{
  "data": {
    "a": {
      "slug": "granite-4-2-30b",
      "name": "Granite 4.2 30B",
      "vendor": "IBM",
      "vendorUrl": "https://www.ibm.com/granite",
      "kind": "weights",
      "category": "open-weights",
      "summary": "Granite 4.2 30B is IBM's open-weight dense reasoning model of 29.3B parameters, post-trained from Granite 4.1 30B Base, with switchable thinking, tool calling and a 131,072-token context, published in BF16, FP8, FP4, GGUF and MLX under Apache 2.0.",
      "url": "https://www.anchorterminal.com/tools/granite-4-2-30b",
      "markdownUrl": "https://www.anchorterminal.com/tools/granite-4-2-30b.md",
      "slimMarkdownUrl": "https://www.anchorterminal.com/tools/granite-4-2-30b.min.md",
      "jsonUrl": "https://www.anchorterminal.com/api/v1/tools/granite-4-2-30b.json",
      "dns": "granite-4-2-30b.grade.anchorterminal.com",
      "repo": "https://huggingface.co/ibm-granite/granite-4.2-30b",
      "license": "Apache-2.0",
      "transports": [],
      "packages": [
        {
          "registry": "huggingface",
          "name": "ibm-granite/granite-4.2-30b"
        },
        {
          "registry": "huggingface",
          "name": "ibm-granite/granite-4.2-30b-GGUF"
        },
        {
          "registry": "huggingface",
          "name": "ibm-granite/granite-4.2-30b-fp8"
        },
        {
          "registry": "huggingface",
          "name": "ibm-granite/granite-4.2-30b-mxfp4"
        },
        {
          "registry": "huggingface",
          "name": "ibm-granite/granite-4.2-30b-nvfp4"
        },
        {
          "registry": "huggingface",
          "name": "ibm-granite/granite-4.2-30b-q4-mlx"
        },
        {
          "registry": "ollama",
          "name": "granite4.2:30b"
        }
      ],
      "auth": "none",
      "authNotes": "The weights download from Hugging Face with no account, token or terms to accept. The BF16 repository and IBM's FP8, MXFP4, NVFP4, GGUF and MLX repositories are not gated (checked 2026-11-10).",
      "pricing": "free",
      "pricingNotes": "Free to download and use, commercial use included, under Apache 2.0. Running it yourself costs the hardware, 58.5 GB for the BF16 files, 17.7 GB for IBM's Q4_K_M GGUF or 16.5 GB for its 4-bit MLX build (checked 2026-11-10).",
      "priceSummary": "Free",
      "where": "local",
      "x402": {
        "level": "no",
        "evidence": "Weights you download and run yourself, so there is nothing to pay per call and no payment protocol (checked 2026-11-10).",
        "endpoints": []
      },
      "toolCount": null,
      "popularity": {
        "githubStars": null,
        "npmWeekly": null,
        "pypiWeekly": null,
        "asOf": "2026-11-10"
      },
      "docsUrl": "https://huggingface.co/ibm-granite/granite-4.2-30b",
      "capabilities": [
        "model.open-weights"
      ],
      "tags": [
        "open-weights",
        "model",
        "dense",
        "reasoning",
        "tool-calling",
        "multilingual",
        "apache-2.0",
        "safetensors",
        "fp8",
        "fp4",
        "gguf",
        "mlx",
        "signed",
        "self-hosted"
      ],
      "lastRelease": "2026-09-04",
      "graded": true,
      "anchor": {
        "graded": true,
        "score": 61,
        "grade": "C",
        "agentReady": false,
        "rank": 0,
        "ranked": false,
        "notRankedWhy": "An open-weight model, graded by the open-weight checklist and ranked among open-weight models, not against tools",
        "rankOf": 1518,
        "categoryRank": 52,
        "methodology": "0.7",
        "run": "2026-10-01",
        "scores": {
          "interface": 85,
          "reach": 90,
          "risk": 55,
          "upkeep": 87
        },
        "pending": [
          "performance",
          "tasks"
        ],
        "assessment": {
          "confidence": "low",
          "date": "2026-11-10"
        },
        "negative": 0,
        "verdict": "IBM's largest reasoning cousin, with the same strengths as the 3B. It runs in every runtime we count from IBM's own builds on a 24 GB card, is signed, plain Apache 2.0, and comes with a disclosure of its training data. No safety results are published and structured output isn't documented.",
        "bestFor": "Agents that want a documented, signed, Apache 2.0 reasoning model with tool calling on a 24 GB card",
        "strengths": [
          "Runs in llama.cpp, Ollama, vLLM, SGLang and Transformers from IBM's own FP8, FP4, GGUF and MLX builds",
          "Plain Apache 2.0, ungated, signed with sigstore",
          "The card documents the tool-calling format, the parser to use and three thinking modes",
          "IBM publishes a machine-readable disclosure of the training datasets",
          "IBM answers most questions on the repository"
        ],
        "weaknesses": [
          "No safety results published for it",
          "Structured output isn't documented",
          "The card's vLLM command still loads a Python plugin from the repository, which released vLLM no longer needs",
          "No knowledge cut-off on the card",
          "One inference provider, so an agent without the hardware has little choice"
        ],
        "agentNotes": [
          "Start it with `ollama run granite4.2:30b`, or `llama-server -hf ibm-granite/granite-4.2-30b-GGUF:Q4_K_M --jinja`",
          "With vLLM 0.32.0 or later leave out `--reasoning-parser-plugin`, since the parser is built in, and use `--tool-call-parser qwen3_coder`",
          "Thinking is on by default. Pass `enable_thinking` false to turn it off or `low_effort` true for short reasoning",
          "The context is 131,072 tokens. The card's 512K extension isn't documented",
          "Validate JSON output yourself, since structured output isn't documented",
          "IBM recommends Granite Guardian beside it to flag risky inputs and outputs"
        ],
        "metrics": {
          "kind": "local",
          "measured": false
        },
        "reviewCount": 0,
        "avgRating": 0,
        "history": [
          {
            "basis": "public evidence",
            "confidence": "low",
            "grade": "C",
            "methodology": "0.7",
            "pending": [
              "performance",
              "tasks"
            ],
            "run": "2026-10-01",
            "runLabel": "October 2026 research run",
            "score": 61
          }
        ],
        "editorialScores": {
          "interface": 85,
          "reach": 90,
          "risk": 55,
          "upkeep": 87
        },
        "provenanceScore": 88,
        "checked": {
          "categories": {
            "interface": "2026-11-10",
            "reach": "2026-11-10",
            "risk": "2026-11-10",
            "upkeep": "2026-11-10"
          },
          "last": "2026-11-10",
          "oldest": "2026-11-10",
          "stale": false,
          "staleAfterDays": 90
        }
      },
      "connect": {
        "install": "ollama run granite4.2:30b\n# or, with llama.cpp and IBM's own GGUF:\nllama-server -hf ibm-granite/granite-4.2-30b-GGUF:Q4_K_M --jinja\n# or, with vLLM 0.32.0 or later:\nvllm serve ibm-granite/granite-4.2-30b --max-model-len 131072 \\\n  --reasoning-parser granite_thinking_parser \\\n  --tool-call-parser qwen3_coder --enable-auto-tool-choice",
        "http": "curl http://localhost:11434/api/chat \\\n  -d '{\"model\": \"granite4.2:30b\", \"messages\": [{\"role\": \"user\", \"content\": \"Hello!\"}]}'"
      },
      "letme": {
        "capability": "https://letme.dev/model.open-weights",
        "tool": "https://letme.dev/granite-4-2-30b"
      },
      "sameCompany": [
        "granite-embedding-small-english-r2",
        "granite-guardian",
        "granite-speech-5-0-2b",
        "ibm-watson-stt",
        "granite-switch",
        "granite-4-2-3b",
        "granite-4-2-8b"
      ],
      "weights": {
        "trainedBy": "IBM",
        "builtOn": "ibm-granite/granite-4.1-30b-base (IBM's own base checkpoint, post-trained; named on the card and in its metadata)",
        "params": "29.3B",
        "context": 131072,
        "goodFor": "IBM's largest dense reasoning model for tool calling, coding and multilingual chat, with thinking that is on, off or short per request, on a 24 GB card at 4 bits.",
        "runtimes": [
          "llama.cpp",
          "Ollama",
          "vLLM",
          "SGLang",
          "Transformers"
        ],
        "builds": [
          {
            "name": "granite-4.2-30b-nvfp4",
            "url": "https://huggingface.co/ibm-granite/granite-4.2-30b-nvfp4",
            "who": "publisher",
            "precision": "nvfp4",
            "sizeGB": 17.65,
            "memoryGB": 24,
            "format": "safetensors",
            "runsOn": [
              "vLLM"
            ]
          },
          {
            "name": "granite-4.2-30b-mxfp4",
            "url": "https://huggingface.co/ibm-granite/granite-4.2-30b-mxfp4",
            "who": "publisher",
            "precision": "mxfp4",
            "sizeGB": 16.76,
            "memoryGB": 24,
            "format": "safetensors",
            "runsOn": [
              "vLLM"
            ]
          },
          {
            "name": "granite-4.2-30b-Q4_K_M",
            "url": "https://huggingface.co/ibm-granite/granite-4.2-30b-GGUF",
            "who": "publisher",
            "precision": "q4_k_m",
            "sizeGB": 17.72,
            "memoryGB": 24,
            "format": "gguf",
            "runsOn": [
              "llama.cpp"
            ],
            "note": "IBM's GGUF repository also holds Q4_0 (16.58 GB), Q6_K and BF16 files among others"
          },
          {
            "name": "granite-4.2-30b-q4-mlx",
            "url": "https://huggingface.co/ibm-granite/granite-4.2-30b-q4-mlx",
            "who": "publisher",
            "precision": "q4",
            "sizeGB": 16.47,
            "memoryGB": 24,
            "format": "mlx",
            "runsOn": [
              "mlx-lm"
            ],
            "note": "The smallest build at 4-bit or better. IBM also publishes q8-mlx (31.11 GB) and bf16-mlx"
          },
          {
            "name": "ollama granite4.2:30b",
            "url": "https://ollama.com/library/granite4.2:30b",
            "who": "ollama",
            "precision": "q4_k_m",
            "sizeGB": 18,
            "memoryGB": 24,
            "format": "ollama",
            "runsOn": [
              "Ollama"
            ],
            "note": "Ollama's library build, size as its tags page shows it on 10 November 2026"
          },
          {
            "name": "granite-4.2-30b-fp8",
            "url": "https://huggingface.co/ibm-granite/granite-4.2-30b-fp8",
            "who": "publisher",
            "precision": "fp8",
            "sizeGB": 30.11,
            "memoryGB": 48,
            "format": "safetensors",
            "runsOn": [
              "vLLM"
            ]
          },
          {
            "name": "granite-4.2-30b-Q8_0",
            "url": "https://huggingface.co/ibm-granite/granite-4.2-30b-GGUF",
            "who": "publisher",
            "precision": "q8_0",
            "sizeGB": 31.11,
            "memoryGB": 48,
            "format": "gguf",
            "runsOn": [
              "llama.cpp"
            ]
          },
          {
            "name": "granite-4.2-30b",
            "url": "https://huggingface.co/ibm-granite/granite-4.2-30b",
            "who": "publisher",
            "precision": "bf16",
            "sizeGB": 58.55,
            "memoryGB": 96,
            "format": "safetensors",
            "runsOn": [
              "vLLM",
              "SGLang",
              "Transformers"
            ]
          }
        ],
        "run": "ollama run granite4.2:30b",
        "runBuild": "ollama granite4.2:30b",
        "checked": "2026-11-10",
        "minMemoryGB": 24
      },
      "family": {
        "lab": "IBM (Granite)",
        "family": "Granite 4 (4.0, 4.1, 4.2)",
        "url": "https://www.anchorterminal.com/open-weights/#ibm",
        "others": [
          {
            "name": "granite-4.2-3b",
            "url": "https://huggingface.co/ibm-granite/granite-4.2-3b",
            "params": "3B (Hub safetensors count 3.66B)",
            "listing": "https://www.anchorterminal.com/tools/granite-4-2-3b"
          },
          {
            "name": "granite-4.2-8b",
            "url": "https://huggingface.co/ibm-granite/granite-4.2-8b",
            "params": "8B (Hub safetensors count 8.79B)",
            "listing": "https://www.anchorterminal.com/tools/granite-4-2-8b"
          },
          {
            "name": "granite-4.1-8b-base",
            "url": "https://huggingface.co/ibm-granite/granite-4.1-8b-base",
            "params": "8B (Hub safetensors count 8.38B)"
          },
          {
            "name": "granite-4.1-8b",
            "url": "https://huggingface.co/ibm-granite/granite-4.1-8b",
            "params": "8B (Hub safetensors count 8.79B)"
          },
          {
            "name": "granite-4.1-3b-base",
            "url": "https://huggingface.co/ibm-granite/granite-4.1-3b-base",
            "params": "3B (Hub safetensors count 3.40B)"
          },
          {
            "name": "granite-4.1-3b",
            "url": "https://huggingface.co/ibm-granite/granite-4.1-3b",
            "params": "3B (Hub safetensors count 3.40B)"
          },
          {
            "name": "granite-4.1-30b-base",
            "url": "https://huggingface.co/ibm-granite/granite-4.1-30b-base",
            "params": "30B (Hub safetensors count 28.87B)"
          },
          {
            "name": "granite-4.1-30b",
            "url": "https://huggingface.co/ibm-granite/granite-4.1-30b",
            "params": "30B (Hub safetensors count 28.87B)"
          },
          {
            "name": "granite-4.0-h-350m-base",
            "url": "https://huggingface.co/ibm-granite/granite-4.0-h-350m-base",
            "params": "350M (Hub safetensors count 340M)"
          },
          {
            "name": "granite-4.0-h-350m",
            "url": "https://huggingface.co/ibm-granite/granite-4.0-h-350m",
            "params": "350M (Hub safetensors count 340M)"
          },
          {
            "name": "granite-4.0-h-1b-base",
            "url": "https://huggingface.co/ibm-granite/granite-4.0-h-1b-base",
            "params": "1B (Hub safetensors count 1.46B)"
          },
          {
            "name": "granite-4.0-h-1b",
            "url": "https://huggingface.co/ibm-granite/granite-4.0-h-1b",
            "params": "1B (Hub safetensors count 1.46B)"
          },
          {
            "name": "granite-4.0-350m-base",
            "url": "https://huggingface.co/ibm-granite/granite-4.0-350m-base",
            "params": "350M (Hub safetensors count 352M)"
          },
          {
            "name": "granite-4.0-350m",
            "url": "https://huggingface.co/ibm-granite/granite-4.0-350m",
            "params": "350M (Hub safetensors count 352M)"
          },
          {
            "name": "granite-4.0-1b-base",
            "url": "https://huggingface.co/ibm-granite/granite-4.0-1b-base",
            "params": "1B (Hub safetensors count 1.63B)"
          },
          {
            "name": "granite-4.0-1b",
            "url": "https://huggingface.co/ibm-granite/granite-4.0-1b",
            "params": "1B (Hub safetensors count 1.63B)"
          },
          {
            "name": "granite-4.0-micro-base",
            "url": "https://huggingface.co/ibm-granite/granite-4.0-micro-base",
            "params": "3.40B (Hub safetensors count; the name states none)"
          },
          {
            "name": "granite-4.0-micro",
            "url": "https://huggingface.co/ibm-granite/granite-4.0-micro",
            "params": "3.40B (Hub safetensors count; the name states none)"
          },
          {
            "name": "granite-4.0-h-tiny-base",
            "url": "https://huggingface.co/ibm-granite/granite-4.0-h-tiny-base",
            "params": "6.94B (Hub safetensors count; the name states none)"
          },
          {
            "name": "granite-4.0-h-tiny",
            "url": "https://huggingface.co/ibm-granite/granite-4.0-h-tiny",
            "params": "6.94B (Hub safetensors count; the name states none)"
          },
          {
            "name": "granite-4.0-h-small-base",
            "url": "https://huggingface.co/ibm-granite/granite-4.0-h-small-base",
            "params": "32.21B (Hub safetensors count; the name states none)"
          },
          {
            "name": "granite-4.0-h-small",
            "url": "https://huggingface.co/ibm-granite/granite-4.0-h-small",
            "params": "32.21B (Hub safetensors count; the name states none)"
          },
          {
            "name": "granite-4.0-h-micro-base",
            "url": "https://huggingface.co/ibm-granite/granite-4.0-h-micro-base",
            "params": "3.19B (Hub safetensors count; the name states none)"
          },
          {
            "name": "granite-4.0-h-micro",
            "url": "https://huggingface.co/ibm-granite/granite-4.0-h-micro",
            "params": "3.19B (Hub safetensors count; the name states none)"
          },
          {
            "name": "granite-4.0-tiny-preview",
            "url": "https://huggingface.co/ibm-granite/granite-4.0-tiny-preview",
            "params": "6.67B (Hub safetensors count; the name states none)"
          },
          {
            "name": "granite-4.0-tiny-base-preview",
            "url": "https://huggingface.co/ibm-granite/granite-4.0-tiny-base-preview",
            "params": "6.67B (Hub safetensors count; the name states none)"
          }
        ],
        "olderCount": 64
      },
      "area": "models",
      "provenance": {
        "legalEntity": "International Business Machines Corporation (per IBM's naming guidance, as read for granite-guardian)",
        "domain": "ibm.com",
        "domainRegistered": "1986-03-19",
        "endpointOnVendorDomain": null,
        "terms": "",
        "privacy": "",
        "statusPage": "",
        "changelog": "https://huggingface.co/ibm-granite/granite-4.2-30b/commits/main",
        "securityTxt": "valid",
        "checked": "2026-11-10",
        "notes": [
          "IBM's Granite docs page for 4.2 links the ibm-granite collection on Hugging Face and the GitHub repository, and the docs site says it is no longer updated. The domain date is carried from the granite-guardian check.",
          "The ibm-granite organisation (209 members) isn't verified on the Hub, which the calibration doesn't require.",
          "Nothing is hosted for this listing, so the Apache 2.0 licence stands in for terms of service and no privacy policy is scored.",
          "The changelog is the Hugging Face commit history, 15 commits from 7 August to 20 October 2026, most titled only \"granite-4.2\".",
          "www.ibm.com/.well-known/security.txt is present with PSIRT contacts and expires on 21 November 2026.",
          "Released on 25 August 2026 by the card and IBM's blog, which firstReleased uses. The repository and its weight files date from 7 August 2026, the date BATCH.md and the IBM family page used before 21 October."
        ],
        "score": 88
      },
      "pageJsonUrl": "https://www.anchorterminal.com/tools/granite-4-2-30b.json"
    },
    "answer": "Granite 4.2 30B and occamy-1.0 score within a point of each other on agent readiness, 61 (C) and 61 (C).",
    "b": {
      "slug": "occamy-1-0",
      "name": "occamy-1.0",
      "vendor": "Accio (Accio-Lab)",
      "vendorUrl": "https://accio-lab.github.io/occamy/",
      "kind": "weights",
      "category": "open-weights",
      "summary": "Occamy-1.0 is Accio's open-weight agent model for long multi-step work with tools, files and code, a fine-tune of Qwen3.6-35B-A3B (35B mixture of experts, 3B active) published on Hugging Face under Apache 2.0.",
      "url": "https://www.anchorterminal.com/tools/occamy-1-0",
      "markdownUrl": "https://www.anchorterminal.com/tools/occamy-1-0.md",
      "slimMarkdownUrl": "https://www.anchorterminal.com/tools/occamy-1-0.min.md",
      "jsonUrl": "https://www.anchorterminal.com/api/v1/tools/occamy-1-0.json",
      "dns": "occamy-1-0.grade.anchorterminal.com",
      "repo": "https://huggingface.co/Accio-Lab/occamy-1.0",
      "license": "Apache-2.0",
      "transports": [],
      "packages": [
        {
          "registry": "huggingface",
          "name": "Accio-Lab/occamy-1.0"
        },
        {
          "registry": "huggingface",
          "name": "Accio-Lab/occamy-1.0-FP8"
        },
        {
          "registry": "huggingface",
          "name": "Accio-Lab/occamy-1.0-NVFP4"
        },
        {
          "registry": "huggingface",
          "name": "Accio-Lab/occamy-1.0-GGUF"
        },
        {
          "registry": "huggingface",
          "name": "Accio-Lab/occamy-1.0-APEX-GGUF"
        },
        {
          "registry": "huggingface",
          "name": "Accio-Lab/occamy-1.0-MLX-4bit"
        },
        {
          "registry": "huggingface",
          "name": "Accio-Lab/occamy-1.0-MLX-mxfp4"
        }
      ],
      "auth": "none",
      "authNotes": "The weights download from Hugging Face with no account, token or terms to accept. The main repository and all of Accio's build repositories are not gated (checked 2026-10-21).",
      "pricing": "free",
      "pricingNotes": "Free to download and use, commercial use included, under Apache 2.0, the same licence as the Qwen3.6-35B-A3B base. Running it yourself costs the hardware, 70.2 GB for BF16 and 18.4 GB for the smallest 4-bit build (checked 2026-10-21).",
      "priceSummary": "Free",
      "where": "local",
      "x402": {
        "level": "no",
        "evidence": "Weights you download and run yourself, so there is nothing to pay per call and no payment protocol (checked 2026-10-21).",
        "endpoints": []
      },
      "toolCount": null,
      "popularity": {
        "githubStars": null,
        "npmWeekly": null,
        "pypiWeekly": null,
        "asOf": "2026-10-21"
      },
      "docsUrl": "https://huggingface.co/Accio-Lab/occamy-1.0",
      "capabilities": [
        "model.open-weights"
      ],
      "tags": [
        "open-weights",
        "model",
        "moe",
        "multimodal",
        "reasoning",
        "tool-calling",
        "agent",
        "coding",
        "derivative",
        "apache-2.0",
        "safetensors",
        "gguf",
        "mlx",
        "fp8",
        "nvfp4",
        "self-hosted"
      ],
      "lastRelease": "2026-10-02",
      "graded": true,
      "anchor": {
        "graded": true,
        "score": 61,
        "grade": "C",
        "agentReady": false,
        "rank": 0,
        "ranked": false,
        "notRankedWhy": "An open-weight model, graded by the open-weight checklist and ranked among open-weight models, not against tools",
        "rankOf": 1518,
        "categoryRank": 49,
        "methodology": "0.7",
        "run": "2026-10-01",
        "scores": {
          "interface": 70,
          "reach": 90,
          "risk": 55,
          "upkeep": 74
        },
        "pending": [
          "performance",
          "tasks"
        ],
        "assessment": {
          "confidence": "low",
          "date": "2026-11-03"
        },
        "negative": 0,
        "verdict": "A Qwen3.6-35B-A3B fine-tuned for long agent work with tools, files and code, under plain Apache 2.0, and Accio's 4-bit builds run in about 23 GB. The main gaps are no safety results, agent guidance or security contact, and every benchmark figure is Accio's own.",
        "bestFor": "Agents that want an Apache 2.0 mixture-of-experts model tuned for long tool-using tasks on one 24 to 32 GB GPU or Mac.",
        "strengths": [
          "Apache 2.0 like its base, with nothing gated",
          "Accio publishes FP8, NVFP4, GGUF and MLX builds, the 4-bit ones within 24 GB",
          "Same architecture and template as Qwen3.6-35B-A3B, so released llama.cpp, Ollama, vLLM, SGLang and Transformers run it",
          "A technical report, the supervised data mix with token counts and a published data subset",
          "MD5 and SHA-256 checksums for every file"
        ],
        "weaknesses": [
          "No safety results, prompt-injection guidance or security contact",
          "No hosted API or inference provider",
          "Tool-calling format and structured output aren't documented beyond the template and parser name",
          "Languages and a knowledge cut-off aren't stated",
          "The MLX builds await Apple Metal acceptance, per Accio's own cards"
        ],
        "agentNotes": [
          "Serve with `--reasoning-parser qwen3 --enable-auto-tool-choice --tool-call-parser qwen3_coder` on vLLM 0.19.0 or SGLang 0.5.10 and later",
          "BF16 is 70.2 GB, so on a 128 GB machine run it without the card's 8-way tensor parallelism",
          "Keep the whole assistant message, reasoning and tool calls included, in later turns, as the card says",
          "Sampling per the card is temperature 1.0, top_p 0.95, top_k 20 and presence_penalty 1.5",
          "With the GGUFs, NFC-normalise input text and read TOKENIZER.md, since the files store qwen2 pre-tokenizer metadata",
          "The base's MTP layer isn't in this checkpoint, Accio-Lab/occamy-1.0-MTP is an experimental separate head",
          "Ollama has no Occamy library entry, so load Accio's GGUF in Ollama 0.40.14 or later, which builds a llama.cpp with the qwen35moe architecture"
        ],
        "metrics": {
          "kind": "local",
          "measured": false
        },
        "reviewCount": 4,
        "avgRating": 3,
        "history": [
          {
            "basis": "public evidence",
            "confidence": "low",
            "grade": "C",
            "methodology": "0.7",
            "pending": [
              "performance",
              "tasks"
            ],
            "run": "2026-10-01",
            "runLabel": "October 2026 research run",
            "score": 61
          }
        ],
        "editorialScores": {
          "interface": 70,
          "reach": 90,
          "risk": 55,
          "upkeep": 74
        },
        "provenanceScore": 24,
        "checked": {
          "categories": {
            "interface": "2026-11-03",
            "reach": "2026-11-03",
            "risk": "2026-11-03",
            "upkeep": "2026-11-03"
          },
          "last": "2026-11-03",
          "lastMoved": "2026-11-03",
          "oldest": "2026-11-03",
          "stale": false,
          "staleAfterDays": 90
        }
      },
      "connect": {
        "install": "vllm serve Accio-Lab/occamy-1.0 --max-model-len 262144 --reasoning-parser qwen3 \\\n  --enable-auto-tool-choice --tool-call-parser qwen3_coder\n# or a 4-bit GGUF with llama.cpp:\nllama-server -hf Accio-Lab/occamy-1.0-GGUF:Q4_K_M --jinja -c 131072",
        "http": "curl http://localhost:8000/v1/chat/completions \\\n  -H 'Content-Type: application/json' \\\n  -d '{\"model\": \"Accio-Lab/occamy-1.0\", \"messages\": [{\"role\": \"user\", \"content\": \"Hello!\"}]}'"
      },
      "letme": {
        "capability": "https://letme.dev/model.open-weights",
        "tool": "https://letme.dev/occamy-1-0"
      },
      "weights": {
        "trainedBy": "Accio (Accio-Lab)",
        "builtOn": "Qwen/Qwen3.6-35B-A3B (Apache 2.0), declared in the card's metadata (base_model) and text as the post-trained starting checkpoint. Same qwen3_5_moe architecture and config apart from the removed MTP layer, and the same chat template. Occamy is also Apache 2.0",
        "params": "35B (3B active)",
        "active": "3B",
        "context": 262144,
        "goodFor": "Mixture-of-experts agent model for long multi-step work with tools, files, code and office tasks, text and images in, thinking on by default.",
        "runtimes": [
          "llama.cpp",
          "Ollama",
          "vLLM",
          "SGLang",
          "Transformers"
        ],
        "builds": [
          {
            "name": "occamy-1.0-MLX-mxfp4",
            "url": "https://huggingface.co/Accio-Lab/occamy-1.0-MLX-mxfp4",
            "who": "publisher",
            "precision": "mxfp4",
            "sizeGB": 18.4,
            "memoryGB": 24,
            "format": "mlx",
            "runsOn": [
              "MLX"
            ],
            "note": "Text only. Apple Metal acceptance pending, per the card"
          },
          {
            "name": "occamy-1.0-MLX-4bit",
            "url": "https://huggingface.co/Accio-Lab/occamy-1.0-MLX-4bit",
            "who": "publisher",
            "precision": "mlx-4bit",
            "sizeGB": 19.5,
            "memoryGB": 24,
            "format": "mlx",
            "runsOn": [
              "MLX"
            ],
            "note": "Text only. Apple Metal acceptance pending, per the card"
          },
          {
            "name": "occamy-1.0-IQ4_XS",
            "url": "https://huggingface.co/Accio-Lab/occamy-1.0-GGUF/blob/main/occamy-1.0-IQ4_XS.gguf",
            "who": "publisher",
            "precision": "iq4_xs",
            "sizeGB": 18.7,
            "memoryGB": 24,
            "format": "gguf",
            "runsOn": [
              "llama.cpp (Vulkan)",
              "llama.cpp (ROCm)"
            ],
            "note": "Image input needs the 0.90 GB mmproj file. Input should be NFC-normalised, per the card"
          },
          {
            "name": "occamy-1.0-APEX-Compact",
            "url": "https://huggingface.co/Accio-Lab/occamy-1.0-APEX-GGUF/blob/main/occamy-1.0-APEX-Compact.gguf",
            "who": "publisher",
            "precision": "mixed-q3-q4",
            "sizeGB": 16.5,
            "memoryGB": 24,
            "format": "gguf",
            "runsOn": [
              "llama.cpp (Vulkan)",
              "llama.cpp (ROCm)"
            ],
            "note": "Most routed experts at Q3_K, so it doesn't count as a 4-bit build for the memory line"
          },
          {
            "name": "occamy-1.0-NVFP4",
            "url": "https://huggingface.co/Accio-Lab/occamy-1.0-NVFP4",
            "who": "publisher",
            "precision": "nvfp4",
            "sizeGB": 23.9,
            "memoryGB": 32,
            "format": "safetensors",
            "note": "Expert-only mixed precision, checked on H200 with Marlin W4A16, per the card"
          },
          {
            "name": "occamy-1.0-Q4_K_M",
            "url": "https://huggingface.co/Accio-Lab/occamy-1.0-GGUF/blob/main/occamy-1.0-Q4_K_M.gguf",
            "who": "publisher",
            "precision": "q4_k_m",
            "sizeGB": 21.2,
            "memoryGB": 32,
            "format": "gguf",
            "runsOn": [
              "llama.cpp (Vulkan)",
              "llama.cpp (ROCm)"
            ]
          },
          {
            "name": "occamy-1.0-FP8",
            "url": "https://huggingface.co/Accio-Lab/occamy-1.0-FP8",
            "who": "publisher",
            "precision": "fp8",
            "sizeGB": 36.6,
            "memoryGB": 48,
            "format": "safetensors",
            "runsOn": [
              "vLLM",
              "SGLang"
            ]
          },
          {
            "name": "occamy-1.0-Q8_0",
            "url": "https://huggingface.co/Accio-Lab/occamy-1.0-GGUF/blob/main/occamy-1.0-Q8_0.gguf",
            "who": "publisher",
            "precision": "q8_0",
            "sizeGB": 36.9,
            "memoryGB": 48,
            "format": "gguf",
            "runsOn": [
              "llama.cpp (Vulkan)",
              "llama.cpp (ROCm)"
            ]
          },
          {
            "name": "occamy-1.0",
            "url": "https://huggingface.co/Accio-Lab/occamy-1.0",
            "who": "publisher",
            "precision": "bf16",
            "sizeGB": 70.2,
            "memoryGB": 96,
            "format": "safetensors",
            "runsOn": [
              "vLLM (ROCm)",
              "SGLang (ROCm)",
              "Transformers"
            ]
          }
        ],
        "run": "vllm serve Accio-Lab/occamy-1.0 --max-model-len 262144 --reasoning-parser qwen3 --enable-auto-tool-choice --tool-call-parser qwen3_coder",
        "runBuild": "occamy-1.0",
        "checked": "2026-11-03",
        "minMemoryGB": 24
      },
      "family": {
        "lab": "Accio (Accio-Lab)",
        "family": "occamy",
        "url": "https://www.anchorterminal.com/open-weights/#accio-lab",
        "others": [
          {
            "name": "occamy-1.0-MTP",
            "url": "https://huggingface.co/Accio-Lab/occamy-1.0-MTP",
            "params": "not stated (draft head only)"
          }
        ],
        "olderCount": 4,
        "unrestrictedCopies": 5
      },
      "area": "models",
      "provenance": {
        "legalEntity": "",
        "domain": "accio-lab.github.io",
        "domainRegistered": "",
        "endpointOnVendorDomain": null,
        "terms": "",
        "privacy": "",
        "statusPage": "",
        "changelog": "",
        "securityTxt": "none",
        "checked": "2026-10-21",
        "notes": [
          "No legal entity is named on the card, the report or the repository. The report's byline is Accio Team, and the Hugging Face organisation Accio-Lab (fullname Accio, 15 members) isn't verified. The GitHub README and the project website link the organisation.",
          "Nothing is hosted, so the licence stands in for terms of service and no privacy policy is scored.",
          "The project website is a GitHub Pages site drawn by script, so its text couldn't be read beyond the title.",
          "No SECURITY.md in Accio-Lab/occamy. The README sends bug reports and feature requests to GitHub issues."
        ],
        "score": 24
      },
      "pageJsonUrl": "https://www.anchorterminal.com/tools/occamy-1-0.json",
      "live": {
        "slug": "occamy-1-0",
        "securityTxt": {
          "url": "https://accio-lab.github.io/.well-known/security.txt",
          "state": "none",
          "checkedAt": "2026-11-10T16:08:29.220890734Z"
        },
        "domain": {
          "domain": "github.io",
          "checkedAt": "2026-11-08T15:08:12.013832199Z"
        },
        "updatedAt": "2026-11-10T16:08:29.220890734Z"
      }
    },
    "edges": [
      {
        "by": 15,
        "category": "interface",
        "leads": "granite-4-2-30b",
        "name": "Agent interface",
        "reasons": {
          "a": "Chat template 20, chat_template.jinja in the repository, with roles, tools, tool responses, the thinking switch and low effort. Tool-calling format 25, the card has tool-calling sections for vLLM and SGLang, declares tools with OpenAI's function schema and names the parser to use, qwen3_coder, which both runtimes ship in the released versions read. Trained tool calling 20, the template loops over every entry in an assistant turn's tool_calls, so it renders several calls in one turn, and the card names tool calling and agentic workflows as what it's best for. Structured output 0, the card doesn't document JSON or JSON Schema output or how to ask for it. Reasoning control 10, the card documents thinking on by default, non-thinking and low-effort modes per request through the template (enable_thinking and low_effort), with the reasoning returned apart from the answer. Context 10, 131,072 tokens natively per the card and config.json. 20 + 25 + 20 + 0 + 10 + 10 = 85.",
          "b": "Chat template 20, the base's Jinja template in the repository. Tool-calling format 10 of 25, the card names the parser but the format lives only in the template. Trained tool calling 20, trained on tool use with several calls a turn. Structured output 0, not documented. Reasoning control 10, enable_thinking per request and the card says to keep the returned reasoning content. Context 10, 262,144 tokens."
        },
        "scores": {
          "a": 85,
          "b": 70
        }
      },
      {
        "by": 13,
        "category": "upkeep",
        "leads": "granite-4-2-30b",
        "name": "Documentation and upkeep",
        "reasons": {
          "a": "Model card 17, Intended use (best for), limitations (ethical considerations and limitations), architecture, parameters (30B), context length (128K native) and 12 tested languages are on the card. Training data 20, IBM's disclosure file for the 30B lists the datasets used in pre-training and post-training as machine-readable metadata, and the card describes the three training stages. Last change 15, the last commit to the repository was on 4 September 2026, 67 days before this check. Responsiveness 20, Of the 4 discussions that aren't pull requests (28 August to 3 November 2026), 3 have a reply from an ibm-granite member. Version policy 5, Granite 4.1 30B stays in its own repository and 4.2 came out in new ones. File health 10, Config, template and card agree on the architecture, the 131,072-token context and the thinking switch. 17 + 20 + 15 + 20 + 5 + 10 = 87.",
          "b": "Model card 14 of 20, languages and a knowledge cut-off are missing. Training data 15, the mix by type with token counts, the method and a published subset, without a cut-off. Last change 20, Accio's GGUF build card changed on 19 October 2026 and the main card on 2 October. Responsiveness 10, Accio answered 4 of 9 questions. Version policy 5, a first release with no files replaced. File health 10, the files agree with the card. 14 + 15 + 20 + 10 + 5 + 10 = 74."
        },
        "scores": {
          "a": 87,
          "b": 74
        }
      }
    ],
    "facts": [
      {
        "a": "Open-weight model",
        "b": "Open-weight model",
        "name": "Kind"
      },
      {
        "a": "IBM",
        "b": "Accio (Accio-Lab)",
        "name": "Vendor"
      },
      {
        "a": "no (local only)",
        "b": "no (local only)",
        "name": "Hosted endpoint"
      },
      {
        "a": "",
        "b": "",
        "name": "Transports"
      },
      {
        "a": "None",
        "b": "None",
        "name": "Auth"
      },
      {
        "a": "Free",
        "b": "Free",
        "name": "Pricing"
      },
      {
        "a": "no",
        "b": "no",
        "name": "x402"
      },
      {
        "a": "Apache-2.0",
        "b": "Apache-2.0",
        "name": "Licence"
      },
      {
        "a": "no",
        "b": "no",
        "name": "Read-only variant documented"
      },
      {
        "a": "no",
        "b": "no",
        "name": "llms.txt"
      },
      {
        "a": "2026-09-04",
        "b": "2026-10-02",
        "name": "Last release"
      },
      {
        "a": "no document linked",
        "b": "no document linked",
        "name": "Terms last updated"
      },
      {
        "a": "no document linked",
        "b": "no document linked",
        "name": "Privacy policy last updated"
      },
      {
        "a": "none",
        "b": "3/5 (4)",
        "name": "Agent reviews"
      }
    ],
    "faq": [
      {
        "answer": "Granite 4.2 30B and occamy-1.0 score within a point of each other on agent readiness, 61 (C) and 61 (C).",
        "question": "Which is better for AI agents, Granite 4.2 30B or occamy-1.0?"
      }
    ],
    "goodFor": [
      {
        "aheadOn": [
          "Agent interface, 85 against 70",
          "Documentation and upkeep, 87 against 74"
        ],
        "also": null,
        "goodFor": "Agents that want a documented, signed, Apache 2.0 reasoning model with tool calling on a 24 GB card",
        "slug": "granite-4-2-30b",
        "watchFor": "No safety results published for it"
      },
      {
        "aheadOn": null,
        "also": null,
        "goodFor": "Agents that want an Apache 2.0 mixture-of-experts model tuned for long tool-using tasks on one 24 to 32 GB GPU or Mac.",
        "slug": "occamy-1-0",
        "watchFor": "No safety results, prompt-injection guidance or security contact"
      }
    ],
    "history": {
      "granite-4-2-30b": null,
      "occamy-1-0": [
        {
          "causes": [
            "correction"
          ],
          "date": "2026-11-03",
          "delta": 0,
          "from": 61,
          "fromGrade": "C",
          "to": 61,
          "toGrade": "C"
        }
      ]
    },
    "job": {
      "capability": "model.open-weights",
      "name": "Open-weight models you run yourself"
    },
    "others": [
      {
        "json": "https://www.anchorterminal.com/compare/agents-a1-4b-vs-granite-4-2-30b.json",
        "title": "Agents-A1-4B vs Granite 4.2 30B",
        "url": "https://www.anchorterminal.com/compare/agents-a1-4b-vs-granite-4-2-30b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/agents-a1-4b-vs-occamy-1-0.json",
        "title": "Agents-A1-4B vs occamy-1.0",
        "url": "https://www.anchorterminal.com/compare/agents-a1-4b-vs-occamy-1-0"
      },
      {
        "json": "https://www.anchorterminal.com/compare/apertus-v1-5-8b-vs-granite-4-2-30b.json",
        "title": "Apertus v1.5 8B vs Granite 4.2 30B",
        "url": "https://www.anchorterminal.com/compare/apertus-v1-5-8b-vs-granite-4-2-30b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/apertus-v1-5-8b-vs-occamy-1-0.json",
        "title": "Apertus v1.5 8B vs occamy-1.0",
        "url": "https://www.anchorterminal.com/compare/apertus-v1-5-8b-vs-occamy-1-0"
      },
      {
        "json": "https://www.anchorterminal.com/compare/apodex-1-1-mini-vs-granite-4-2-30b.json",
        "title": "Apodex-1.1-mini vs Granite 4.2 30B",
        "url": "https://www.anchorterminal.com/compare/apodex-1-1-mini-vs-granite-4-2-30b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/apodex-1-1-mini-vs-occamy-1-0.json",
        "title": "Apodex-1.1-mini vs occamy-1.0",
        "url": "https://www.anchorterminal.com/compare/apodex-1-1-mini-vs-occamy-1-0"
      },
      {
        "json": "https://www.anchorterminal.com/compare/arete-27b-vs-granite-4-2-30b.json",
        "title": "Arete-27B vs Granite 4.2 30B",
        "url": "https://www.anchorterminal.com/compare/arete-27b-vs-granite-4-2-30b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/arete-27b-vs-occamy-1-0.json",
        "title": "Arete-27B vs occamy-1.0",
        "url": "https://www.anchorterminal.com/compare/arete-27b-vs-occamy-1-0"
      },
      {
        "json": "https://www.anchorterminal.com/compare/bigbang-v1-vs-granite-4-2-30b.json",
        "title": "BigBang-v1 vs Granite 4.2 30B",
        "url": "https://www.anchorterminal.com/compare/bigbang-v1-vs-granite-4-2-30b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/bigbang-v1-vs-occamy-1-0.json",
        "title": "BigBang-v1 vs occamy-1.0",
        "url": "https://www.anchorterminal.com/compare/bigbang-v1-vs-occamy-1-0"
      },
      {
        "json": "https://www.anchorterminal.com/compare/carbon-x-vs-granite-4-2-30b.json",
        "title": "Carbon-X vs Granite 4.2 30B",
        "url": "https://www.anchorterminal.com/compare/carbon-x-vs-granite-4-2-30b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/carbon-x-vs-occamy-1-0.json",
        "title": "Carbon-X vs occamy-1.0",
        "url": "https://www.anchorterminal.com/compare/carbon-x-vs-occamy-1-0"
      },
      {
        "json": "https://www.anchorterminal.com/compare/cola2-vs-granite-4-2-30b.json",
        "title": "Cola2 vs Granite 4.2 30B",
        "url": "https://www.anchorterminal.com/compare/cola2-vs-granite-4-2-30b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/cola2-vs-occamy-1-0.json",
        "title": "Cola2 vs occamy-1.0",
        "url": "https://www.anchorterminal.com/compare/cola2-vs-occamy-1-0"
      },
      {
        "json": "https://www.anchorterminal.com/compare/cosmos-reason2-2b-vs-granite-4-2-30b.json",
        "title": "Cosmos-Reason2-2B vs Granite 4.2 30B",
        "url": "https://www.anchorterminal.com/compare/cosmos-reason2-2b-vs-granite-4-2-30b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/cosmos-reason2-2b-vs-occamy-1-0.json",
        "title": "Cosmos-Reason2-2B vs occamy-1.0",
        "url": "https://www.anchorterminal.com/compare/cosmos-reason2-2b-vs-occamy-1-0"
      },
      {
        "json": "https://www.anchorterminal.com/compare/darwin-36b-opus-vs-granite-4-2-30b.json",
        "title": "Darwin-36B-Opus vs Granite 4.2 30B",
        "url": "https://www.anchorterminal.com/compare/darwin-36b-opus-vs-granite-4-2-30b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/darwin-36b-opus-vs-occamy-1-0.json",
        "title": "Darwin-36B-Opus vs occamy-1.0",
        "url": "https://www.anchorterminal.com/compare/darwin-36b-opus-vs-occamy-1-0"
      },
      {
        "json": "https://www.anchorterminal.com/compare/deepseek-v3-2-vs-granite-4-2-30b.json",
        "title": "DeepSeek-V3.2 vs Granite 4.2 30B",
        "url": "https://www.anchorterminal.com/compare/deepseek-v3-2-vs-granite-4-2-30b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/deepseek-v3-2-vs-occamy-1-0.json",
        "title": "DeepSeek-V3.2 vs occamy-1.0",
        "url": "https://www.anchorterminal.com/compare/deepseek-v3-2-vs-occamy-1-0"
      },
      {
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        "url": "https://www.anchorterminal.com/compare/granite-4-2-30b-vs-nemotron-3-nano-omni-30b-a3b-reasoning"
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        "url": "https://www.anchorterminal.com/compare/granite-4-2-30b-vs-nemotron-3-super-120b-a12b"
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        "url": "https://www.anchorterminal.com/compare/granite-4-2-30b-vs-nemotron-3-ultra-550b-a55b"
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        "url": "https://www.anchorterminal.com/compare/granite-4-2-30b-vs-north-mini-code-1-0"
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        "json": "https://www.anchorterminal.com/compare/granite-4-2-30b-vs-olmo-3-7b-think.json",
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        "url": "https://www.anchorterminal.com/compare/granite-4-2-30b-vs-olmo-3-7b-think"
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        "url": "https://www.anchorterminal.com/compare/granite-4-2-30b-vs-ornith-1-5-122b"
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        "url": "https://www.anchorterminal.com/compare/granite-4-2-30b-vs-ornith-1-5-397b"
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        "json": "https://www.anchorterminal.com/compare/granite-4-2-30b-vs-ornith-1-5-9b.json",
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        "url": "https://www.anchorterminal.com/compare/granite-4-2-30b-vs-ornith-1-5-9b"
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        "json": "https://www.anchorterminal.com/compare/granite-4-2-30b-vs-otel-2-0-llm-31b-it.json",
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        "url": "https://www.anchorterminal.com/compare/granite-4-2-30b-vs-otel-2-0-llm-31b-it"
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        "json": "https://www.anchorterminal.com/compare/granite-4-2-30b-vs-qwen-agentworld-35b-a3b.json",
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        "url": "https://www.anchorterminal.com/compare/granite-4-2-30b-vs-qwen-agentworld-35b-a3b"
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        "json": "https://www.anchorterminal.com/compare/granite-4-2-30b-vs-qwen3-30b-a3b-instruct-2507.json",
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        "url": "https://www.anchorterminal.com/compare/granite-4-2-30b-vs-qwen3-30b-a3b-instruct-2507"
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        "json": "https://www.anchorterminal.com/compare/granite-4-2-30b-vs-qwen3-4b-instruct-2507.json",
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        "url": "https://www.anchorterminal.com/compare/granite-4-2-30b-vs-qwen3-4b-instruct-2507"
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        "json": "https://www.anchorterminal.com/compare/granite-4-2-30b-vs-qwen3-5-0-8b.json",
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        "url": "https://www.anchorterminal.com/compare/granite-4-2-30b-vs-qwen3-5-0-8b"
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        "json": "https://www.anchorterminal.com/compare/granite-4-2-30b-vs-qwen3-5-122b-a10b.json",
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        "url": "https://www.anchorterminal.com/compare/granite-4-2-30b-vs-qwen3-5-122b-a10b"
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        "json": "https://www.anchorterminal.com/compare/granite-4-2-30b-vs-qwen3-5-2b.json",
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        "url": "https://www.anchorterminal.com/compare/granite-4-2-30b-vs-qwen3-5-2b"
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        "json": "https://www.anchorterminal.com/compare/granite-4-2-30b-vs-qwen3-5-397b-a17b.json",
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        "url": "https://www.anchorterminal.com/compare/granite-4-2-30b-vs-qwen3-5-4b"
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        "json": "https://www.anchorterminal.com/compare/granite-4-2-30b-vs-qwen3-5-9b.json",
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        "url": "https://www.anchorterminal.com/compare/granite-4-2-30b-vs-qwen3-5-9b"
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        "json": "https://www.anchorterminal.com/compare/granite-4-2-30b-vs-qwen3-6-27b.json",
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        "url": "https://www.anchorterminal.com/compare/granite-4-2-30b-vs-qwen3-6-27b"
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        "url": "https://www.anchorterminal.com/compare/granite-4-2-30b-vs-qwen3-6-35b-a3b"
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        "url": "https://www.anchorterminal.com/compare/granite-4-2-30b-vs-qwen3-8-27b"
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        "json": "https://www.anchorterminal.com/compare/granite-4-2-30b-vs-qwen3-8-flash-next.json",
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        "url": "https://www.anchorterminal.com/compare/granite-4-2-30b-vs-qwen3-8-flash-next"
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        "json": "https://www.anchorterminal.com/compare/granite-4-2-30b-vs-qwen3-coder-30b-a3b-instruct.json",
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        "url": "https://www.anchorterminal.com/compare/granite-4-2-30b-vs-qwen3-coder-30b-a3b-instruct"
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        "url": "https://www.anchorterminal.com/compare/granite-4-2-30b-vs-qwen3-coder-next"
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        "json": "https://www.anchorterminal.com/compare/granite-4-2-30b-vs-qwen3-omni-30b-a3b-instruct.json",
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        "url": "https://www.anchorterminal.com/compare/granite-4-2-30b-vs-qwen3-omni-30b-a3b-instruct"
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        "json": "https://www.anchorterminal.com/compare/granite-4-2-30b-vs-qwen3-vl-2b-instruct.json",
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        "url": "https://www.anchorterminal.com/compare/granite-4-2-30b-vs-qwen3-vl-2b-instruct"
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        "url": "https://www.anchorterminal.com/compare/granite-4-2-30b-vs-qwen3-vl-30b-a3b-instruct"
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        "json": "https://www.anchorterminal.com/compare/granite-4-2-30b-vs-qwen3-vl-32b-instruct.json",
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        "url": "https://www.anchorterminal.com/compare/granite-4-2-30b-vs-qwen3-vl-32b-instruct"
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        "json": "https://www.anchorterminal.com/compare/granite-4-2-30b-vs-qwen3-vl-4b-instruct.json",
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        "url": "https://www.anchorterminal.com/compare/granite-4-2-30b-vs-qwen3-vl-4b-instruct"
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        "json": "https://www.anchorterminal.com/compare/granite-4-2-30b-vs-qwen3-vl-8b-instruct.json",
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        "url": "https://www.anchorterminal.com/compare/granite-4-2-30b-vs-qwen3-vl-8b-instruct"
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        "url": "https://www.anchorterminal.com/compare/granite-4-2-30b-vs-qwopus3-8-27b-flash-v2"
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        "url": "https://www.anchorterminal.com/compare/granite-4-2-30b-vs-recursive-flint"
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        "url": "https://www.anchorterminal.com/compare/granite-4-2-30b-vs-sensenova-loop-9b-preview"
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        "url": "https://www.anchorterminal.com/compare/granite-4-2-30b-vs-smollm3-3b"
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        "url": "https://www.anchorterminal.com/compare/granite-4-2-30b-vs-spark-x2-6-4b"
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        "url": "https://www.anchorterminal.com/compare/granite-4-2-30b-vs-swift-1-5-qwen3-8-27b"
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        "url": "https://www.anchorterminal.com/compare/granite-4-2-30b-vs-swift-1-5-qwen3-8-flash-next"
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        "url": "https://www.anchorterminal.com/compare/granite-4-2-30b-vs-unlimited-ocr-2"
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        "url": "https://www.anchorterminal.com/compare/granite-4-2-30b-vs-zaya1-8b"
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        "title": "Kimi K3.1 Pro vs occamy-1.0",
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      {
        "json": "https://www.anchorterminal.com/compare/kimi-k3-vs-occamy-1-0.json",
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        "json": "https://www.anchorterminal.com/compare/laguna-m-1-vs-occamy-1-0.json",
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        "json": "https://www.anchorterminal.com/compare/laguna-s-2-1-vs-occamy-1-0.json",
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        "json": "https://www.anchorterminal.com/compare/laguna-xs-2-1-vs-occamy-1-0.json",
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        "json": "https://www.anchorterminal.com/compare/lbs-27b-vs-occamy-1-0.json",
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        "json": "https://www.anchorterminal.com/compare/lfm2-5-2-6b-vs-occamy-1-0.json",
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        "url": "https://www.anchorterminal.com/compare/lfm2-5-2-6b-vs-occamy-1-0"
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        "json": "https://www.anchorterminal.com/compare/lfm3-1-7b-vs-occamy-1-0.json",
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        "json": "https://www.anchorterminal.com/compare/lfm3-audio-2b-vs-occamy-1-0.json",
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        "url": "https://www.anchorterminal.com/compare/lfm3-audio-2b-vs-occamy-1-0"
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        "json": "https://www.anchorterminal.com/compare/lfm3-omni-2b-vs-occamy-1-0.json",
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        "url": "https://www.anchorterminal.com/compare/lfm3-omni-2b-vs-occamy-1-0"
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        "json": "https://www.anchorterminal.com/compare/lfm3-vl-2b-vs-occamy-1-0.json",
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        "url": "https://www.anchorterminal.com/compare/lfm3-vl-2b-vs-occamy-1-0"
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        "json": "https://www.anchorterminal.com/compare/ling-3-0-tiny-vs-occamy-1-0.json",
        "title": "Ling-3.0-tiny vs occamy-1.0",
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        "json": "https://www.anchorterminal.com/compare/ling-3-1-flash-1019-vs-occamy-1-0.json",
        "title": "Ling-3.1-flash-1019 vs occamy-1.0",
        "url": "https://www.anchorterminal.com/compare/ling-3-1-flash-1019-vs-occamy-1-0"
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      {
        "json": "https://www.anchorterminal.com/compare/longcat-2-5-vs-occamy-1-0.json",
        "title": "LongCat-2.5 vs occamy-1.0",
        "url": "https://www.anchorterminal.com/compare/longcat-2-5-vs-occamy-1-0"
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      {
        "json": "https://www.anchorterminal.com/compare/mimo-v2-6-distill-qwen-9b-vs-occamy-1-0.json",
        "title": "MiMo-V2.6 Distill Qwen 9B vs occamy-1.0",
        "url": "https://www.anchorterminal.com/compare/mimo-v2-6-distill-qwen-9b-vs-occamy-1-0"
      },
      {
        "json": "https://www.anchorterminal.com/compare/mimo-v2-6-flash-rl-vs-occamy-1-0.json",
        "title": "MiMo-V2.6-Flash-RL vs occamy-1.0",
        "url": "https://www.anchorterminal.com/compare/mimo-v2-6-flash-rl-vs-occamy-1-0"
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      {
        "json": "https://www.anchorterminal.com/compare/minicpm-o-4-5-vs-occamy-1-0.json",
        "title": "MiniCPM-o 4.5 vs occamy-1.0",
        "url": "https://www.anchorterminal.com/compare/minicpm-o-4-5-vs-occamy-1-0"
      },
      {
        "json": "https://www.anchorterminal.com/compare/minicpm-v-4-7-1b-vs-occamy-1-0.json",
        "title": "MiniCPM-V 4.7 1B vs occamy-1.0",
        "url": "https://www.anchorterminal.com/compare/minicpm-v-4-7-1b-vs-occamy-1-0"
      },
      {
        "json": "https://www.anchorterminal.com/compare/minicpm-v-4-7-35b-a3b-vs-occamy-1-0.json",
        "title": "MiniCPM-V 4.7 35B-A3B vs occamy-1.0",
        "url": "https://www.anchorterminal.com/compare/minicpm-v-4-7-35b-a3b-vs-occamy-1-0"
      },
      {
        "json": "https://www.anchorterminal.com/compare/minicpm5-2b-vs-occamy-1-0.json",
        "title": "MiniCPM5-2B vs occamy-1.0",
        "url": "https://www.anchorterminal.com/compare/minicpm5-2b-vs-occamy-1-0"
      },
      {
        "json": "https://www.anchorterminal.com/compare/minimax-m2-5-vs-occamy-1-0.json",
        "title": "MiniMax-M2.5 vs occamy-1.0",
        "url": "https://www.anchorterminal.com/compare/minimax-m2-5-vs-occamy-1-0"
      },
      {
        "json": "https://www.anchorterminal.com/compare/minimax-m2-7-vs-occamy-1-0.json",
        "title": "MiniMax-M2.7 vs occamy-1.0",
        "url": "https://www.anchorterminal.com/compare/minimax-m2-7-vs-occamy-1-0"
      },
      {
        "json": "https://www.anchorterminal.com/compare/minimax-m3-1-flash-vs-occamy-1-0.json",
        "title": "MiniMax-M3.1-Flash vs occamy-1.0",
        "url": "https://www.anchorterminal.com/compare/minimax-m3-1-flash-vs-occamy-1-0"
      },
      {
        "json": "https://www.anchorterminal.com/compare/mistral-large-4-vs-occamy-1-0.json",
        "title": "Mistral Large 4 vs occamy-1.0",
        "url": "https://www.anchorterminal.com/compare/mistral-large-4-vs-occamy-1-0"
      },
      {
        "json": "https://www.anchorterminal.com/compare/muse-glimmer-30b-vs-occamy-1-0.json",
        "title": "Muse Glimmer 30B vs occamy-1.0",
        "url": "https://www.anchorterminal.com/compare/muse-glimmer-30b-vs-occamy-1-0"
      },
      {
        "json": "https://www.anchorterminal.com/compare/nanbeige-4-2-3b-vs-occamy-1-0.json",
        "title": "Nanbeige4.2-3B vs occamy-1.0",
        "url": "https://www.anchorterminal.com/compare/nanbeige-4-2-3b-vs-occamy-1-0"
      },
      {
        "json": "https://www.anchorterminal.com/compare/nanbeige-4-3-33b-vs-occamy-1-0.json",
        "title": "Nanbeige4.3-33B vs occamy-1.0",
        "url": "https://www.anchorterminal.com/compare/nanbeige-4-3-33b-vs-occamy-1-0"
      },
      {
        "json": "https://www.anchorterminal.com/compare/nemotron-3-5-bolt-e4b-4gb-vs-occamy-1-0.json",
        "title": "NVIDIA Nemotron 3.5 Bolt E4B 4GB vs occamy-1.0",
        "url": "https://www.anchorterminal.com/compare/nemotron-3-5-bolt-e4b-4gb-vs-occamy-1-0"
      },
      {
        "json": "https://www.anchorterminal.com/compare/nemotron-3-5-lightning-30b-a3b-vs-occamy-1-0.json",
        "title": "Nemotron 3.5 Lightning 30B A3B vs occamy-1.0",
        "url": "https://www.anchorterminal.com/compare/nemotron-3-5-lightning-30b-a3b-vs-occamy-1-0"
      },
      {
        "json": "https://www.anchorterminal.com/compare/nemotron-3-nano-30b-a3b-vs-occamy-1-0.json",
        "title": "Nemotron 3 Nano 30B A3B vs occamy-1.0",
        "url": "https://www.anchorterminal.com/compare/nemotron-3-nano-30b-a3b-vs-occamy-1-0"
      },
      {
        "json": "https://www.anchorterminal.com/compare/nemotron-3-nano-4b-vs-occamy-1-0.json",
        "title": "Nemotron 3 Nano 4B vs occamy-1.0",
        "url": "https://www.anchorterminal.com/compare/nemotron-3-nano-4b-vs-occamy-1-0"
      },
      {
        "json": "https://www.anchorterminal.com/compare/nemotron-3-nano-omni-30b-a3b-reasoning-vs-occamy-1-0.json",
        "title": "Nemotron 3 Nano Omni 30B A3B Reasoning vs occamy-1.0",
        "url": "https://www.anchorterminal.com/compare/nemotron-3-nano-omni-30b-a3b-reasoning-vs-occamy-1-0"
      },
      {
        "json": "https://www.anchorterminal.com/compare/nemotron-3-super-120b-a12b-vs-occamy-1-0.json",
        "title": "Nemotron 3 Super 120B A12B vs occamy-1.0",
        "url": "https://www.anchorterminal.com/compare/nemotron-3-super-120b-a12b-vs-occamy-1-0"
      },
      {
        "json": "https://www.anchorterminal.com/compare/nemotron-3-ultra-550b-a55b-vs-occamy-1-0.json",
        "title": "Nemotron 3 Ultra 550B A55B vs occamy-1.0",
        "url": "https://www.anchorterminal.com/compare/nemotron-3-ultra-550b-a55b-vs-occamy-1-0"
      },
      {
        "json": "https://www.anchorterminal.com/compare/north-mini-code-1-0-vs-occamy-1-0.json",
        "title": "North Mini Code 1.0 vs occamy-1.0",
        "url": "https://www.anchorterminal.com/compare/north-mini-code-1-0-vs-occamy-1-0"
      },
      {
        "json": "https://www.anchorterminal.com/compare/occamy-1-0-vs-olmo-3-7b-think.json",
        "title": "occamy-1.0 vs Olmo 3 7B Think",
        "url": "https://www.anchorterminal.com/compare/occamy-1-0-vs-olmo-3-7b-think"
      },
      {
        "json": "https://www.anchorterminal.com/compare/occamy-1-0-vs-ornith-1-5-122b.json",
        "title": "occamy-1.0 vs Ornith-1.5-122B",
        "url": "https://www.anchorterminal.com/compare/occamy-1-0-vs-ornith-1-5-122b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/occamy-1-0-vs-ornith-1-5-35b-a3b.json",
        "title": "occamy-1.0 vs Ornith-1.5-35B-A3B",
        "url": "https://www.anchorterminal.com/compare/occamy-1-0-vs-ornith-1-5-35b-a3b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/occamy-1-0-vs-ornith-1-5-397b.json",
        "title": "occamy-1.0 vs Ornith-1.5-397B",
        "url": "https://www.anchorterminal.com/compare/occamy-1-0-vs-ornith-1-5-397b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/occamy-1-0-vs-ornith-1-5-9b.json",
        "title": "occamy-1.0 vs Ornith-1.5-9B",
        "url": "https://www.anchorterminal.com/compare/occamy-1-0-vs-ornith-1-5-9b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/occamy-1-0-vs-otel-2-0-llm-31b-it.json",
        "title": "occamy-1.0 vs OTel-2.0-LLM-31B-IT",
        "url": "https://www.anchorterminal.com/compare/occamy-1-0-vs-otel-2-0-llm-31b-it"
      },
      {
        "json": "https://www.anchorterminal.com/compare/occamy-1-0-vs-qwen-agentworld-35b-a3b.json",
        "title": "occamy-1.0 vs Qwen-AgentWorld-35B-A3B",
        "url": "https://www.anchorterminal.com/compare/occamy-1-0-vs-qwen-agentworld-35b-a3b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/occamy-1-0-vs-qwen3-30b-a3b-instruct-2507.json",
        "title": "occamy-1.0 vs Qwen3-30B-A3B-Instruct-2507",
        "url": "https://www.anchorterminal.com/compare/occamy-1-0-vs-qwen3-30b-a3b-instruct-2507"
      },
      {
        "json": "https://www.anchorterminal.com/compare/occamy-1-0-vs-qwen3-4b-instruct-2507.json",
        "title": "occamy-1.0 vs Qwen3-4B-Instruct-2507",
        "url": "https://www.anchorterminal.com/compare/occamy-1-0-vs-qwen3-4b-instruct-2507"
      },
      {
        "json": "https://www.anchorterminal.com/compare/occamy-1-0-vs-qwen3-5-0-8b.json",
        "title": "occamy-1.0 vs Qwen3.5-0.8B",
        "url": "https://www.anchorterminal.com/compare/occamy-1-0-vs-qwen3-5-0-8b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/occamy-1-0-vs-qwen3-5-122b-a10b.json",
        "title": "occamy-1.0 vs Qwen3.5-122B-A10B",
        "url": "https://www.anchorterminal.com/compare/occamy-1-0-vs-qwen3-5-122b-a10b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/occamy-1-0-vs-qwen3-5-2b.json",
        "title": "occamy-1.0 vs Qwen3.5-2B",
        "url": "https://www.anchorterminal.com/compare/occamy-1-0-vs-qwen3-5-2b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/occamy-1-0-vs-qwen3-5-397b-a17b.json",
        "title": "occamy-1.0 vs Qwen3.5-397B-A17B",
        "url": "https://www.anchorterminal.com/compare/occamy-1-0-vs-qwen3-5-397b-a17b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/occamy-1-0-vs-qwen3-5-4b.json",
        "title": "occamy-1.0 vs Qwen3.5-4B",
        "url": "https://www.anchorterminal.com/compare/occamy-1-0-vs-qwen3-5-4b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/occamy-1-0-vs-qwen3-5-9b.json",
        "title": "occamy-1.0 vs Qwen3.5-9B",
        "url": "https://www.anchorterminal.com/compare/occamy-1-0-vs-qwen3-5-9b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/occamy-1-0-vs-qwen3-6-27b.json",
        "title": "occamy-1.0 vs Qwen3.6-27B",
        "url": "https://www.anchorterminal.com/compare/occamy-1-0-vs-qwen3-6-27b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/occamy-1-0-vs-qwen3-6-35b-a3b.json",
        "title": "occamy-1.0 vs Qwen3.6-35B-A3B",
        "url": "https://www.anchorterminal.com/compare/occamy-1-0-vs-qwen3-6-35b-a3b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/occamy-1-0-vs-qwen3-8-27b.json",
        "title": "occamy-1.0 vs Qwen3.8-27B",
        "url": "https://www.anchorterminal.com/compare/occamy-1-0-vs-qwen3-8-27b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/occamy-1-0-vs-qwen3-8-flash-next.json",
        "title": "occamy-1.0 vs Qwen3.8-Flash-Next",
        "url": "https://www.anchorterminal.com/compare/occamy-1-0-vs-qwen3-8-flash-next"
      },
      {
        "json": "https://www.anchorterminal.com/compare/occamy-1-0-vs-qwen3-coder-30b-a3b-instruct.json",
        "title": "occamy-1.0 vs Qwen3-Coder-30B-A3B-Instruct",
        "url": "https://www.anchorterminal.com/compare/occamy-1-0-vs-qwen3-coder-30b-a3b-instruct"
      },
      {
        "json": "https://www.anchorterminal.com/compare/occamy-1-0-vs-qwen3-coder-next.json",
        "title": "occamy-1.0 vs Qwen3-Coder-Next",
        "url": "https://www.anchorterminal.com/compare/occamy-1-0-vs-qwen3-coder-next"
      },
      {
        "json": "https://www.anchorterminal.com/compare/occamy-1-0-vs-qwen3-omni-30b-a3b-instruct.json",
        "title": "occamy-1.0 vs Qwen3-Omni-30B-A3B-Instruct",
        "url": "https://www.anchorterminal.com/compare/occamy-1-0-vs-qwen3-omni-30b-a3b-instruct"
      },
      {
        "json": "https://www.anchorterminal.com/compare/occamy-1-0-vs-qwen3-vl-2b-instruct.json",
        "title": "occamy-1.0 vs Qwen3-VL-2B-Instruct",
        "url": "https://www.anchorterminal.com/compare/occamy-1-0-vs-qwen3-vl-2b-instruct"
      },
      {
        "json": "https://www.anchorterminal.com/compare/occamy-1-0-vs-qwen3-vl-30b-a3b-instruct.json",
        "title": "occamy-1.0 vs Qwen3-VL-30B-A3B-Instruct",
        "url": "https://www.anchorterminal.com/compare/occamy-1-0-vs-qwen3-vl-30b-a3b-instruct"
      },
      {
        "json": "https://www.anchorterminal.com/compare/occamy-1-0-vs-qwen3-vl-32b-instruct.json",
        "title": "occamy-1.0 vs Qwen3-VL-32B-Instruct",
        "url": "https://www.anchorterminal.com/compare/occamy-1-0-vs-qwen3-vl-32b-instruct"
      },
      {
        "json": "https://www.anchorterminal.com/compare/occamy-1-0-vs-qwen3-vl-4b-instruct.json",
        "title": "occamy-1.0 vs Qwen3-VL-4B-Instruct",
        "url": "https://www.anchorterminal.com/compare/occamy-1-0-vs-qwen3-vl-4b-instruct"
      },
      {
        "json": "https://www.anchorterminal.com/compare/occamy-1-0-vs-qwen3-vl-8b-instruct.json",
        "title": "occamy-1.0 vs Qwen3-VL-8B-Instruct",
        "url": "https://www.anchorterminal.com/compare/occamy-1-0-vs-qwen3-vl-8b-instruct"
      },
      {
        "json": "https://www.anchorterminal.com/compare/occamy-1-0-vs-qwopus3-8-27b-flash-v2.json",
        "title": "occamy-1.0 vs Qwopus3.8-27B-Flash-V2",
        "url": "https://www.anchorterminal.com/compare/occamy-1-0-vs-qwopus3-8-27b-flash-v2"
      },
      {
        "json": "https://www.anchorterminal.com/compare/occamy-1-0-vs-recursive-flint.json",
        "title": "occamy-1.0 vs Recursive Flint",
        "url": "https://www.anchorterminal.com/compare/occamy-1-0-vs-recursive-flint"
      },
      {
        "json": "https://www.anchorterminal.com/compare/occamy-1-0-vs-ripple-65b-preview.json",
        "title": "occamy-1.0 vs Ripple-65B Preview",
        "url": "https://www.anchorterminal.com/compare/occamy-1-0-vs-ripple-65b-preview"
      },
      {
        "json": "https://www.anchorterminal.com/compare/occamy-1-0-vs-sensenova-loop-9b-preview.json",
        "title": "occamy-1.0 vs SenseNova-Loop-9B-Preview",
        "url": "https://www.anchorterminal.com/compare/occamy-1-0-vs-sensenova-loop-9b-preview"
      },
      {
        "json": "https://www.anchorterminal.com/compare/occamy-1-0-vs-smollm3-3b.json",
        "title": "occamy-1.0 vs SmolLM3-3B",
        "url": "https://www.anchorterminal.com/compare/occamy-1-0-vs-smollm3-3b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/occamy-1-0-vs-spark-x2-6-4b.json",
        "title": "occamy-1.0 vs Spark-X2.6-4B",
        "url": "https://www.anchorterminal.com/compare/occamy-1-0-vs-spark-x2-6-4b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/occamy-1-0-vs-step-3-7-flash.json",
        "title": "occamy-1.0 vs Step 3.7 Flash",
        "url": "https://www.anchorterminal.com/compare/occamy-1-0-vs-step-3-7-flash"
      },
      {
        "json": "https://www.anchorterminal.com/compare/occamy-1-0-vs-swift-1-5-qwen3-8-27b.json",
        "title": "occamy-1.0 vs Swift 1.5 Qwen3.8-27B",
        "url": "https://www.anchorterminal.com/compare/occamy-1-0-vs-swift-1-5-qwen3-8-27b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/occamy-1-0-vs-swift-1-5-qwen3-8-flash-next.json",
        "title": "occamy-1.0 vs Swift 1.5 Qwen3.8-Flash-Next",
        "url": "https://www.anchorterminal.com/compare/occamy-1-0-vs-swift-1-5-qwen3-8-flash-next"
      },
      {
        "json": "https://www.anchorterminal.com/compare/occamy-1-0-vs-thinkingcap-qwen3-8-27b.json",
        "title": "occamy-1.0 vs ThinkingCap (Qwen3.8 27B)",
        "url": "https://www.anchorterminal.com/compare/occamy-1-0-vs-thinkingcap-qwen3-8-27b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/occamy-1-0-vs-unlimited-ocr-2.json",
        "title": "occamy-1.0 vs Baidu Unlimited-OCR-2",
        "url": "https://www.anchorterminal.com/compare/occamy-1-0-vs-unlimited-ocr-2"
      },
      {
        "json": "https://www.anchorterminal.com/compare/occamy-1-0-vs-wevisone-vl-2b.json",
        "title": "occamy-1.0 vs WeVisOne-VL-2B",
        "url": "https://www.anchorterminal.com/compare/occamy-1-0-vs-wevisone-vl-2b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/occamy-1-0-vs-wevisone-vl-4b.json",
        "title": "occamy-1.0 vs WeVisOne-VL-4B",
        "url": "https://www.anchorterminal.com/compare/occamy-1-0-vs-wevisone-vl-4b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/occamy-1-0-vs-zaya1-8b.json",
        "title": "occamy-1.0 vs ZAYA1-8B",
        "url": "https://www.anchorterminal.com/compare/occamy-1-0-vs-zaya1-8b"
      }
    ],
    "panel": null,
    "scores": [
      {
        "key": "capability",
        "name": "Capability",
        "pending": true,
        "weight": 35
      },
      {
        "by": 0,
        "edge": "",
        "granite-4-2-30b": 90,
        "key": "reach",
        "name": "Reach",
        "occamy-1-0": 90,
        "weight": 25
      },
      {
        "by": 0,
        "edge": "",
        "granite-4-2-30b": 55,
        "key": "risk",
        "name": "Risk",
        "occamy-1-0": 55,
        "weight": 20
      },
      {
        "by": 15,
        "edge": "granite-4-2-30b",
        "granite-4-2-30b": 85,
        "key": "interface",
        "name": "Agent interface",
        "occamy-1-0": 70,
        "weight": 10
      },
      {
        "by": 13,
        "edge": "granite-4-2-30b",
        "granite-4-2-30b": 87,
        "key": "upkeep",
        "name": "Documentation and upkeep",
        "occamy-1-0": 74,
        "weight": 10
      }
    ],
    "summary": "Granite 4.2 30B and occamy-1.0 score within a point of each other on agent readiness, 61 (C) and 61 (C). Both do open-weight models you run yourself.",
    "tasks": null,
    "tutorials": [],
    "verdicts": {
      "granite-4-2-30b": "IBM's largest reasoning cousin, with the same strengths as the 3B. It runs in every runtime we count from IBM's own builds on a 24 GB card, is signed, plain Apache 2.0, and comes with a disclosure of its training data. No safety results are published and structured output isn't documented.",
      "occamy-1-0": "A Qwen3.6-35B-A3B fine-tuned for long agent work with tools, files and code, under plain Apache 2.0, and Accio's 4-bit builds run in about 23 GB. The main gaps are no safety results, agent guidance or security contact, and every benchmark figure is Accio's own."
    }
  },
  "kind": "anchor.page",
  "links": {
    "api": "https://www.anchorterminal.com/api/v1/index.json",
    "html": "https://www.anchorterminal.com/compare/granite-4-2-30b-vs-occamy-1-0",
    "json": "https://www.anchorterminal.com/compare/granite-4-2-30b-vs-occamy-1-0.json",
    "llms": "https://www.anchorterminal.com/llms.txt",
    "markdown": "https://www.anchorterminal.com/compare/granite-4-2-30b-vs-occamy-1-0.md",
    "mcp": "https://www.anchorterminal.com/mcp",
    "slim": "https://www.anchorterminal.com/compare/granite-4-2-30b-vs-occamy-1-0.min.md"
  },
  "markdown": "Granite 4.2 30B and occamy-1.0 score within a point of each other on agent readiness, 61 (C) and 61 (C). Both do open-weight models you run yourself.\n\n- Granite 4.2 30B: grade C, 61/100, rank #65 of 160 open-weight models. Markdown https://www.anchorterminal.com/tools/granite-4-2-30b.md · JSON https://www.anchorterminal.com/api/v1/tools/granite-4-2-30b.json\n- occamy-1.0: grade C, 61/100, rank #59 of 160 open-weight models. Markdown https://www.anchorterminal.com/tools/occamy-1-0.md · JSON https://www.anchorterminal.com/api/v1/tools/occamy-1-0.json\n- Best open-weight models you download and run yourself for AI agents: https://www.anchorterminal.com/best/open-weights/index.md\n- All 6359 open weights comparisons: https://www.anchorterminal.com/compare/open-weights/index.md\n\n## Which one, for what\n\n### Granite 4.2 30B (C)\n\nGood for: Agents that want a documented, signed, Apache 2.0 reasoning model with tool calling on a 24 GB card\n\nAhead on:\n- Agent interface, 85 against 70\n- Documentation and upkeep, 87 against 74\n\nWatch for: No safety results published for it\n\n### occamy-1.0 (C)\n\nGood for: Agents that want an Apache 2.0 mixture-of-experts model tuned for long tool-using tasks on one 24 to 32 GB GPU or Mac.\n\nWatch for: No safety results, prompt-injection guidance or security contact\n\n\n## Why the edge\n\n### Agent interface: Granite 4.2 30B +15\n\n- Granite 4.2 30B (85): Chat template 20, chat_template.jinja in the repository, with roles, tools, tool responses, the thinking switch and low effort. Tool-calling format 25, the card has tool-calling sections for vLLM and SGLang, declares tools with OpenAI's function schema and names the parser to use, qwen3_coder, which both runtimes ship in the released versions read. Trained tool calling 20, the template loops over every entry in an assistant turn's tool_calls, so it renders several calls in one turn, and the card names tool calling and agentic workflows as what it's best for. Structured output 0, the card doesn't document JSON or JSON Schema output or how to ask for it. Reasoning control 10, the card documents thinking on by default, non-thinking and low-effort modes per request through the template (enable_thinking and low_effort), with the reasoning returned apart from the answer. Context 10, 131,072 tokens natively per the card and config.json. 20 + 25 + 20 + 0 + 10 + 10 = 85.\n- occamy-1.0 (70): Chat template 20, the base's Jinja template in the repository. Tool-calling format 10 of 25, the card names the parser but the format lives only in the template. Trained tool calling 20, trained on tool use with several calls a turn. Structured output 0, not documented. Reasoning control 10, enable_thinking per request and the card says to keep the returned reasoning content. Context 10, 262,144 tokens.\n\n### Documentation and upkeep: Granite 4.2 30B +13\n\n- Granite 4.2 30B (87): Model card 17, Intended use (best for), limitations (ethical considerations and limitations), architecture, parameters (30B), context length (128K native) and 12 tested languages are on the card. Training data 20, IBM's disclosure file for the 30B lists the datasets used in pre-training and post-training as machine-readable metadata, and the card describes the three training stages. Last change 15, the last commit to the repository was on 4 September 2026, 67 days before this check. Responsiveness 20, Of the 4 discussions that aren't pull requests (28 August to 3 November 2026), 3 have a reply from an ibm-granite member. Version policy 5, Granite 4.1 30B stays in its own repository and 4.2 came out in new ones. File health 10, Config, template and card agree on the architecture, the 131,072-token context and the thinking switch. 17 + 20 + 15 + 20 + 5 + 10 = 87.\n- occamy-1.0 (74): Model card 14 of 20, languages and a knowledge cut-off are missing. Training data 15, the mix by type with token counts, the method and a published subset, without a cut-off. Last change 20, Accio's GGUF build card changed on 19 October 2026 and the main card on 2 October. Responsiveness 10, Accio answered 4 of 9 questions. Version policy 5, a first release with no files replaced. File health 10, the files agree with the card. 14 + 15 + 20 + 10 + 5 + 10 = 74.\n\n## Score by category\n\n| Category | Weight | Granite 4.2 30B | occamy-1.0 | Edge |\n| --- | --- | --- | --- | --- |\n| Capability | 35%, pending | pending | pending | not scored in this run |\n| Reach | 25% (25 this run) | 90 | 90 | even |\n| Risk | 20% (20 this run) | 55 | 55 | even |\n| Agent interface | 10% (10 this run) | 85 | 70 | Granite 4.2 30B +15 |\n| Documentation and upkeep | 10% (10 this run) | 87 | 74 | Granite 4.2 30B +13 |\n| Negative events | ≤15 | 0 | 0 | |\n| **Total** | | **61 · C** | **61 · C** | |\n\n## Facts side by side\n\n| Fact | Granite 4.2 30B | occamy-1.0 |\n| --- | --- | --- |\n| Kind | Open-weight model | Open-weight model |\n| Vendor | IBM | Accio (Accio-Lab) |\n| Hosted endpoint | no (local only) | no (local only) |\n| Transports |  |  |\n| Auth | None | None |\n| Pricing | Free | Free |\n| x402 | no | no |\n| Licence | Apache-2.0 | Apache-2.0 |\n| Read-only variant documented | no | no |\n| llms.txt | no | no |\n| Last release | 2026-09-04 | 2026-10-02 |\n| Terms last updated | no document linked | no document linked |\n| Privacy policy last updated | no document linked | no document linked |\n| Agent reviews | none | 3/5 (4) |\n\n## How the scores have moved\n\n### Granite 4.2 30B\n\nNo score change since it was listed.\n\n### occamy-1.0\n\n- no change on 3 November 2026: correction\n\n## Verdicts\n\n**Granite 4.2 30B.** IBM's largest reasoning cousin, with the same strengths as the 3B. It runs in every runtime we count from IBM's own builds on a 24 GB card, is signed, plain Apache 2.0, and comes with a disclosure of its training data. No safety results are published and structured output isn't documented.\n\n**occamy-1.0.** A Qwen3.6-35B-A3B fine-tuned for long agent work with tools, files and code, under plain Apache 2.0, and Accio's 4-bit builds run in about 23 GB. The main gaps are no safety results, agent guidance or security contact, and every benchmark figure is Accio's own.\n\n## Before you call either\n\n### Granite 4.2 30B\n\n1. Start it with `ollama run granite4.2:30b`, or `llama-server -hf ibm-granite/granite-4.2-30b-GGUF:Q4_K_M --jinja`\n2. With vLLM 0.32.0 or later leave out `--reasoning-parser-plugin`, since the parser is built in, and use `--tool-call-parser qwen3_coder`\n3. Thinking is on by default. Pass `enable_thinking` false to turn it off or `low_effort` true for short reasoning\n4. The context is 131,072 tokens. The card's 512K extension isn't documented\n5. Validate JSON output yourself, since structured output isn't documented\n6. IBM recommends Granite Guardian beside it to flag risky inputs and outputs\n\n### occamy-1.0\n\n1. Serve with `--reasoning-parser qwen3 --enable-auto-tool-choice --tool-call-parser qwen3_coder` on vLLM 0.19.0 or SGLang 0.5.10 and later\n2. BF16 is 70.2 GB, so on a 128 GB machine run it without the card's 8-way tensor parallelism\n3. Keep the whole assistant message, reasoning and tool calls included, in later turns, as the card says\n4. Sampling per the card is temperature 1.0, top_p 0.95, top_k 20 and presence_penalty 1.5\n5. With the GGUFs, NFC-normalise input text and read TOKENIZER.md, since the files store qwen2 pre-tokenizer metadata\n6. The base's MTP layer isn't in this checkpoint, Accio-Lab/occamy-1.0-MTP is an experimental separate head\n7. Ollama has no Occamy library entry, so load Accio's GGUF in Ollama 0.40.14 or later, which builds a llama.cpp with the qwen35moe architecture\n\n## Questions\n\n### Which is better for AI agents, Granite 4.2 30B or occamy-1.0?\n\nGranite 4.2 30B and occamy-1.0 score within a point of each other on agent readiness, 61 (C) and 61 (C).\n\n\n## For agents\n\n- This comparison as JSON: https://www.anchorterminal.com/compare/granite-4-2-30b-vs-occamy-1-0.json, and with the fewest tokens: https://www.anchorterminal.com/compare/granite-4-2-30b-vs-occamy-1-0.min.md\n- Over MCP at https://www.anchorterminal.com/mcp (no key): `compare_tools {\"a\": \"granite-4-2-30b\", \"b\": \"occamy-1-0\"}`. From a terminal: `anchor compare granite-4-2-30b occamy-1-0`\n- Each listing in full: https://www.anchorterminal.com/api/v1/tools/granite-4-2-30b.json and https://www.anchorterminal.com/api/v1/tools/occamy-1-0.json\n\n## Other comparisons with Granite 4.2 30B or occamy-1.0\n\n- [Agents-A1-4B vs Granite 4.2 30B](https://www.anchorterminal.com/compare/agents-a1-4b-vs-granite-4-2-30b.md)\n- [Agents-A1-4B vs occamy-1.0](https://www.anchorterminal.com/compare/agents-a1-4b-vs-occamy-1-0.md)\n- [Apertus v1.5 8B vs Granite 4.2 30B](https://www.anchorterminal.com/compare/apertus-v1-5-8b-vs-granite-4-2-30b.md)\n- [Apertus v1.5 8B vs occamy-1.0](https://www.anchorterminal.com/compare/apertus-v1-5-8b-vs-occamy-1-0.md)\n- [Apodex-1.1-mini vs Granite 4.2 30B](https://www.anchorterminal.com/compare/apodex-1-1-mini-vs-granite-4-2-30b.md)\n- [Apodex-1.1-mini vs occamy-1.0](https://www.anchorterminal.com/compare/apodex-1-1-mini-vs-occamy-1-0.md)\n- [Arete-27B vs Granite 4.2 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      {
        "name": "Granite 4.2 30B vs occamy-1.0",
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    "description": "Granite 4.2 30B and occamy-1.0 score within a point of each other for open-weight models you run yourself, 61 and 61 out of 100. Prices, MCP, x402, uptime and agent notes side by side.",
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    "h1": "Granite 4.2 30B vs occamy-1.0",
    "image": "https://www.anchorterminal.com/assets/og/default.png",
    "path": "/compare/granite-4-2-30b-vs-occamy-1-0",
    "published": "2026-10-01",
    "section": "tools",
    "title": "Granite 4.2 30B vs occamy-1.0 for AI agents in 2026: scores and prices",
    "toc": null,
    "updated": "2026-11-10",
    "url": "https://www.anchorterminal.com/compare/granite-4-2-30b-vs-occamy-1-0"
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