{ "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 scores 61 (C) on agent readiness against Olmo 3 7B Think's 52.3 (D), and leads in 2 of 4 scored categories. Olmo 3 7B Think leads on risk and documentation and upkeep.", "b": { "slug": "olmo-3-7b-think", "name": "Olmo 3 7B Think", "vendor": "Ai2 (Allen Institute for AI)", "vendorUrl": "https://allenai.org", "kind": "weights", "category": "open-weights", "summary": "Olmo 3 7B Think is Ai2's fully open 7B reasoning model for maths, code and step-by-step answers, with training data, code and checkpoints published, a 65,536-token context and thinking always on, released in November 2025 under Apache 2.0.", "url": "https://www.anchorterminal.com/tools/olmo-3-7b-think", "markdownUrl": "https://www.anchorterminal.com/tools/olmo-3-7b-think.md", "slimMarkdownUrl": "https://www.anchorterminal.com/tools/olmo-3-7b-think.min.md", "jsonUrl": "https://www.anchorterminal.com/api/v1/tools/olmo-3-7b-think.json", "dns": "olmo-3-7b-think.grade.anchorterminal.com", "repo": "https://huggingface.co/allenai/Olmo-3-7B-Think", "license": "Apache-2.0, with Ai2's Responsible Use Guidelines named on the card", "transports": [], "packages": [ { "registry": "huggingface", "name": "allenai/Olmo-3-7B-Think" }, { "registry": "ollama", "name": "olmo-3:7b-think" } ], "auth": "none", "authNotes": "The weights download from Hugging Face with no account, token or terms to accept. The repository is not gated (checked 2026-10-21).", "pricing": "free", "pricingNotes": "Free to download and use, commercial use included, under Apache 2.0. The card says it is intended for research and educational use in line with Ai2's Responsible Use Guidelines, which list disallowed uses outside research. Running it yourself costs the hardware, 14.6 GB in BF16 and 4.5 GB for Ollama's 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/allenai/Olmo-3-7B-Think", "capabilities": [ "model.open-weights" ], "tags": [ "open-weights", "model", "dense", "reasoning", "fully-open", "open-data", "apache-2.0", "safetensors", "self-hosted" ], "lastRelease": "2026-06-25", "graded": true, "anchor": { "graded": true, "score": 52.3, "grade": "D", "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": 103, "methodology": "0.7", "run": "2026-10-01", "scores": { "capability": 28, "interface": 35, "reach": 75, "risk": 75, "upkeep": 52 }, "pending": [ "performance", "tasks" ], "assessment": { "confidence": "high", "date": "2026-11-04" }, "negative": 0, "verdict": "A fully open 7B reasoning model for maths, code and step-by-step answers, with every dataset and checkpoint published and its safety results rerunnable. Ollama's 4-bit build needs about 5.4 GB. It always thinks, wasn't trained for tool calls, has 65K of context, and Ai2 hasn't answered its discussions.", "bestFor": "Researchers and agents that want a small fully open reasoning model for maths and code, with its training data on hand", "strengths": [ "Training data, code, checkpoints and evaluation harness all published, the data with sources and sizes", "Safety results published with a harness to rerun them", "Ollama's 4-bit build fits in about 5.4 GB, and released llama.cpp, Ollama, vLLM, LM Studio and Transformers run it", "Safetensors only with no repository code, a checksum on every file and no gate", "Apache 2.0 with no revenue threshold" ], "weaknesses": [ "Not trained for tool calling, and the tool format lives only in the template", "Thinking is always on with no way to turn it off, and 65,536 tokens of context", "Ai2 publishes no quantised build and no provider hosts it", "The card binds use to Ai2's Responsible Use Guidelines, which Ai2 can change", "No Ai2 reply in the discussions, and the template's default prompt contradicts the card" ], "agentNotes": [ "Quickest start is `ollama run olmo-3:7b-think`, about 4.5 GB", "With vLLM, `vllm serve allenai/Olmo-3-7B-Think --max-model-len 65536`; vLLM runs it through its Transformers backend", "Sample at temperature 0.6 and top_p 0.95 with up to 32,768 output tokens, as the card recommends, since thinking traces are long", "Every reply starts with a think block; strip it yourself or use a reasoning parser that reads think tags", "Pass your own system prompt; the template's default says the cut-off is November 2024 and that no functions are available", "For tool calls use Olmo 3 7B Instruct instead, which Ai2 trained for function calling", "A discussion reports endless reasoning loops when served with vLLM, unanswered, so cap max_tokens", "Check the use against Ai2's Responsible Use Guidelines, which bar automated social-media posting and undisclosed automated content outside research" ], "metrics": { "kind": "local", "measured": false }, "reviewCount": 4, "avgRating": 2.8, "history": [ { "basis": "public evidence", "confidence": "high", "grade": "D", "methodology": "0.7", "pending": [ "performance", "tasks" ], "run": "2026-10-01", "runLabel": "October 2026 research run", "score": 52.3 } ], "editorialScores": { "capability": 28, "interface": 35, "reach": 75, "risk": 75, "upkeep": 52 }, "provenanceScore": 70, "checked": { "categories": { "capability": "2026-11-04", "interface": "2026-11-04", "reach": "2026-11-04", "risk": "2026-11-04", "upkeep": "2026-11-04" }, "last": "2026-11-04", "oldest": "2026-11-04", "stale": false, "staleAfterDays": 90 } }, "connect": { "install": "ollama run olmo-3:7b-think\n# or\nvllm serve allenai/Olmo-3-7B-Think --max-model-len 65536", "http": "curl http://localhost:11434/api/chat \\\n -d '{\"model\": \"olmo-3:7b-think\", \"messages\": [{\"role\": \"user\", \"content\": \"Hello!\"}], \"options\": {\"temperature\": 0.6, \"top_p\": 0.95}}'" }, "letme": { "capability": "https://letme.dev/model.open-weights", "tool": "https://letme.dev/olmo-3-7b-think" }, "weights": { "trainedBy": "Ai2 (Allen Institute for AI)", "builtOn": "allenai/Olmo-3-7B-Think-DPO", "params": "7.3B", "context": 65536, "goodFor": "Fully open 7B reasoning model for maths, code and step-by-step answers in English, with published training data and checkpoints for research, always thinking, not trained for tool calls.", "runtimes": [ "llama.cpp", "Ollama", "vLLM", "LM Studio", "Transformers" ], "builds": [ { "name": "ollama olmo-3:7b-think-q4_K_M", "url": "https://ollama.com/library/olmo-3:7b-think-q4_K_M", "who": "ollama", "precision": "q4_k_m", "sizeGB": 4.5, "memoryGB": 8, "format": "ollama", "runsOn": [ "Ollama" ], "note": "Digest b8d4c92ac9c1, also the 7b-think and latest tags. q8_0 is 7.8 GB and fp16 15 GB. Sizes as Ollama's tags page shows them" }, { "name": "LM Studio allenai/olmo-3-7b-think (Q4_K_M GGUF)", "url": "https://huggingface.co/lmstudio-community/Olmo-3-7B-Think-GGUF", "who": "lmstudio", "precision": "q4_k_m", "sizeGB": 4.5, "memoryGB": 8, "format": "gguf", "runsOn": [ "LM Studio", "llama.cpp" ], "note": "Olmo-3-7B-Think-Q4_K_M.gguf, 4.47 GB from the Hub's file list. The catalogue entry also lists Q6_K, Q8_0 and MLX 4, 6 and 8-bit builds; the MLX 4-bit is 4.12 GB (Mac only)" }, { "name": "Olmo-3-7B-Think", "url": "https://huggingface.co/allenai/Olmo-3-7B-Think", "who": "publisher", "precision": "bf16", "sizeGB": 14.6, "memoryGB": 24, "format": "safetensors", "runsOn": [ "vLLM", "Transformers" ] } ], "run": "vllm serve allenai/Olmo-3-7B-Think --max-model-len 65536", "runBuild": "Olmo-3-7B-Think", "checked": "2026-11-04", "minMemoryGB": 8 }, "family": { "lab": "Ai2 (Allen Institute for AI)", "family": "Olmo 3 (3, 3.1)", "url": "https://www.anchorterminal.com/open-weights/#ai2", "others": [ { "name": "Olmo-3.1-7B-RL-Zero-Math", "url": "https://huggingface.co/allenai/Olmo-3.1-7B-RL-Zero-Math", "params": "7B (Hub safetensors count 7.30B)" }, { "name": "Olmo-3.1-7B-RL-Zero-Code", "url": "https://huggingface.co/allenai/Olmo-3.1-7B-RL-Zero-Code", "params": "7B (Hub safetensors count 7.30B)" }, { "name": "Olmo-3.1-32B-Think", "url": "https://huggingface.co/allenai/Olmo-3.1-32B-Think", "params": "32B (Hub safetensors count 32.23B)" }, { "name": "Olmo-3.1-32B-Instruct", "url": "https://huggingface.co/allenai/Olmo-3.1-32B-Instruct", "params": "32B (Hub safetensors count 32.23B)" }, { "name": "Olmo-3-7B-RL-Zero-Mix", "url": "https://huggingface.co/allenai/Olmo-3-7B-RL-Zero-Mix", "params": "7B (Hub safetensors count 7.30B)" }, { "name": "Olmo-3-7B-Instruct-DPO", "url": "https://huggingface.co/allenai/Olmo-3-7B-Instruct-DPO", "params": "7B (Hub safetensors count 7.30B)" }, { "name": "Olmo-3-7B-Instruct", "url": "https://huggingface.co/allenai/Olmo-3-7B-Instruct", "params": "7B (Hub safetensors count 7.30B)" }, { "name": "Olmo-3-32B-Think", "url": "https://huggingface.co/allenai/Olmo-3-32B-Think", "params": "32B (Hub safetensors count 32.23B)" }, { "name": "Olmo-3.1-32B-Instruct-SFT", "url": "https://huggingface.co/allenai/Olmo-3.1-32B-Instruct-SFT", "params": "32B (Hub safetensors count 32.23B)" }, { "name": "Olmo-3.1-32B-Instruct-DPO", "url": "https://huggingface.co/allenai/Olmo-3.1-32B-Instruct-DPO", "params": "32B (Hub safetensors count 32.23B)" }, { "name": "Olmo-3-7B-Think-DPO", "url": "https://huggingface.co/allenai/Olmo-3-7B-Think-DPO", "params": "7B (Hub safetensors count 7.30B)" }, { "name": "Olmo-3-7B-RL-Zero-Math", "url": "https://huggingface.co/allenai/Olmo-3-7B-RL-Zero-Math", "params": "7B (Hub safetensors count 7.30B)" }, { "name": "Olmo-3-7B-RL-Zero-IF", "url": "https://huggingface.co/allenai/Olmo-3-7B-RL-Zero-IF", "params": "7B (Hub safetensors count 7.30B)" }, { "name": "Olmo-3-7B-RL-Zero-General", "url": "https://huggingface.co/allenai/Olmo-3-7B-RL-Zero-General", "params": "7B (Hub safetensors count 7.30B)" }, { "name": "Olmo-3-7B-RL-Zero-Code", "url": "https://huggingface.co/allenai/Olmo-3-7B-RL-Zero-Code", "params": "7B (Hub safetensors count 7.30B)" }, { "name": "Olmo-3-7B-Instruct-SFT", "url": "https://huggingface.co/allenai/Olmo-3-7B-Instruct-SFT", "params": "7B (Hub safetensors count 7.30B)" }, { "name": "Olmo-3-32B-Think-SFT", "url": "https://huggingface.co/allenai/Olmo-3-32B-Think-SFT", "params": "32B (Hub safetensors count 32.23B)" }, { "name": "Olmo-3-32B-Think-DPO", "url": "https://huggingface.co/allenai/Olmo-3-32B-Think-DPO", "params": "32B (Hub safetensors count 32.23B)" }, { "name": "Olmo-3-1125-32B", "url": "https://huggingface.co/allenai/Olmo-3-1125-32B", "params": "32B (Hub safetensors count 32.23B)" }, { "name": "Olmo-3-7B-Think-SFT", "url": "https://huggingface.co/allenai/Olmo-3-7B-Think-SFT", "params": "7B (Hub safetensors count 7.30B)" }, { "name": "Olmo-3-1025-7B", "url": "https://huggingface.co/allenai/Olmo-3-1025-7B", "params": "7B (Hub safetensors count 7.30B)" } ], "olderCount": 95, "unrestrictedCopies": 5 }, "area": "models", "provenance": { "legalEntity": "The Allen Institute for Artificial Intelligence (Ai2), a 501(c)(3) nonprofit, per its Responsible Use Guidelines", "domain": "allenai.org", "domainRegistered": "2010-12-03", "endpointOnVendorDomain": null, "terms": "https://allenai.org/terms", "privacy": "https://allenai.org/privacy-policy", "statusPage": "", "changelog": "", "securityTxt": "expired", "checked": "2026-10-21", "notes": [ "RDAP for allenai.org gives a registration date of 3 December 2010.", "Nothing is hosted, so the licence stands in for terms of service and no privacy policy is scored. Ai2's guidelines say its website terms also govern use of its tools.", "allenai.org serves a security.txt with a contact and an Expires date of 31 July 2026, which has passed. The Responsible Use Guidelines name a channel for bugs and security concerns with Ai2's models.", "No changelog. The commits are card edits, two configuration fixes from pull requests in November and December 2025, and a parameter-count fix on 25 June 2026.", "allenai.org links to huggingface.co/allenai, so the repository is the publisher's own." ], "score": 70 }, "pageJsonUrl": "https://www.anchorterminal.com/tools/olmo-3-7b-think.json", "live": { "slug": "olmo-3-7b-think", "securityTxt": { "url": "https://allenai.org/.well-known/security.txt", "state": "expired", "expires": "2026-07-31T05:00:00.000Z", "checkedAt": "2026-11-10T16:07:23.74126383Z" }, "domain": { "domain": "allenai.org", "registered": "2010-12-03", "source": "https://rdap.publicinterestregistry.org/rdap/domain/allenai.org", "checkedAt": "2026-11-08T15:03:50.561358192Z" }, "pages": [ { "url": "https://allenai.org/privacy-policy", "kind": "privacy", "status": 200, "checkedAt": "2026-11-10T16:09:31.69478417Z", "changedAt": "0001-01-01T00:00:00Z", "fingerprint": "6575e6dd3713" }, { "url": "https://allenai.org/terms", "kind": "terms", "status": 200, "checkedAt": "2026-11-10T16:09:35.047986684Z", "changedAt": "0001-01-01T00:00:00Z", "fingerprint": "fde9cf039435" } ], "updatedAt": "2026-11-10T16:09:35.047986684Z" } }, "edges": [ { "by": 50, "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": "The chat template earns 20 for chat_template.jinja in the repository. The tool-calling format earns 10, since only the template and vLLM's own parser describe it. Trained tool calling earns nothing, because Ai2's report says tool calling was trained into the Instruct model, not Think. Structured output earns nothing. Reasoning control earns nothing, since it always thinks. Context earns 5 for 65,536 tokens trained. 20 + 10 + 0 + 0 + 0 + 5 = 35." }, "scores": { "a": 85, "b": 35 } }, { "by": 16, "category": "upkeep", "leads": "olmo-3-7b-think", "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": "The model card earns 17, missing only the context length. Training data earns the full 20, as every dataset is released with sources and sizes. The last change earns 10, a card fix on 25 June 2026, within 180 days. Responsiveness earns nothing, with no Ai2 reply among the 4 replies in the discussions. Version policy earns 5, with earlier and later models in their own repositories and no dated notes. File health earns nothing, because the template's default prompt contradicts the card's on the cut-off and a stray swap file and an unanswered report sit in the repository. 17 + 20 + 10 + 0 + 5 + 0 = 52." }, "scores": { "a": 36, "b": 52 } }, { "by": 15, "category": "risk", "leads": "olmo-3-7b-think", "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 earns 25, safetensors only and nothing from the repository runs. Provenance earns 15, files in the allenai organisation Ai2 links to, with a checksum for every file. Safety evaluation earns 20, as Ai2 publishes its safety results and the OLMES harness to rerun them. Agent guidance earns 5 for the card's general cautions. Licence risk earns 5, losing 5 for disallowed uses beyond the law and 5 because Ai2 can update the guidelines and end access at its discretion. The security programme earns 5 for a reporting route, a security.txt now past its expiry and a channel for security concerns in the guidelines, with no public advisories. 25 + 15 + 20 + 5 + 5 + 5 = 75." }, "scores": { "a": 60, "b": 75 } }, { "by": 10, "category": "reach", "leads": "north-mini-code-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 earns the full 30, since Ollama's 4-bit build is 4.5 GB and fits 8 GB (per the 21 October check of Ollama's library). Runtimes earn 25, with released llama.cpp (b11963), Ollama (v0.40.14, pinning b11963), vLLM, LM Studio and Transformers all running it. Builds earn nothing, because Ai2 publishes no quantised build of its own. Terms earn 10, since the card binds Apache 2.0 to Ai2's Responsible Use Guidelines, a use policy. Download earns 10, with no gate. Hosted earns nothing, as the Hub's provider mapping is empty and Ai2 has no API for it. 30 + 25 + 0 + 10 + 10 + 0 = 75." }, "scores": { "a": 85, "b": 75 } } ], "facts": [ { "a": "Open-weight model", "b": "Open-weight model", "name": "Kind" }, { "a": "Cohere", "b": "Ai2 (Allen Institute for AI)", "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, with Ai2's Responsible Use Guidelines named on the card", "name": "Licence" }, { "a": "no", "b": "no", "name": "Read-only variant documented" }, { "a": "no", "b": "no", "name": "llms.txt" }, { "a": "2026-07-29", "b": "2026-06-25", "name": "Last release" }, { "a": "no document linked", "b": "2024-09-25", "name": "Terms last updated" }, { "a": "no document linked", "b": "2025-02-19", "name": "Privacy policy last updated" }, { "a": "not read yet", "b": "yes", "name": "Customer content may train models" }, { "a": "not read yet", "b": "not found in the text", "name": "Terms restrict automated access" }, { "a": "not read yet", "b": "not found in the text", "name": "Terms restrict benchmarking" }, { "a": "not read yet", "b": "yes", "name": "Terms or service can change without notice" }, { "a": "not read yet", "b": "not found in the text", "name": "Arbitration or class-action waiver" }, { "a": "none", "b": "2.8/5 (4)", "name": "Agent reviews" } ], "faq": [ { "answer": "North Mini Code 1.0 scores 61 (C) on agent readiness against Olmo 3 7B Think's 52.3 (D), and leads in 2 of 4 scored categories. Olmo 3 7B Think leads on risk and documentation and upkeep.", "question": "Which is better for AI agents, North Mini Code 1.0 or Olmo 3 7B Think?" } ], "goodFor": [ { "aheadOn": [ "Reach, 85 against 75", "Agent interface, 85 against 35" ], "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": [ "Risk, 75 against 60", "Documentation and upkeep, 52 against 36" ], "also": null, "goodFor": "Researchers and agents that want a small fully open reasoning model for maths and code, with its training data on hand", "slug": "olmo-3-7b-think", "watchFor": "Not trained for tool calling, and the tool format lives only in the template" } ], "history": null, "job": { "capability": "model.open-weights", "name": "Open-weight models you run yourself" }, "others": [ { "json": 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"https://www.anchorterminal.com/compare/gpt-oss-20b-vs-olmo-3-7b-think.json", "title": "gpt-oss-20b vs Olmo 3 7B Think", "url": "https://www.anchorterminal.com/compare/gpt-oss-20b-vs-olmo-3-7b-think" }, { "json": "https://www.anchorterminal.com/compare/granite-4-2-30b-vs-north-mini-code-1-0.json", "title": "Granite 4.2 30B vs North Mini Code 1.0", "url": "https://www.anchorterminal.com/compare/granite-4-2-30b-vs-north-mini-code-1-0" }, { "json": "https://www.anchorterminal.com/compare/granite-4-2-30b-vs-olmo-3-7b-think.json", "title": "Granite 4.2 30B vs Olmo 3 7B Think", "url": "https://www.anchorterminal.com/compare/granite-4-2-30b-vs-olmo-3-7b-think" }, { "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" }, { "json": "https://www.anchorterminal.com/compare/granite-4-2-3b-vs-olmo-3-7b-think.json", "title": "Granite 4.2 3B vs Olmo 3 7B Think", "url": "https://www.anchorterminal.com/compare/granite-4-2-3b-vs-olmo-3-7b-think" }, { "json": "https://www.anchorterminal.com/compare/granite-4-2-8b-vs-north-mini-code-1-0.json", "title": "Granite 4.2 8B vs North Mini Code 1.0", "url": "https://www.anchorterminal.com/compare/granite-4-2-8b-vs-north-mini-code-1-0" }, { "json": "https://www.anchorterminal.com/compare/granite-4-2-8b-vs-olmo-3-7b-think.json", "title": "Granite 4.2 8B vs Olmo 3 7B Think", "url": "https://www.anchorterminal.com/compare/granite-4-2-8b-vs-olmo-3-7b-think" }, { "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" }, { "json": "https://www.anchorterminal.com/compare/hy-memory-30b-a3b-vs-olmo-3-7b-think.json", "title": "Hy-Memory-30B-A3B vs Olmo 3 7B Think", "url": "https://www.anchorterminal.com/compare/hy-memory-30b-a3b-vs-olmo-3-7b-think" }, { "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" }, { "json": "https://www.anchorterminal.com/compare/hy3-vs-olmo-3-7b-think.json", "title": "Hy3 vs Olmo 3 7B Think", "url": "https://www.anchorterminal.com/compare/hy3-vs-olmo-3-7b-think" }, { "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" }, { "json": "https://www.anchorterminal.com/compare/inkling-small-vs-olmo-3-7b-think.json", "title": "Inkling-Small vs Olmo 3 7B Think", "url": "https://www.anchorterminal.com/compare/inkling-small-vs-olmo-3-7b-think" }, { "json": "https://www.anchorterminal.com/compare/inkling-vs-north-mini-code-1-0.json", "title": "Inkling vs North Mini Code 1.0", "url": "https://www.anchorterminal.com/compare/inkling-vs-north-mini-code-1-0" }, { "json": "https://www.anchorterminal.com/compare/inkling-vs-olmo-3-7b-think.json", "title": "Inkling vs Olmo 3 7B Think", "url": "https://www.anchorterminal.com/compare/inkling-vs-olmo-3-7b-think" }, { "json": "https://www.anchorterminal.com/compare/internvl3-5-gpt-oss-20b-a4b-preview-vs-north-mini-code-1-0.json", "title": "InternVL3.5-GPT-OSS-20B-A4B-Preview vs North Mini Code 1.0", "url": "https://www.anchorterminal.com/compare/internvl3-5-gpt-oss-20b-a4b-preview-vs-north-mini-code-1-0" }, { "json": "https://www.anchorterminal.com/compare/internvl3-5-gpt-oss-20b-a4b-preview-vs-olmo-3-7b-think.json", "title": "InternVL3.5-GPT-OSS-20B-A4B-Preview vs Olmo 3 7B Think", "url": "https://www.anchorterminal.com/compare/internvl3-5-gpt-oss-20b-a4b-preview-vs-olmo-3-7b-think" }, { "json": "https://www.anchorterminal.com/compare/kimi-k3-1-pro-vs-north-mini-code-1-0.json", "title": "Kimi K3.1 Pro vs North Mini Code 1.0", "url": "https://www.anchorterminal.com/compare/kimi-k3-1-pro-vs-north-mini-code-1-0" }, { "json": "https://www.anchorterminal.com/compare/kimi-k3-1-pro-vs-olmo-3-7b-think.json", "title": "Kimi K3.1 Pro vs Olmo 3 7B Think", "url": "https://www.anchorterminal.com/compare/kimi-k3-1-pro-vs-olmo-3-7b-think" }, { "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" }, { "json": "https://www.anchorterminal.com/compare/kimi-k3-vs-olmo-3-7b-think.json", "title": "Kimi K3 vs Olmo 3 7B Think", "url": "https://www.anchorterminal.com/compare/kimi-k3-vs-olmo-3-7b-think" }, { "json": "https://www.anchorterminal.com/compare/kolibri-1-vs-north-mini-code-1-0.json", "title": "Kolibri-1 vs North Mini Code 1.0", "url": "https://www.anchorterminal.com/compare/kolibri-1-vs-north-mini-code-1-0" }, { "json": "https://www.anchorterminal.com/compare/kolibri-1-vs-olmo-3-7b-think.json", "title": "Kolibri-1 vs Olmo 3 7B Think", "url": "https://www.anchorterminal.com/compare/kolibri-1-vs-olmo-3-7b-think" }, { "json": "https://www.anchorterminal.com/compare/kronos-vs-north-mini-code-1-0.json", "title": "Kronos vs North Mini Code 1.0", "url": "https://www.anchorterminal.com/compare/kronos-vs-north-mini-code-1-0" }, { "json": "https://www.anchorterminal.com/compare/kronos-vs-olmo-3-7b-think.json", "title": "Kronos vs Olmo 3 7B Think", "url": "https://www.anchorterminal.com/compare/kronos-vs-olmo-3-7b-think" }, { "json": "https://www.anchorterminal.com/compare/laguna-m-1-vs-north-mini-code-1-0.json", "title": "Laguna M.1 vs North Mini Code 1.0", "url": "https://www.anchorterminal.com/compare/laguna-m-1-vs-north-mini-code-1-0" }, { "json": "https://www.anchorterminal.com/compare/laguna-m-1-vs-olmo-3-7b-think.json", "title": "Laguna M.1 vs Olmo 3 7B Think", "url": "https://www.anchorterminal.com/compare/laguna-m-1-vs-olmo-3-7b-think" }, { "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" }, { "json": "https://www.anchorterminal.com/compare/laguna-s-2-1-vs-olmo-3-7b-think.json", "title": "Laguna S 2.1 vs Olmo 3 7B Think", "url": "https://www.anchorterminal.com/compare/laguna-s-2-1-vs-olmo-3-7b-think" }, { "json": "https://www.anchorterminal.com/compare/laguna-xs-2-1-vs-north-mini-code-1-0.json", "title": "Laguna XS 2.1 vs North Mini Code 1.0", "url": "https://www.anchorterminal.com/compare/laguna-xs-2-1-vs-north-mini-code-1-0" }, { "json": "https://www.anchorterminal.com/compare/laguna-xs-2-1-vs-olmo-3-7b-think.json", "title": "Laguna XS 2.1 vs Olmo 3 7B Think", "url": "https://www.anchorterminal.com/compare/laguna-xs-2-1-vs-olmo-3-7b-think" }, { "json": "https://www.anchorterminal.com/compare/lbs-27b-vs-north-mini-code-1-0.json", "title": "LBS-27B vs North Mini Code 1.0", "url": "https://www.anchorterminal.com/compare/lbs-27b-vs-north-mini-code-1-0" }, { "json": "https://www.anchorterminal.com/compare/lbs-27b-vs-olmo-3-7b-think.json", "title": "LBS-27B vs Olmo 3 7B Think", "url": "https://www.anchorterminal.com/compare/lbs-27b-vs-olmo-3-7b-think" }, { "json": "https://www.anchorterminal.com/compare/lfm2-5-2-6b-vs-north-mini-code-1-0.json", "title": "LFM2.5-2.6B vs North Mini Code 1.0", "url": "https://www.anchorterminal.com/compare/lfm2-5-2-6b-vs-north-mini-code-1-0" }, { "json": "https://www.anchorterminal.com/compare/lfm2-5-2-6b-vs-olmo-3-7b-think.json", "title": "LFM2.5-2.6B vs Olmo 3 7B Think", "url": "https://www.anchorterminal.com/compare/lfm2-5-2-6b-vs-olmo-3-7b-think" }, { "json": "https://www.anchorterminal.com/compare/lfm3-1-7b-vs-north-mini-code-1-0.json", "title": "LFM3-1.7B vs North Mini Code 1.0", "url": "https://www.anchorterminal.com/compare/lfm3-1-7b-vs-north-mini-code-1-0" }, { "json": "https://www.anchorterminal.com/compare/lfm3-1-7b-vs-olmo-3-7b-think.json", "title": "LFM3-1.7B vs Olmo 3 7B Think", "url": "https://www.anchorterminal.com/compare/lfm3-1-7b-vs-olmo-3-7b-think" }, { "json": "https://www.anchorterminal.com/compare/lfm3-audio-2b-vs-north-mini-code-1-0.json", "title": "LFM3-Audio-2B vs North Mini Code 1.0", "url": "https://www.anchorterminal.com/compare/lfm3-audio-2b-vs-north-mini-code-1-0" }, { "json": "https://www.anchorterminal.com/compare/lfm3-audio-2b-vs-olmo-3-7b-think.json", "title": "LFM3-Audio-2B vs Olmo 3 7B Think", "url": "https://www.anchorterminal.com/compare/lfm3-audio-2b-vs-olmo-3-7b-think" }, { "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" }, { "json": "https://www.anchorterminal.com/compare/lfm3-omni-2b-vs-olmo-3-7b-think.json", "title": "LFM3-Omni-2B vs Olmo 3 7B Think", "url": "https://www.anchorterminal.com/compare/lfm3-omni-2b-vs-olmo-3-7b-think" }, { "json": "https://www.anchorterminal.com/compare/lfm3-vl-2b-vs-north-mini-code-1-0.json", "title": "LFM3-VL-2B vs North Mini Code 1.0", "url": "https://www.anchorterminal.com/compare/lfm3-vl-2b-vs-north-mini-code-1-0" }, { "json": "https://www.anchorterminal.com/compare/lfm3-vl-2b-vs-olmo-3-7b-think.json", "title": "LFM3-VL-2B vs Olmo 3 7B Think", "url": "https://www.anchorterminal.com/compare/lfm3-vl-2b-vs-olmo-3-7b-think" }, { "json": "https://www.anchorterminal.com/compare/ling-3-0-tiny-vs-north-mini-code-1-0.json", "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" }, { "json": "https://www.anchorterminal.com/compare/ling-3-0-tiny-vs-olmo-3-7b-think.json", "title": "Ling-3.0-tiny vs Olmo 3 7B Think", "url": "https://www.anchorterminal.com/compare/ling-3-0-tiny-vs-olmo-3-7b-think" }, { "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" }, { "json": "https://www.anchorterminal.com/compare/ling-3-1-flash-1019-vs-olmo-3-7b-think.json", "title": "Ling-3.1-flash-1019 vs Olmo 3 7B Think", "url": "https://www.anchorterminal.com/compare/ling-3-1-flash-1019-vs-olmo-3-7b-think" }, { "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", "url": "https://www.anchorterminal.com/compare/longcat-2-5-vs-north-mini-code-1-0" }, { "json": "https://www.anchorterminal.com/compare/longcat-2-5-vs-olmo-3-7b-think.json", "title": "LongCat-2.5 vs Olmo 3 7B Think", "url": "https://www.anchorterminal.com/compare/longcat-2-5-vs-olmo-3-7b-think" }, { "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" }, { "json": "https://www.anchorterminal.com/compare/mimo-v2-6-distill-qwen-9b-vs-olmo-3-7b-think.json", "title": "MiMo-V2.6 Distill Qwen 9B vs Olmo 3 7B Think", "url": "https://www.anchorterminal.com/compare/mimo-v2-6-distill-qwen-9b-vs-olmo-3-7b-think" }, { "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" }, { "json": "https://www.anchorterminal.com/compare/mimo-v2-6-flash-rl-vs-olmo-3-7b-think.json", "title": "MiMo-V2.6-Flash-RL vs Olmo 3 7B Think", "url": "https://www.anchorterminal.com/compare/mimo-v2-6-flash-rl-vs-olmo-3-7b-think" }, { "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" }, { "json": "https://www.anchorterminal.com/compare/minicpm-o-4-5-vs-olmo-3-7b-think.json", "title": "MiniCPM-o 4.5 vs Olmo 3 7B Think", "url": "https://www.anchorterminal.com/compare/minicpm-o-4-5-vs-olmo-3-7b-think" }, { "json": "https://www.anchorterminal.com/compare/minicpm-v-4-7-1b-vs-north-mini-code-1-0.json", "title": "MiniCPM-V 4.7 1B vs North Mini Code 1.0", "url": "https://www.anchorterminal.com/compare/minicpm-v-4-7-1b-vs-north-mini-code-1-0" }, { "json": "https://www.anchorterminal.com/compare/minicpm-v-4-7-1b-vs-olmo-3-7b-think.json", "title": "MiniCPM-V 4.7 1B vs Olmo 3 7B Think", "url": "https://www.anchorterminal.com/compare/minicpm-v-4-7-1b-vs-olmo-3-7b-think" }, { "json": "https://www.anchorterminal.com/compare/minicpm-v-4-7-35b-a3b-vs-north-mini-code-1-0.json", "title": "MiniCPM-V 4.7 35B-A3B vs North Mini Code 1.0", "url": "https://www.anchorterminal.com/compare/minicpm-v-4-7-35b-a3b-vs-north-mini-code-1-0" }, { "json": "https://www.anchorterminal.com/compare/minicpm-v-4-7-35b-a3b-vs-olmo-3-7b-think.json", "title": "MiniCPM-V 4.7 35B-A3B vs Olmo 3 7B Think", "url": "https://www.anchorterminal.com/compare/minicpm-v-4-7-35b-a3b-vs-olmo-3-7b-think" }, { "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" }, { "json": "https://www.anchorterminal.com/compare/minicpm5-2b-vs-olmo-3-7b-think.json", "title": "MiniCPM5-2B vs Olmo 3 7B Think", "url": "https://www.anchorterminal.com/compare/minicpm5-2b-vs-olmo-3-7b-think" }, { "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" }, { "json": "https://www.anchorterminal.com/compare/minimax-m2-5-vs-olmo-3-7b-think.json", "title": "MiniMax-M2.5 vs Olmo 3 7B Think", "url": "https://www.anchorterminal.com/compare/minimax-m2-5-vs-olmo-3-7b-think" }, { "json": "https://www.anchorterminal.com/compare/minimax-m2-7-vs-north-mini-code-1-0.json", "title": "MiniMax-M2.7 vs North Mini Code 1.0", "url": "https://www.anchorterminal.com/compare/minimax-m2-7-vs-north-mini-code-1-0" }, { "json": "https://www.anchorterminal.com/compare/minimax-m2-7-vs-olmo-3-7b-think.json", "title": "MiniMax-M2.7 vs Olmo 3 7B Think", "url": "https://www.anchorterminal.com/compare/minimax-m2-7-vs-olmo-3-7b-think" }, { "json": "https://www.anchorterminal.com/compare/minimax-m3-1-flash-vs-north-mini-code-1-0.json", "title": "MiniMax-M3.1-Flash vs North Mini Code 1.0", "url": "https://www.anchorterminal.com/compare/minimax-m3-1-flash-vs-north-mini-code-1-0" }, { "json": "https://www.anchorterminal.com/compare/minimax-m3-1-flash-vs-olmo-3-7b-think.json", "title": "MiniMax-M3.1-Flash vs Olmo 3 7B Think", "url": "https://www.anchorterminal.com/compare/minimax-m3-1-flash-vs-olmo-3-7b-think" }, { "json": "https://www.anchorterminal.com/compare/mistral-large-4-vs-north-mini-code-1-0.json", "title": "Mistral Large 4 vs North Mini Code 1.0", "url": "https://www.anchorterminal.com/compare/mistral-large-4-vs-north-mini-code-1-0" }, { "json": "https://www.anchorterminal.com/compare/mistral-large-4-vs-olmo-3-7b-think.json", "title": "Mistral Large 4 vs Olmo 3 7B Think", "url": 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"https://www.anchorterminal.com/compare/nemotron-3-nano-30b-a3b-vs-olmo-3-7b-think.json", "title": "Nemotron 3 Nano 30B A3B vs Olmo 3 7B Think", "url": "https://www.anchorterminal.com/compare/nemotron-3-nano-30b-a3b-vs-olmo-3-7b-think" }, { "json": "https://www.anchorterminal.com/compare/nemotron-3-nano-4b-vs-north-mini-code-1-0.json", "title": "Nemotron 3 Nano 4B vs North Mini Code 1.0", "url": "https://www.anchorterminal.com/compare/nemotron-3-nano-4b-vs-north-mini-code-1-0" }, { "json": "https://www.anchorterminal.com/compare/nemotron-3-nano-4b-vs-olmo-3-7b-think.json", "title": "Nemotron 3 Nano 4B vs Olmo 3 7B Think", "url": "https://www.anchorterminal.com/compare/nemotron-3-nano-4b-vs-olmo-3-7b-think" }, { "json": "https://www.anchorterminal.com/compare/nemotron-3-nano-omni-30b-a3b-reasoning-vs-north-mini-code-1-0.json", "title": "Nemotron 3 Nano Omni 30B A3B Reasoning vs North Mini Code 1.0", "url": 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"https://www.anchorterminal.com/compare/north-mini-code-1-0-vs-ornith-1-5-35b-a3b.json", "title": "North Mini Code 1.0 vs Ornith-1.5-35B-A3B", "url": "https://www.anchorterminal.com/compare/north-mini-code-1-0-vs-ornith-1-5-35b-a3b" }, { "json": "https://www.anchorterminal.com/compare/north-mini-code-1-0-vs-ornith-1-5-397b.json", "title": "North Mini Code 1.0 vs Ornith-1.5-397B", "url": "https://www.anchorterminal.com/compare/north-mini-code-1-0-vs-ornith-1-5-397b" }, { "json": "https://www.anchorterminal.com/compare/north-mini-code-1-0-vs-ornith-1-5-9b.json", "title": "North Mini Code 1.0 vs Ornith-1.5-9B", "url": "https://www.anchorterminal.com/compare/north-mini-code-1-0-vs-ornith-1-5-9b" }, { "json": "https://www.anchorterminal.com/compare/north-mini-code-1-0-vs-otel-2-0-llm-31b-it.json", "title": "North Mini Code 1.0 vs OTel-2.0-LLM-31B-IT", "url": "https://www.anchorterminal.com/compare/north-mini-code-1-0-vs-otel-2-0-llm-31b-it" }, { "json": "https://www.anchorterminal.com/compare/north-mini-code-1-0-vs-qwen-agentworld-35b-a3b.json", "title": "North Mini Code 1.0 vs Qwen-AgentWorld-35B-A3B", "url": "https://www.anchorterminal.com/compare/north-mini-code-1-0-vs-qwen-agentworld-35b-a3b" }, { "json": "https://www.anchorterminal.com/compare/north-mini-code-1-0-vs-qwen3-30b-a3b-instruct-2507.json", "title": "North Mini Code 1.0 vs Qwen3-30B-A3B-Instruct-2507", "url": "https://www.anchorterminal.com/compare/north-mini-code-1-0-vs-qwen3-30b-a3b-instruct-2507" }, { "json": "https://www.anchorterminal.com/compare/north-mini-code-1-0-vs-qwen3-4b-instruct-2507.json", "title": "North Mini Code 1.0 vs Qwen3-4B-Instruct-2507", "url": "https://www.anchorterminal.com/compare/north-mini-code-1-0-vs-qwen3-4b-instruct-2507" }, { "json": "https://www.anchorterminal.com/compare/north-mini-code-1-0-vs-qwen3-5-0-8b.json", "title": "North Mini Code 1.0 vs Qwen3.5-0.8B", "url": 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vs Qwen3-VL-4B-Instruct", "url": "https://www.anchorterminal.com/compare/north-mini-code-1-0-vs-qwen3-vl-4b-instruct" }, { "json": "https://www.anchorterminal.com/compare/north-mini-code-1-0-vs-qwen3-vl-8b-instruct.json", "title": "North Mini Code 1.0 vs Qwen3-VL-8B-Instruct", "url": "https://www.anchorterminal.com/compare/north-mini-code-1-0-vs-qwen3-vl-8b-instruct" }, { "json": "https://www.anchorterminal.com/compare/north-mini-code-1-0-vs-qwopus3-8-27b-flash-v2.json", "title": "North Mini Code 1.0 vs Qwopus3.8-27B-Flash-V2", "url": "https://www.anchorterminal.com/compare/north-mini-code-1-0-vs-qwopus3-8-27b-flash-v2" }, { "json": "https://www.anchorterminal.com/compare/north-mini-code-1-0-vs-recursive-flint.json", "title": "North Mini Code 1.0 vs Recursive Flint", "url": "https://www.anchorterminal.com/compare/north-mini-code-1-0-vs-recursive-flint" }, { "json": "https://www.anchorterminal.com/compare/north-mini-code-1-0-vs-ripple-65b-preview.json", "title": "North Mini Code 1.0 vs 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"https://www.anchorterminal.com/compare/olmo-3-7b-think-vs-qwen3-5-0-8b.json", "title": "Olmo 3 7B Think vs Qwen3.5-0.8B", "url": "https://www.anchorterminal.com/compare/olmo-3-7b-think-vs-qwen3-5-0-8b" }, { "json": "https://www.anchorterminal.com/compare/olmo-3-7b-think-vs-qwen3-5-122b-a10b.json", "title": "Olmo 3 7B Think vs Qwen3.5-122B-A10B", "url": "https://www.anchorterminal.com/compare/olmo-3-7b-think-vs-qwen3-5-122b-a10b" }, { "json": "https://www.anchorterminal.com/compare/olmo-3-7b-think-vs-qwen3-5-2b.json", "title": "Olmo 3 7B Think vs Qwen3.5-2B", "url": "https://www.anchorterminal.com/compare/olmo-3-7b-think-vs-qwen3-5-2b" }, { "json": "https://www.anchorterminal.com/compare/olmo-3-7b-think-vs-qwen3-5-397b-a17b.json", "title": "Olmo 3 7B Think vs Qwen3.5-397B-A17B", "url": "https://www.anchorterminal.com/compare/olmo-3-7b-think-vs-qwen3-5-397b-a17b" }, { "json": "https://www.anchorterminal.com/compare/olmo-3-7b-think-vs-qwen3-5-4b.json", "title": "Olmo 3 7B Think vs Qwen3.5-4B", "url": "https://www.anchorterminal.com/compare/olmo-3-7b-think-vs-qwen3-5-4b" }, { "json": "https://www.anchorterminal.com/compare/olmo-3-7b-think-vs-qwen3-5-9b.json", "title": "Olmo 3 7B Think vs Qwen3.5-9B", "url": "https://www.anchorterminal.com/compare/olmo-3-7b-think-vs-qwen3-5-9b" }, { "json": "https://www.anchorterminal.com/compare/olmo-3-7b-think-vs-qwen3-6-27b.json", "title": "Olmo 3 7B Think vs Qwen3.6-27B", "url": "https://www.anchorterminal.com/compare/olmo-3-7b-think-vs-qwen3-6-27b" }, { "json": "https://www.anchorterminal.com/compare/olmo-3-7b-think-vs-qwen3-6-35b-a3b.json", "title": "Olmo 3 7B Think vs Qwen3.6-35B-A3B", "url": "https://www.anchorterminal.com/compare/olmo-3-7b-think-vs-qwen3-6-35b-a3b" }, { "json": "https://www.anchorterminal.com/compare/olmo-3-7b-think-vs-qwen3-8-27b.json", "title": "Olmo 3 7B Think vs Qwen3.8-27B", "url": "https://www.anchorterminal.com/compare/olmo-3-7b-think-vs-qwen3-8-27b" }, { "json": "https://www.anchorterminal.com/compare/olmo-3-7b-think-vs-qwen3-8-flash-next.json", "title": "Olmo 3 7B Think vs Qwen3.8-Flash-Next", "url": "https://www.anchorterminal.com/compare/olmo-3-7b-think-vs-qwen3-8-flash-next" }, { "json": "https://www.anchorterminal.com/compare/olmo-3-7b-think-vs-qwen3-coder-30b-a3b-instruct.json", "title": "Olmo 3 7B Think vs Qwen3-Coder-30B-A3B-Instruct", "url": "https://www.anchorterminal.com/compare/olmo-3-7b-think-vs-qwen3-coder-30b-a3b-instruct" }, { "json": "https://www.anchorterminal.com/compare/olmo-3-7b-think-vs-qwen3-coder-next.json", "title": "Olmo 3 7B Think vs Qwen3-Coder-Next", "url": "https://www.anchorterminal.com/compare/olmo-3-7b-think-vs-qwen3-coder-next" }, { "json": "https://www.anchorterminal.com/compare/olmo-3-7b-think-vs-qwen3-omni-30b-a3b-instruct.json", "title": "Olmo 3 7B Think vs Qwen3-Omni-30B-A3B-Instruct", "url": "https://www.anchorterminal.com/compare/olmo-3-7b-think-vs-qwen3-omni-30b-a3b-instruct" }, { "json": "https://www.anchorterminal.com/compare/olmo-3-7b-think-vs-qwen3-vl-2b-instruct.json", "title": "Olmo 3 7B Think vs Qwen3-VL-2B-Instruct", "url": "https://www.anchorterminal.com/compare/olmo-3-7b-think-vs-qwen3-vl-2b-instruct" }, { "json": "https://www.anchorterminal.com/compare/olmo-3-7b-think-vs-qwen3-vl-30b-a3b-instruct.json", "title": "Olmo 3 7B Think vs Qwen3-VL-30B-A3B-Instruct", "url": "https://www.anchorterminal.com/compare/olmo-3-7b-think-vs-qwen3-vl-30b-a3b-instruct" }, { "json": "https://www.anchorterminal.com/compare/olmo-3-7b-think-vs-qwen3-vl-32b-instruct.json", "title": "Olmo 3 7B Think vs Qwen3-VL-32B-Instruct", "url": "https://www.anchorterminal.com/compare/olmo-3-7b-think-vs-qwen3-vl-32b-instruct" }, { "json": "https://www.anchorterminal.com/compare/olmo-3-7b-think-vs-qwen3-vl-4b-instruct.json", "title": "Olmo 3 7B Think vs Qwen3-VL-4B-Instruct", "url": "https://www.anchorterminal.com/compare/olmo-3-7b-think-vs-qwen3-vl-4b-instruct" }, { "json": "https://www.anchorterminal.com/compare/olmo-3-7b-think-vs-qwen3-vl-8b-instruct.json", "title": "Olmo 3 7B Think vs Qwen3-VL-8B-Instruct", "url": "https://www.anchorterminal.com/compare/olmo-3-7b-think-vs-qwen3-vl-8b-instruct" }, { "json": "https://www.anchorterminal.com/compare/olmo-3-7b-think-vs-qwopus3-8-27b-flash-v2.json", "title": "Olmo 3 7B Think vs Qwopus3.8-27B-Flash-V2", "url": "https://www.anchorterminal.com/compare/olmo-3-7b-think-vs-qwopus3-8-27b-flash-v2" }, { "json": "https://www.anchorterminal.com/compare/olmo-3-7b-think-vs-recursive-flint.json", "title": "Olmo 3 7B Think vs Recursive Flint", "url": "https://www.anchorterminal.com/compare/olmo-3-7b-think-vs-recursive-flint" }, { "json": "https://www.anchorterminal.com/compare/olmo-3-7b-think-vs-ripple-65b-preview.json", "title": "Olmo 3 7B Think vs Ripple-65B Preview", "url": "https://www.anchorterminal.com/compare/olmo-3-7b-think-vs-ripple-65b-preview" }, { "json": "https://www.anchorterminal.com/compare/olmo-3-7b-think-vs-sensenova-loop-9b-preview.json", "title": "Olmo 3 7B Think vs SenseNova-Loop-9B-Preview", "url": "https://www.anchorterminal.com/compare/olmo-3-7b-think-vs-sensenova-loop-9b-preview" }, { "json": "https://www.anchorterminal.com/compare/olmo-3-7b-think-vs-smollm3-3b.json", "title": "Olmo 3 7B Think vs SmolLM3-3B", "url": "https://www.anchorterminal.com/compare/olmo-3-7b-think-vs-smollm3-3b" }, { "json": "https://www.anchorterminal.com/compare/olmo-3-7b-think-vs-spark-x2-6-4b.json", "title": "Olmo 3 7B Think vs Spark-X2.6-4B", "url": "https://www.anchorterminal.com/compare/olmo-3-7b-think-vs-spark-x2-6-4b" }, { "json": "https://www.anchorterminal.com/compare/olmo-3-7b-think-vs-step-3-7-flash.json", "title": "Olmo 3 7B Think vs Step 3.7 Flash", "url": "https://www.anchorterminal.com/compare/olmo-3-7b-think-vs-step-3-7-flash" }, { "json": "https://www.anchorterminal.com/compare/olmo-3-7b-think-vs-swift-1-5-qwen3-8-27b.json", "title": "Olmo 3 7B Think vs Swift 1.5 Qwen3.8-27B", "url": "https://www.anchorterminal.com/compare/olmo-3-7b-think-vs-swift-1-5-qwen3-8-27b" }, { "json": "https://www.anchorterminal.com/compare/olmo-3-7b-think-vs-swift-1-5-qwen3-8-flash-next.json", "title": "Olmo 3 7B Think vs Swift 1.5 Qwen3.8-Flash-Next", "url": "https://www.anchorterminal.com/compare/olmo-3-7b-think-vs-swift-1-5-qwen3-8-flash-next" }, { "json": "https://www.anchorterminal.com/compare/olmo-3-7b-think-vs-thinkingcap-qwen3-8-27b.json", "title": "Olmo 3 7B Think vs ThinkingCap (Qwen3.8 27B)", "url": "https://www.anchorterminal.com/compare/olmo-3-7b-think-vs-thinkingcap-qwen3-8-27b" }, { "json": "https://www.anchorterminal.com/compare/olmo-3-7b-think-vs-unlimited-ocr-2.json", "title": "Olmo 3 7B Think vs Baidu Unlimited-OCR-2", "url": "https://www.anchorterminal.com/compare/olmo-3-7b-think-vs-unlimited-ocr-2" }, { "json": "https://www.anchorterminal.com/compare/olmo-3-7b-think-vs-wevisone-vl-2b.json", "title": "Olmo 3 7B Think vs WeVisOne-VL-2B", "url": "https://www.anchorterminal.com/compare/olmo-3-7b-think-vs-wevisone-vl-2b" }, { "json": "https://www.anchorterminal.com/compare/olmo-3-7b-think-vs-wevisone-vl-4b.json", "title": "Olmo 3 7B Think vs WeVisOne-VL-4B", "url": "https://www.anchorterminal.com/compare/olmo-3-7b-think-vs-wevisone-vl-4b" }, { "json": "https://www.anchorterminal.com/compare/olmo-3-7b-think-vs-zaya1-8b.json", "title": "Olmo 3 7B Think vs ZAYA1-8B", "url": "https://www.anchorterminal.com/compare/olmo-3-7b-think-vs-zaya1-8b" } ], "panel": null, "scores": [ { "key": "capability", "name": "Capability", "pending": true, "weight": 35 }, { "by": 10, "edge": "north-mini-code-1-0", "key": "reach", "name": "Reach", "north-mini-code-1-0": 85, "olmo-3-7b-think": 75, "weight": 25 }, { "by": 15, "edge": "olmo-3-7b-think", "key": "risk", "name": "Risk", "north-mini-code-1-0": 60, "olmo-3-7b-think": 75, "weight": 20 }, { "by": 50, "edge": "north-mini-code-1-0", "key": "interface", "name": "Agent interface", "north-mini-code-1-0": 85, "olmo-3-7b-think": 35, "weight": 10 }, { "by": 16, "edge": "olmo-3-7b-think", "key": "upkeep", "name": "Documentation and upkeep", "north-mini-code-1-0": 36, "olmo-3-7b-think": 52, "weight": 10 } ], "summary": "North Mini Code 1.0 scores 61 (C) on agent readiness against Olmo 3 7B Think's 52.3 (D), and leads in 2 of 4 scored categories. Olmo 3 7B Think leads on risk 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.", "olmo-3-7b-think": "A fully open 7B reasoning model for maths, code and step-by-step answers, with every dataset and checkpoint published and its safety results rerunnable. Ollama's 4-bit build needs about 5.4 GB. It always thinks, wasn't trained for tool calls, has 65K of context, and Ai2 hasn't answered its discussions." } }, "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-olmo-3-7b-think", "json": "https://www.anchorterminal.com/compare/north-mini-code-1-0-vs-olmo-3-7b-think.json", "llms": "https://www.anchorterminal.com/llms.txt", "markdown": "https://www.anchorterminal.com/compare/north-mini-code-1-0-vs-olmo-3-7b-think.md", "mcp": "https://www.anchorterminal.com/mcp", "slim": "https://www.anchorterminal.com/compare/north-mini-code-1-0-vs-olmo-3-7b-think.min.md" }, "markdown": "North Mini Code 1.0 scores 61 (C) on agent readiness against Olmo 3 7B Think's 52.3 (D), and leads in 2 of 4 scored categories. Olmo 3 7B Think leads on risk 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- Olmo 3 7B Think: grade D, 52.3/100, rank #139 of 160 open-weight models. Markdown https://www.anchorterminal.com/tools/olmo-3-7b-think.md · JSON https://www.anchorterminal.com/api/v1/tools/olmo-3-7b-think.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- Reach, 85 against 75\n- Agent interface, 85 against 35\n\nWatch for: No limitations, safety results, languages or data description on the card\n\n### Olmo 3 7B Think (D)\n\nGood for: Researchers and agents that want a small fully open reasoning model for maths and code, with its training data on hand\n\nAhead on:\n- Risk, 75 against 60\n- Documentation and upkeep, 52 against 36\n\nWatch for: Not trained for tool calling, and the tool format lives only in the template\n\n\n## Why the edge\n\n### Agent interface: North Mini Code 1.0 +50\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- Olmo 3 7B Think (35): The chat template earns 20 for chat_template.jinja in the repository. The tool-calling format earns 10, since only the template and vLLM's own parser describe it. Trained tool calling earns nothing, because Ai2's report says tool calling was trained into the Instruct model, not Think. Structured output earns nothing. Reasoning control earns nothing, since it always thinks. Context earns 5 for 65,536 tokens trained. 20 + 10 + 0 + 0 + 0 + 5 = 35.\n\n### Documentation and upkeep: Olmo 3 7B Think +16\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- Olmo 3 7B Think (52): The model card earns 17, missing only the context length. Training data earns the full 20, as every dataset is released with sources and sizes. The last change earns 10, a card fix on 25 June 2026, within 180 days. Responsiveness earns nothing, with no Ai2 reply among the 4 replies in the discussions. Version policy earns 5, with earlier and later models in their own repositories and no dated notes. File health earns nothing, because the template's default prompt contradicts the card's on the cut-off and a stray swap file and an unanswered report sit in the repository. 17 + 20 + 10 + 0 + 5 + 0 = 52.\n\n### Risk: Olmo 3 7B Think +15\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- Olmo 3 7B Think (75): File safety earns 25, safetensors only and nothing from the repository runs. Provenance earns 15, files in the allenai organisation Ai2 links to, with a checksum for every file. Safety evaluation earns 20, as Ai2 publishes its safety results and the OLMES harness to rerun them. Agent guidance earns 5 for the card's general cautions. Licence risk earns 5, losing 5 for disallowed uses beyond the law and 5 because Ai2 can update the guidelines and end access at its discretion. The security programme earns 5 for a reporting route, a security.txt now past its expiry and a channel for security concerns in the guidelines, with no public advisories. 25 + 15 + 20 + 5 + 5 + 5 = 75.\n\n### Reach: North Mini Code 1.0 +10\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- Olmo 3 7B Think (75): Memory earns the full 30, since Ollama's 4-bit build is 4.5 GB and fits 8 GB (per the 21 October check of Ollama's library). Runtimes earn 25, with released llama.cpp (b11963), Ollama (v0.40.14, pinning b11963), vLLM, LM Studio and Transformers all running it. Builds earn nothing, because Ai2 publishes no quantised build of its own. Terms earn 10, since the card binds Apache 2.0 to Ai2's Responsible Use Guidelines, a use policy. Download earns 10, with no gate. Hosted earns nothing, as the Hub's provider mapping is empty and Ai2 has no API for it. 30 + 25 + 0 + 10 + 10 + 0 = 75.\n\n## Score by category\n\n| Category | Weight | North Mini Code 1.0 | Olmo 3 7B Think | Edge |\n| --- | --- | --- | --- | --- |\n| Capability | 35%, pending | pending | pending | not scored in this run |\n| Reach | 25% (25 this run) | 85 | 75 | North Mini Code 1.0 +10 |\n| Risk | 20% (20 this run) | 60 | 75 | Olmo 3 7B Think +15 |\n| Agent interface | 10% (10 this run) | 85 | 35 | North Mini Code 1.0 +50 |\n| Documentation and upkeep | 10% (10 this run) | 36 | 52 | Olmo 3 7B Think +16 |\n| Negative events | ≤15 | 0 | 0 | |\n| **Total** | | **61 · C** | **52.3 · D** | |\n\n## Facts side by side\n\n| Fact | North Mini Code 1.0 | Olmo 3 7B Think |\n| --- | --- | --- |\n| Kind | Open-weight model | Open-weight model |\n| Vendor | Cohere | Ai2 (Allen Institute for AI) |\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, with Ai2's Responsible Use Guidelines named on the card |\n| Read-only variant documented | no | no |\n| llms.txt | no | no |\n| Last release | 2026-07-29 | 2026-06-25 |\n| Terms last updated | no document linked | 2024-09-25 |\n| Privacy policy last updated | no document linked | 2025-02-19 |\n| Customer content may train models | not read yet | yes |\n| Terms restrict automated access | not read yet | not found in the text |\n| Terms restrict benchmarking | not read yet | not found in the text |\n| Terms or service can change without notice | not read yet | yes |\n| Arbitration or class-action waiver | not read yet | not found in the text |\n| Agent reviews | none | 2.8/5 (4) |\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**Olmo 3 7B Think.** A fully open 7B reasoning model for maths, code and step-by-step answers, with every dataset and checkpoint published and its safety results rerunnable. Ollama's 4-bit build needs about 5.4 GB. It always thinks, wasn't trained for tool calls, has 65K of context, and Ai2 hasn't answered its discussions.\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### Olmo 3 7B Think\n\n1. Quickest start is `ollama run olmo-3:7b-think`, about 4.5 GB\n2. With vLLM, `vllm serve allenai/Olmo-3-7B-Think --max-model-len 65536`; vLLM runs it through its Transformers backend\n3. Sample at temperature 0.6 and top_p 0.95 with up to 32,768 output tokens, as the card recommends, since thinking traces are long\n4. Every reply starts with a think block; strip it yourself or use a reasoning parser that reads think tags\n5. Pass your own system prompt; the template's default says the cut-off is November 2024 and that no functions are available\n6. For tool calls use Olmo 3 7B Instruct instead, which Ai2 trained for function calling\n7. A discussion reports endless reasoning loops when served with vLLM, unanswered, so cap max_tokens\n8. Check the use against Ai2's Responsible Use Guidelines, which bar automated social-media posting and undisclosed automated content outside research\n\n## Questions\n\n### Which is better for AI agents, North Mini Code 1.0 or Olmo 3 7B Think?\n\nNorth Mini Code 1.0 scores 61 (C) on agent readiness against Olmo 3 7B Think's 52.3 (D), and leads in 2 of 4 scored categories. Olmo 3 7B Think leads on risk 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-olmo-3-7b-think.json, and with the fewest tokens: https://www.anchorterminal.com/compare/north-mini-code-1-0-vs-olmo-3-7b-think.min.md\n- Over MCP at https://www.anchorterminal.com/mcp (no key): `compare_tools {\"a\": \"north-mini-code-1-0\", \"b\": \"olmo-3-7b-think\"}`. From a terminal: `anchor compare north-mini-code-1-0 olmo-3-7b-think`\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/olmo-3-7b-think.json\n\n## Other comparisons with North Mini Code 1.0 or Olmo 3 7B Think\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 Olmo 3 7B Think](https://www.anchorterminal.com/compare/agents-a1-4b-vs-olmo-3-7b-think.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 Olmo 3 7B Think](https://www.anchorterminal.com/compare/apertus-v1-5-8b-vs-olmo-3-7b-think.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 Olmo 3 7B Think](https://www.anchorterminal.com/compare/apodex-1-1-mini-vs-olmo-3-7b-think.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 Olmo 3 7B Think](https://www.anchorterminal.com/compare/arete-27b-vs-olmo-3-7b-think.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 Olmo 3 7B Think](https://www.anchorterminal.com/compare/bigbang-v1-vs-olmo-3-7b-think.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 Olmo 3 7B Think](https://www.anchorterminal.com/compare/carbon-x-vs-olmo-3-7b-think.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 Olmo 3 7B Think](https://www.anchorterminal.com/compare/cola2-vs-olmo-3-7b-think.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 Olmo 3 7B Think](https://www.anchorterminal.com/compare/cosmos-reason2-2b-vs-olmo-3-7b-think.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 Olmo 3 7B Think](https://www.anchorterminal.com/compare/darwin-36b-opus-vs-olmo-3-7b-think.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 Olmo 3 7B Think](https://www.anchorterminal.com/compare/deepseek-v3-2-vs-olmo-3-7b-think.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 Olmo 3 7B Think](https://www.anchorterminal.com/compare/deepseek-v4-1-flash-vs-olmo-3-7b-think.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 Olmo 3 7B Think](https://www.anchorterminal.com/compare/deepseek-v4-flash-0731-vs-olmo-3-7b-think.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 Olmo 3 7B Think](https://www.anchorterminal.com/compare/devstral-small-2-vs-olmo-3-7b-think.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 Olmo 3 7B Think](https://www.anchorterminal.com/compare/diffusiongemma-26b-a4b-it-vs-olmo-3-7b-think.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 Olmo 3 7B Think](https://www.anchorterminal.com/compare/exaone-4-5-33b-vs-olmo-3-7b-think.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 Olmo 3 7B Think](https://www.anchorterminal.com/compare/gemma-4-12b-it-vs-olmo-3-7b-think.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 Olmo 3 7B Think](https://www.anchorterminal.com/compare/gemma-4-26b-a4b-it-vs-olmo-3-7b-think.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 Olmo 3 7B Think](https://www.anchorterminal.com/compare/gemma-4-31b-it-vs-olmo-3-7b-think.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 Olmo 3 7B Think](https://www.anchorterminal.com/compare/gemma-4-e2b-it-vs-olmo-3-7b-think.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 Olmo 3 7B Think](https://www.anchorterminal.com/compare/gemma-4-e4b-it-vs-olmo-3-7b-think.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 Olmo 3 7B Think](https://www.anchorterminal.com/compare/glm-4-5-air-vs-olmo-3-7b-think.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 Olmo 3 7B Think](https://www.anchorterminal.com/compare/glm-4-7-flash-vs-olmo-3-7b-think.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 Olmo 3 7B Think](https://www.anchorterminal.com/compare/glm-5-3-flash-vs-olmo-3-7b-think.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 Olmo 3 7B Think](https://www.anchorterminal.com/compare/glm-5-3-vs-olmo-3-7b-think.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 Olmo 3 7B Think](https://www.anchorterminal.com/compare/gpt-oss-120b-vs-olmo-3-7b-think.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 Olmo 3 7B Think](https://www.anchorterminal.com/compare/gpt-oss-20b-vs-olmo-3-7b-think.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 Olmo 3 7B Think](https://www.anchorterminal.com/compare/granite-4-2-30b-vs-olmo-3-7b-think.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 Olmo 3 7B Think](https://www.anchorterminal.com/compare/granite-4-2-3b-vs-olmo-3-7b-think.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 Olmo 3 7B Think](https://www.anchorterminal.com/compare/granite-4-2-8b-vs-olmo-3-7b-think.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 Olmo 3 7B Think](https://www.anchorterminal.com/compare/hy-memory-30b-a3b-vs-olmo-3-7b-think.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 Olmo 3 7B Think](https://www.anchorterminal.com/compare/hy3-vs-olmo-3-7b-think.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 Olmo 3 7B Think](https://www.anchorterminal.com/compare/inkling-small-vs-olmo-3-7b-think.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 Olmo 3 7B Think](https://www.anchorterminal.com/compare/inkling-vs-olmo-3-7b-think.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 Olmo 3 7B Think](https://www.anchorterminal.com/compare/internvl3-5-gpt-oss-20b-a4b-preview-vs-olmo-3-7b-think.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 Olmo 3 7B Think](https://www.anchorterminal.com/compare/kimi-k3-1-pro-vs-olmo-3-7b-think.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 Olmo 3 7B Think](https://www.anchorterminal.com/compare/kimi-k3-vs-olmo-3-7b-think.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 Olmo 3 7B Think](https://www.anchorterminal.com/compare/kolibri-1-vs-olmo-3-7b-think.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 Olmo 3 7B Think](https://www.anchorterminal.com/compare/kronos-vs-olmo-3-7b-think.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 Olmo 3 7B Think](https://www.anchorterminal.com/compare/laguna-m-1-vs-olmo-3-7b-think.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 Olmo 3 7B Think](https://www.anchorterminal.com/compare/laguna-s-2-1-vs-olmo-3-7b-think.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 Olmo 3 7B Think](https://www.anchorterminal.com/compare/laguna-xs-2-1-vs-olmo-3-7b-think.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 Olmo 3 7B Think](https://www.anchorterminal.com/compare/lbs-27b-vs-olmo-3-7b-think.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 Olmo 3 7B Think](https://www.anchorterminal.com/compare/lfm2-5-2-6b-vs-olmo-3-7b-think.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 Olmo 3 7B Think](https://www.anchorterminal.com/compare/lfm3-1-7b-vs-olmo-3-7b-think.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 Olmo 3 7B Think](https://www.anchorterminal.com/compare/lfm3-audio-2b-vs-olmo-3-7b-think.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 Olmo 3 7B Think](https://www.anchorterminal.com/compare/lfm3-omni-2b-vs-olmo-3-7b-think.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 Olmo 3 7B Think](https://www.anchorterminal.com/compare/lfm3-vl-2b-vs-olmo-3-7b-think.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 Olmo 3 7B Think](https://www.anchorterminal.com/compare/ling-3-0-tiny-vs-olmo-3-7b-think.md)\n- [Ling-3.1-flash-1019 vs North Mini Code 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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 Olmo 3 7B Think](https://www.anchorterminal.com/compare/minicpm-o-4-5-vs-olmo-3-7b-think.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 Olmo 3 7B Think](https://www.anchorterminal.com/compare/minicpm-v-4-7-1b-vs-olmo-3-7b-think.md)\n- [MiniCPM-V 4.7 35B-A3B vs North Mini Code 1.0](https://www.anchorterminal.com/compare/minicpm-v-4-7-35b-a3b-vs-north-mini-code-1-0.md)\n- [MiniCPM-V 4.7 35B-A3B vs Olmo 3 7B Think](https://www.anchorterminal.com/compare/minicpm-v-4-7-35b-a3b-vs-olmo-3-7b-think.md)\n- [MiniCPM5-2B vs North Mini Code 1.0](https://www.anchorterminal.com/compare/minicpm5-2b-vs-north-mini-code-1-0.md)\n- [MiniCPM5-2B vs Olmo 3 7B Think](https://www.anchorterminal.com/compare/minicpm5-2b-vs-olmo-3-7b-think.md)\n- [MiniMax-M2.5 vs North Mini Code 1.0](https://www.anchorterminal.com/compare/minimax-m2-5-vs-north-mini-code-1-0.md)\n- [MiniMax-M2.5 vs Olmo 3 7B Think](https://www.anchorterminal.com/compare/minimax-m2-5-vs-olmo-3-7b-think.md)\n- [MiniMax-M2.7 vs North Mini Code 1.0](https://www.anchorterminal.com/compare/minimax-m2-7-vs-north-mini-code-1-0.md)\n- [MiniMax-M2.7 vs Olmo 3 7B Think](https://www.anchorterminal.com/compare/minimax-m2-7-vs-olmo-3-7b-think.md)\n- [MiniMax-M3.1-Flash vs North Mini Code 1.0](https://www.anchorterminal.com/compare/minimax-m3-1-flash-vs-north-mini-code-1-0.md)\n- [MiniMax-M3.1-Flash vs Olmo 3 7B Think](https://www.anchorterminal.com/compare/minimax-m3-1-flash-vs-olmo-3-7b-think.md)\n- [Mistral Large 4 vs North Mini Code 1.0](https://www.anchorterminal.com/compare/mistral-large-4-vs-north-mini-code-1-0.md)\n- [Mistral Large 4 vs Olmo 3 7B Think](https://www.anchorterminal.com/compare/mistral-large-4-vs-olmo-3-7b-think.md)\n- [Muse Glimmer 30B vs North Mini Code 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