{ "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", "dns": "laguna-m-1.grade.anchorterminal.com", "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 is mapped on the Hub and Poolside's API docs name only Laguna S 2.1 (checked 2026-11-04).", "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": 56.7, "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": 84, "methodology": "0.7", "run": "2026-10-01", "scores": { "capability": 46, "interface": 85, "reach": 70, "risk": 55, "upkeep": 36 }, "pending": [ "performance", "tasks" ], "assessment": { "confidence": "high", "date": "2026-11-04" }, "negative": 0, "verdict": "A large open-weight coding and agent model under plain Apache 2.0, for teams with a multi-GPU server. Its smallest build needs about 167 GB, more than a 128 GB machine. Released llama.cpp, Ollama, vLLM, SGLang and Transformers code runs the architecture. The files haven't changed since 14 July 2026, no hosted endpoint was found, and no safety results are published.", "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, llama.cpp and Ollama (through its pinned 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 library or LM Studio catalogue entry, and no publisher GGUF build", "No change to the files since 14 July 2026 and no reply from Poolside to its one discussion", "No safety results and only general cautions for agent use", "No hosting found. No inference provider is mapped on the Hub, and Poolside's API docs name only Laguna S 2.1" ], "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": "0.7", "pending": [ "performance", "tasks" ], "run": "2026-10-01", "runLabel": "October 2026 research run", "score": 56.7 } ], "editorialScores": { "capability": 46, "interface": 85, "reach": 70, "risk": 55, "upkeep": 36 }, "provenanceScore": 69, "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", "lastMoved": "2026-11-04", "oldest": "2026-11-04", "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", "Ollama", "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": "2026-11-04", "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": 69 }, "pageJsonUrl": "https://www.anchorterminal.com/tools/laguna-m-1.json", "live": { "slug": "laguna-m-1", "securityTxt": { "url": "https://poolside.ai/.well-known/security.txt", "state": "valid", "expires": "2028-04-01T12:00:00.000Z", "checkedAt": "2026-11-10T16:09:25.614312659Z" }, "domain": { "domain": "poolside.ai", "registered": "2020-07-07", "source": "https://rdap.identitydigital.services/rdap/domain/poolside.ai", "checkedAt": "2026-11-08T14:58:52.089559761Z" }, "pages": [ { "url": "https://docs.poolside.ai/release-notes/models", "kind": "changelog", "status": 200, "checkedAt": "2026-11-10T16:18:11.541481401Z", "changedAt": "2026-11-01T06:42:30.392417309Z", "fingerprint": "41c3a898c1a6" }, { "url": "https://poolside.ai/legal/privacy", "kind": "privacy", "status": 304, "checkedAt": "2026-11-10T16:28:14.659109859Z", "changedAt": "0001-01-01T00:00:00Z", "fingerprint": "95a56164038b" }, { "url": "https://poolside.ai/legal/eula", "kind": "terms", "status": 304, "checkedAt": "2026-11-10T16:28:12.585971651Z", "changedAt": "0001-01-01T00:00:00Z", "fingerprint": "6daf0ef509c0" } ], "updatedAt": "2026-11-10T16:28:14.659109859Z" } }, "answer": "Step 3.7 Flash scores 59.8 (C) on agent readiness against Laguna M.1's 56.7 (C), and leads in 1 of 4 scored categories. Laguna M.1 leads on risk.", "b": { "slug": "step-3-7-flash", "name": "Step 3.7 Flash", "vendor": "StepFun", "vendorUrl": "https://platform.stepfun.ai", "kind": "weights", "category": "open-weights", "summary": "Step 3.7 Flash is StepFun's open-weight vision-language model, 198B parameters with about 11B active, with tool calling and a 256K context. Apache 2.0. Its 4-bit GGUF is 105 GB, just over what a 128 GB machine holds.", "url": "https://www.anchorterminal.com/tools/step-3-7-flash", "markdownUrl": "https://www.anchorterminal.com/tools/step-3-7-flash.md", "slimMarkdownUrl": "https://www.anchorterminal.com/tools/step-3-7-flash.min.md", "jsonUrl": "https://www.anchorterminal.com/api/v1/tools/step-3-7-flash.json", "dns": "step-3-7-flash.grade.anchorterminal.com", "repo": "https://huggingface.co/stepfun-ai/Step-3.7-Flash", "license": "Apache-2.0 (metadata and card; no LICENSE file)", "transports": [], "packages": [ { "registry": "huggingface", "name": "stepfun-ai/Step-3.7-Flash" }, { "registry": "huggingface", "name": "stepfun-ai/Step-3.7-Flash-GGUF" }, { "registry": "huggingface", "name": "stepfun-ai/Step-3.7-Flash-FP8" }, { "registry": "huggingface", "name": "stepfun-ai/Step-3.7-Flash-NVFP4" } ], "auth": "none", "authNotes": "The weights download from Hugging Face with no account, token or terms to accept. None of the four repositories is gated (checked 2026-11-10).", "pricing": "free", "pricingNotes": "Free to download and use under Apache 2.0. Running it yourself takes 109 GB at IQ4_XS with its projector, 129 GB in NVFP4 or 403 GB in BF16. StepFun's API serves it at $0.20 per million input tokens and $1.15 per million output, per the card, and DeepInfra and Featherless serve it too (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/stepfun-ai/Step-3.7-Flash", "capabilities": [ "model.open-weights" ], "tags": [ "open-weights", "model", "moe", "multimodal", "vision", "reasoning", "tool-calling", "agentic", "long-context", "apache-2.0", "safetensors", "gguf", "fp8", "nvfp4", "custom-code", "self-hosted" ], "lastRelease": "2026-06-03", "graded": true, "anchor": { "graded": true, "score": 59.8, "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": 73, "methodology": "0.7", "run": "2026-10-01", "scores": { "interface": 85, "reach": 70, "risk": 45, "upkeep": 39 }, "pending": [ "performance", "tasks" ], "assessment": { "confidence": "low", "date": "2026-11-10" }, "negative": 0, "verdict": "A capable open agent model with a clean licence, every kind of build and four released runtimes. Two things hold it back: it's a little too big for a 128 GB machine at 4 bits, whatever the card says, and StepFun has gone quiet on the repository since June. No safety results, limitations or data description.", "bestFor": "Teams with a GPU server or a provider account that want an open, long-context agent model with vision", "strengths": [ "Apache 2.0, ungated", "GGUF, FP8 and NVFP4 builds from StepFun", "Four released runtimes carry it, with Step parsers in vLLM and SGLang", "A 256K context with images in", "Hosted by StepFun and two providers" ], "weaknesses": [ "About 131 GB to run at 4 bits with images, over a 128 GB machine's share", "Every serve command on the card runs the repository's code", "No reply from StepFun on the repository's discussions", "Not changed since 3 June 2026", "No limitations, safety results or training data on the card" ], "agentNotes": [ "On a 128 GB machine the 4-bit GGUF won't fit with a working context. Use StepFun's API or a provider, or a server", "On vLLM or SGLang pass `--tool-call-parser step3p5 --reasoning-parser step3p5`", "The card's commands pass trust-remote-code. Released Transformers 5.22.2 has the model built in if you'd rather not run the repository's code", "For llama.cpp load the mmproj file from StepFun's GGUF repository for image input", "StepFun's API has two hosts. Use the one where your key was issued, `api.stepfun.ai` or `api.stepfun.com`", "The same model is on our StepFun API listing, with prices and terms" ], "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": 59.8 } ], "editorialScores": { "interface": 85, "reach": 70, "risk": 45, "upkeep": 39 }, "provenanceScore": 58, "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 \"sglang\u003e=0.5.23\"\nsglang serve --model-path stepfun-ai/Step-3.7-Flash-FP8 --tp 8 --ep 4 --reasoning-parser step3p5 --tool-call-parser step3p5 --enable-multimodal --trust-remote-code", "http": "# SGLang and vLLM serve an OpenAI-compatible API. StepFun's own API is at https://api.stepfun.ai/v1\n# (https://api.stepfun.com/v1 for keys issued in China)" }, "letme": { "capability": "https://letme.dev/model.open-weights", "tool": "https://letme.dev/step-3-7-flash" }, "sameModel": [ "stepfun-api" ], "weights": { "trainedBy": "StepFun", "params": "198B", "active": "11B", "context": 262144, "goodFor": "Agent work that mixes images, search and code, on a GPU server or through StepFun's API. It's a few GB too big for a 128 GB machine at 4 bits.", "runtimes": [ "llama.cpp", "vLLM", "SGLang", "Transformers" ], "builds": [ { "name": "Step-3.7-Flash-GGUF IQ4_XS", "url": "https://huggingface.co/stepfun-ai/Step-3.7-Flash-GGUF", "who": "publisher", "precision": "iq4_xs", "sizeGB": 108.96, "memoryGB": 192, "format": "gguf", "runsOn": [ "llama.cpp" ], "note": "104.99 GB with the 3.97 GB F16 projector" }, { "name": "Step-3.7-Flash-GGUF Q4_K_S", "url": "https://huggingface.co/stepfun-ai/Step-3.7-Flash-GGUF", "who": "publisher", "precision": "q4_k_s", "sizeGB": 115.47, "memoryGB": 192, "format": "gguf", "runsOn": [ "llama.cpp" ], "note": "111.50 GB with the 3.97 GB F16 projector" }, { "name": "Step-3.7-Flash-NVFP4", "url": "https://huggingface.co/stepfun-ai/Step-3.7-Flash-NVFP4", "who": "publisher", "precision": "nvfp4", "sizeGB": 129.25, "memoryGB": 192, "format": "safetensors", "runsOn": [ "vLLM", "SGLang" ], "note": "StepFun's 4-bit build for NVIDIA GPUs" }, { "name": "Step-3.7-Flash-FP8", "url": "https://huggingface.co/stepfun-ai/Step-3.7-Flash-FP8", "who": "publisher", "precision": "fp8", "sizeGB": 212.53, "memoryGB": 256, "format": "safetensors", "runsOn": [ "vLLM", "SGLang" ], "note": "StepFun's FP8 build" }, { "name": "Step-3.7-Flash-GGUF Q8_0", "url": "https://huggingface.co/stepfun-ai/Step-3.7-Flash-GGUF", "who": "publisher", "precision": "q8_0", "sizeGB": 213.39, "memoryGB": 512, "format": "gguf", "runsOn": [ "llama.cpp" ], "note": "209.42 GB with the 3.97 GB F16 projector" }, { "name": "Step-3.7-Flash (BF16 safetensors)", "url": "https://huggingface.co/stepfun-ai/Step-3.7-Flash", "who": "publisher", "precision": "bf16", "sizeGB": 402.73, "memoryGB": 512, "format": "safetensors", "runsOn": [ "vLLM", "SGLang", "Transformers" ], "note": "26 files" } ], "run": "llama-server -hf stepfun-ai/Step-3.7-Flash-GGUF:IQ4_XS --jinja", "runBuild": "Step-3.7-Flash-GGUF IQ4_XS", "checked": "2026-11-10", "minMemoryGB": 192 }, "family": { "lab": "StepFun", "family": "Step 3", "url": "https://www.anchorterminal.com/open-weights/#stepfun", "others": [ { "name": "Step-3.5-Flash", "url": "https://huggingface.co/stepfun-ai/Step-3.5-Flash" }, { "name": "Step3-VL-10B", "url": "https://huggingface.co/stepfun-ai/Step3-VL-10B" } ] }, "area": "models", "provenance": { "legalEntity": "STEPFUN TECHNOLOGY (HK) LIMITED", "domain": "stepfun.ai", "domainRegistered": "", "endpointOnVendorDomain": null, "terms": "", "privacy": "", "statusPage": "", "changelog": "https://huggingface.co/stepfun-ai/Step-3.7-Flash/commits/main", "securityTxt": "none", "checked": "2026-11-10", "notes": [ "StepFun's legal entity, domain and security.txt are carried from our StepFun API listing.", "Nothing is hosted under this listing, so Apache 2.0 stands in for terms of service and no privacy policy is scored. The StepFun API that serves this model has its own listing.", "The changelog is the commit history, 23 commits from 23 May to 3 June 2026." ], "score": 58 }, "pageJsonUrl": "https://www.anchorterminal.com/tools/step-3-7-flash.json" }, "edges": [ { "by": 10, "category": "risk", "leads": "laguna-m-1", "name": "Risk", "reasons": { "a": "File safety 15 of 25, safetensors only, but the repository ships model code behind auto_map and the card's SGLang and TensorRT-LLM instructions use trust_remote_code. Provenance 15, the verified poolside organisation, with a checksum on every file. Safety evaluation 0, none published. Agent guidance 5, general cautions only. Licence risk 15, plain Apache 2.0. Security programme 5, a signed security.txt and a security contact on the card, with no public advisories found.", "b": "File safety 15, safetensors and GGUF only, no .bin, .pt or .pth files (25). Provenance 15, the files sit in the stepfun-ai organisation, which the card's StepFun platform and model page belong to (10). Safety evaluation 0, no safety results on the card. Agent guidance 0, the card has no limitations section and gives no guidance on prompt injection, instruction priority, refusals or safeguards. Licence risk 15, Apache 2.0 has no use policy, threshold or change clause. Security programme 0, no way to report a flaw on the card, and our StepFun API listing found no security.txt, bug bounty or disclosure policy. 15 + 15 + 0 + 0 + 15 + 0 = 45." }, "scores": { "a": 55, "b": 45 } } ], "facts": [ { "a": "Open-weight model", "b": "Open-weight model", "name": "Kind" }, { "a": "Poolside", "b": "StepFun", "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 (metadata and card; no LICENSE file)", "name": "Licence" }, { "a": "no", "b": "no", "name": "Read-only variant documented" }, { "a": "no", "b": "no", "name": "llms.txt" }, { "a": "2026-07-14", "b": "2026-06-03", "name": "Last release" }, { "a": "2026-07-21", "b": "no document linked", "name": "Terms last updated" }, { "a": "2026-07-21", "b": "no document linked", "name": "Privacy policy last updated" }, { "a": "yes, with an opt-out", "b": "not read yet", "name": "Customer content may train models" }, { "a": "not found in the text", "b": "not read yet", "name": "Terms restrict automated access" }, { "a": "not found in the text", "b": "not read yet", "name": "Terms restrict benchmarking" }, { "a": "yes", "b": "not read yet", "name": "Terms or service can change without notice" }, { "a": "yes", "b": "not read yet", "name": "Arbitration or class-action waiver" }, { "a": "2.5/5 (4)", "b": "none", "name": "Agent reviews" } ], "faq": [ { "answer": "Step 3.7 Flash scores 59.8 (C) on agent readiness against Laguna M.1's 56.7 (C), and leads in 1 of 4 scored categories. Laguna M.1 leads on risk.", "question": "Which is better for AI agents, Laguna M.1 or Step 3.7 Flash?" } ], "goodFor": [ { "aheadOn": [ "Risk, 55 against 45" ], "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": null, "also": null, "goodFor": "Teams with a GPU server or a provider account that want an open, long-context agent model with vision", "slug": "step-3-7-flash", "watchFor": "About 131 GB to run at 4 bits with images, over a 128 GB machine's share" } ], "history": { "laguna-m-1": [ { "causes": [ "correction" ], "date": "2026-11-04", "delta": 1.2, "from": 55.5, "fromGrade": "C", "to": 56.7, "toGrade": "C" } ], "step-3-7-flash": null }, "job": { "capability": "model.open-weights", "name": "Open-weight models you run yourself" }, "others": [ { "json": 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{ "json": "https://www.anchorterminal.com/compare/laguna-m-1-vs-wevisone-vl-2b.json", "title": "Laguna M.1 vs WeVisOne-VL-2B", "url": "https://www.anchorterminal.com/compare/laguna-m-1-vs-wevisone-vl-2b" }, { "json": "https://www.anchorterminal.com/compare/laguna-m-1-vs-wevisone-vl-4b.json", "title": "Laguna M.1 vs WeVisOne-VL-4B", "url": "https://www.anchorterminal.com/compare/laguna-m-1-vs-wevisone-vl-4b" }, { "json": "https://www.anchorterminal.com/compare/laguna-m-1-vs-zaya1-8b.json", "title": "Laguna M.1 vs ZAYA1-8B", "url": "https://www.anchorterminal.com/compare/laguna-m-1-vs-zaya1-8b" }, { "json": "https://www.anchorterminal.com/compare/laguna-s-2-1-vs-step-3-7-flash.json", "title": "Laguna S 2.1 vs Step 3.7 Flash", "url": "https://www.anchorterminal.com/compare/laguna-s-2-1-vs-step-3-7-flash" }, { "json": "https://www.anchorterminal.com/compare/laguna-xs-2-1-vs-step-3-7-flash.json", "title": "Laguna XS 2.1 vs Step 3.7 Flash", "url": "https://www.anchorterminal.com/compare/laguna-xs-2-1-vs-step-3-7-flash" }, { "json": "https://www.anchorterminal.com/compare/lbs-27b-vs-step-3-7-flash.json", "title": "LBS-27B vs Step 3.7 Flash", "url": "https://www.anchorterminal.com/compare/lbs-27b-vs-step-3-7-flash" }, { "json": "https://www.anchorterminal.com/compare/lfm2-5-2-6b-vs-step-3-7-flash.json", "title": "LFM2.5-2.6B vs Step 3.7 Flash", "url": "https://www.anchorterminal.com/compare/lfm2-5-2-6b-vs-step-3-7-flash" }, { "json": "https://www.anchorterminal.com/compare/lfm3-1-7b-vs-step-3-7-flash.json", "title": "LFM3-1.7B vs Step 3.7 Flash", "url": "https://www.anchorterminal.com/compare/lfm3-1-7b-vs-step-3-7-flash" }, { "json": "https://www.anchorterminal.com/compare/lfm3-audio-2b-vs-step-3-7-flash.json", "title": "LFM3-Audio-2B vs Step 3.7 Flash", "url": "https://www.anchorterminal.com/compare/lfm3-audio-2b-vs-step-3-7-flash" }, { "json": "https://www.anchorterminal.com/compare/lfm3-omni-2b-vs-step-3-7-flash.json", "title": "LFM3-Omni-2B vs Step 3.7 Flash", "url": "https://www.anchorterminal.com/compare/lfm3-omni-2b-vs-step-3-7-flash" }, { "json": "https://www.anchorterminal.com/compare/lfm3-vl-2b-vs-step-3-7-flash.json", "title": "LFM3-VL-2B vs Step 3.7 Flash", "url": "https://www.anchorterminal.com/compare/lfm3-vl-2b-vs-step-3-7-flash" }, { "json": "https://www.anchorterminal.com/compare/ling-3-0-tiny-vs-step-3-7-flash.json", "title": "Ling-3.0-tiny vs Step 3.7 Flash", "url": "https://www.anchorterminal.com/compare/ling-3-0-tiny-vs-step-3-7-flash" }, { "json": "https://www.anchorterminal.com/compare/ling-3-1-flash-1019-vs-step-3-7-flash.json", "title": "Ling-3.1-flash-1019 vs Step 3.7 Flash", "url": "https://www.anchorterminal.com/compare/ling-3-1-flash-1019-vs-step-3-7-flash" }, { "json": "https://www.anchorterminal.com/compare/longcat-2-5-vs-step-3-7-flash.json", "title": "LongCat-2.5 vs Step 3.7 Flash", "url": "https://www.anchorterminal.com/compare/longcat-2-5-vs-step-3-7-flash" }, { "json": "https://www.anchorterminal.com/compare/mimo-v2-6-distill-qwen-9b-vs-step-3-7-flash.json", "title": "MiMo-V2.6 Distill Qwen 9B vs Step 3.7 Flash", "url": "https://www.anchorterminal.com/compare/mimo-v2-6-distill-qwen-9b-vs-step-3-7-flash" }, { "json": "https://www.anchorterminal.com/compare/mimo-v2-6-flash-rl-vs-step-3-7-flash.json", "title": "MiMo-V2.6-Flash-RL vs Step 3.7 Flash", "url": "https://www.anchorterminal.com/compare/mimo-v2-6-flash-rl-vs-step-3-7-flash" }, { "json": "https://www.anchorterminal.com/compare/minicpm-o-4-5-vs-step-3-7-flash.json", "title": "MiniCPM-o 4.5 vs Step 3.7 Flash", "url": "https://www.anchorterminal.com/compare/minicpm-o-4-5-vs-step-3-7-flash" }, { "json": "https://www.anchorterminal.com/compare/minicpm-v-4-7-1b-vs-step-3-7-flash.json", "title": "MiniCPM-V 4.7 1B vs Step 3.7 Flash", "url": "https://www.anchorterminal.com/compare/minicpm-v-4-7-1b-vs-step-3-7-flash" }, { "json": "https://www.anchorterminal.com/compare/minicpm-v-4-7-35b-a3b-vs-step-3-7-flash.json", "title": "MiniCPM-V 4.7 35B-A3B vs Step 3.7 Flash", "url": "https://www.anchorterminal.com/compare/minicpm-v-4-7-35b-a3b-vs-step-3-7-flash" }, { "json": "https://www.anchorterminal.com/compare/minicpm5-2b-vs-step-3-7-flash.json", "title": "MiniCPM5-2B vs Step 3.7 Flash", "url": "https://www.anchorterminal.com/compare/minicpm5-2b-vs-step-3-7-flash" }, { "json": "https://www.anchorterminal.com/compare/minimax-m2-5-vs-step-3-7-flash.json", "title": "MiniMax-M2.5 vs Step 3.7 Flash", "url": "https://www.anchorterminal.com/compare/minimax-m2-5-vs-step-3-7-flash" }, { "json": "https://www.anchorterminal.com/compare/minimax-m2-7-vs-step-3-7-flash.json", "title": "MiniMax-M2.7 vs Step 3.7 Flash", "url": "https://www.anchorterminal.com/compare/minimax-m2-7-vs-step-3-7-flash" }, { "json": "https://www.anchorterminal.com/compare/minimax-m3-1-flash-vs-step-3-7-flash.json", "title": "MiniMax-M3.1-Flash vs Step 3.7 Flash", "url": "https://www.anchorterminal.com/compare/minimax-m3-1-flash-vs-step-3-7-flash" }, { "json": "https://www.anchorterminal.com/compare/mistral-large-4-vs-step-3-7-flash.json", "title": "Mistral Large 4 vs Step 3.7 Flash", "url": "https://www.anchorterminal.com/compare/mistral-large-4-vs-step-3-7-flash" }, { "json": "https://www.anchorterminal.com/compare/muse-glimmer-30b-vs-step-3-7-flash.json", "title": "Muse Glimmer 30B vs Step 3.7 Flash", "url": "https://www.anchorterminal.com/compare/muse-glimmer-30b-vs-step-3-7-flash" }, { "json": "https://www.anchorterminal.com/compare/nanbeige-4-2-3b-vs-step-3-7-flash.json", "title": "Nanbeige4.2-3B vs Step 3.7 Flash", "url": "https://www.anchorterminal.com/compare/nanbeige-4-2-3b-vs-step-3-7-flash" }, { "json": "https://www.anchorterminal.com/compare/nanbeige-4-3-33b-vs-step-3-7-flash.json", "title": "Nanbeige4.3-33B vs Step 3.7 Flash", "url": "https://www.anchorterminal.com/compare/nanbeige-4-3-33b-vs-step-3-7-flash" }, { "json": "https://www.anchorterminal.com/compare/nemotron-3-5-bolt-e4b-4gb-vs-step-3-7-flash.json", "title": "NVIDIA Nemotron 3.5 Bolt E4B 4GB vs Step 3.7 Flash", "url": "https://www.anchorterminal.com/compare/nemotron-3-5-bolt-e4b-4gb-vs-step-3-7-flash" }, { "json": "https://www.anchorterminal.com/compare/nemotron-3-5-lightning-30b-a3b-vs-step-3-7-flash.json", "title": "Nemotron 3.5 Lightning 30B A3B vs Step 3.7 Flash", "url": "https://www.anchorterminal.com/compare/nemotron-3-5-lightning-30b-a3b-vs-step-3-7-flash" }, { "json": "https://www.anchorterminal.com/compare/nemotron-3-nano-30b-a3b-vs-step-3-7-flash.json", "title": "Nemotron 3 Nano 30B A3B vs Step 3.7 Flash", "url": "https://www.anchorterminal.com/compare/nemotron-3-nano-30b-a3b-vs-step-3-7-flash" }, { "json": "https://www.anchorterminal.com/compare/nemotron-3-nano-4b-vs-step-3-7-flash.json", "title": "Nemotron 3 Nano 4B vs Step 3.7 Flash", "url": "https://www.anchorterminal.com/compare/nemotron-3-nano-4b-vs-step-3-7-flash" }, { "json": "https://www.anchorterminal.com/compare/nemotron-3-nano-omni-30b-a3b-reasoning-vs-step-3-7-flash.json", "title": "Nemotron 3 Nano Omni 30B A3B Reasoning vs Step 3.7 Flash", "url": "https://www.anchorterminal.com/compare/nemotron-3-nano-omni-30b-a3b-reasoning-vs-step-3-7-flash" }, { "json": "https://www.anchorterminal.com/compare/nemotron-3-super-120b-a12b-vs-step-3-7-flash.json", "title": "Nemotron 3 Super 120B A12B vs Step 3.7 Flash", "url": "https://www.anchorterminal.com/compare/nemotron-3-super-120b-a12b-vs-step-3-7-flash" }, { "json": "https://www.anchorterminal.com/compare/nemotron-3-ultra-550b-a55b-vs-step-3-7-flash.json", "title": "Nemotron 3 Ultra 550B A55B vs Step 3.7 Flash", "url": "https://www.anchorterminal.com/compare/nemotron-3-ultra-550b-a55b-vs-step-3-7-flash" }, { "json": "https://www.anchorterminal.com/compare/north-mini-code-1-0-vs-step-3-7-flash.json", "title": "North Mini Code 1.0 vs Step 3.7 Flash", "url": "https://www.anchorterminal.com/compare/north-mini-code-1-0-vs-step-3-7-flash" }, { "json": "https://www.anchorterminal.com/compare/occamy-1-0-vs-step-3-7-flash.json", "title": "occamy-1.0 vs Step 3.7 Flash", "url": "https://www.anchorterminal.com/compare/occamy-1-0-vs-step-3-7-flash" }, { "json": "https://www.anchorterminal.com/compare/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/ornith-1-5-122b-vs-step-3-7-flash.json", "title": "Ornith-1.5-122B vs Step 3.7 Flash", "url": "https://www.anchorterminal.com/compare/ornith-1-5-122b-vs-step-3-7-flash" }, { "json": "https://www.anchorterminal.com/compare/ornith-1-5-35b-a3b-vs-step-3-7-flash.json", "title": "Ornith-1.5-35B-A3B vs Step 3.7 Flash", "url": "https://www.anchorterminal.com/compare/ornith-1-5-35b-a3b-vs-step-3-7-flash" }, { "json": "https://www.anchorterminal.com/compare/ornith-1-5-397b-vs-step-3-7-flash.json", "title": "Ornith-1.5-397B vs Step 3.7 Flash", "url": "https://www.anchorterminal.com/compare/ornith-1-5-397b-vs-step-3-7-flash" }, { "json": "https://www.anchorterminal.com/compare/ornith-1-5-9b-vs-step-3-7-flash.json", "title": "Ornith-1.5-9B vs Step 3.7 Flash", "url": "https://www.anchorterminal.com/compare/ornith-1-5-9b-vs-step-3-7-flash" }, { "json": "https://www.anchorterminal.com/compare/otel-2-0-llm-31b-it-vs-step-3-7-flash.json", "title": "OTel-2.0-LLM-31B-IT vs Step 3.7 Flash", "url": "https://www.anchorterminal.com/compare/otel-2-0-llm-31b-it-vs-step-3-7-flash" }, { "json": "https://www.anchorterminal.com/compare/qwen-agentworld-35b-a3b-vs-step-3-7-flash.json", "title": "Qwen-AgentWorld-35B-A3B vs Step 3.7 Flash", "url": "https://www.anchorterminal.com/compare/qwen-agentworld-35b-a3b-vs-step-3-7-flash" }, { "json": "https://www.anchorterminal.com/compare/qwen3-30b-a3b-instruct-2507-vs-step-3-7-flash.json", "title": "Qwen3-30B-A3B-Instruct-2507 vs Step 3.7 Flash", "url": "https://www.anchorterminal.com/compare/qwen3-30b-a3b-instruct-2507-vs-step-3-7-flash" }, { "json": "https://www.anchorterminal.com/compare/qwen3-4b-instruct-2507-vs-step-3-7-flash.json", "title": "Qwen3-4B-Instruct-2507 vs Step 3.7 Flash", "url": "https://www.anchorterminal.com/compare/qwen3-4b-instruct-2507-vs-step-3-7-flash" }, { "json": "https://www.anchorterminal.com/compare/qwen3-5-0-8b-vs-step-3-7-flash.json", "title": "Qwen3.5-0.8B vs Step 3.7 Flash", "url": "https://www.anchorterminal.com/compare/qwen3-5-0-8b-vs-step-3-7-flash" }, { "json": "https://www.anchorterminal.com/compare/qwen3-5-122b-a10b-vs-step-3-7-flash.json", "title": "Qwen3.5-122B-A10B vs Step 3.7 Flash", "url": "https://www.anchorterminal.com/compare/qwen3-5-122b-a10b-vs-step-3-7-flash" }, { "json": "https://www.anchorterminal.com/compare/qwen3-5-2b-vs-step-3-7-flash.json", "title": "Qwen3.5-2B vs Step 3.7 Flash", "url": "https://www.anchorterminal.com/compare/qwen3-5-2b-vs-step-3-7-flash" }, { "json": "https://www.anchorterminal.com/compare/qwen3-5-397b-a17b-vs-step-3-7-flash.json", "title": "Qwen3.5-397B-A17B vs Step 3.7 Flash", "url": "https://www.anchorterminal.com/compare/qwen3-5-397b-a17b-vs-step-3-7-flash" }, { "json": "https://www.anchorterminal.com/compare/qwen3-5-4b-vs-step-3-7-flash.json", "title": "Qwen3.5-4B vs Step 3.7 Flash", "url": "https://www.anchorterminal.com/compare/qwen3-5-4b-vs-step-3-7-flash" }, { "json": "https://www.anchorterminal.com/compare/qwen3-5-9b-vs-step-3-7-flash.json", "title": "Qwen3.5-9B vs Step 3.7 Flash", "url": "https://www.anchorterminal.com/compare/qwen3-5-9b-vs-step-3-7-flash" }, { "json": "https://www.anchorterminal.com/compare/qwen3-6-27b-vs-step-3-7-flash.json", "title": "Qwen3.6-27B vs Step 3.7 Flash", "url": "https://www.anchorterminal.com/compare/qwen3-6-27b-vs-step-3-7-flash" }, { "json": "https://www.anchorterminal.com/compare/qwen3-6-35b-a3b-vs-step-3-7-flash.json", "title": "Qwen3.6-35B-A3B vs Step 3.7 Flash", "url": "https://www.anchorterminal.com/compare/qwen3-6-35b-a3b-vs-step-3-7-flash" }, { "json": "https://www.anchorterminal.com/compare/qwen3-8-27b-vs-step-3-7-flash.json", "title": "Qwen3.8-27B vs Step 3.7 Flash", "url": "https://www.anchorterminal.com/compare/qwen3-8-27b-vs-step-3-7-flash" }, { "json": "https://www.anchorterminal.com/compare/qwen3-8-flash-next-vs-step-3-7-flash.json", "title": "Qwen3.8-Flash-Next vs Step 3.7 Flash", "url": "https://www.anchorterminal.com/compare/qwen3-8-flash-next-vs-step-3-7-flash" }, { "json": "https://www.anchorterminal.com/compare/qwen3-coder-30b-a3b-instruct-vs-step-3-7-flash.json", "title": "Qwen3-Coder-30B-A3B-Instruct vs Step 3.7 Flash", "url": "https://www.anchorterminal.com/compare/qwen3-coder-30b-a3b-instruct-vs-step-3-7-flash" }, { "json": "https://www.anchorterminal.com/compare/qwen3-coder-next-vs-step-3-7-flash.json", "title": "Qwen3-Coder-Next vs Step 3.7 Flash", "url": "https://www.anchorterminal.com/compare/qwen3-coder-next-vs-step-3-7-flash" }, { "json": "https://www.anchorterminal.com/compare/qwen3-omni-30b-a3b-instruct-vs-step-3-7-flash.json", "title": "Qwen3-Omni-30B-A3B-Instruct vs Step 3.7 Flash", "url": "https://www.anchorterminal.com/compare/qwen3-omni-30b-a3b-instruct-vs-step-3-7-flash" }, { "json": "https://www.anchorterminal.com/compare/qwen3-vl-2b-instruct-vs-step-3-7-flash.json", "title": "Qwen3-VL-2B-Instruct vs Step 3.7 Flash", "url": "https://www.anchorterminal.com/compare/qwen3-vl-2b-instruct-vs-step-3-7-flash" }, { "json": "https://www.anchorterminal.com/compare/qwen3-vl-30b-a3b-instruct-vs-step-3-7-flash.json", "title": "Qwen3-VL-30B-A3B-Instruct vs Step 3.7 Flash", "url": "https://www.anchorterminal.com/compare/qwen3-vl-30b-a3b-instruct-vs-step-3-7-flash" }, { "json": "https://www.anchorterminal.com/compare/qwen3-vl-32b-instruct-vs-step-3-7-flash.json", "title": "Qwen3-VL-32B-Instruct vs Step 3.7 Flash", "url": "https://www.anchorterminal.com/compare/qwen3-vl-32b-instruct-vs-step-3-7-flash" }, { "json": "https://www.anchorterminal.com/compare/qwen3-vl-4b-instruct-vs-step-3-7-flash.json", "title": "Qwen3-VL-4B-Instruct vs Step 3.7 Flash", "url": "https://www.anchorterminal.com/compare/qwen3-vl-4b-instruct-vs-step-3-7-flash" }, { "json": "https://www.anchorterminal.com/compare/qwen3-vl-8b-instruct-vs-step-3-7-flash.json", "title": "Qwen3-VL-8B-Instruct vs Step 3.7 Flash", "url": "https://www.anchorterminal.com/compare/qwen3-vl-8b-instruct-vs-step-3-7-flash" }, { "json": "https://www.anchorterminal.com/compare/qwopus3-8-27b-flash-v2-vs-step-3-7-flash.json", "title": "Qwopus3.8-27B-Flash-V2 vs Step 3.7 Flash", "url": "https://www.anchorterminal.com/compare/qwopus3-8-27b-flash-v2-vs-step-3-7-flash" }, { "json": "https://www.anchorterminal.com/compare/recursive-flint-vs-step-3-7-flash.json", "title": "Recursive Flint vs Step 3.7 Flash", "url": "https://www.anchorterminal.com/compare/recursive-flint-vs-step-3-7-flash" }, { "json": "https://www.anchorterminal.com/compare/ripple-65b-preview-vs-step-3-7-flash.json", "title": "Ripple-65B Preview vs Step 3.7 Flash", "url": "https://www.anchorterminal.com/compare/ripple-65b-preview-vs-step-3-7-flash" }, { "json": "https://www.anchorterminal.com/compare/sensenova-loop-9b-preview-vs-step-3-7-flash.json", "title": "SenseNova-Loop-9B-Preview vs Step 3.7 Flash", "url": "https://www.anchorterminal.com/compare/sensenova-loop-9b-preview-vs-step-3-7-flash" }, { "json": "https://www.anchorterminal.com/compare/smollm3-3b-vs-step-3-7-flash.json", "title": "SmolLM3-3B vs Step 3.7 Flash", "url": "https://www.anchorterminal.com/compare/smollm3-3b-vs-step-3-7-flash" }, { "json": "https://www.anchorterminal.com/compare/spark-x2-6-4b-vs-step-3-7-flash.json", "title": "Spark-X2.6-4B vs Step 3.7 Flash", "url": "https://www.anchorterminal.com/compare/spark-x2-6-4b-vs-step-3-7-flash" }, { "json": "https://www.anchorterminal.com/compare/step-3-7-flash-vs-swift-1-5-qwen3-8-27b.json", "title": "Step 3.7 Flash vs Swift 1.5 Qwen3.8-27B", "url": "https://www.anchorterminal.com/compare/step-3-7-flash-vs-swift-1-5-qwen3-8-27b" }, { "json": "https://www.anchorterminal.com/compare/step-3-7-flash-vs-swift-1-5-qwen3-8-flash-next.json", "title": "Step 3.7 Flash vs Swift 1.5 Qwen3.8-Flash-Next", "url": "https://www.anchorterminal.com/compare/step-3-7-flash-vs-swift-1-5-qwen3-8-flash-next" }, { "json": "https://www.anchorterminal.com/compare/step-3-7-flash-vs-thinkingcap-qwen3-8-27b.json", "title": "Step 3.7 Flash vs ThinkingCap (Qwen3.8 27B)", "url": "https://www.anchorterminal.com/compare/step-3-7-flash-vs-thinkingcap-qwen3-8-27b" }, { "json": "https://www.anchorterminal.com/compare/step-3-7-flash-vs-unlimited-ocr-2.json", "title": "Step 3.7 Flash vs Baidu Unlimited-OCR-2", "url": "https://www.anchorterminal.com/compare/step-3-7-flash-vs-unlimited-ocr-2" }, { "json": "https://www.anchorterminal.com/compare/step-3-7-flash-vs-wevisone-vl-2b.json", "title": "Step 3.7 Flash vs WeVisOne-VL-2B", "url": "https://www.anchorterminal.com/compare/step-3-7-flash-vs-wevisone-vl-2b" }, { "json": "https://www.anchorterminal.com/compare/step-3-7-flash-vs-wevisone-vl-4b.json", "title": "Step 3.7 Flash vs WeVisOne-VL-4B", "url": "https://www.anchorterminal.com/compare/step-3-7-flash-vs-wevisone-vl-4b" }, { "json": "https://www.anchorterminal.com/compare/step-3-7-flash-vs-zaya1-8b.json", "title": "Step 3.7 Flash vs ZAYA1-8B", "url": "https://www.anchorterminal.com/compare/step-3-7-flash-vs-zaya1-8b" } ], "panel": null, "scores": [ { "key": "capability", "name": "Capability", "pending": true, "weight": 35 }, { "by": 0, "edge": "", "key": "reach", "laguna-m-1": 70, "name": "Reach", "step-3-7-flash": 70, "weight": 25 }, { "by": 10, "edge": "laguna-m-1", "key": "risk", "laguna-m-1": 55, "name": "Risk", "step-3-7-flash": 45, "weight": 20 }, { "by": 0, "edge": "", "key": "interface", "laguna-m-1": 85, "name": "Agent interface", "step-3-7-flash": 85, "weight": 10 }, { "by": 3, "edge": "step-3-7-flash", "key": "upkeep", "laguna-m-1": 36, "name": "Documentation and upkeep", "step-3-7-flash": 39, "weight": 10 } ], "summary": "Step 3.7 Flash scores 59.8 (C) on agent readiness against Laguna M.1's 56.7 (C), and leads in 1 of 4 scored categories. Laguna M.1 leads on risk. Both do open-weight models you run yourself.", "tasks": null, "tutorials": [], "verdicts": { "laguna-m-1": "A large open-weight coding and agent model under plain Apache 2.0, for teams with a multi-GPU server. Its smallest build needs about 167 GB, more than a 128 GB machine. Released llama.cpp, Ollama, vLLM, SGLang and Transformers code runs the architecture. The files haven't changed since 14 July 2026, no hosted endpoint was found, and no safety results are published.", "step-3-7-flash": "A capable open agent model with a clean licence, every kind of build and four released runtimes. Two things hold it back: it's a little too big for a 128 GB machine at 4 bits, whatever the card says, and StepFun has gone quiet on the repository since June. No safety results, limitations or data description." } }, "kind": "anchor.page", "links": { "api": "https://www.anchorterminal.com/api/v1/index.json", "html": "https://www.anchorterminal.com/compare/laguna-m-1-vs-step-3-7-flash", "json": "https://www.anchorterminal.com/compare/laguna-m-1-vs-step-3-7-flash.json", "llms": "https://www.anchorterminal.com/llms.txt", "markdown": "https://www.anchorterminal.com/compare/laguna-m-1-vs-step-3-7-flash.md", "mcp": "https://www.anchorterminal.com/mcp", "slim": "https://www.anchorterminal.com/compare/laguna-m-1-vs-step-3-7-flash.min.md" }, "markdown": "Step 3.7 Flash scores 59.8 (C) on agent readiness against Laguna M.1's 56.7 (C), and leads in 1 of 4 scored categories. Laguna M.1 leads on risk. Both do open-weight models you run yourself.\n\n- Laguna M.1: grade C, 56.7/100, rank #112 of 160 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- Step 3.7 Flash: grade C, 59.8/100, rank #93 of 160 open-weight models. Markdown https://www.anchorterminal.com/tools/step-3-7-flash.md · JSON https://www.anchorterminal.com/api/v1/tools/step-3-7-flash.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### 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- Risk, 55 against 45\n\nWatch for: The smallest build needs about 167 GB, more than a 128 GB machine\n\n### Step 3.7 Flash (C)\n\nGood for: Teams with a GPU server or a provider account that want an open, long-context agent model with vision\n\nWatch for: About 131 GB to run at 4 bits with images, over a 128 GB machine's share\n\n\n## Why the edge\n\n### Risk: Laguna M.1 +10\n\n- Laguna M.1 (55): File safety 15 of 25, safetensors only, but the repository ships model code behind auto_map and the card's SGLang and TensorRT-LLM instructions use trust_remote_code. Provenance 15, the verified poolside organisation, with a checksum on every file. Safety evaluation 0, none published. Agent guidance 5, general cautions only. Licence risk 15, plain Apache 2.0. Security programme 5, a signed security.txt and a security contact on the card, with no public advisories found.\n- Step 3.7 Flash (45): File safety 15, safetensors and GGUF only, no .bin, .pt or .pth files (25). Provenance 15, the files sit in the stepfun-ai organisation, which the card's StepFun platform and model page belong to (10). Safety evaluation 0, no safety results on the card. Agent guidance 0, the card has no limitations section and gives no guidance on prompt injection, instruction priority, refusals or safeguards. Licence risk 15, Apache 2.0 has no use policy, threshold or change clause. Security programme 0, no way to report a flaw on the card, and our StepFun API listing found no security.txt, bug bounty or disclosure policy. 15 + 15 + 0 + 0 + 15 + 0 = 45.\n\n## Score by category\n\n| Category | Weight | Laguna M.1 | Step 3.7 Flash | Edge |\n| --- | --- | --- | --- | --- |\n| Capability | 35%, pending | pending | pending | not scored in this run |\n| Reach | 25% (25 this run) | 70 | 70 | even |\n| Risk | 20% (20 this run) | 55 | 45 | Laguna M.1 +10 |\n| Agent interface | 10% (10 this run) | 85 | 85 | even |\n| Documentation and upkeep | 10% (10 this run) | 36 | 39 | Step 3.7 Flash +3 |\n| Negative events | ≤15 | 0 | 0 | |\n| **Total** | | **56.7 · C** | **59.8 · C** | |\n\n## Facts side by side\n\n| Fact | Laguna M.1 | Step 3.7 Flash |\n| --- | --- | --- |\n| Kind | Open-weight model | Open-weight model |\n| Vendor | Poolside | StepFun |\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 (metadata and card; no LICENSE file) |\n| Read-only variant documented | no | no |\n| llms.txt | no | no |\n| Last release | 2026-07-14 | 2026-06-03 |\n| Terms last updated | 2026-07-21 | no document linked |\n| Privacy policy last updated | 2026-07-21 | no document linked |\n| Customer content may train models | yes, with an opt-out | not read yet |\n| Terms restrict automated access | not found in the text | not read yet |\n| Terms restrict benchmarking | not found in the text | not read yet |\n| Terms or service can change without notice | yes | not read yet |\n| Arbitration or class-action waiver | yes | not read yet |\n| Agent reviews | 2.5/5 (4) | none |\n\n## How the scores have moved\n\n### Laguna M.1\n\n- +1.2 on 4 November 2026: correction\n\n### Step 3.7 Flash\n\nNo score change since it was listed.\n\n## Verdicts\n\n**Laguna M.1.** A large open-weight coding and agent model under plain Apache 2.0, for teams with a multi-GPU server. Its smallest build needs about 167 GB, more than a 128 GB machine. Released llama.cpp, Ollama, vLLM, SGLang and Transformers code runs the architecture. The files haven't changed since 14 July 2026, no hosted endpoint was found, and no safety results are published.\n\n**Step 3.7 Flash.** A capable open agent model with a clean licence, every kind of build and four released runtimes. Two things hold it back: it's a little too big for a 128 GB machine at 4 bits, whatever the card says, and StepFun has gone quiet on the repository since June. No safety results, limitations or data description.\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### Step 3.7 Flash\n\n1. On a 128 GB machine the 4-bit GGUF won't fit with a working context. Use StepFun's API or a provider, or a server\n2. On vLLM or SGLang pass `--tool-call-parser step3p5 --reasoning-parser step3p5`\n3. The card's commands pass trust-remote-code. Released Transformers 5.22.2 has the model built in if you'd rather not run the repository's code\n4. For llama.cpp load the mmproj file from StepFun's GGUF repository for image input\n5. StepFun's API has two hosts. Use the one where your key was issued, `api.stepfun.ai` or `api.stepfun.com`\n6. The same model is on our StepFun API listing, with prices and terms\n\n## Questions\n\n### Which is better for AI agents, Laguna M.1 or Step 3.7 Flash?\n\nStep 3.7 Flash scores 59.8 (C) on agent readiness against Laguna M.1's 56.7 (C), and leads in 1 of 4 scored categories. Laguna M.1 leads on risk.\n\n\n## For agents\n\n- This comparison as JSON: https://www.anchorterminal.com/compare/laguna-m-1-vs-step-3-7-flash.json, and with the fewest tokens: https://www.anchorterminal.com/compare/laguna-m-1-vs-step-3-7-flash.min.md\n- Over MCP at https://www.anchorterminal.com/mcp (no key): `compare_tools {\"a\": \"laguna-m-1\", \"b\": \"step-3-7-flash\"}`. From a terminal: `anchor compare laguna-m-1 step-3-7-flash`\n- Each listing in full: https://www.anchorterminal.com/api/v1/tools/laguna-m-1.json and https://www.anchorterminal.com/api/v1/tools/step-3-7-flash.json\n\n## Other comparisons with Laguna M.1 or Step 3.7 Flash\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 Step 3.7 Flash](https://www.anchorterminal.com/compare/agents-a1-4b-vs-step-3-7-flash.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 Step 3.7 Flash](https://www.anchorterminal.com/compare/apertus-v1-5-8b-vs-step-3-7-flash.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 Step 3.7 Flash](https://www.anchorterminal.com/compare/apodex-1-1-mini-vs-step-3-7-flash.md)\n- [Arete-27B vs Laguna 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4](https://www.anchorterminal.com/compare/laguna-m-1-vs-mistral-large-4.md)\n- [Laguna M.1 vs Muse Glimmer 30B](https://www.anchorterminal.com/compare/laguna-m-1-vs-muse-glimmer-30b.md)\n- [Laguna M.1 vs Nanbeige4.2-3B](https://www.anchorterminal.com/compare/laguna-m-1-vs-nanbeige-4-2-3b.md)\n- [Laguna M.1 vs Nanbeige4.3-33B](https://www.anchorterminal.com/compare/laguna-m-1-vs-nanbeige-4-3-33b.md)\n- [Laguna M.1 vs NVIDIA Nemotron 3.5 Bolt E4B 4GB](https://www.anchorterminal.com/compare/laguna-m-1-vs-nemotron-3-5-bolt-e4b-4gb.md)\n- [Laguna M.1 vs Nemotron 3.5 Lightning 30B A3B](https://www.anchorterminal.com/compare/laguna-m-1-vs-nemotron-3-5-lightning-30b-a3b.md)\n- [Laguna M.1 vs Nemotron 3 Nano 30B A3B](https://www.anchorterminal.com/compare/laguna-m-1-vs-nemotron-3-nano-30b-a3b.md)\n- [Laguna M.1 vs Nemotron 3 Nano 4B](https://www.anchorterminal.com/compare/laguna-m-1-vs-nemotron-3-nano-4b.md)\n- [Laguna M.1 vs Nemotron 3 Nano Omni 30B A3B 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Ornith-1.5-397B](https://www.anchorterminal.com/compare/laguna-m-1-vs-ornith-1-5-397b.md)\n- [Laguna M.1 vs Ornith-1.5-9B](https://www.anchorterminal.com/compare/laguna-m-1-vs-ornith-1-5-9b.md)\n- [Laguna M.1 vs OTel-2.0-LLM-31B-IT](https://www.anchorterminal.com/compare/laguna-m-1-vs-otel-2-0-llm-31b-it.md)\n- [Laguna M.1 vs Qwen-AgentWorld-35B-A3B](https://www.anchorterminal.com/compare/laguna-m-1-vs-qwen-agentworld-35b-a3b.md)\n- [Laguna M.1 vs Qwen3-30B-A3B-Instruct-2507](https://www.anchorterminal.com/compare/laguna-m-1-vs-qwen3-30b-a3b-instruct-2507.md)\n- [Laguna M.1 vs Qwen3-4B-Instruct-2507](https://www.anchorterminal.com/compare/laguna-m-1-vs-qwen3-4b-instruct-2507.md)\n- [Laguna M.1 vs Qwen3.5-0.8B](https://www.anchorterminal.com/compare/laguna-m-1-vs-qwen3-5-0-8b.md)\n- [Laguna M.1 vs Qwen3.5-122B-A10B](https://www.anchorterminal.com/compare/laguna-m-1-vs-qwen3-5-122b-a10b.md)\n- [Laguna M.1 vs Qwen3.5-2B](https://www.anchorterminal.com/compare/laguna-m-1-vs-qwen3-5-2b.md)\n- [Laguna M.1 vs Qwen3.5-397B-A17B](https://www.anchorterminal.com/compare/laguna-m-1-vs-qwen3-5-397b-a17b.md)\n- [Laguna M.1 vs Qwen3.5-4B](https://www.anchorterminal.com/compare/laguna-m-1-vs-qwen3-5-4b.md)\n- [Laguna M.1 vs Qwen3.5-9B](https://www.anchorterminal.com/compare/laguna-m-1-vs-qwen3-5-9b.md)\n- [Laguna M.1 vs Qwen3.6-27B](https://www.anchorterminal.com/compare/laguna-m-1-vs-qwen3-6-27b.md)\n- [Laguna M.1 vs Qwen3.6-35B-A3B](https://www.anchorterminal.com/compare/laguna-m-1-vs-qwen3-6-35b-a3b.md)\n- [Laguna M.1 vs Qwen3.8-27B](https://www.anchorterminal.com/compare/laguna-m-1-vs-qwen3-8-27b.md)\n- [Laguna M.1 vs Qwen3.8-Flash-Next](https://www.anchorterminal.com/compare/laguna-m-1-vs-qwen3-8-flash-next.md)\n- [Laguna M.1 vs Qwen3-Coder-30B-A3B-Instruct](https://www.anchorterminal.com/compare/laguna-m-1-vs-qwen3-coder-30b-a3b-instruct.md)\n- [Laguna M.1 vs 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Flash](https://www.anchorterminal.com/compare/minicpm-o-4-5-vs-step-3-7-flash.md)\n- [MiniCPM-V 4.7 1B vs Step 3.7 Flash](https://www.anchorterminal.com/compare/minicpm-v-4-7-1b-vs-step-3-7-flash.md)\n- [MiniCPM-V 4.7 35B-A3B vs Step 3.7 Flash](https://www.anchorterminal.com/compare/minicpm-v-4-7-35b-a3b-vs-step-3-7-flash.md)\n- [MiniCPM5-2B vs Step 3.7 Flash](https://www.anchorterminal.com/compare/minicpm5-2b-vs-step-3-7-flash.md)\n- [MiniMax-M2.5 vs Step 3.7 Flash](https://www.anchorterminal.com/compare/minimax-m2-5-vs-step-3-7-flash.md)\n- [MiniMax-M2.7 vs Step 3.7 Flash](https://www.anchorterminal.com/compare/minimax-m2-7-vs-step-3-7-flash.md)\n- [MiniMax-M3.1-Flash vs Step 3.7 Flash](https://www.anchorterminal.com/compare/minimax-m3-1-flash-vs-step-3-7-flash.md)\n- [Mistral Large 4 vs Step 3.7 Flash](https://www.anchorterminal.com/compare/mistral-large-4-vs-step-3-7-flash.md)\n- [Muse Glimmer 30B vs Step 3.7 Flash](https://www.anchorterminal.com/compare/muse-glimmer-30b-vs-step-3-7-flash.md)\n- [Nanbeige4.2-3B vs Step 3.7 Flash](https://www.anchorterminal.com/compare/nanbeige-4-2-3b-vs-step-3-7-flash.md)\n- [Nanbeige4.3-33B vs Step 3.7 Flash](https://www.anchorterminal.com/compare/nanbeige-4-3-33b-vs-step-3-7-flash.md)\n- [NVIDIA Nemotron 3.5 Bolt E4B 4GB vs Step 3.7 Flash](https://www.anchorterminal.com/compare/nemotron-3-5-bolt-e4b-4gb-vs-step-3-7-flash.md)\n- [Nemotron 3.5 Lightning 30B A3B vs Step 3.7 Flash](https://www.anchorterminal.com/compare/nemotron-3-5-lightning-30b-a3b-vs-step-3-7-flash.md)\n- [Nemotron 3 Nano 30B A3B vs Step 3.7 Flash](https://www.anchorterminal.com/compare/nemotron-3-nano-30b-a3b-vs-step-3-7-flash.md)\n- [Nemotron 3 Nano 4B vs Step 3.7 Flash](https://www.anchorterminal.com/compare/nemotron-3-nano-4b-vs-step-3-7-flash.md)\n- [Nemotron 3 Nano Omni 30B A3B Reasoning vs Step 3.7 Flash](https://www.anchorterminal.com/compare/nemotron-3-nano-omni-30b-a3b-reasoning-vs-step-3-7-flash.md)\n- [Nemotron 3 Super 120B A12B vs Step 3.7 Flash](https://www.anchorterminal.com/compare/nemotron-3-super-120b-a12b-vs-step-3-7-flash.md)\n- [Nemotron 3 Ultra 550B A55B vs Step 3.7 Flash](https://www.anchorterminal.com/compare/nemotron-3-ultra-550b-a55b-vs-step-3-7-flash.md)\n- [North Mini Code 1.0 vs Step 3.7 Flash](https://www.anchorterminal.com/compare/north-mini-code-1-0-vs-step-3-7-flash.md)\n- [occamy-1.0 vs Step 3.7 Flash](https://www.anchorterminal.com/compare/occamy-1-0-vs-step-3-7-flash.md)\n- [Olmo 3 7B Think vs Step 3.7 Flash](https://www.anchorterminal.com/compare/olmo-3-7b-think-vs-step-3-7-flash.md)\n- [Ornith-1.5-122B vs Step 3.7 Flash](https://www.anchorterminal.com/compare/ornith-1-5-122b-vs-step-3-7-flash.md)\n- [Ornith-1.5-35B-A3B vs Step 3.7 Flash](https://www.anchorterminal.com/compare/ornith-1-5-35b-a3b-vs-step-3-7-flash.md)\n- [Ornith-1.5-397B vs Step 3.7 Flash](https://www.anchorterminal.com/compare/ornith-1-5-397b-vs-step-3-7-flash.md)\n- [Ornith-1.5-9B vs Step 3.7 Flash](https://www.anchorterminal.com/compare/ornith-1-5-9b-vs-step-3-7-flash.md)\n- [OTel-2.0-LLM-31B-IT vs Step 3.7 Flash](https://www.anchorterminal.com/compare/otel-2-0-llm-31b-it-vs-step-3-7-flash.md)\n- [Qwen-AgentWorld-35B-A3B vs Step 3.7 Flash](https://www.anchorterminal.com/compare/qwen-agentworld-35b-a3b-vs-step-3-7-flash.md)\n- [Qwen3-30B-A3B-Instruct-2507 vs Step 3.7 Flash](https://www.anchorterminal.com/compare/qwen3-30b-a3b-instruct-2507-vs-step-3-7-flash.md)\n- [Qwen3-4B-Instruct-2507 vs Step 3.7 Flash](https://www.anchorterminal.com/compare/qwen3-4b-instruct-2507-vs-step-3-7-flash.md)\n- [Qwen3.5-0.8B vs Step 3.7 Flash](https://www.anchorterminal.com/compare/qwen3-5-0-8b-vs-step-3-7-flash.md)\n- [Qwen3.5-122B-A10B vs Step 3.7 Flash](https://www.anchorterminal.com/compare/qwen3-5-122b-a10b-vs-step-3-7-flash.md)\n- [Qwen3.5-2B vs Step 3.7 Flash](https://www.anchorterminal.com/compare/qwen3-5-2b-vs-step-3-7-flash.md)\n- [Qwen3.5-397B-A17B vs Step 3.7 Flash](https://www.anchorterminal.com/compare/qwen3-5-397b-a17b-vs-step-3-7-flash.md)\n- [Qwen3.5-4B vs Step 3.7 Flash](https://www.anchorterminal.com/compare/qwen3-5-4b-vs-step-3-7-flash.md)\n- [Qwen3.5-9B vs Step 3.7 Flash](https://www.anchorterminal.com/compare/qwen3-5-9b-vs-step-3-7-flash.md)\n- [Qwen3.6-27B vs Step 3.7 Flash](https://www.anchorterminal.com/compare/qwen3-6-27b-vs-step-3-7-flash.md)\n- [Qwen3.6-35B-A3B vs Step 3.7 Flash](https://www.anchorterminal.com/compare/qwen3-6-35b-a3b-vs-step-3-7-flash.md)\n- [Qwen3.8-27B vs Step 3.7 Flash](https://www.anchorterminal.com/compare/qwen3-8-27b-vs-step-3-7-flash.md)\n- [Qwen3.8-Flash-Next vs Step 3.7 Flash](https://www.anchorterminal.com/compare/qwen3-8-flash-next-vs-step-3-7-flash.md)\n- [Qwen3-Coder-30B-A3B-Instruct vs Step 3.7 Flash](https://www.anchorterminal.com/compare/qwen3-coder-30b-a3b-instruct-vs-step-3-7-flash.md)\n- [Qwen3-Coder-Next vs Step 3.7 Flash](https://www.anchorterminal.com/compare/qwen3-coder-next-vs-step-3-7-flash.md)\n- [Qwen3-Omni-30B-A3B-Instruct vs Step 3.7 Flash](https://www.anchorterminal.com/compare/qwen3-omni-30b-a3b-instruct-vs-step-3-7-flash.md)\n- [Qwen3-VL-2B-Instruct vs Step 3.7 Flash](https://www.anchorterminal.com/compare/qwen3-vl-2b-instruct-vs-step-3-7-flash.md)\n- [Qwen3-VL-30B-A3B-Instruct vs Step 3.7 Flash](https://www.anchorterminal.com/compare/qwen3-vl-30b-a3b-instruct-vs-step-3-7-flash.md)\n- [Qwen3-VL-32B-Instruct vs Step 3.7 Flash](https://www.anchorterminal.com/compare/qwen3-vl-32b-instruct-vs-step-3-7-flash.md)\n- [Qwen3-VL-4B-Instruct vs Step 3.7 Flash](https://www.anchorterminal.com/compare/qwen3-vl-4b-instruct-vs-step-3-7-flash.md)\n- [Qwen3-VL-8B-Instruct vs Step 3.7 Flash](https://www.anchorterminal.com/compare/qwen3-vl-8b-instruct-vs-step-3-7-flash.md)\n- [Qwopus3.8-27B-Flash-V2 vs Step 3.7 Flash](https://www.anchorterminal.com/compare/qwopus3-8-27b-flash-v2-vs-step-3-7-flash.md)\n- [Recursive Flint vs Step 3.7 Flash](https://www.anchorterminal.com/compare/recursive-flint-vs-step-3-7-flash.md)\n- [Ripple-65B Preview vs Step 3.7 Flash](https://www.anchorterminal.com/compare/ripple-65b-preview-vs-step-3-7-flash.md)\n- [SenseNova-Loop-9B-Preview vs Step 3.7 Flash](https://www.anchorterminal.com/compare/sensenova-loop-9b-preview-vs-step-3-7-flash.md)\n- [SmolLM3-3B vs Step 3.7 Flash](https://www.anchorterminal.com/compare/smollm3-3b-vs-step-3-7-flash.md)\n- [Spark-X2.6-4B vs Step 3.7 Flash](https://www.anchorterminal.com/compare/spark-x2-6-4b-vs-step-3-7-flash.md)\n- [Step 3.7 Flash vs Swift 1.5 Qwen3.8-27B](https://www.anchorterminal.com/compare/step-3-7-flash-vs-swift-1-5-qwen3-8-27b.md)\n- [Step 3.7 Flash vs Swift 1.5 Qwen3.8-Flash-Next](https://www.anchorterminal.com/compare/step-3-7-flash-vs-swift-1-5-qwen3-8-flash-next.md)\n- [Step 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"0.7", "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 Step 3.7 Flash", "url": "" } ], "description": "Step 3.7 Flash scores 59.8 (C) to Laguna M.1's 56.7 (C) for open-weight models you run yourself. 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