{
  "data": {
    "a": {
      "slug": "north-mini-code-1-0",
      "name": "North Mini Code 1.0",
      "vendor": "Cohere",
      "vendorUrl": "https://cohere.com",
      "kind": "weights",
      "category": "open-weights",
      "summary": "North Mini Code 1.0 is Cohere's open-weight coding agent model, a mixture of experts of 30B parameters with 3B active, trained for tool use, with interleaved thinking and a 256K context. Apache 2.0. Cohere's 4-bit build is 19 GB.",
      "url": "https://www.anchorterminal.com/tools/north-mini-code-1-0",
      "markdownUrl": "https://www.anchorterminal.com/tools/north-mini-code-1-0.md",
      "slimMarkdownUrl": "https://www.anchorterminal.com/tools/north-mini-code-1-0.min.md",
      "jsonUrl": "https://www.anchorterminal.com/api/v1/tools/north-mini-code-1-0.json",
      "dns": "north-mini-code-1-0.grade.anchorterminal.com",
      "repo": "https://huggingface.co/CohereLabs/North-Mini-Code-1.0",
      "license": "Apache-2.0",
      "transports": [],
      "packages": [
        {
          "registry": "huggingface",
          "name": "CohereLabs/North-Mini-Code-1.0"
        },
        {
          "registry": "huggingface",
          "name": "CohereLabs/North-Mini-Code-1.0-fp8"
        },
        {
          "registry": "huggingface",
          "name": "CohereLabs/North-Mini-Code-1.0-w4a16"
        }
      ],
      "auth": "none",
      "authNotes": "The weights download from Hugging Face with no account, token or terms to accept. None of the repositories is gated (checked 2026-11-10).",
      "pricing": "free",
      "pricingNotes": "Free to download and use under Apache 2.0. The card calls it a research release. Running it yourself takes 19.4 GB at 4 bits (w4a16), 32.1 GB in FP8 or 61.0 GB in BF16 (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/CohereLabs/North-Mini-Code-1.0",
      "capabilities": [
        "model.open-weights"
      ],
      "tags": [
        "open-weights",
        "model",
        "moe",
        "coding",
        "agentic",
        "reasoning",
        "tool-calling",
        "long-context",
        "apache-2.0",
        "safetensors",
        "fp8",
        "4-bit",
        "self-hosted"
      ],
      "lastRelease": "2026-07-29",
      "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": 63,
        "methodology": "0.7",
        "run": "2026-10-01",
        "scores": {
          "interface": 85,
          "reach": 85,
          "risk": 60,
          "upkeep": 36
        },
        "pending": [
          "performance",
          "tasks"
        ],
        "assessment": {
          "confidence": "low",
          "date": "2026-11-10"
        },
        "negative": 0,
        "verdict": "A coding agent model that fits one 24 GB GPU at 4 bits, trained for tool use, with a 256K context, Apache 2.0 and four released runtimes. It's a research release and reads like one: nothing on limitations, safety or data, the card's run instructions are out of date, and Cohere hasn't answered a question on the repository.",
        "bestFor": "Developers who want a coding agent on their own GPU with a permissive licence",
        "strengths": [
          "Trained for tool use in coding agents, with parsers in released vLLM",
          "19 GB at 4 bits from Cohere, and a 256K context",
          "Apache 2.0, ungated",
          "Four released runtimes carry the architecture",
          "Tool use documented with a worked example"
        ],
        "weaknesses": [
          "No limitations, safety results, languages or data description on the card",
          "No reply from Cohere on the repository's discussions",
          "The card's instructions still point at unreleased vLLM and Transformers",
          "No GGUF from Cohere",
          "Text only",
          "No hosted API named"
        ],
        "agentNotes": [
          "Serve it with vLLM 0.33.0 or later and `--tool-call-parser cohere_command4 --reasoning-parser cohere_command4 --enable-auto-tool-choice`, with `cohere_melody` installed",
          "Pass the model's thinking back with its tool calls on every turn. The card says results drop without it",
          "Describe tools in JSON schema and append tool results as a dictionary with the tool role",
          "Use temperature 1.0 and top_p 0.95",
          "For llama.cpp the GGUF files are Unsloth's or bartowski's conversions, not Cohere's",
          "It's text only. Don't send images"
        ],
        "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": 85,
          "risk": 60,
          "upkeep": 36
        },
        "provenanceScore": 75,
        "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": "pip install \"vllm\u003e=0.33.0\" \"cohere_melody\u003e=0.9.0\"\nvllm serve CohereLabs/North-Mini-Code-1.0 -tp 2 --max-model-len 320000 --tool-call-parser cohere_command4 --reasoning-parser cohere_command4 --enable-auto-tool-choice",
        "http": "# vLLM serves an OpenAI-compatible API at http://localhost:8000/v1. Use temperature 1.0 and top_p 0.95,\n# and send the model's earlier thinking back with each turn"
      },
      "letme": {
        "capability": "https://letme.dev/model.open-weights",
        "tool": "https://letme.dev/north-mini-code-1-0"
      },
      "sameCompany": [
        "cohere-chat",
        "cohere-embed",
        "cohere-transcribe-03-2026",
        "cohere-north"
      ],
      "weights": {
        "trainedBy": "Cohere and Cohere Labs",
        "params": "30B",
        "active": "3B",
        "context": 256000,
        "goodFor": "A local coding agent: repository work, terminal tasks and long tool-calling sessions, on one 24 GB GPU at 4 bits.",
        "runtimes": [
          "llama.cpp",
          "vLLM",
          "SGLang",
          "Transformers"
        ],
        "builds": [
          {
            "name": "North-Mini-Code-1.0-w4a16",
            "url": "https://huggingface.co/CohereLabs/North-Mini-Code-1.0-w4a16",
            "who": "publisher",
            "precision": "w4a16",
            "sizeGB": 19.38,
            "memoryGB": 24,
            "format": "safetensors",
            "runsOn": [
              "vLLM"
            ],
            "note": "Cohere's 4-bit weight build"
          },
          {
            "name": "unsloth North-Mini-Code-1.0-GGUF (UD-Q4_K_M)",
            "url": "https://huggingface.co/unsloth/North-Mini-Code-1.0-GGUF",
            "who": "unsloth",
            "precision": "q4_k_m",
            "sizeGB": 19.2,
            "memoryGB": 24,
            "format": "gguf",
            "runsOn": [
              "llama.cpp"
            ],
            "note": "From Unsloth, a third party's conversion and not Cohere's. 19.20 GB of UD-Q4_K_M weights, from the Hub's model information on 10 November 2026. Reach doesn't count it"
          },
          {
            "name": "North-Mini-Code-1.0-fp8",
            "url": "https://huggingface.co/CohereLabs/North-Mini-Code-1.0-fp8",
            "who": "publisher",
            "precision": "fp8",
            "sizeGB": 32.06,
            "memoryGB": 48,
            "format": "safetensors",
            "runsOn": [
              "vLLM",
              "SGLang"
            ],
            "note": "Cohere's FP8 build"
          },
          {
            "name": "unsloth North-Mini-Code-1.0-GGUF (Q8_0)",
            "url": "https://huggingface.co/unsloth/North-Mini-Code-1.0-GGUF",
            "who": "unsloth",
            "precision": "q8_0",
            "sizeGB": 32.44,
            "memoryGB": 48,
            "format": "gguf",
            "runsOn": [
              "llama.cpp"
            ],
            "note": "From Unsloth, a third party's conversion and not Cohere's. 32.44 GB of Q8_0 weights, from the Hub's model information on 10 November 2026. Reach doesn't count it"
          },
          {
            "name": "North-Mini-Code-1.0 (BF16 safetensors)",
            "url": "https://huggingface.co/CohereLabs/North-Mini-Code-1.0",
            "who": "publisher",
            "precision": "bf16",
            "sizeGB": 60.97,
            "memoryGB": 96,
            "format": "safetensors",
            "runsOn": [
              "vLLM",
              "SGLang",
              "Transformers"
            ],
            "note": "49 files"
          }
        ],
        "run": "vllm serve CohereLabs/North-Mini-Code-1.0-w4a16 --tool-call-parser cohere_command4 --reasoning-parser cohere_command4 --enable-auto-tool-choice",
        "runBuild": "North-Mini-Code-1.0-w4a16",
        "checked": "2026-11-10",
        "minMemoryGB": 24
      },
      "family": {
        "lab": "Cohere (Cohere Labs)",
        "family": "North Mini Code",
        "url": "https://www.anchorterminal.com/open-weights/#cohere",
        "olderCount": 29
      },
      "area": "models",
      "provenance": {
        "legalEntity": "Cohere Inc.",
        "domain": "cohere.com",
        "domainRegistered": "2000-03-07",
        "endpointOnVendorDomain": null,
        "terms": "",
        "privacy": "",
        "statusPage": "",
        "changelog": "https://huggingface.co/CohereLabs/North-Mini-Code-1.0/commits/main",
        "securityTxt": "none",
        "checked": "2026-11-10",
        "notes": [
          "The card says Developed by Cohere and Cohere Labs. Legal entity, domain and security facts are carried from our other Cohere listings.",
          "Nothing is hosted under this listing, so Apache 2.0 stands in for terms of service and no privacy policy is scored.",
          "The changelog is the commit history, 8 commits from 5 to 15 June 2026."
        ],
        "score": 75
      },
      "pageJsonUrl": "https://www.anchorterminal.com/tools/north-mini-code-1-0.json"
    },
    "answer": "North Mini Code 1.0 and occamy-1.0 score within a point of each other on agent readiness, 61 (C) and 61 (C). occamy-1.0 leads on reach and documentation and upkeep.",
    "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": 38,
        "category": "upkeep",
        "leads": "occamy-1-0",
        "name": "Documentation and upkeep",
        "reasons": {
          "a": "Model card 11, Intended use, the architecture, the parameters and the context are on the card. Training data 0, the card gives the training method and nothing about the data. Last change 10, the main repository last changed on 15 June 2026 (outdated chat templates removed), 148 days before this check, and the draft model's repository on 29 July, 104 days. Responsiveness 0, none of the 11 most recent discussions that aren't pull requests (7 June to 6 November 2026) has a reply from a CohereLabs member, counted on 10 November by author flags and dates with a script, text not read. Version policy 5, A first release, with each build in its own repository. File health 10, Config, template and card agree on the architecture, and the June commit that removed broken templates says so. 11 + 0 + 10 + 0 + 5 + 10 = 36.",
          "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": 36,
          "b": 74
        }
      },
      {
        "by": 15,
        "category": "interface",
        "leads": "north-mini-code-1-0",
        "name": "Agent interface",
        "reasons": {
          "a": "Chat template 20, chat_template.jinja in the repository (12,397 characters). Tool-calling format 25, the card documents how tools are declared (JSON schema through the chat template), how the call and its thinking go back into the history and how results are appended, and names the cohere_command4 tool-call parser for vLLM, which released vLLM has. Trained tool calling 20, the card says the model was specifically trained with tool-use capabilities for agentic coding, with reinforcement learning on verifiable tasks, and the template renders every call in a turn with thinking between them. Structured output 0, JSON schema is for describing tools. Reasoning control 10, the template has a reasoning_effort setting, and the card names the cohere_command4 reasoning parser, which returns thinking apart from the answer. Context 10, 256K tokens per the card, with 64K of output, and 500,000 positions in 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": 5,
        "category": "reach",
        "leads": "occamy-1-0",
        "name": "Reach",
        "reasons": {
          "a": "Memory 25, the smallest build from Cohere is the w4a16 repository, 19.38 GB, and 19.38 GB × 1.2 = 23.3 GB, within 24 GB. Unsloth's GGUF isn't read for this line. Runtimes 20, Released vLLM 0.33.0, SGLang 0.5.23 and Transformers 5.22.2 have the cohere2_moe model, and llama.cpp b12242 has the cohere2moe architecture. Builds 15, Quantised builds from Cohere at two precisions, FP8 and 4-bit weights (w4a16), each in its own repository. Terms 15, Apache 2.0 in the metadata and on the card, an OSI licence with nothing added. Download 10, the Hub API reports gated false for the model and its builds on 10 November 2026, so the files download with no account and nothing to accept. Hosted 0, Hugging Face maps no inference provider to it. 25 + 20 + 15 + 15 + 10 + 0 = 85.",
          "b": "Memory 25 of 30, Accio's MLX mxfp4 build is 18.4 GB, 22.1 GB with a fifth added, and its IQ4_XS GGUF needs 22.5 GB, both within 24 GB. Runtimes 25, the most the line gives, it keeps the base's qwen3_5_moe architecture, which llama.cpp, vLLM, SGLang and Transformers run in released versions, and Ollama v0.40.14 builds a llama.cpp (b11963) that has it. Builds 15, FP8, NVFP4, GGUF and MLX from Accio. Terms 15, Apache 2.0 like its base. Download 10, nothing is gated. Hosted 0, no API or inference provider serves it. 25 + 25 + 15 + 15 + 10 + 0 = 90."
        },
        "scores": {
          "a": 85,
          "b": 90
        }
      },
      {
        "by": 5,
        "category": "risk",
        "leads": "north-mini-code-1-0",
        "name": "Risk",
        "reasons": {
          "a": "File safety 25, safetensors only, no .bin, .pt or .pth files and no Python in the repository. Provenance 15, the files sit in Cohere's verified CohereLabs organisation, which cohere.com links to per our other Cohere listings (10). Safety evaluation 0, no safety results on the card. Agent guidance 0, the card has no limitations or safety section, and nothing on prompt injection, instruction priority or what the model refuses. Licence risk 15, Apache 2.0 has no use policy, threshold or change clause. Security programme 5, Cohere's trust centre holds a responsible disclosure policy with a bug bounty, as recorded on our Cohere listings (5). 25 + 15 + 0 + 0 + 15 + 5 = 60.",
          "b": "File safety 25, safetensors only and nothing from the repository runs to load it or build prompts. Provenance 15, the files are in the organisation Accio's GitHub links, with MD5 sums and SHA-256 for every file. Safety evaluation 0, none published. Agent guidance 0. Licence risk 15, plain Apache 2.0 that hasn't changed. Security programme 0, bug reports go to public GitHub issues and there's no security contact."
        },
        "scores": {
          "a": 60,
          "b": 55
        }
      }
    ],
    "facts": [
      {
        "a": "Open-weight model",
        "b": "Open-weight model",
        "name": "Kind"
      },
      {
        "a": "Cohere",
        "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": "2026-07-29",
        "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": "North Mini Code 1.0 and occamy-1.0 score within a point of each other on agent readiness, 61 (C) and 61 (C). occamy-1.0 leads on reach and documentation and upkeep.",
        "question": "Which is better for AI agents, North Mini Code 1.0 or occamy-1.0?"
      }
    ],
    "goodFor": [
      {
        "aheadOn": [
          "Risk, 60 against 55",
          "Agent interface, 85 against 70"
        ],
        "also": null,
        "goodFor": "Developers who want a coding agent on their own GPU with a permissive licence",
        "slug": "north-mini-code-1-0",
        "watchFor": "No limitations, safety results, languages or data description on the card"
      },
      {
        "aheadOn": [
          "Reach, 90 against 85",
          "Documentation and upkeep, 74 against 36"
        ],
        "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": {
      "north-mini-code-1-0": 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-north-mini-code-1-0.json",
        "title": "Agents-A1-4B vs North Mini Code 1.0",
        "url": "https://www.anchorterminal.com/compare/agents-a1-4b-vs-north-mini-code-1-0"
      },
      {
        "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-north-mini-code-1-0.json",
        "title": "Apertus v1.5 8B vs North Mini Code 1.0",
        "url": "https://www.anchorterminal.com/compare/apertus-v1-5-8b-vs-north-mini-code-1-0"
      },
      {
        "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-north-mini-code-1-0.json",
        "title": "Apodex-1.1-mini vs North Mini Code 1.0",
        "url": "https://www.anchorterminal.com/compare/apodex-1-1-mini-vs-north-mini-code-1-0"
      },
      {
        "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-north-mini-code-1-0.json",
        "title": "Arete-27B vs North Mini Code 1.0",
        "url": "https://www.anchorterminal.com/compare/arete-27b-vs-north-mini-code-1-0"
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      {
        "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-north-mini-code-1-0.json",
        "title": "BigBang-v1 vs North Mini Code 1.0",
        "url": "https://www.anchorterminal.com/compare/bigbang-v1-vs-north-mini-code-1-0"
      },
      {
        "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-north-mini-code-1-0.json",
        "title": "Carbon-X vs North Mini Code 1.0",
        "url": "https://www.anchorterminal.com/compare/carbon-x-vs-north-mini-code-1-0"
      },
      {
        "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-north-mini-code-1-0.json",
        "title": "Cola2 vs North Mini Code 1.0",
        "url": "https://www.anchorterminal.com/compare/cola2-vs-north-mini-code-1-0"
      },
      {
        "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-north-mini-code-1-0.json",
        "title": "Cosmos-Reason2-2B vs North Mini Code 1.0",
        "url": "https://www.anchorterminal.com/compare/cosmos-reason2-2b-vs-north-mini-code-1-0"
      },
      {
        "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-north-mini-code-1-0.json",
        "title": "Darwin-36B-Opus vs North Mini Code 1.0",
        "url": "https://www.anchorterminal.com/compare/darwin-36b-opus-vs-north-mini-code-1-0"
      },
      {
        "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-north-mini-code-1-0.json",
        "title": "DeepSeek-V3.2 vs North Mini Code 1.0",
        "url": "https://www.anchorterminal.com/compare/deepseek-v3-2-vs-north-mini-code-1-0"
      },
      {
        "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"
      },
      {
        "json": "https://www.anchorterminal.com/compare/deepseek-v4-1-flash-vs-north-mini-code-1-0.json",
        "title": "DeepSeek V4.1 Flash vs North Mini Code 1.0",
        "url": "https://www.anchorterminal.com/compare/deepseek-v4-1-flash-vs-north-mini-code-1-0"
      },
      {
        "json": "https://www.anchorterminal.com/compare/deepseek-v4-1-flash-vs-occamy-1-0.json",
        "title": "DeepSeek V4.1 Flash vs occamy-1.0",
        "url": "https://www.anchorterminal.com/compare/deepseek-v4-1-flash-vs-occamy-1-0"
      },
      {
        "json": "https://www.anchorterminal.com/compare/deepseek-v4-flash-0731-vs-north-mini-code-1-0.json",
        "title": "DeepSeek-V4-Flash-0731 vs North Mini Code 1.0",
        "url": "https://www.anchorterminal.com/compare/deepseek-v4-flash-0731-vs-north-mini-code-1-0"
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      {
        "json": "https://www.anchorterminal.com/compare/deepseek-v4-flash-0731-vs-occamy-1-0.json",
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        "url": "https://www.anchorterminal.com/compare/deepseek-v4-flash-0731-vs-occamy-1-0"
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      {
        "json": "https://www.anchorterminal.com/compare/devstral-small-2-vs-north-mini-code-1-0.json",
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        "url": "https://www.anchorterminal.com/compare/devstral-small-2-vs-north-mini-code-1-0"
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      {
        "json": "https://www.anchorterminal.com/compare/devstral-small-2-vs-occamy-1-0.json",
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        "url": "https://www.anchorterminal.com/compare/devstral-small-2-vs-occamy-1-0"
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      {
        "json": "https://www.anchorterminal.com/compare/diffusiongemma-26b-a4b-it-vs-north-mini-code-1-0.json",
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      {
        "json": "https://www.anchorterminal.com/compare/exaone-4-5-33b-vs-north-mini-code-1-0.json",
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        "url": "https://www.anchorterminal.com/compare/exaone-4-5-33b-vs-north-mini-code-1-0"
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        "json": "https://www.anchorterminal.com/compare/exaone-4-5-33b-vs-occamy-1-0.json",
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        "url": "https://www.anchorterminal.com/compare/exaone-4-5-33b-vs-occamy-1-0"
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      {
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        "url": "https://www.anchorterminal.com/compare/gemma-4-12b-it-vs-north-mini-code-1-0"
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        "url": "https://www.anchorterminal.com/compare/gemma-4-12b-it-vs-occamy-1-0"
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      {
        "json": "https://www.anchorterminal.com/compare/gemma-4-26b-a4b-it-vs-north-mini-code-1-0.json",
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        "url": "https://www.anchorterminal.com/compare/gemma-4-e2b-it-vs-north-mini-code-1-0"
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        "json": "https://www.anchorterminal.com/compare/gemma-4-e2b-it-vs-occamy-1-0.json",
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        "url": "https://www.anchorterminal.com/compare/gemma-4-e2b-it-vs-occamy-1-0"
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        "url": "https://www.anchorterminal.com/compare/gemma-4-e4b-it-vs-north-mini-code-1-0"
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        "title": "Gemma 4 E4B IT vs occamy-1.0",
        "url": "https://www.anchorterminal.com/compare/gemma-4-e4b-it-vs-occamy-1-0"
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        "json": "https://www.anchorterminal.com/compare/glm-4-5-air-vs-north-mini-code-1-0.json",
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        "url": "https://www.anchorterminal.com/compare/glm-5-3-flash-vs-north-mini-code-1-0"
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        "json": "https://www.anchorterminal.com/compare/glm-5-3-flash-vs-occamy-1-0.json",
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        "url": "https://www.anchorterminal.com/compare/glm-5-3-flash-vs-occamy-1-0"
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        "json": "https://www.anchorterminal.com/compare/glm-5-3-vs-north-mini-code-1-0.json",
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        "url": "https://www.anchorterminal.com/compare/glm-5-3-vs-north-mini-code-1-0"
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        "json": "https://www.anchorterminal.com/compare/glm-5-3-vs-occamy-1-0.json",
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        "url": "https://www.anchorterminal.com/compare/glm-5-3-vs-occamy-1-0"
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        "json": "https://www.anchorterminal.com/compare/gpt-oss-120b-vs-north-mini-code-1-0.json",
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        "url": "https://www.anchorterminal.com/compare/gpt-oss-120b-vs-north-mini-code-1-0"
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        "json": "https://www.anchorterminal.com/compare/gpt-oss-120b-vs-occamy-1-0.json",
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        "url": "https://www.anchorterminal.com/compare/gpt-oss-120b-vs-occamy-1-0"
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        "json": "https://www.anchorterminal.com/compare/gpt-oss-20b-vs-north-mini-code-1-0.json",
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        "url": "https://www.anchorterminal.com/compare/gpt-oss-20b-vs-north-mini-code-1-0"
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        "json": "https://www.anchorterminal.com/compare/gpt-oss-20b-vs-occamy-1-0.json",
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        "url": "https://www.anchorterminal.com/compare/gpt-oss-20b-vs-occamy-1-0"
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        "json": "https://www.anchorterminal.com/compare/granite-4-2-30b-vs-north-mini-code-1-0.json",
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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-occamy-1-0.json",
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        "url": "https://www.anchorterminal.com/compare/granite-4-2-30b-vs-occamy-1-0"
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        "json": "https://www.anchorterminal.com/compare/granite-4-2-3b-vs-north-mini-code-1-0.json",
        "title": "Granite 4.2 3B vs North Mini Code 1.0",
        "url": "https://www.anchorterminal.com/compare/granite-4-2-3b-vs-north-mini-code-1-0"
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        "json": "https://www.anchorterminal.com/compare/granite-4-2-3b-vs-occamy-1-0.json",
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        "url": "https://www.anchorterminal.com/compare/granite-4-2-3b-vs-occamy-1-0"
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        "json": "https://www.anchorterminal.com/compare/granite-4-2-8b-vs-north-mini-code-1-0.json",
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        "url": "https://www.anchorterminal.com/compare/granite-4-2-8b-vs-north-mini-code-1-0"
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      {
        "json": "https://www.anchorterminal.com/compare/granite-4-2-8b-vs-occamy-1-0.json",
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        "url": "https://www.anchorterminal.com/compare/granite-4-2-8b-vs-occamy-1-0"
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        "json": "https://www.anchorterminal.com/compare/hy-memory-30b-a3b-vs-north-mini-code-1-0.json",
        "title": "Hy-Memory-30B-A3B vs North Mini Code 1.0",
        "url": "https://www.anchorterminal.com/compare/hy-memory-30b-a3b-vs-north-mini-code-1-0"
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        "json": "https://www.anchorterminal.com/compare/hy-memory-30b-a3b-vs-occamy-1-0.json",
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        "url": "https://www.anchorterminal.com/compare/hy-memory-30b-a3b-vs-occamy-1-0"
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      {
        "json": "https://www.anchorterminal.com/compare/hy3-vs-north-mini-code-1-0.json",
        "title": "Hy3 vs North Mini Code 1.0",
        "url": "https://www.anchorterminal.com/compare/hy3-vs-north-mini-code-1-0"
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      {
        "json": "https://www.anchorterminal.com/compare/hy3-vs-occamy-1-0.json",
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        "url": "https://www.anchorterminal.com/compare/hy3-vs-occamy-1-0"
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        "json": "https://www.anchorterminal.com/compare/inkling-small-vs-north-mini-code-1-0.json",
        "title": "Inkling-Small vs North Mini Code 1.0",
        "url": "https://www.anchorterminal.com/compare/inkling-small-vs-north-mini-code-1-0"
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        "json": "https://www.anchorterminal.com/compare/inkling-small-vs-occamy-1-0.json",
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        "url": "https://www.anchorterminal.com/compare/inkling-small-vs-occamy-1-0"
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        "json": "https://www.anchorterminal.com/compare/inkling-vs-north-mini-code-1-0.json",
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        "url": "https://www.anchorterminal.com/compare/inkling-vs-north-mini-code-1-0"
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        "json": "https://www.anchorterminal.com/compare/inkling-vs-occamy-1-0.json",
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        "url": "https://www.anchorterminal.com/compare/inkling-vs-occamy-1-0"
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        "json": "https://www.anchorterminal.com/compare/internvl3-5-gpt-oss-20b-a4b-preview-vs-north-mini-code-1-0.json",
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        "url": "https://www.anchorterminal.com/compare/internvl3-5-gpt-oss-20b-a4b-preview-vs-north-mini-code-1-0"
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        "url": "https://www.anchorterminal.com/compare/internvl3-5-gpt-oss-20b-a4b-preview-vs-occamy-1-0"
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        "json": "https://www.anchorterminal.com/compare/kimi-k3-1-pro-vs-north-mini-code-1-0.json",
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        "url": "https://www.anchorterminal.com/compare/kimi-k3-1-pro-vs-north-mini-code-1-0"
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      {
        "json": "https://www.anchorterminal.com/compare/kimi-k3-1-pro-vs-occamy-1-0.json",
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        "url": "https://www.anchorterminal.com/compare/kimi-k3-1-pro-vs-occamy-1-0"
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      {
        "json": "https://www.anchorterminal.com/compare/kimi-k3-vs-north-mini-code-1-0.json",
        "title": "Kimi K3 vs North Mini Code 1.0",
        "url": "https://www.anchorterminal.com/compare/kimi-k3-vs-north-mini-code-1-0"
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        "json": "https://www.anchorterminal.com/compare/kimi-k3-vs-occamy-1-0.json",
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        "url": "https://www.anchorterminal.com/compare/kimi-k3-vs-occamy-1-0"
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        "json": "https://www.anchorterminal.com/compare/kolibri-1-vs-north-mini-code-1-0.json",
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        "url": "https://www.anchorterminal.com/compare/kolibri-1-vs-north-mini-code-1-0"
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      {
        "json": "https://www.anchorterminal.com/compare/kolibri-1-vs-occamy-1-0.json",
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        "url": "https://www.anchorterminal.com/compare/kolibri-1-vs-occamy-1-0"
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        "json": "https://www.anchorterminal.com/compare/kronos-vs-north-mini-code-1-0.json",
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        "url": "https://www.anchorterminal.com/compare/kronos-vs-north-mini-code-1-0"
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        "json": "https://www.anchorterminal.com/compare/kronos-vs-occamy-1-0.json",
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        "url": "https://www.anchorterminal.com/compare/kronos-vs-occamy-1-0"
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        "json": "https://www.anchorterminal.com/compare/laguna-m-1-vs-north-mini-code-1-0.json",
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        "url": "https://www.anchorterminal.com/compare/laguna-m-1-vs-north-mini-code-1-0"
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        "json": "https://www.anchorterminal.com/compare/laguna-m-1-vs-occamy-1-0.json",
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        "url": "https://www.anchorterminal.com/compare/laguna-m-1-vs-occamy-1-0"
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        "json": "https://www.anchorterminal.com/compare/laguna-s-2-1-vs-north-mini-code-1-0.json",
        "title": "Laguna S 2.1 vs North Mini Code 1.0",
        "url": "https://www.anchorterminal.com/compare/laguna-s-2-1-vs-north-mini-code-1-0"
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        "json": "https://www.anchorterminal.com/compare/laguna-s-2-1-vs-occamy-1-0.json",
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        "url": "https://www.anchorterminal.com/compare/laguna-s-2-1-vs-occamy-1-0"
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        "json": "https://www.anchorterminal.com/compare/laguna-xs-2-1-vs-north-mini-code-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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        "url": "https://www.anchorterminal.com/compare/laguna-xs-2-1-vs-occamy-1-0"
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        "json": "https://www.anchorterminal.com/compare/lbs-27b-vs-north-mini-code-1-0.json",
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        "url": "https://www.anchorterminal.com/compare/lbs-27b-vs-north-mini-code-1-0"
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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-north-mini-code-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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        "json": "https://www.anchorterminal.com/compare/lfm3-1-7b-vs-north-mini-code-1-0.json",
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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-north-mini-code-1-0.json",
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        "url": "https://www.anchorterminal.com/compare/lfm3-audio-2b-vs-north-mini-code-1-0"
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        "json": "https://www.anchorterminal.com/compare/lfm3-audio-2b-vs-occamy-1-0.json",
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        "json": "https://www.anchorterminal.com/compare/lfm3-omni-2b-vs-north-mini-code-1-0.json",
        "title": "LFM3-Omni-2B vs North Mini Code 1.0",
        "url": "https://www.anchorterminal.com/compare/lfm3-omni-2b-vs-north-mini-code-1-0"
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        "json": "https://www.anchorterminal.com/compare/lfm3-omni-2b-vs-occamy-1-0.json",
        "title": "LFM3-Omni-2B vs occamy-1.0",
        "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-north-mini-code-1-0.json",
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        "url": "https://www.anchorterminal.com/compare/lfm3-vl-2b-vs-north-mini-code-1-0"
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        "title": "Ling-3.0-tiny vs North Mini Code 1.0",
        "url": "https://www.anchorterminal.com/compare/ling-3-0-tiny-vs-north-mini-code-1-0"
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        "json": "https://www.anchorterminal.com/compare/ling-3-1-flash-1019-vs-north-mini-code-1-0.json",
        "title": "Ling-3.1-flash-1019 vs North Mini Code 1.0",
        "url": "https://www.anchorterminal.com/compare/ling-3-1-flash-1019-vs-north-mini-code-1-0"
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        "json": "https://www.anchorterminal.com/compare/ling-3-1-flash-1019-vs-occamy-1-0.json",
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        "json": "https://www.anchorterminal.com/compare/longcat-2-5-vs-north-mini-code-1-0.json",
        "title": "LongCat-2.5 vs North Mini Code 1.0",
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        "json": "https://www.anchorterminal.com/compare/longcat-2-5-vs-occamy-1-0.json",
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        "json": "https://www.anchorterminal.com/compare/mimo-v2-6-distill-qwen-9b-vs-north-mini-code-1-0.json",
        "title": "MiMo-V2.6 Distill Qwen 9B vs North Mini Code 1.0",
        "url": "https://www.anchorterminal.com/compare/mimo-v2-6-distill-qwen-9b-vs-north-mini-code-1-0"
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        "json": "https://www.anchorterminal.com/compare/mimo-v2-6-flash-rl-vs-north-mini-code-1-0.json",
        "title": "MiMo-V2.6-Flash-RL vs North Mini Code 1.0",
        "url": "https://www.anchorterminal.com/compare/mimo-v2-6-flash-rl-vs-north-mini-code-1-0"
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        "json": "https://www.anchorterminal.com/compare/mimo-v2-6-flash-rl-vs-occamy-1-0.json",
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        "json": "https://www.anchorterminal.com/compare/minicpm-o-4-5-vs-north-mini-code-1-0.json",
        "title": "MiniCPM-o 4.5 vs North Mini Code 1.0",
        "url": "https://www.anchorterminal.com/compare/minicpm-o-4-5-vs-north-mini-code-1-0"
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        "json": "https://www.anchorterminal.com/compare/minicpm-o-4-5-vs-occamy-1-0.json",
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        "title": "MiniCPM-V 4.7 1B vs North Mini Code 1.0",
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        "json": "https://www.anchorterminal.com/compare/minicpm-v-4-7-1b-vs-occamy-1-0.json",
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        "json": "https://www.anchorterminal.com/compare/minicpm-v-4-7-35b-a3b-vs-occamy-1-0.json",
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        "json": "https://www.anchorterminal.com/compare/minicpm5-2b-vs-north-mini-code-1-0.json",
        "title": "MiniCPM5-2B vs North Mini Code 1.0",
        "url": "https://www.anchorterminal.com/compare/minicpm5-2b-vs-north-mini-code-1-0"
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        "json": "https://www.anchorterminal.com/compare/minicpm5-2b-vs-occamy-1-0.json",
        "title": "MiniCPM5-2B vs occamy-1.0",
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        "json": "https://www.anchorterminal.com/compare/minimax-m2-5-vs-north-mini-code-1-0.json",
        "title": "MiniMax-M2.5 vs North Mini Code 1.0",
        "url": "https://www.anchorterminal.com/compare/minimax-m2-5-vs-north-mini-code-1-0"
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        "json": "https://www.anchorterminal.com/compare/minimax-m2-5-vs-occamy-1-0.json",
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        "url": "https://www.anchorterminal.com/compare/minimax-m2-5-vs-occamy-1-0"
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        "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"
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      {
        "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"
      },
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        "json": "https://www.anchorterminal.com/compare/occamy-1-0-vs-qwen3-4b-instruct-2507.json",
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        "url": "https://www.anchorterminal.com/compare/occamy-1-0-vs-qwen3-4b-instruct-2507"
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      {
        "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"
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      {
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        "title": "occamy-1.0 vs Qwen3.5-2B",
        "url": "https://www.anchorterminal.com/compare/occamy-1-0-vs-qwen3-5-2b"
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      {
        "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"
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      {
        "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"
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      {
        "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"
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      {
        "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"
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      {
        "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"
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      {
        "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"
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        "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"
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      {
        "json": "https://www.anchorterminal.com/compare/occamy-1-0-vs-qwen3-omni-30b-a3b-instruct.json",
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        "url": "https://www.anchorterminal.com/compare/occamy-1-0-vs-qwen3-omni-30b-a3b-instruct"
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        "json": "https://www.anchorterminal.com/compare/occamy-1-0-vs-qwen3-vl-2b-instruct.json",
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        "url": "https://www.anchorterminal.com/compare/occamy-1-0-vs-qwen3-vl-2b-instruct"
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      {
        "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"
      },
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        "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"
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        "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"
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      {
        "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": 5,
        "edge": "occamy-1-0",
        "key": "reach",
        "name": "Reach",
        "north-mini-code-1-0": 85,
        "occamy-1-0": 90,
        "weight": 25
      },
      {
        "by": 5,
        "edge": "north-mini-code-1-0",
        "key": "risk",
        "name": "Risk",
        "north-mini-code-1-0": 60,
        "occamy-1-0": 55,
        "weight": 20
      },
      {
        "by": 15,
        "edge": "north-mini-code-1-0",
        "key": "interface",
        "name": "Agent interface",
        "north-mini-code-1-0": 85,
        "occamy-1-0": 70,
        "weight": 10
      },
      {
        "by": 38,
        "edge": "occamy-1-0",
        "key": "upkeep",
        "name": "Documentation and upkeep",
        "north-mini-code-1-0": 36,
        "occamy-1-0": 74,
        "weight": 10
      }
    ],
    "summary": "North Mini Code 1.0 and occamy-1.0 score within a point of each other on agent readiness, 61 (C) and 61 (C). occamy-1.0 leads on reach and documentation and upkeep. Both do open-weight models you run yourself.",
    "tasks": null,
    "tutorials": [],
    "verdicts": {
      "north-mini-code-1-0": "A coding agent model that fits one 24 GB GPU at 4 bits, trained for tool use, with a 256K context, Apache 2.0 and four released runtimes. It's a research release and reads like one: nothing on limitations, safety or data, the card's run instructions are out of date, and Cohere hasn't answered a question on the repository.",
      "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/north-mini-code-1-0-vs-occamy-1-0",
    "json": "https://www.anchorterminal.com/compare/north-mini-code-1-0-vs-occamy-1-0.json",
    "llms": "https://www.anchorterminal.com/llms.txt",
    "markdown": "https://www.anchorterminal.com/compare/north-mini-code-1-0-vs-occamy-1-0.md",
    "mcp": "https://www.anchorterminal.com/mcp",
    "slim": "https://www.anchorterminal.com/compare/north-mini-code-1-0-vs-occamy-1-0.min.md"
  },
  "markdown": "North Mini Code 1.0 and occamy-1.0 score within a point of each other on agent readiness, 61 (C) and 61 (C). occamy-1.0 leads on reach and documentation and upkeep. Both do open-weight models you run yourself.\n\n- North Mini Code 1.0: grade C, 61/100, rank #80 of 160 open-weight models. Markdown https://www.anchorterminal.com/tools/north-mini-code-1-0.md · JSON https://www.anchorterminal.com/api/v1/tools/north-mini-code-1-0.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### North Mini Code 1.0 (C)\n\nGood for: Developers who want a coding agent on their own GPU with a permissive licence\n\nAhead on:\n- Risk, 60 against 55\n- Agent interface, 85 against 70\n\nWatch for: No limitations, safety results, languages or data description on the card\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\nAhead on:\n- Reach, 90 against 85\n- Documentation and upkeep, 74 against 36\n\nWatch for: No safety results, prompt-injection guidance or security contact\n\n\n## Why the edge\n\n### Documentation and upkeep: occamy-1.0 +38\n\n- North Mini Code 1.0 (36): Model card 11, Intended use, the architecture, the parameters and the context are on the card. Training data 0, the card gives the training method and nothing about the data. Last change 10, the main repository last changed on 15 June 2026 (outdated chat templates removed), 148 days before this check, and the draft model's repository on 29 July, 104 days. Responsiveness 0, none of the 11 most recent discussions that aren't pull requests (7 June to 6 November 2026) has a reply from a CohereLabs member, counted on 10 November by author flags and dates with a script, text not read. Version policy 5, A first release, with each build in its own repository. File health 10, Config, template and card agree on the architecture, and the June commit that removed broken templates says so. 11 + 0 + 10 + 0 + 5 + 10 = 36.\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### Agent interface: North Mini Code 1.0 +15\n\n- North Mini Code 1.0 (85): Chat template 20, chat_template.jinja in the repository (12,397 characters). Tool-calling format 25, the card documents how tools are declared (JSON schema through the chat template), how the call and its thinking go back into the history and how results are appended, and names the cohere_command4 tool-call parser for vLLM, which released vLLM has. Trained tool calling 20, the card says the model was specifically trained with tool-use capabilities for agentic coding, with reinforcement learning on verifiable tasks, and the template renders every call in a turn with thinking between them. Structured output 0, JSON schema is for describing tools. Reasoning control 10, the template has a reasoning_effort setting, and the card names the cohere_command4 reasoning parser, which returns thinking apart from the answer. Context 10, 256K tokens per the card, with 64K of output, and 500,000 positions in 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### Reach: occamy-1.0 +5\n\n- North Mini Code 1.0 (85): Memory 25, the smallest build from Cohere is the w4a16 repository, 19.38 GB, and 19.38 GB × 1.2 = 23.3 GB, within 24 GB. Unsloth's GGUF isn't read for this line. Runtimes 20, Released vLLM 0.33.0, SGLang 0.5.23 and Transformers 5.22.2 have the cohere2_moe model, and llama.cpp b12242 has the cohere2moe architecture. Builds 15, Quantised builds from Cohere at two precisions, FP8 and 4-bit weights (w4a16), each in its own repository. Terms 15, Apache 2.0 in the metadata and on the card, an OSI licence with nothing added. Download 10, the Hub API reports gated false for the model and its builds on 10 November 2026, so the files download with no account and nothing to accept. Hosted 0, Hugging Face maps no inference provider to it. 25 + 20 + 15 + 15 + 10 + 0 = 85.\n- occamy-1.0 (90): Memory 25 of 30, Accio's MLX mxfp4 build is 18.4 GB, 22.1 GB with a fifth added, and its IQ4_XS GGUF needs 22.5 GB, both within 24 GB. Runtimes 25, the most the line gives, it keeps the base's qwen3_5_moe architecture, which llama.cpp, vLLM, SGLang and Transformers run in released versions, and Ollama v0.40.14 builds a llama.cpp (b11963) that has it. Builds 15, FP8, NVFP4, GGUF and MLX from Accio. Terms 15, Apache 2.0 like its base. Download 10, nothing is gated. Hosted 0, no API or inference provider serves it. 25 + 25 + 15 + 15 + 10 + 0 = 90.\n\n### Risk: North Mini Code 1.0 +5\n\n- North Mini Code 1.0 (60): File safety 25, safetensors only, no .bin, .pt or .pth files and no Python in the repository. Provenance 15, the files sit in Cohere's verified CohereLabs organisation, which cohere.com links to per our other Cohere listings (10). Safety evaluation 0, no safety results on the card. Agent guidance 0, the card has no limitations or safety section, and nothing on prompt injection, instruction priority or what the model refuses. Licence risk 15, Apache 2.0 has no use policy, threshold or change clause. Security programme 5, Cohere's trust centre holds a responsible disclosure policy with a bug bounty, as recorded on our Cohere listings (5). 25 + 15 + 0 + 0 + 15 + 5 = 60.\n- occamy-1.0 (55): File safety 25, safetensors only and nothing from the repository runs to load it or build prompts. Provenance 15, the files are in the organisation Accio's GitHub links, with MD5 sums and SHA-256 for every file. Safety evaluation 0, none published. Agent guidance 0. Licence risk 15, plain Apache 2.0 that hasn't changed. Security programme 0, bug reports go to public GitHub issues and there's no security contact.\n\n## Score by category\n\n| Category | Weight | North Mini Code 1.0 | occamy-1.0 | Edge |\n| --- | --- | --- | --- | --- |\n| Capability | 35%, pending | pending | pending | not scored in this run |\n| Reach | 25% (25 this run) | 85 | 90 | occamy-1.0 +5 |\n| Risk | 20% (20 this run) | 60 | 55 | North Mini Code 1.0 +5 |\n| Agent interface | 10% (10 this run) | 85 | 70 | North Mini Code 1.0 +15 |\n| Documentation and upkeep | 10% (10 this run) | 36 | 74 | occamy-1.0 +38 |\n| Negative events | ≤15 | 0 | 0 | |\n| **Total** | | **61 · C** | **61 · C** | |\n\n## Facts side by side\n\n| Fact | North Mini Code 1.0 | occamy-1.0 |\n| --- | --- | --- |\n| Kind | Open-weight model | Open-weight model |\n| Vendor | Cohere | 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 | 2026-07-29 | 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### North Mini Code 1.0\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**North Mini Code 1.0.** A coding agent model that fits one 24 GB GPU at 4 bits, trained for tool use, with a 256K context, Apache 2.0 and four released runtimes. It's a research release and reads like one: nothing on limitations, safety or data, the card's run instructions are out of date, and Cohere hasn't answered a question on the repository.\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### North Mini Code 1.0\n\n1. Serve it with vLLM 0.33.0 or later and `--tool-call-parser cohere_command4 --reasoning-parser cohere_command4 --enable-auto-tool-choice`, with `cohere_melody` installed\n2. Pass the model's thinking back with its tool calls on every turn. The card says results drop without it\n3. Describe tools in JSON schema and append tool results as a dictionary with the tool role\n4. Use temperature 1.0 and top_p 0.95\n5. For llama.cpp the GGUF files are Unsloth's or bartowski's conversions, not Cohere's\n6. It's text only. Don't send images\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, North Mini Code 1.0 or occamy-1.0?\n\nNorth Mini Code 1.0 and occamy-1.0 score within a point of each other on agent readiness, 61 (C) and 61 (C). occamy-1.0 leads on reach and documentation and upkeep.\n\n\n## For agents\n\n- This comparison as JSON: https://www.anchorterminal.com/compare/north-mini-code-1-0-vs-occamy-1-0.json, and with the fewest tokens: https://www.anchorterminal.com/compare/north-mini-code-1-0-vs-occamy-1-0.min.md\n- Over MCP at https://www.anchorterminal.com/mcp (no key): `compare_tools {\"a\": \"north-mini-code-1-0\", \"b\": \"occamy-1-0\"}`. From a terminal: `anchor compare north-mini-code-1-0 occamy-1-0`\n- Each listing in full: https://www.anchorterminal.com/api/v1/tools/north-mini-code-1-0.json and https://www.anchorterminal.com/api/v1/tools/occamy-1-0.json\n\n## Other comparisons with North Mini Code 1.0 or occamy-1.0\n\n- [Agents-A1-4B vs North Mini Code 1.0](https://www.anchorterminal.com/compare/agents-a1-4b-vs-north-mini-code-1-0.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 North Mini Code 1.0](https://www.anchorterminal.com/compare/apertus-v1-5-8b-vs-north-mini-code-1-0.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 North Mini Code 1.0](https://www.anchorterminal.com/compare/apodex-1-1-mini-vs-north-mini-code-1-0.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 North Mini Code 1.0](https://www.anchorterminal.com/compare/arete-27b-vs-north-mini-code-1-0.md)\n- [Arete-27B vs occamy-1.0](https://www.anchorterminal.com/compare/arete-27b-vs-occamy-1-0.md)\n- [BigBang-v1 vs North Mini Code 1.0](https://www.anchorterminal.com/compare/bigbang-v1-vs-north-mini-code-1-0.md)\n- [BigBang-v1 vs occamy-1.0](https://www.anchorterminal.com/compare/bigbang-v1-vs-occamy-1-0.md)\n- [Carbon-X vs North Mini Code 1.0](https://www.anchorterminal.com/compare/carbon-x-vs-north-mini-code-1-0.md)\n- [Carbon-X vs occamy-1.0](https://www.anchorterminal.com/compare/carbon-x-vs-occamy-1-0.md)\n- [Cola2 vs North Mini Code 1.0](https://www.anchorterminal.com/compare/cola2-vs-north-mini-code-1-0.md)\n- [Cola2 vs occamy-1.0](https://www.anchorterminal.com/compare/cola2-vs-occamy-1-0.md)\n- [Cosmos-Reason2-2B vs North Mini Code 1.0](https://www.anchorterminal.com/compare/cosmos-reason2-2b-vs-north-mini-code-1-0.md)\n- [Cosmos-Reason2-2B vs occamy-1.0](https://www.anchorterminal.com/compare/cosmos-reason2-2b-vs-occamy-1-0.md)\n- [Darwin-36B-Opus vs North Mini Code 1.0](https://www.anchorterminal.com/compare/darwin-36b-opus-vs-north-mini-code-1-0.md)\n- [Darwin-36B-Opus vs occamy-1.0](https://www.anchorterminal.com/compare/darwin-36b-opus-vs-occamy-1-0.md)\n- [DeepSeek-V3.2 vs North Mini Code 1.0](https://www.anchorterminal.com/compare/deepseek-v3-2-vs-north-mini-code-1-0.md)\n- [DeepSeek-V3.2 vs occamy-1.0](https://www.anchorterminal.com/compare/deepseek-v3-2-vs-occamy-1-0.md)\n- [DeepSeek V4.1 Flash vs North Mini Code 1.0](https://www.anchorterminal.com/compare/deepseek-v4-1-flash-vs-north-mini-code-1-0.md)\n- [DeepSeek V4.1 Flash vs occamy-1.0](https://www.anchorterminal.com/compare/deepseek-v4-1-flash-vs-occamy-1-0.md)\n- [DeepSeek-V4-Flash-0731 vs North Mini Code 1.0](https://www.anchorterminal.com/compare/deepseek-v4-flash-0731-vs-north-mini-code-1-0.md)\n- [DeepSeek-V4-Flash-0731 vs occamy-1.0](https://www.anchorterminal.com/compare/deepseek-v4-flash-0731-vs-occamy-1-0.md)\n- [Devstral Small 2 vs North Mini Code 1.0](https://www.anchorterminal.com/compare/devstral-small-2-vs-north-mini-code-1-0.md)\n- [Devstral Small 2 vs occamy-1.0](https://www.anchorterminal.com/compare/devstral-small-2-vs-occamy-1-0.md)\n- [DiffusionGemma 26B A4B IT vs North Mini Code 1.0](https://www.anchorterminal.com/compare/diffusiongemma-26b-a4b-it-vs-north-mini-code-1-0.md)\n- [DiffusionGemma 26B A4B IT vs occamy-1.0](https://www.anchorterminal.com/compare/diffusiongemma-26b-a4b-it-vs-occamy-1-0.md)\n- [EXAONE 4.5 33B vs North Mini Code 1.0](https://www.anchorterminal.com/compare/exaone-4-5-33b-vs-north-mini-code-1-0.md)\n- [EXAONE 4.5 33B vs occamy-1.0](https://www.anchorterminal.com/compare/exaone-4-5-33b-vs-occamy-1-0.md)\n- [Gemma 4 12B IT vs North Mini Code 1.0](https://www.anchorterminal.com/compare/gemma-4-12b-it-vs-north-mini-code-1-0.md)\n- [Gemma 4 12B IT vs occamy-1.0](https://www.anchorterminal.com/compare/gemma-4-12b-it-vs-occamy-1-0.md)\n- [Gemma 4 26B A4B IT vs North Mini Code 1.0](https://www.anchorterminal.com/compare/gemma-4-26b-a4b-it-vs-north-mini-code-1-0.md)\n- [Gemma 4 26B A4B IT vs occamy-1.0](https://www.anchorterminal.com/compare/gemma-4-26b-a4b-it-vs-occamy-1-0.md)\n- [Gemma 4 31B IT vs North Mini Code 1.0](https://www.anchorterminal.com/compare/gemma-4-31b-it-vs-north-mini-code-1-0.md)\n- [Gemma 4 31B IT vs occamy-1.0](https://www.anchorterminal.com/compare/gemma-4-31b-it-vs-occamy-1-0.md)\n- [Gemma 4 E2B IT vs North Mini Code 1.0](https://www.anchorterminal.com/compare/gemma-4-e2b-it-vs-north-mini-code-1-0.md)\n- [Gemma 4 E2B IT vs occamy-1.0](https://www.anchorterminal.com/compare/gemma-4-e2b-it-vs-occamy-1-0.md)\n- [Gemma 4 E4B IT vs North Mini Code 1.0](https://www.anchorterminal.com/compare/gemma-4-e4b-it-vs-north-mini-code-1-0.md)\n- [Gemma 4 E4B IT vs occamy-1.0](https://www.anchorterminal.com/compare/gemma-4-e4b-it-vs-occamy-1-0.md)\n- [GLM-4.5-Air vs North Mini Code 1.0](https://www.anchorterminal.com/compare/glm-4-5-air-vs-north-mini-code-1-0.md)\n- [GLM-4.5-Air vs occamy-1.0](https://www.anchorterminal.com/compare/glm-4-5-air-vs-occamy-1-0.md)\n- [GLM-4.7-Flash vs North Mini Code 1.0](https://www.anchorterminal.com/compare/glm-4-7-flash-vs-north-mini-code-1-0.md)\n- [GLM-4.7-Flash vs occamy-1.0](https://www.anchorterminal.com/compare/glm-4-7-flash-vs-occamy-1-0.md)\n- [GLM-5.3-Flash vs North Mini Code 1.0](https://www.anchorterminal.com/compare/glm-5-3-flash-vs-north-mini-code-1-0.md)\n- [GLM-5.3-Flash vs occamy-1.0](https://www.anchorterminal.com/compare/glm-5-3-flash-vs-occamy-1-0.md)\n- [GLM-5.3 vs North Mini Code 1.0](https://www.anchorterminal.com/compare/glm-5-3-vs-north-mini-code-1-0.md)\n- [GLM-5.3 vs occamy-1.0](https://www.anchorterminal.com/compare/glm-5-3-vs-occamy-1-0.md)\n- [gpt-oss-120b vs North Mini Code 1.0](https://www.anchorterminal.com/compare/gpt-oss-120b-vs-north-mini-code-1-0.md)\n- [gpt-oss-120b vs occamy-1.0](https://www.anchorterminal.com/compare/gpt-oss-120b-vs-occamy-1-0.md)\n- [gpt-oss-20b vs North Mini Code 1.0](https://www.anchorterminal.com/compare/gpt-oss-20b-vs-north-mini-code-1-0.md)\n- [gpt-oss-20b vs occamy-1.0](https://www.anchorterminal.com/compare/gpt-oss-20b-vs-occamy-1-0.md)\n- [Granite 4.2 30B vs North Mini Code 1.0](https://www.anchorterminal.com/compare/granite-4-2-30b-vs-north-mini-code-1-0.md)\n- [Granite 4.2 30B vs occamy-1.0](https://www.anchorterminal.com/compare/granite-4-2-30b-vs-occamy-1-0.md)\n- [Granite 4.2 3B vs North Mini Code 1.0](https://www.anchorterminal.com/compare/granite-4-2-3b-vs-north-mini-code-1-0.md)\n- [Granite 4.2 3B vs occamy-1.0](https://www.anchorterminal.com/compare/granite-4-2-3b-vs-occamy-1-0.md)\n- [Granite 4.2 8B vs North Mini Code 1.0](https://www.anchorterminal.com/compare/granite-4-2-8b-vs-north-mini-code-1-0.md)\n- [Granite 4.2 8B vs occamy-1.0](https://www.anchorterminal.com/compare/granite-4-2-8b-vs-occamy-1-0.md)\n- [Hy-Memory-30B-A3B vs North Mini Code 1.0](https://www.anchorterminal.com/compare/hy-memory-30b-a3b-vs-north-mini-code-1-0.md)\n- [Hy-Memory-30B-A3B vs occamy-1.0](https://www.anchorterminal.com/compare/hy-memory-30b-a3b-vs-occamy-1-0.md)\n- [Hy3 vs North Mini Code 1.0](https://www.anchorterminal.com/compare/hy3-vs-north-mini-code-1-0.md)\n- [Hy3 vs occamy-1.0](https://www.anchorterminal.com/compare/hy3-vs-occamy-1-0.md)\n- [Inkling-Small vs North Mini Code 1.0](https://www.anchorterminal.com/compare/inkling-small-vs-north-mini-code-1-0.md)\n- [Inkling-Small vs occamy-1.0](https://www.anchorterminal.com/compare/inkling-small-vs-occamy-1-0.md)\n- [Inkling vs North Mini Code 1.0](https://www.anchorterminal.com/compare/inkling-vs-north-mini-code-1-0.md)\n- [Inkling vs occamy-1.0](https://www.anchorterminal.com/compare/inkling-vs-occamy-1-0.md)\n- [InternVL3.5-GPT-OSS-20B-A4B-Preview vs North Mini Code 1.0](https://www.anchorterminal.com/compare/internvl3-5-gpt-oss-20b-a4b-preview-vs-north-mini-code-1-0.md)\n- [InternVL3.5-GPT-OSS-20B-A4B-Preview vs occamy-1.0](https://www.anchorterminal.com/compare/internvl3-5-gpt-oss-20b-a4b-preview-vs-occamy-1-0.md)\n- [Kimi K3.1 Pro vs North Mini Code 1.0](https://www.anchorterminal.com/compare/kimi-k3-1-pro-vs-north-mini-code-1-0.md)\n- [Kimi K3.1 Pro vs occamy-1.0](https://www.anchorterminal.com/compare/kimi-k3-1-pro-vs-occamy-1-0.md)\n- [Kimi K3 vs North Mini Code 1.0](https://www.anchorterminal.com/compare/kimi-k3-vs-north-mini-code-1-0.md)\n- [Kimi K3 vs occamy-1.0](https://www.anchorterminal.com/compare/kimi-k3-vs-occamy-1-0.md)\n- [Kolibri-1 vs North Mini Code 1.0](https://www.anchorterminal.com/compare/kolibri-1-vs-north-mini-code-1-0.md)\n- [Kolibri-1 vs occamy-1.0](https://www.anchorterminal.com/compare/kolibri-1-vs-occamy-1-0.md)\n- [Kronos vs North Mini Code 1.0](https://www.anchorterminal.com/compare/kronos-vs-north-mini-code-1-0.md)\n- [Kronos vs occamy-1.0](https://www.anchorterminal.com/compare/kronos-vs-occamy-1-0.md)\n- [Laguna M.1 vs North Mini Code 1.0](https://www.anchorterminal.com/compare/laguna-m-1-vs-north-mini-code-1-0.md)\n- [Laguna M.1 vs occamy-1.0](https://www.anchorterminal.com/compare/laguna-m-1-vs-occamy-1-0.md)\n- [Laguna S 2.1 vs North Mini Code 1.0](https://www.anchorterminal.com/compare/laguna-s-2-1-vs-north-mini-code-1-0.md)\n- [Laguna S 2.1 vs occamy-1.0](https://www.anchorterminal.com/compare/laguna-s-2-1-vs-occamy-1-0.md)\n- [Laguna XS 2.1 vs North Mini Code 1.0](https://www.anchorterminal.com/compare/laguna-xs-2-1-vs-north-mini-code-1-0.md)\n- [Laguna XS 2.1 vs occamy-1.0](https://www.anchorterminal.com/compare/laguna-xs-2-1-vs-occamy-1-0.md)\n- [LBS-27B vs North Mini Code 1.0](https://www.anchorterminal.com/compare/lbs-27b-vs-north-mini-code-1-0.md)\n- [LBS-27B vs occamy-1.0](https://www.anchorterminal.com/compare/lbs-27b-vs-occamy-1-0.md)\n- [LFM2.5-2.6B vs North Mini Code 1.0](https://www.anchorterminal.com/compare/lfm2-5-2-6b-vs-north-mini-code-1-0.md)\n- [LFM2.5-2.6B vs occamy-1.0](https://www.anchorterminal.com/compare/lfm2-5-2-6b-vs-occamy-1-0.md)\n- [LFM3-1.7B vs North Mini Code 1.0](https://www.anchorterminal.com/compare/lfm3-1-7b-vs-north-mini-code-1-0.md)\n- [LFM3-1.7B vs occamy-1.0](https://www.anchorterminal.com/compare/lfm3-1-7b-vs-occamy-1-0.md)\n- [LFM3-Audio-2B vs North Mini Code 1.0](https://www.anchorterminal.com/compare/lfm3-audio-2b-vs-north-mini-code-1-0.md)\n- [LFM3-Audio-2B vs occamy-1.0](https://www.anchorterminal.com/compare/lfm3-audio-2b-vs-occamy-1-0.md)\n- [LFM3-Omni-2B vs North Mini Code 1.0](https://www.anchorterminal.com/compare/lfm3-omni-2b-vs-north-mini-code-1-0.md)\n- [LFM3-Omni-2B vs occamy-1.0](https://www.anchorterminal.com/compare/lfm3-omni-2b-vs-occamy-1-0.md)\n- [LFM3-VL-2B vs North Mini Code 1.0](https://www.anchorterminal.com/compare/lfm3-vl-2b-vs-north-mini-code-1-0.md)\n- [LFM3-VL-2B vs occamy-1.0](https://www.anchorterminal.com/compare/lfm3-vl-2b-vs-occamy-1-0.md)\n- [Ling-3.0-tiny vs North Mini Code 1.0](https://www.anchorterminal.com/compare/ling-3-0-tiny-vs-north-mini-code-1-0.md)\n- [Ling-3.0-tiny vs occamy-1.0](https://www.anchorterminal.com/compare/ling-3-0-tiny-vs-occamy-1-0.md)\n- [Ling-3.1-flash-1019 vs North Mini Code 1.0](https://www.anchorterminal.com/compare/ling-3-1-flash-1019-vs-north-mini-code-1-0.md)\n- [Ling-3.1-flash-1019 vs occamy-1.0](https://www.anchorterminal.com/compare/ling-3-1-flash-1019-vs-occamy-1-0.md)\n- [LongCat-2.5 vs North Mini Code 1.0](https://www.anchorterminal.com/compare/longcat-2-5-vs-north-mini-code-1-0.md)\n- [LongCat-2.5 vs occamy-1.0](https://www.anchorterminal.com/compare/longcat-2-5-vs-occamy-1-0.md)\n- [MiMo-V2.6 Distill Qwen 9B vs North Mini Code 1.0](https://www.anchorterminal.com/compare/mimo-v2-6-distill-qwen-9b-vs-north-mini-code-1-0.md)\n- [MiMo-V2.6 Distill Qwen 9B vs occamy-1.0](https://www.anchorterminal.com/compare/mimo-v2-6-distill-qwen-9b-vs-occamy-1-0.md)\n- [MiMo-V2.6-Flash-RL vs North Mini Code 1.0](https://www.anchorterminal.com/compare/mimo-v2-6-flash-rl-vs-north-mini-code-1-0.md)\n- [MiMo-V2.6-Flash-RL vs occamy-1.0](https://www.anchorterminal.com/compare/mimo-v2-6-flash-rl-vs-occamy-1-0.md)\n- [MiniCPM-o 4.5 vs North Mini Code 1.0](https://www.anchorterminal.com/compare/minicpm-o-4-5-vs-north-mini-code-1-0.md)\n- [MiniCPM-o 4.5 vs occamy-1.0](https://www.anchorterminal.com/compare/minicpm-o-4-5-vs-occamy-1-0.md)\n- [MiniCPM-V 4.7 1B vs North Mini Code 1.0](https://www.anchorterminal.com/compare/minicpm-v-4-7-1b-vs-north-mini-code-1-0.md)\n- [MiniCPM-V 4.7 1B vs occamy-1.0](https://www.anchorterminal.com/compare/minicpm-v-4-7-1b-vs-occamy-1-0.md)\n- [MiniCPM-V 4.7 35B-A3B vs North Mini Code 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Qwopus3.8-27B-Flash-V2](https://www.anchorterminal.com/compare/occamy-1-0-vs-qwopus3-8-27b-flash-v2.md)\n- [occamy-1.0 vs Recursive Flint](https://www.anchorterminal.com/compare/occamy-1-0-vs-recursive-flint.md)\n- [occamy-1.0 vs Ripple-65B Preview](https://www.anchorterminal.com/compare/occamy-1-0-vs-ripple-65b-preview.md)\n- [occamy-1.0 vs SenseNova-Loop-9B-Preview](https://www.anchorterminal.com/compare/occamy-1-0-vs-sensenova-loop-9b-preview.md)\n- [occamy-1.0 vs SmolLM3-3B](https://www.anchorterminal.com/compare/occamy-1-0-vs-smollm3-3b.md)\n- [occamy-1.0 vs Spark-X2.6-4B](https://www.anchorterminal.com/compare/occamy-1-0-vs-spark-x2-6-4b.md)\n- [occamy-1.0 vs Step 3.7 Flash](https://www.anchorterminal.com/compare/occamy-1-0-vs-step-3-7-flash.md)\n- [occamy-1.0 vs Swift 1.5 Qwen3.8-27B](https://www.anchorterminal.com/compare/occamy-1-0-vs-swift-1-5-qwen3-8-27b.md)\n- [occamy-1.0 vs Swift 1.5 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