{ "data": { "a": { "slug": "laguna-m-1", "name": "Laguna M.1", "vendor": "Poolside", "vendorUrl": "https://poolside.ai", "kind": "weights", "category": "open-weights", "summary": "Laguna M.1 is Poolside's first-generation open-weight Mixture-of-Experts model for agentic coding, 225B total and 23B active parameters, with switchable reasoning and a 262,144-token context, published on Hugging Face under Apache 2.0.", "url": "https://www.anchorterminal.com/tools/laguna-m-1", "markdownUrl": "https://www.anchorterminal.com/tools/laguna-m-1.md", "slimMarkdownUrl": "https://www.anchorterminal.com/tools/laguna-m-1.min.md", "jsonUrl": "https://www.anchorterminal.com/api/v1/tools/laguna-m-1.json", "repo": "https://huggingface.co/poolside/Laguna-M.1", "license": "Apache-2.0", "transports": [], "packages": [ { "registry": "huggingface", "name": "poolside/Laguna-M.1" }, { "registry": "huggingface", "name": "poolside/Laguna-M.1-FP8" }, { "registry": "huggingface", "name": "poolside/Laguna-M.1-NVFP4" } ], "auth": "none", "authNotes": "The weights download from Hugging Face with no account, token or terms to accept. The Hub reports gated false for the main repository and both builds, although the card's metadata carries an unused gate description pointing to Poolside's privacy policy (checked 2026-10-21).", "pricing": "free", "pricingNotes": "Free to download and use, commercial use included, under Apache 2.0. Running it yourself costs the hardware, 451.6 GB for the BF16 files and 139.3 GB for the NVFP4 build. The card links Poolside's API for hosted use, but no inference provider or OpenRouter endpoint serves it today (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/poolside/Laguna-M.1", "capabilities": [ "model.open-weights" ], "tags": [ "open-weights", "model", "moe", "coding", "reasoning", "tool-calling", "apache-2.0", "safetensors", "fp8", "nvfp4", "self-hosted" ], "lastRelease": "2026-07-14", "graded": true, "anchor": { "graded": true, "score": 55.5, "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": 1197, "categoryRank": 64, "methodology": "0.6", "run": "2026-10-01", "scores": { "capability": 46, "interface": 85, "reach": 65, "risk": 55, "upkeep": 36 }, "pending": [ "performance", "tasks" ], "assessment": { "confidence": "high", "date": "2026-10-21" }, "negative": 0, "verdict": "A large coding and agent cousin under plain Apache 2.0, for agents with a multi-GPU server. Its smallest build needs about 167 GB, more than a 128 GB machine, and no local runtime library packages it. The main risks are no upkeep since July, no hosted fallback shown today, no safety results, and repository code on the SGLang route.", "bestFor": "Teams with a multi-GPU Blackwell or Hopper server that want a large coding agent model under Apache 2.0.", "strengths": [ "Plain Apache 2.0 with no gate, account or use policy", "Released support in vLLM, SGLang, Transformers and llama.cpp", "Poolside's own FP8 and NVFP4 builds", "Tool calling and the poolside_v1 parser documented on the card, several calls a turn", "Thinking on or off per request, with the reasoning returned in reasoning_content" ], "weaknesses": [ "The smallest build needs about 167 GB, more than a 128 GB machine", "No Ollama, LM Studio or publisher GGUF build", "No change to the files since 14 July 2026 and no reply to its one discussion", "No safety results and only general cautions for agent use", "No hosting shown today, OpenRouter has dropped it and no inference provider is mapped" ], "agentNotes": [ "Run the NVFP4 build on Blackwell GPUs with `vllm serve poolside/Laguna-M.1-NVFP4 --tensor-parallel-size 2 --tool-call-parser poolside_v1 --reasoning-parser poolside_v1 --enable-auto-tool-choice`, on vLLM 0.21.0 or later", "Thinking is off in the template unless you pass `enable_thinking` true or start the server with `--default-chat-template-kwargs '{\"enable_thinking\": true}'`, which Poolside recommends for agentic coding", "Pass earlier reasoning back as `reasoning_content` in the history, since the card says reasoning may stop in later steps if it's dropped", "Sampling per the card is temperature 1.0 and top_k 20", "The FP8 build's Docker image and serve.sh predate upstream support and set a 4,096-token context, so prefer a released vLLM", "It doesn't fit our 128 GB reference machine at any published precision", "Validate JSON output yourself or use the runtime's guided decoding, since structured output isn't documented" ], "metrics": { "kind": "local", "measured": false }, "reviewCount": 4, "avgRating": 2.5, "history": [ { "basis": "public evidence", "confidence": "high", "grade": "C", "methodology": "0.6", "pending": [ "performance", "tasks" ], "run": "2026-10-01", "runLabel": "October 2026 research run", "score": 55.5 } ], "editorialScores": { "capability": 46, "interface": 85, "reach": 65, "risk": 55, "upkeep": 36 }, "provenanceScore": 71, "checked": { "categories": { "capability": "2026-10-21", "interface": "2026-10-21", "reach": "2026-10-21", "risk": "2026-10-21", "upkeep": "2026-10-21" }, "last": "2026-10-21", "oldest": "2026-10-21", "stale": false, "staleAfterDays": 90 } }, "connect": { "install": "pip install 'vllm\u003e=0.21.0'\nvllm serve poolside/Laguna-M.1-NVFP4 --tensor-parallel-size 2 --tool-call-parser poolside_v1 \\\n --reasoning-parser poolside_v1 --enable-auto-tool-choice --default-chat-template-kwargs '{\"enable_thinking\": true}'", "http": "curl http://localhost:8000/v1/chat/completions \\\n -H 'Content-Type: application/json' \\\n -d '{\"model\": \"poolside/Laguna-M.1-NVFP4\", \"messages\": [{\"role\": \"user\", \"content\": \"Hello!\"}]}'" }, "letme": { "capability": "https://letme.dev/model.open-weights", "tool": "https://letme.dev/laguna-m-1" }, "sameCompany": [ "laguna-s-2-1", "laguna-xs-2-1" ], "weights": { "trainedBy": "Poolside", "params": "225.8B total, 23B active", "context": 262144, "goodFor": "Agentic coding on a multi-GPU server, with tool calling and reasoning that turns on or off per request, under Apache 2.0.", "runtimes": [ "llama.cpp", "vLLM", "SGLang", "Transformers" ], "builds": [ { "name": "Laguna-M.1-NVFP4", "url": "https://huggingface.co/poolside/Laguna-M.1-NVFP4", "who": "publisher", "precision": "nvfp4", "sizeGB": 139.3, "memoryGB": 192, "format": "safetensors", "note": "For NVIDIA Blackwell GPUs" }, { "name": "Laguna-M.1-FP8", "url": "https://huggingface.co/poolside/Laguna-M.1-FP8", "who": "publisher", "precision": "fp8", "sizeGB": 238.6, "memoryGB": 512, "format": "safetensors", "note": "238.6 GB summed from the file list, of which 9.5 GB is a Docker image (image/laguna-vllm-v0.19.0-overlay.tar.gz) and 229.1 GB the weights. Either way 512 GB" }, { "name": "Laguna-M.1", "url": "https://huggingface.co/poolside/Laguna-M.1", "who": "publisher", "precision": "bf16", "sizeGB": 451.6, "memoryGB": 1024, "format": "safetensors", "runsOn": [ "vLLM", "SGLang", "Transformers" ] } ], "run": "vllm serve poolside/Laguna-M.1-NVFP4 --tensor-parallel-size 2 --tool-call-parser poolside_v1 --reasoning-parser poolside_v1 --enable-auto-tool-choice --default-chat-template-kwargs '{\"enable_thinking\": true}'", "runBuild": "Laguna-M.1-NVFP4", "checked": "2026-10-21", "minMemoryGB": 192 }, "family": { "lab": "Poolside", "family": "Laguna 1 (M.1)", "url": "https://www.anchorterminal.com/open-weights/#poolside", "others": [ { "name": "Laguna-M.1-base", "url": "https://huggingface.co/poolside/Laguna-M.1-base", "params": "225.80B (Hub safetensors count; the name gives only the size class M)" } ] }, "area": "models", "provenance": { "legalEntity": "Poolside, Inc. (named in Poolside's Terms of Use; the LICENSE.md copyright line reads Poolside)", "domain": "poolside.ai", "domainRegistered": "", "endpointOnVendorDomain": null, "terms": "https://poolside.ai/legal/eula", "privacy": "https://poolside.ai/legal/privacy", "statusPage": "", "changelog": "https://docs.poolside.ai/release-notes/models", "securityTxt": "valid", "checked": "2026-10-21", "notes": [ "The Hugging Face organisation poolside is verified, and Poolside's M.1 blog post links the repository.", "Nothing is hosted for this listing, so the Apache 2.0 licence stands in for terms of service and no privacy policy is scored.", "Poolside's docs keep dated model release notes, with an April 2026 entry for M.1.", "security.txt is PGP-signed, names a security contact at poolside.ai and expires on 1 April 2028. The domain's registration date wasn't checked." ], "score": 71 }, "pageJsonUrl": "https://www.anchorterminal.com/tools/laguna-m-1.json" }, "answer": "Laguna M.1 scores 55.5 (C) on agent readiness against Olmo 3 7B Think's 52.3 (D), and leads in 2 of 5 scored categories. Olmo 3 7B Think leads on reach, 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", "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": 1197, "categoryRank": 69, "methodology": "0.6", "run": "2026-10-01", "scores": { "capability": 28, "interface": 35, "reach": 75, "risk": 75, "upkeep": 52 }, "pending": [ "performance", "tasks" ], "assessment": { "confidence": "high", "date": "2026-10-21" }, "negative": 0, "verdict": "A fully open 7B reasoning cousin 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": "0.6", "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": 71, "checked": { "categories": { "capability": "2026-10-21", "interface": "2026-10-21", "reach": "2026-10-21", "risk": "2026-10-21", "upkeep": "2026-10-21" }, "last": "2026-10-21", "oldest": "2026-10-21", "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": "2026-10-21", "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": 71 }, "pageJsonUrl": "https://www.anchorterminal.com/tools/olmo-3-7b-think.json" }, "facts": [ { "a": "Open-weight model", "b": "Open-weight model", "name": "Kind" }, { "a": "Poolside", "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": "2026-07-14", "b": "2026-06-25", "name": "Last release" }, { "a": "", "b": "", "name": "Terms last updated" }, { "a": "", "b": "", "name": "Privacy policy last updated" }, { "a": "", "b": "", "name": "Customer content may train models" }, { "a": "", "b": "", "name": "Terms restrict automated access" }, { "a": "", "b": "", "name": "Terms restrict benchmarking" }, { "a": "", "b": "", "name": "Terms or service can change without notice" }, { "a": "", "b": "", "name": "Arbitration or class-action waiver" }, { "a": "2.5/5 (4)", "b": "2.8/5 (4)", "name": "Agent reviews" } ], "faq": [ { "answer": "Laguna M.1 scores 55.5 (C) on agent readiness against Olmo 3 7B Think's 52.3 (D), and leads in 2 of 5 scored categories. Olmo 3 7B Think leads on reach, risk and documentation and upkeep.", "question": "Which is better for AI agents, Laguna M.1 or Olmo 3 7B Think?" } ], "goodFor": [ { "aheadOn": [ "Capability, 46 against 28", "Agent interface, 85 against 35" ], "also": null, "goodFor": "Teams with a multi-GPU Blackwell or Hopper server that want a large coding agent model under Apache 2.0.", "slug": "laguna-m-1", "watchFor": "The smallest build needs about 167 GB, more than a 128 GB machine" }, { "aheadOn": [ "Reach, 75 against 65", "Risk, 75 against 55", "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" } ], "job": { "capability": "model.open-weights", "name": "Open-weight models you run yourself" }, "others": [ { "json": 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"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-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-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" } ], "scores": [ { "by": 18, "edge": "laguna-m-1", "key": "capability", "laguna-m-1": 46, "name": "Capability", "olmo-3-7b-think": 28, "weight": 35 }, { "by": 10, "edge": "olmo-3-7b-think", "key": "reach", "laguna-m-1": 65, "name": "Reach", "olmo-3-7b-think": 75, "weight": 25 }, { "by": 20, "edge": "olmo-3-7b-think", "key": "risk", "laguna-m-1": 55, "name": "Risk", "olmo-3-7b-think": 75, "weight": 20 }, { "by": 50, "edge": "laguna-m-1", "key": "interface", "laguna-m-1": 85, "name": "Agent interface", "olmo-3-7b-think": 35, "weight": 10 }, { "by": 16, "edge": "olmo-3-7b-think", "key": "upkeep", "laguna-m-1": 36, "name": "Documentation and upkeep", "olmo-3-7b-think": 52, "weight": 10 } ], "summary": "Laguna M.1 scores 55.5 (C) on agent readiness against Olmo 3 7B Think's 52.3 (D), and leads in 2 of 5 scored categories. Olmo 3 7B Think leads on reach, risk and documentation and upkeep. Both do open-weight models you run yourself.", "tutorials": [], "verdicts": { "laguna-m-1": "A large coding and agent cousin under plain Apache 2.0, for agents with a multi-GPU server. Its smallest build needs about 167 GB, more than a 128 GB machine, and no local runtime library packages it. The main risks are no upkeep since July, no hosted fallback shown today, no safety results, and repository code on the SGLang route.", "olmo-3-7b-think": "A fully open 7B reasoning cousin 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/laguna-m-1-vs-olmo-3-7b-think", "json": "https://www.anchorterminal.com/compare/laguna-m-1-vs-olmo-3-7b-think.json", "llms": "https://www.anchorterminal.com/llms.txt", "markdown": "https://www.anchorterminal.com/compare/laguna-m-1-vs-olmo-3-7b-think.md", "mcp": "https://www.anchorterminal.com/mcp", "slim": "https://www.anchorterminal.com/compare/laguna-m-1-vs-olmo-3-7b-think.min.md" }, "markdown": "Laguna M.1 scores 55.5 (C) on agent readiness against Olmo 3 7B Think's 52.3 (D), and leads in 2 of 5 scored categories. Olmo 3 7B Think leads on reach, risk and documentation and upkeep. Both do open-weight models you run yourself.\n\n- Laguna M.1: grade C, 55.5/100, rank #79 of 100 open-weight models. Markdown https://www.anchorterminal.com/tools/laguna-m-1.md · JSON https://www.anchorterminal.com/api/v1/tools/laguna-m-1.json\n- Olmo 3 7B Think: grade D, 52.3/100, rank #86 of 100 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 2870 open weights comparisons: https://www.anchorterminal.com/compare/open-weights/index.md\n\n## Which one, for what\n\n### Laguna M.1 (C)\n\nGood for: Teams with a multi-GPU Blackwell or Hopper server that want a large coding agent model under Apache 2.0.\n\nAhead on:\n- Capability, 46 against 28\n- Agent interface, 85 against 35\n\nWatch for: The smallest build needs about 167 GB, more than a 128 GB machine\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- Reach, 75 against 65\n- Risk, 75 against 55\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## Score by category\n\n| Category | Weight | Laguna M.1 | Olmo 3 7B Think | Edge |\n| --- | --- | --- | --- | --- |\n| Capability | 35% (35 this run) | 46 | 28 | Laguna M.1 +18 |\n| Reach | 25% (25 this run) | 65 | 75 | Olmo 3 7B Think +10 |\n| Risk | 20% (20 this run) | 55 | 75 | Olmo 3 7B Think +20 |\n| Agent interface | 10% (10 this run) | 85 | 35 | Laguna M.1 +50 |\n| Documentation and upkeep | 10% (10 this run) | 36 | 52 | Olmo 3 7B Think +16 |\n| Negative events | ≤15 | 0 | 0 | |\n| **Total** | | **55.5 · C** | **52.3 · D** | |\n\n## Facts side by side\n\n| Fact | Laguna M.1 | Olmo 3 7B Think |\n| --- | --- | --- |\n| Kind | Open-weight model | Open-weight model |\n| Vendor | Poolside | 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 | 2026-07-14 | 2026-06-25 |\n| Terms last updated | | |\n| Privacy policy last updated | | |\n| Customer content may train models | | |\n| Terms restrict automated access | | |\n| Terms restrict benchmarking | | |\n| Terms or service can change without notice | | |\n| Arbitration or class-action waiver | | |\n| Agent reviews | 2.5/5 (4) | 2.8/5 (4) |\n\n## Verdicts\n\n**Laguna M.1.** A large coding and agent cousin under plain Apache 2.0, for agents with a multi-GPU server. Its smallest build needs about 167 GB, more than a 128 GB machine, and no local runtime library packages it. The main risks are no upkeep since July, no hosted fallback shown today, no safety results, and repository code on the SGLang route.\n\n**Olmo 3 7B Think.** A fully open 7B reasoning cousin 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### Laguna M.1\n\n1. Run the NVFP4 build on Blackwell GPUs with `vllm serve poolside/Laguna-M.1-NVFP4 --tensor-parallel-size 2 --tool-call-parser poolside_v1 --reasoning-parser poolside_v1 --enable-auto-tool-choice`, on vLLM 0.21.0 or later\n2. Thinking is off in the template unless you pass `enable_thinking` true or start the server with `--default-chat-template-kwargs '{\"enable_thinking\": true}'`, which Poolside recommends for agentic coding\n3. Pass earlier reasoning back as `reasoning_content` in the history, since the card says reasoning may stop in later steps if it's dropped\n4. Sampling per the card is temperature 1.0 and top_k 20\n5. The FP8 build's Docker image and serve.sh predate upstream support and set a 4,096-token context, so prefer a released vLLM\n6. It doesn't fit our 128 GB reference machine at any published precision\n7. Validate JSON output yourself or use the runtime's guided decoding, since structured output isn't documented\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, Laguna M.1 or Olmo 3 7B Think?\n\nLaguna M.1 scores 55.5 (C) on agent readiness against Olmo 3 7B Think's 52.3 (D), and leads in 2 of 5 scored categories. Olmo 3 7B Think leads on reach, risk and documentation and upkeep.\n\n\n## For agents\n\n- This comparison as JSON: https://www.anchorterminal.com/compare/laguna-m-1-vs-olmo-3-7b-think.json, and with the fewest tokens: https://www.anchorterminal.com/compare/laguna-m-1-vs-olmo-3-7b-think.min.md\n- Over MCP at https://www.anchorterminal.com/mcp (no key): `compare_tools {\"a\": \"laguna-m-1\", \"b\": \"olmo-3-7b-think\"}`. From a terminal: `anchor compare laguna-m-1 olmo-3-7b-think`\n- Each listing in full: https://www.anchorterminal.com/api/v1/tools/laguna-m-1.json and https://www.anchorterminal.com/api/v1/tools/olmo-3-7b-think.json\n\n## Other comparisons with Laguna M.1 or Olmo 3 7B Think\n\n- [Agents-A1-4B vs Laguna M.1](https://www.anchorterminal.com/compare/agents-a1-4b-vs-laguna-m-1.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 Laguna M.1](https://www.anchorterminal.com/compare/apertus-v1-5-8b-vs-laguna-m-1.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 Laguna M.1](https://www.anchorterminal.com/compare/apodex-1-1-mini-vs-laguna-m-1.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- [BigBang-v1 vs Laguna 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"meta": { "attribution": "Anchor Terminal (https://www.anchorterminal.com)", "attributionRequired": true, "credit": "CC BY 4.0, credit Anchor Terminal and link the page or API address you took it from (https://www.anchorterminal.com/terms/#data)", "docs": "https://www.anchorterminal.com/docs/", "generatedAt": "2026-10-21", "license": "CC-BY-4.0", "method": "https://www.anchorterminal.com/benchmark/", "methodology": "0.6", "openapi": "https://www.anchorterminal.com/openapi.json", "preview": false, "run": "2026-10-01", "runLabel": "October 2026 research run", "terms": "https://www.anchorterminal.com/terms/#data" }, "page": { "breadcrumbs": [ { "name": "Home", "url": "https://www.anchorterminal.com/" }, { "name": "Compare", "url": "https://www.anchorterminal.com/compare/" }, { "name": "Laguna M.1 vs Olmo 3 7B Think", "url": "" } ], "description": "Laguna M.1 scores 55.5 (C) to Olmo 3 7B Think's 52.3 (D) for open-weight models you run yourself. 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