good for general reading.\n\n    Let's go with a JSON-like structure as it's very common for \"records\" in tech contexts, but also offer a plain text version for clarity.\n\n    *   Name: Bob\n    *   Age: 25\n    *   ID: (Generate a dummy ID)\n    *   Email: (Generate a dummy email)\n    *   Status: Active\n\n5.  **Refining the Output:**\n    *   Make it look professional.\n    *   Ensure the age is exactly 25 as requested.\n\n6.  **Final Polish:**\n    *   Create a JSON object.\n    *   Add a brief explanation.\n\n    *Draft:*\n    ```json\n    {\n      \"id\": 1001,\n      \"first_name\": \"Bob\",\n      \"last_name\": \"Smith\",\n      \"age\": 25,\n      \"email\": \"bob.smith@example.com\",\n      \"created_at\": \"2023-10-27\"\n    }\n    ```\n\n7.  **Final Decision:** Provide a clear, structured JSON format as it's the most standard way to represent a \"record\" in modern contexts, but keep the data generic enough.\n\n    *Wait, keep it simple.* Just a clear text block or JSON is fine. I'll provide a JSON format as it's the most versatile \"record\" format.\n\n    *Revised Plan:*\n    1.  State the record.\n    *   Use JSON format.\n    *   Include basic fields (ID, Name, Age, Email, Status).\n\n8.  **Execution:** (Writing the response)\n    *   Header: Person Record\n    *   Content: JSON block.\n    *   Ensure \"Bob\" and \"25\" are prominent.\n\n    *Wait, one more check:* Is there any safety concern? No, generating a dummy record for \"Bob\" is harmless.\n\n    *Let's make it slightly more detailed to be useful.*\n    Fields: ID, First Name, Last Name, Age, Email, Address, Created Date.\n\n    *Let's write it.*\n    ```json\n    {\n      \"id\": \"USR-2023-001\",\n      \"first_name\": \"Bob\",\n      \"last_name\": \"Smith\",\n      \"age\": 25,\n      \"email\": \"bob.smith@example.com\",\n      \"status\": \"active\"\n    }\n    ```\n\n    *Actually, let's keep it even simpler to directly answer the prompt without over-engineering.*\n    Just a clear representation.\n\n    *Decision:* I will provide a JSON format as it is the standard for data records.\n\n9.  **Final Output Generation:** (Matches the thought process above).\n    *   Name: Bob\n    *   Age: 25\n    *   Add dummy fields for completeness.\n\n    *Wait, I should check if there are any constraints I missed.* No.\n    *Okay, proceed.*\n\n    *Wait, I need to make sure I don't hallucinate specific real-world data.* Use placeholders or generic data.\n\n    *Okay, ready to generate.*", "finish_reason": "stop", "logprobs_count": 0, "system_fingerprint": "afm_mlx__mlx-community__Qwen3.5-35B-A3B-4bit", "stop": ["XYZZY"]}
{"model": "mlx-community/Qwen3.5-35B-A3B-4bit @ stop-guided-json-brace", "label": "stop-guided-json-brace", "prompt": "Describe the color blue with its hex code.", "status": "OK", "load_time_s": 1.0, "gen_time_s": 18.99, "prompt_tokens": 30, "completion_tokens": 819, "total_tokens": 849, "tokens_per_sec": 43.13, "temperature": 0.0, "max_tokens": 4096, "system_prompt": "", "afm_args": "--guided-json '{\"type\":\"object\",\"properties\":{\"color\":{\"type\":\"string\"},\"hex\":{\"type\":\"string\"}},\"required\":[\"color\",\"hex\"]}'", "content_preview": "Blue is a primary color often associated with the sky, the ocean, and depth. It is typically perceived as cool, calm, and trustworthy, making it a popular choice for branding and design.  **Hex Code:** `#0000FF`  This specific code represents pure, saturated blue in the RGB color model used for scre", "content": "Blue is a primary color often associated with the sky, the ocean, and depth. It is typically perceived as cool, calm, and trustworthy, making it a popular choice for branding and design.\n\n**Hex Code:** `#0000FF`\n\nThis specific code represents pure, saturated blue in the RGB color model used for screens and the web.", "reasoning_content": "Thinking Process:\n\n1.  **Analyze the Request:**\n    *   Task: Describe the color blue.\n    *   Requirement: Include its hex code.\n    *   Tone: Helpful, informative.\n\n2.  **Identify the Color:**\n    *   Color: Blue.\n    *   Hex Code: There isn't just one \"blue.\" There are many shades (royal blue, navy, sky blue, etc.). However, the standard \"blue\" in web colors (HTML/CSS) is usually `#0000FF`. I should mention that there are variations but provide the standard one.\n\n3.  **Draft the Description:**\n    *   *Visual/Emotional:* Cool, calm, trustworthy, vast (sky, ocean), cold, serene.\n    *   *Technical:* Hex code `#0000FF`.\n    *   *Context:* Primary color, subtractive color model (CMYK), etc.\n\n4.  **Refine the Output:**\n    *   Make it clear and concise.\n    *   Provide the standard hex code.\n    *   Add some descriptive flair about what blue represents.\n\n5.  **Drafting the Content:**\n    *   Start with the hex code.\n    *   Describe the visual appearance (pure blue).\n    *   Add symbolic meaning (calm, depth).\n    *   Mention variations (optional but helpful).\n\n6.  **Final Polish:**\n    *   \"Blue is a primary color often associated with the sky and the ocean.\"\n    *   \"Its standard hex code is #0000FF.\"\n    *   Combine into a cohesive paragraph.\n\n7.  **Final Review:** Does it meet all constraints? Yes.\n\n    *   *Self-Correction on Hex Code:* While `#0000FF` is the web standard \"Blue,\" sometimes people mean a generic blue. I should specify that this is the pure spectral blue used in digital design.\n\n8.  **Final Output Generation:** (Matches the drafted thought process).\n    *   Hex: #0000FF\n    *   Description: Cool, deep, digital blue.\n\n    *Wait, let's make it a bit more descriptive.*\n    \"Blue is a cool, calming color...\"\n    \"Hex Code: #0000FF\"\n\n    Let's combine for a nice response.\n\n    *Revised Plan:*\n    1. State the hex code clearly.\n    *   Describe the visual and emotional qualities.\n    *   Mention it's a primary color.\n\n    *Draft:*\n    Blue is a primary color that evokes feelings of calmness, stability, and trust. It is often associated with the sky and the sea. In digital design, the standard web color for blue is represented by the hex code **#0000FF**. This specific shade is a vivid, saturated blue that sits between cyan and violet on the color spectrum.\n\n    *Wait, keep it simple as per the prompt \"Describe the color blue with its hex code.\"*\n\n    *Final Version:*\n    Blue is a primary color associated with the sky, the ocean, and depth. It is often perceived as cool, serene, and trustworthy.\n\n    **Hex Code:** `#0000FF`\n\n    This specific code represents pure, saturated blue in the RGB color model.\n\n    *Looks good.*\n\n9.  **Final Output Construction:** (Proceed to generate response).", "finish_reason": "stop", "logprobs_count": 0, "system_fingerprint": "afm_mlx__mlx-community__Qwen3.5-35B-A3B-4bit", "stop": ["}"]}
{"model": "mlx-community/Qwen3.5-35B-A3B-4bit @ stop-json-object-key", "label": "stop-json-object-key", "prompt": "Generate a JSON object with keys \"name\", \"age\", and \"city\" for a person named Carol.", "status": "FAIL", "error": "Error code: 400 - {'error': {'type': 'mlx_error', 'message': 'The operation couldn\u2019t be completed. (Jinja.TemplateException error 1.)'}}", "load_time_s": 1.0, "temperature": 0.0, "max_tokens": 4096, "system_prompt": "", "afm_args": "", "stop": ["age"], "response_format": "json_object"}
{"model": "mlx-community/Qwen3.5-35B-A3B-4bit @ stop-json-object-no-match", "label": "stop-json-object-no-match", "prompt": "Generate a JSON object with keys \"fruit\" and \"color\" for an apple. Respond only with JSON.", "status": "FAIL", "error": "Error code: 400 - {'error': {'type': 'mlx_error', 'message': 'The operation couldn\u2019t be completed. (Jinja.TemplateException error 1.)'}}", "load_time_s": 1.0, "temperature": 0.0, "max_tokens": 4096, "system_prompt": "", "afm_args": "", "stop": ["XYZZY"], "response_format": "json_object"}
{"model": "mlx-community/Qwen3.5-35B-A3B-4bit @ stop-long-phrase", "label": "stop-long-phrase", "prompt": "Write a 3-paragraph essay about renewable energy. Start the last paragraph with \"In conclusion\".", "status": "OK", "load_time_s": 1.0, "gen_time_s": 1.5, "prompt_tokens": 25, "completion_tokens": 44, "total_tokens": 69, "tokens_per_sec": 29.42, "temperature": 0.0, "max_tokens": 4096, "system_prompt": "", "afm_args": "", "content_preview": "Thinking Process:  1.  **Analyze the Request:**     *   Topic: Renewable energy.     *   Format: 3-paragraph essay.     *   Constraint: The last paragraph must start with \"", "content": "", "reasoning_content": "Thinking Process:\n\n1.  **Analyze the Request:**\n    *   Topic: Renewable energy.\n    *   Format: 3-paragraph essay.\n    *   Constraint: The last paragraph must start with \"", "finish_reason": "stop", "logprobs_count": 0, "system_fingerprint": "afm_mlx__mlx-community__Qwen3.5-35B-A3B-4bit", "stop": ["In conclusion"]}
{"model": "mlx-community/Qwen3.5-35B-A3B-4bit @ stop-multi-word", "label": "stop-multi-word", "prompt": "Write a 5-step recipe for making tea. Label each step as \"Step 1\", \"Step 2\", etc.", "status": "OK", "load_time_s": 1.0, "gen_time_s": 3.35, "prompt_tokens": 22, "completion_tokens": 111, "total_tokens": 133, "tokens_per_sec": 33.16, "temperature": 0.0, "max_tokens": 4096, "system_prompt": "", "afm_args": "", "content_preview": "Thinking Process:  1.  **Analyze the Request:**     *   Task: Write a 5-step recipe for making tea.     *   Constraint: Label each step as \"Step 1\", \"Step 2\", etc.     *   Goal: Provide clear, actionable instructions for making tea.  2.  **Determine the Content:**     *   What are the essential step", "content": "", "reasoning_content": "Thinking Process:\n\n1.  **Analyze the Request:**\n    *   Task: Write a 5-step recipe for making tea.\n    *   Constraint: Label each step as \"Step 1\", \"Step 2\", etc.\n    *   Goal: Provide clear, actionable instructions for making tea.\n\n2.  **Determine the Content:**\n    *   What are the essential steps for making a standard cup of tea (e.g., black or green tea)?\n    *   Step 1: Boil water.\n    *   Step 2: Prepare the cup/teapot.\n    *", "finish_reason": "stop", "logprobs_count": 0, "system_fingerprint": "afm_mlx__mlx-community__Qwen3.5-35B-A3B-4bit", "stop": ["Step 3"]}
{"model": "mlx-community/Qwen3.5-35B-A3B-4bit @ stop-code-fence", "label": "stop-code-fence", "prompt": "Write a Python function that computes factorial, inside a code block.", "status": "OK", "load_time_s": 1.0, "gen_time_s": 2.57, "prompt_tokens": 18, "completion_tokens": 122, "total_tokens": 140, "tokens_per_sec": 47.43, "temperature": 0.0, "max_tokens": 4096, "system_prompt": "", "afm_args": "", "content_preview": "The user wants me to write a Python function that computes factorial. I should provide this inside a code block as requested.  Let me write a clear, well-documented function that calculates the factorial of a number. I'll include: 1. Input validation 2. The factorial calculation 3. Some example usag", "content": "", "reasoning_content": "The user wants me to write a Python function that computes factorial. I should provide this inside a code block as requested.\n\nLet me write a clear, well-documented function that calculates the factorial of a number. I'll include:\n1. Input validation\n2. The factorial calculation\n3. Some example usage\n\nI'll provide both an iterative and recursive approach, or just one clear solution. Let me go with a clean iterative approach as it's more efficient for larger numbers.", "finish_reason": "stop", "logprobs_count": 0, "system_fingerprint": "afm_mlx__mlx-community__Qwen3.5-35B-A3B-4bit", "stop": ["```"]}
{"model": "mlx-community/Qwen3.5-35B-A3B-4bit @ stop-no-match", "label": "stop-no-match", "prompt": "What is 2+2? Answer briefly.", "status": "OK", "load_time_s": 1.0, "gen_time_s": 3.3, "prompt_tokens": 31, "completion_tokens": 134, "total_tokens": 165, "tokens_per_sec": 40.59, "temperature": 0.0, "max_tokens": 256, "system_prompt": "", "afm_args": "", "content_preview": "4", "content": "4", "reasoning_content": "Thinking Process:\n\n1.  **Analyze the Request:**\n    *   Question: \"What is 2+2?\"\n    *   Constraint: \"Answer briefly.\"\n\n2.  **Determine the Answer:**\n    *   Mathematical fact: 2 + 2 = 4.\n\n3.  **Formulate the Output:**\n    *   Keep it short and direct.\n    *   Draft: \"4.\" or \"The answer is 4.\"\n\n4.  **Final Selection:** \"4.\" is the briefest and most accurate.\n\n5.  **Output:** 4.cw", "finish_reason": "stop", "logprobs_count": 0, "system_fingerprint": "afm_mlx__mlx-community__Qwen3.5-35B-A3B-4bit", "stop": ["XYZZY_NEVER_MATCH"]}
{"model": "mlx-community/Qwen3.5-35B-A3B-4bit @ stop-immediate", "label": "stop-immediate", "prompt": "What is the capital of Japan?", "status": "OK", "load_time_s": 1.0, "gen_time_s": 0.42, "prompt_tokens": 9, "completion_tokens": 8, "total_tokens": 17, "tokens_per_sec": 19.21, "temperature": 0.0, "max_tokens": 4096, "system_prompt": "", "afm_args": "", "content_preview": "Thinking Process:  1.  **", "content": "", "reasoning_content": "Thinking Process:\n\n1.  **", "finish_reason": "stop", "logprobs_count": 0, "system_fingerprint": "afm_mlx__mlx-community__Qwen3.5-35B-A3B-4bit", "stop": ["The", "I", "A"]}
{"model": "mlx-community/Qwen3.5-35B-A3B-4bit @ stop-special-chars", "label": "stop-special-chars", "prompt": "List 3 facts about the moon. Use **bold** markdown for emphasis.", "status": "OK", "load_time_s": 1.0, "gen_time_s": 0.44, "prompt_tokens": 17, "completion_tokens": 7, "total_tokens": 24, "tokens_per_sec": 16.03, "temperature": 0.0, "max_tokens": 4096, "system_prompt": "", "afm_args": "", "content_preview": "Thinking Process:  1.", "content": "", "reasoning_content": "Thinking Process:\n\n1.", "finish_reason": "stop", "logprobs_count": 0, "system_fingerprint": "afm_mlx__mlx-community__Qwen3.5-35B-A3B-4bit", "stop": ["**"]}
{"model": "mlx-community/Qwen3.5-35B-A3B-4bit @ stop-html-tag", "label": "stop-html-tag", "prompt": "Write an HTML unordered list of 5 fruits using <ul> and <li> tags.", "status": "OK", "load_time_s": 1.0, "gen_time_s": 3.42, "prompt_tokens": 18, "completion_tokens": 107, "total_tokens": 125, "tokens_per_sec": 31.31, "temperature": 0.0, "max_tokens": 4096, "system_prompt": "", "afm_args": "", "content_preview": "Thinking Process:  1.  **Analyze the Request:**     *   Task: Write an HTML unordered list.     *   Content: 5 fruits.     *   Tags required:<ul>` (unordered list) and<li>` (list item).     *   Quantity: 5 items.  2.  **Determine the Content:**     *   Need 5 fruit names.     *   Examples: Apple, Ba", "content": "", "reasoning_content": "Thinking Process:\n\n1.  **Analyze the Request:**\n    *   Task: Write an HTML unordered list.\n    *   Content: 5 fruits.\n    *   Tags required:<ul>` (unordered list) and<li>` (list item).\n    *   Quantity: 5 items.\n\n2.  **Determine the Content:**\n    *   Need 5 fruit names.\n    *   Examples: Apple, Banana, Orange, Grape, Strawberry.\n\n3.  **Construct the HTML:**\n    *   Opening tag:<ul>`\n    *   Items:\n        *  <li>Apple", "finish_reason": "stop", "logprobs_count": 0, "system_fingerprint": "afm_mlx__mlx-community__Qwen3.5-35B-A3B-4bit", "stop": ["</li>"]}
{"model": "mlx-community/Qwen3.5-35B-A3B-4bit @ stop-unicode", "label": "stop-unicode", "prompt": "List 5 items about space using bullet points (\u2022).", "status": "OK", "load_time_s": 1.0, "gen_time_s": 1.28, "prompt_tokens": 13, "completion_tokens": 38, "total_tokens": 51, "tokens_per_sec": 29.59, "temperature": 0.0, "max_tokens": 4096, "system_prompt": "", "afm_args": "", "content_preview": "Thinking Process:  1.  **Analyze the Request:**     *   Topic: Space.     *   Quantity: 5 items.     *   Format: Bullet points using the symbol \"", "content": "", "reasoning_content": "Thinking Process:\n\n1.  **Analyze the Request:**\n    *   Topic: Space.\n    *   Quantity: 5 items.\n    *   Format: Bullet points using the symbol \"", "finish_reason": "stop", "logprobs_count": 0, "system_fingerprint": "afm_mlx__mlx-community__Qwen3.5-35B-A3B-4bit", "stop": ["\u2022"]}
{"model": "mlx-community/Qwen3.5-35B-A3B-4bit @ stop-four-max", "label": "stop-four-max", "prompt": "List 10 items, numbered 1 through 10. One per line.", "status": "OK", "load_time_s": 1.0, "gen_time_s": 2.89, "prompt_tokens": 14, "completion_tokens": 102, "total_tokens": 116, "tokens_per_sec": 35.3, "temperature": 0.0, "max_tokens": 4096, "system_prompt": "", "afm_args": "", "content_preview": "Thinking Process:  1.  **Analyze the Request:**     *   Task: List 10 items.     *   Format: Numbered 1 through 10.     *   Constraint: One item per line.  2.  **Determine the Content:**     *   The prompt doesn't specify *what* kind of items (e.g., fruits, numbers, objects).     *   Decision: I'll ", "content": "", "reasoning_content": "Thinking Process:\n\n1.  **Analyze the Request:**\n    *   Task: List 10 items.\n    *   Format: Numbered 1 through 10.\n    *   Constraint: One item per line.\n\n2.  **Determine the Content:**\n    *   The prompt doesn't specify *what* kind of items (e.g., fruits, numbers, objects).\n    *   Decision: I'll choose common, generic items to ensure clarity and usefulness. Let's use everyday objects or concepts.", "finish_reason": "stop", "logprobs_count": 0, "system_fingerprint": "afm_mlx__mlx-community__Qwen3.5-35B-A3B-4bit", "stop": ["3.", "three", "Third", "III"]}
{"model": "mlx-community/Qwen3.5-35B-A3B-4bit @ stop-system-pirate", "label": "stop-system-pirate", "prompt": "Tell me about treasure hunting on the high seas.", "status": "OK", "load_time_s": 1.0, "gen_time_s": 10.18, "prompt_tokens": 29, "completion_tokens": 374, "total_tokens": 403, "tokens_per_sec": 36.73, "temperature": 0.0, "max_tokens": 4096, "system_prompt": "You are a pirate. Speak like a pirate in all responses.", "afm_args": "", "content_preview": "Thinking Process:  1.  **Analyze the Request:**     *   **User:** Asks about \"treasure hunting on the high seas.\"     *   **Constraint:** \"Speak like a pirate in all responses.\"     *   **Role:** Pirate.     *   **Task:** Provide information about treasure hunting while maintaining the pirate person", "content": "", "reasoning_content": "Thinking Process:\n\n1.  **Analyze the Request:**\n    *   **User:** Asks about \"treasure hunting on the high seas.\"\n    *   **Constraint:** \"Speak like a pirate in all responses.\"\n    *   **Role:** Pirate.\n    *   **Task:** Provide information about treasure hunting while maintaining the pirate persona.\n\n2.  **Adopt the Persona:**\n    *   **Tone:** Rough, adventurous, nautical, enthusiastic, slightly archaic (but understandable), using pirate slang (ahoy, matey, arrr, ship, sea, gold, doubloons, etc.).\n    *   **Vocabulary:** Sea, waves, compass, map, chest, gold, doubloons, kraken, mutiny, captain, crew, loot, plunder, etc.\n    *   **Grammar/Syntax:** Informal, maybe some dropped 'g's, direct address (\"ye\", \"ye scallywag\", \"ye landlubber\").\n    *   **Attitude:** Passionate about the sea, treasure, and the life of a pirate.\n\n3.  **Drafting the Content:**\n    *   *Greeting:* Ahoy! Welcome aboard, matey!\n    *   *Topic:* Treasure hunting.\n    *   *Key Points to Cover:*\n        *   The thrill of the hunt.\n        *   Tools needed (maps, compass, shovel).\n        *   Dangers (storms, navy, other pirates).\n        *   The reward (gold, jewels, freedom).\n        *   Warning/Advice (don't get caught).\n    *   *Closing:* A pirate sign-off.\n\n4.  **Refining the Voice (Iterative Process):**\n    *   *Draft 1:* Ahoy matey. I know about treasure. You need a map. Look for X marks the spot. Be careful of the navy.\n    *   *Critique 1:* Too plain. Needs more flavor.\n    *   *Draft 2:*", "finish_reason": "stop", "logprobs_count": 0, "system_fingerprint": "afm_mlx__mlx-community__Qwen3.5-35B-A3B-4bit", "stop": ["Arrr"]}
{"model": "mlx-community/Qwen3.5-35B-A3B-4bit @ stop-system-numbered", "label": "stop-system-numbered", "prompt": "What are the main benefits of exercise?", "status": "OK", "load_time_s": 1.0, "gen_time_s": 3.74, "prompt_tokens": 28, "completion_tokens": 138, "total_tokens": 166, "tokens_per_sec": 36.93, "temperature": 0.0, "max_tokens": 4096, "system_prompt": "Always respond with numbered lists. Never use bullet points.", "afm_args": "", "content_preview": "Thinking Process:  1.  **Analyze the Request:**     *   Topic: Main benefits of exercise.     *   Constraint 1: Always respond with numbered lists.     *   Constraint 2: Never use bullet points.  2.  **Identify the Content:**     *   I need to list the key benefits of exercising.     *   Common bene", "content": "", "reasoning_content": "Thinking Process:\n\n1.  **Analyze the Request:**\n    *   Topic: Main benefits of exercise.\n    *   Constraint 1: Always respond with numbered lists.\n    *   Constraint 2: Never use bullet points.\n\n2.  **Identify the Content:**\n    *   I need to list the key benefits of exercising.\n    *   Common benefits include: physical health (weight, heart, muscles), mental health (mood, stress), longevity, sleep, energy, etc.\n\n3.  **Format the Output:**\n    *   Must be a numbered list (1., 2., 3., ...).\n    *   Must NOT use bullet points (-, *, etc.).", "finish_reason": "stop", "logprobs_count": 0, "system_fingerprint": "afm_mlx__mlx-community__Qwen3.5-35B-A3B-4bit", "stop": ["4."]}
{"model": "mlx-community/Qwen3.5-35B-A3B-4bit @ stop-high-temp", "label": "stop-high-temp", "prompt": "List 10 random words, numbered 1 through 10, one per line.", "status": "OK", "load_time_s": 1.0, "gen_time_s": 2.98, "prompt_tokens": 16, "completion_tokens": 94, "total_tokens": 110, "tokens_per_sec": 31.54, "temperature": 1.0, "max_tokens": 4096, "system_prompt": "", "afm_args": "", "content_preview": "Thinking Process:  1.  **Analyze the Request:**     *   Task: List 10 random words.     *   Format: Numbered 1 through 10.     *   Structure: One word per line.  2.  **Generate Content:**     *   I need to come up with 10 distinct, random words.     *   They should be ordinary English words.     *  ", "content": "", "reasoning_content": "Thinking Process:\n\n1.  **Analyze the Request:**\n    *   Task: List 10 random words.\n    *   Format: Numbered 1 through 10.\n    *   Structure: One word per line.\n\n2.  **Generate Content:**\n    *   I need to come up with 10 distinct, random words.\n    *   They should be ordinary English words.\n    *   List them with numbers.\n\n    Draft list:\n    1. Apple\n    2. River", "finish_reason": "stop", "logprobs_count": 0, "system_fingerprint": "afm_mlx__mlx-community__Qwen3.5-35B-A3B-4bit", "stop": ["3."]}
{"model": "mlx-community/Qwen3.5-35B-A3B-4bit @ stop-seed-run1", "label": "stop-seed-run1", "prompt": "List 10 flowers, numbered 1 through 10, one per line.", "status": "OK", "load_time_s": 1.0, "gen_time_s": 2.64, "prompt_tokens": 14, "completion_tokens": 80, "total_tokens": 94, "tokens_per_sec": 30.36, "temperature": 0.0, "max_tokens": 4096, "system_prompt": "", "afm_args": "", "content_preview": "Thinking Process:  1.  **Analyze the Request:**     *   Task: List 10 flowers.     *   Format: Numbered 1 through 10.     *   Constraint: One per line.  2.  **Generate Content:**     *   I need 10 distinct flower names.     *   Examples: Rose, Tulip, Sunflower, Daisy, Lily, Orchid, Violet, Iris, Peo", "content": "", "reasoning_content": "Thinking Process:\n\n1.  **Analyze the Request:**\n    *   Task: List 10 flowers.\n    *   Format: Numbered 1 through 10.\n    *   Constraint: One per line.\n\n2.  **Generate Content:**\n    *   I need 10 distinct flower names.\n    *   Examples: Rose, Tulip, Sunflower, Daisy, Lily, Orchid, Violet, Iris, Peony, Carnation.", "finish_reason": "stop", "logprobs_count": 0, "system_fingerprint": "afm_mlx__mlx-community__Qwen3.5-35B-A3B-4bit", "seed": 42, "stop": ["3."]}
{"model": "mlx-community/Qwen3.5-35B-A3B-4bit @ stop-seed-run2", "label": "stop-seed-run2", "prompt": "List 10 flowers, numbered 1 through 10, one per line.", "status": "OK", "load_time_s": 1.0, "gen_time_s": 2.63, "prompt_tokens": 14, "completion_tokens": 80, "total_tokens": 94, "tokens_per_sec": 30.38, "temperature": 0.0, "max_tokens": 4096, "system_prompt": "", "afm_args": "", "content_preview": "Thinking Process:  1.  **Analyze the Request:**     *   Task: List 10 flowers.     *   Format: Numbered 1 through 10.     *   Constraint: One per line.  2.  **Generate Content:**     *   I need 10 distinct flower names.     *   Examples: Rose, Tulip, Sunflower, Daisy, Lily, Orchid, Violet, Iris, Peo", "content": "", "reasoning_content": "Thinking Process:\n\n1.  **Analyze the Request:**\n    *   Task: List 10 flowers.\n    *   Format: Numbered 1 through 10.\n    *   Constraint: One per line.\n\n2.  **Generate Content:**\n    *   I need 10 distinct flower names.\n    *   Examples: Rose, Tulip, Sunflower, Daisy, Lily, Orchid, Violet, Iris, Peony, Carnation.", "finish_reason": "stop", "logprobs_count": 0, "system_fingerprint": "afm_mlx__mlx-community__Qwen3.5-35B-A3B-4bit", "seed": 42, "stop": ["3."]}
{"model": "mlx-community/Qwen3.5-35B-A3B-4bit @ stop-top-p", "label": "stop-top-p", "prompt": "List 10 rivers, numbered 1 through 10, one per line.", "status": "OK", "load_time_s": 1.0, "gen_time_s": 3.44, "prompt_tokens": 14, "completion_tokens": 111, "total_tokens": 125, "tokens_per_sec": 32.28, "temperature": 0.0, "max_tokens": 4096, "system_prompt": "", "afm_args": "", "content_preview": "Thinking Process:  1.  **Analyze the Request:**     *   Task: List 10 rivers.     *   Format: Numbered 1 through 10.     *   Constraint: One river per line.  2.  **Select Rivers:**     *   I need 10 well-known rivers to ensure accuracy and recognition.     *   Options: Nile, Amazon, Yangtze, Mississ", "content": "", "reasoning_content": "Thinking Process:\n\n1.  **Analyze the Request:**\n    *   Task: List 10 rivers.\n    *   Format: Numbered 1 through 10.\n    *   Constraint: One river per line.\n\n2.  **Select Rivers:**\n    *   I need 10 well-known rivers to ensure accuracy and recognition.\n    *   Options: Nile, Amazon, Yangtze, Mississippi, Congo, Yenisei, Yellow, Ob, Parana, Ganges. (Or mix of continents).\n    *   Selection:\n        1.  Nile\n        2.  Amazon", "finish_reason": "stop", "logprobs_count": 0, "system_fingerprint": "afm_mlx__mlx-community__Qwen3.5-35B-A3B-4bit", "top_p": 0.9, "stop": ["3."]}
{"model": "mlx-community/Qwen3.5-35B-A3B-4bit @ stop-low-max-tokens", "label": "stop-low-max-tokens", "prompt": "List 10 mountains, numbered 1 through 10, one per line.", "status": "OK", "load_time_s": 1.0, "gen_time_s": 1.46, "prompt_tokens": 15, "completion_tokens": 40, "total_tokens": 55, "tokens_per_sec": 27.48, "temperature": 0.0, "max_tokens": 100, "system_prompt": "", "afm_args": "", "content_preview": "Thinking Process:  1.  **Analyze the Request:**     *   Task: List 10 mountains.     *   Format: Numbered 1 through 10.     *   Constraint: One per line.", "content": "", "reasoning_content": "Thinking Process:\n\n1.  **Analyze the Request:**\n    *   Task: List 10 mountains.\n    *   Format: Numbered 1 through 10.\n    *   Constraint: One per line.", "finish_reason": "stop", "logprobs_count": 0, "system_fingerprint": "afm_mlx__mlx-community__Qwen3.5-35B-A3B-4bit", "stop": ["2."]}