{ "data": { "a": { "slug": "granite-4-2-30b", "name": "Granite 4.2 30B", "vendor": "IBM", "vendorUrl": "https://www.ibm.com/granite", "kind": "weights", "category": "open-weights", "summary": "Granite 4.2 30B is IBM's open-weight dense reasoning model of 29.3B parameters, post-trained from Granite 4.1 30B Base, with switchable thinking, tool calling and a 131,072-token context, published in BF16, FP8, FP4, GGUF and MLX under Apache 2.0.", "url": "https://www.anchorterminal.com/tools/granite-4-2-30b", "markdownUrl": "https://www.anchorterminal.com/tools/granite-4-2-30b.md", "slimMarkdownUrl": "https://www.anchorterminal.com/tools/granite-4-2-30b.min.md", "jsonUrl": "https://www.anchorterminal.com/api/v1/tools/granite-4-2-30b.json", "dns": "granite-4-2-30b.grade.anchorterminal.com", "repo": "https://huggingface.co/ibm-granite/granite-4.2-30b", "license": "Apache-2.0", "transports": [], "packages": [ { "registry": "huggingface", "name": "ibm-granite/granite-4.2-30b" }, { "registry": "huggingface", "name": "ibm-granite/granite-4.2-30b-GGUF" }, { "registry": "huggingface", "name": "ibm-granite/granite-4.2-30b-fp8" }, { "registry": "huggingface", "name": "ibm-granite/granite-4.2-30b-mxfp4" }, { "registry": "huggingface", "name": "ibm-granite/granite-4.2-30b-nvfp4" }, { "registry": "huggingface", "name": "ibm-granite/granite-4.2-30b-q4-mlx" }, { "registry": "ollama", "name": "granite4.2:30b" } ], "auth": "none", "authNotes": "The weights download from Hugging Face with no account, token or terms to accept. The BF16 repository and IBM's FP8, MXFP4, NVFP4, GGUF and MLX repositories are not gated (checked 2026-11-10).", "pricing": "free", "pricingNotes": "Free to download and use, commercial use included, under Apache 2.0. Running it yourself costs the hardware, 58.5 GB for the BF16 files, 17.7 GB for IBM's Q4_K_M GGUF or 16.5 GB for its 4-bit MLX build (checked 2026-11-10).", "priceSummary": "Free", "where": "local", "x402": { "level": "no", "evidence": "Weights you download and run yourself, so there is nothing to pay per call and no payment protocol (checked 2026-11-10).", "endpoints": [] }, "toolCount": null, "popularity": { "githubStars": null, "npmWeekly": null, "pypiWeekly": null, "asOf": "2026-11-10" }, "docsUrl": "https://huggingface.co/ibm-granite/granite-4.2-30b", "capabilities": [ "model.open-weights" ], "tags": [ "open-weights", "model", "dense", "reasoning", "tool-calling", "multilingual", "apache-2.0", "safetensors", "fp8", "fp4", "gguf", "mlx", "signed", "self-hosted" ], "lastRelease": "2026-09-04", "graded": true, "anchor": { "graded": true, "score": 61, "grade": "C", "agentReady": false, "rank": 0, "ranked": false, "notRankedWhy": "An open-weight model, graded by the open-weight checklist and ranked among open-weight models, not against tools", "rankOf": 1518, "categoryRank": 52, "methodology": "0.7", "run": "2026-10-01", "scores": { "interface": 85, "reach": 90, "risk": 55, "upkeep": 87 }, "pending": [ "performance", "tasks" ], "assessment": { "confidence": "low", "date": "2026-11-10" }, "negative": 0, "verdict": "IBM's largest reasoning cousin, with the same strengths as the 3B. It runs in every runtime we count from IBM's own builds on a 24 GB card, is signed, plain Apache 2.0, and comes with a disclosure of its training data. No safety results are published and structured output isn't documented.", "bestFor": "Agents that want a documented, signed, Apache 2.0 reasoning model with tool calling on a 24 GB card", "strengths": [ "Runs in llama.cpp, Ollama, vLLM, SGLang and Transformers from IBM's own FP8, FP4, GGUF and MLX builds", "Plain Apache 2.0, ungated, signed with sigstore", "The card documents the tool-calling format, the parser to use and three thinking modes", "IBM publishes a machine-readable disclosure of the training datasets", "IBM answers most questions on the repository" ], "weaknesses": [ "No safety results published for it", "Structured output isn't documented", "The card's vLLM command still loads a Python plugin from the repository, which released vLLM no longer needs", "No knowledge cut-off on the card", "One inference provider, so an agent without the hardware has little choice" ], "agentNotes": [ "Start it with `ollama run granite4.2:30b`, or `llama-server -hf ibm-granite/granite-4.2-30b-GGUF:Q4_K_M --jinja`", "With vLLM 0.32.0 or later leave out `--reasoning-parser-plugin`, since the parser is built in, and use `--tool-call-parser qwen3_coder`", "Thinking is on by default. Pass `enable_thinking` false to turn it off or `low_effort` true for short reasoning", "The context is 131,072 tokens. The card's 512K extension isn't documented", "Validate JSON output yourself, since structured output isn't documented", "IBM recommends Granite Guardian beside it to flag risky inputs and outputs" ], "metrics": { "kind": "local", "measured": false }, "reviewCount": 0, "avgRating": 0, "history": [ { "basis": "public evidence", "confidence": "low", "grade": "C", "methodology": "0.7", "pending": [ "performance", "tasks" ], "run": "2026-10-01", "runLabel": "October 2026 research run", "score": 61 } ], "editorialScores": { "interface": 85, "reach": 90, "risk": 55, "upkeep": 87 }, "provenanceScore": 88, "checked": { "categories": { "interface": "2026-11-10", "reach": "2026-11-10", "risk": "2026-11-10", "upkeep": "2026-11-10" }, "last": "2026-11-10", "oldest": "2026-11-10", "stale": false, "staleAfterDays": 90 } }, "connect": { "install": "ollama run granite4.2:30b\n# or, with llama.cpp and IBM's own GGUF:\nllama-server -hf ibm-granite/granite-4.2-30b-GGUF:Q4_K_M --jinja\n# or, with vLLM 0.32.0 or later:\nvllm serve ibm-granite/granite-4.2-30b --max-model-len 131072 \\\n --reasoning-parser granite_thinking_parser \\\n --tool-call-parser qwen3_coder --enable-auto-tool-choice", "http": "curl http://localhost:11434/api/chat \\\n -d '{\"model\": \"granite4.2:30b\", \"messages\": [{\"role\": \"user\", \"content\": \"Hello!\"}]}'" }, "letme": { "capability": "https://letme.dev/model.open-weights", "tool": "https://letme.dev/granite-4-2-30b" }, "sameCompany": [ "granite-embedding-small-english-r2", "granite-guardian", "granite-speech-5-0-2b", "ibm-watson-stt", "granite-switch", "granite-4-2-3b", "granite-4-2-8b" ], "weights": { "trainedBy": "IBM", "builtOn": "ibm-granite/granite-4.1-30b-base (IBM's own base checkpoint, post-trained; named on the card and in its metadata)", "params": "29.3B", "context": 131072, "goodFor": "IBM's largest dense reasoning model for tool calling, coding and multilingual chat, with thinking that is on, off or short per request, on a 24 GB card at 4 bits.", "runtimes": [ "llama.cpp", "Ollama", "vLLM", "SGLang", "Transformers" ], "builds": [ { "name": "granite-4.2-30b-nvfp4", "url": "https://huggingface.co/ibm-granite/granite-4.2-30b-nvfp4", "who": "publisher", "precision": "nvfp4", "sizeGB": 17.65, "memoryGB": 24, "format": "safetensors", "runsOn": [ "vLLM" ] }, { "name": "granite-4.2-30b-mxfp4", "url": "https://huggingface.co/ibm-granite/granite-4.2-30b-mxfp4", "who": "publisher", "precision": "mxfp4", "sizeGB": 16.76, "memoryGB": 24, "format": "safetensors", "runsOn": [ "vLLM" ] }, { "name": "granite-4.2-30b-Q4_K_M", "url": "https://huggingface.co/ibm-granite/granite-4.2-30b-GGUF", "who": "publisher", "precision": "q4_k_m", "sizeGB": 17.72, "memoryGB": 24, "format": "gguf", "runsOn": [ "llama.cpp" ], "note": "IBM's GGUF repository also holds Q4_0 (16.58 GB), Q6_K and BF16 files among others" }, { "name": "granite-4.2-30b-q4-mlx", "url": "https://huggingface.co/ibm-granite/granite-4.2-30b-q4-mlx", "who": "publisher", "precision": "q4", "sizeGB": 16.47, "memoryGB": 24, "format": "mlx", "runsOn": [ "mlx-lm" ], "note": "The smallest build at 4-bit or better. IBM also publishes q8-mlx (31.11 GB) and bf16-mlx" }, { "name": "ollama granite4.2:30b", "url": "https://ollama.com/library/granite4.2:30b", "who": "ollama", "precision": "q4_k_m", "sizeGB": 18, "memoryGB": 24, "format": "ollama", "runsOn": [ "Ollama" ], "note": "Ollama's library build, size as its tags page shows it on 10 November 2026" }, { "name": "granite-4.2-30b-fp8", "url": "https://huggingface.co/ibm-granite/granite-4.2-30b-fp8", "who": "publisher", "precision": "fp8", "sizeGB": 30.11, "memoryGB": 48, "format": "safetensors", "runsOn": [ "vLLM" ] }, { "name": "granite-4.2-30b-Q8_0", "url": "https://huggingface.co/ibm-granite/granite-4.2-30b-GGUF", "who": "publisher", "precision": "q8_0", "sizeGB": 31.11, "memoryGB": 48, "format": "gguf", "runsOn": [ "llama.cpp" ] }, { "name": "granite-4.2-30b", "url": "https://huggingface.co/ibm-granite/granite-4.2-30b", "who": "publisher", "precision": "bf16", "sizeGB": 58.55, "memoryGB": 96, "format": "safetensors", "runsOn": [ "vLLM", "SGLang", "Transformers" ] } ], "run": "ollama run granite4.2:30b", "runBuild": "ollama granite4.2:30b", "checked": "2026-11-10", "minMemoryGB": 24 }, "family": { "lab": "IBM (Granite)", "family": "Granite 4 (4.0, 4.1, 4.2)", "url": "https://www.anchorterminal.com/open-weights/#ibm", "others": [ { "name": "granite-4.2-3b", "url": "https://huggingface.co/ibm-granite/granite-4.2-3b", "params": "3B (Hub safetensors count 3.66B)", "listing": "https://www.anchorterminal.com/tools/granite-4-2-3b" }, { "name": "granite-4.2-8b", "url": "https://huggingface.co/ibm-granite/granite-4.2-8b", "params": "8B (Hub safetensors count 8.79B)", "listing": "https://www.anchorterminal.com/tools/granite-4-2-8b" }, { "name": "granite-4.1-8b-base", "url": "https://huggingface.co/ibm-granite/granite-4.1-8b-base", "params": "8B (Hub safetensors count 8.38B)" }, { "name": "granite-4.1-8b", "url": "https://huggingface.co/ibm-granite/granite-4.1-8b", "params": "8B (Hub safetensors count 8.79B)" }, { "name": "granite-4.1-3b-base", "url": "https://huggingface.co/ibm-granite/granite-4.1-3b-base", "params": "3B (Hub safetensors count 3.40B)" }, { "name": "granite-4.1-3b", "url": "https://huggingface.co/ibm-granite/granite-4.1-3b", "params": "3B (Hub safetensors count 3.40B)" }, { "name": "granite-4.1-30b-base", "url": "https://huggingface.co/ibm-granite/granite-4.1-30b-base", "params": "30B (Hub safetensors count 28.87B)" }, { "name": "granite-4.1-30b", "url": "https://huggingface.co/ibm-granite/granite-4.1-30b", "params": "30B (Hub safetensors count 28.87B)" }, { "name": "granite-4.0-h-350m-base", "url": "https://huggingface.co/ibm-granite/granite-4.0-h-350m-base", "params": "350M (Hub safetensors count 340M)" }, { "name": "granite-4.0-h-350m", "url": "https://huggingface.co/ibm-granite/granite-4.0-h-350m", "params": "350M (Hub safetensors count 340M)" }, { "name": "granite-4.0-h-1b-base", "url": "https://huggingface.co/ibm-granite/granite-4.0-h-1b-base", "params": "1B (Hub safetensors count 1.46B)" }, { "name": "granite-4.0-h-1b", "url": "https://huggingface.co/ibm-granite/granite-4.0-h-1b", "params": "1B (Hub safetensors count 1.46B)" }, { "name": "granite-4.0-350m-base", "url": "https://huggingface.co/ibm-granite/granite-4.0-350m-base", "params": "350M (Hub safetensors count 352M)" }, { "name": "granite-4.0-350m", "url": "https://huggingface.co/ibm-granite/granite-4.0-350m", "params": "350M (Hub safetensors count 352M)" }, { "name": "granite-4.0-1b-base", "url": "https://huggingface.co/ibm-granite/granite-4.0-1b-base", "params": "1B (Hub safetensors count 1.63B)" }, { "name": "granite-4.0-1b", "url": "https://huggingface.co/ibm-granite/granite-4.0-1b", "params": "1B (Hub safetensors count 1.63B)" }, { "name": "granite-4.0-micro-base", "url": "https://huggingface.co/ibm-granite/granite-4.0-micro-base", "params": "3.40B (Hub safetensors count; the name states none)" }, { "name": "granite-4.0-micro", "url": "https://huggingface.co/ibm-granite/granite-4.0-micro", "params": "3.40B (Hub safetensors count; the name states none)" }, { "name": "granite-4.0-h-tiny-base", "url": "https://huggingface.co/ibm-granite/granite-4.0-h-tiny-base", "params": "6.94B (Hub safetensors count; the name states none)" }, { "name": "granite-4.0-h-tiny", "url": "https://huggingface.co/ibm-granite/granite-4.0-h-tiny", "params": "6.94B (Hub safetensors count; the name states none)" }, { "name": "granite-4.0-h-small-base", "url": "https://huggingface.co/ibm-granite/granite-4.0-h-small-base", "params": "32.21B (Hub safetensors count; the name states none)" }, { "name": "granite-4.0-h-small", "url": "https://huggingface.co/ibm-granite/granite-4.0-h-small", "params": "32.21B (Hub safetensors count; the name states none)" }, { "name": "granite-4.0-h-micro-base", "url": "https://huggingface.co/ibm-granite/granite-4.0-h-micro-base", "params": "3.19B (Hub safetensors count; the name states none)" }, { "name": "granite-4.0-h-micro", "url": "https://huggingface.co/ibm-granite/granite-4.0-h-micro", "params": "3.19B (Hub safetensors count; the name states none)" }, { "name": "granite-4.0-tiny-preview", "url": "https://huggingface.co/ibm-granite/granite-4.0-tiny-preview", "params": "6.67B (Hub safetensors count; the name states none)" }, { "name": "granite-4.0-tiny-base-preview", "url": "https://huggingface.co/ibm-granite/granite-4.0-tiny-base-preview", "params": "6.67B (Hub safetensors count; the name states none)" } ], "olderCount": 64 }, "area": "models", "provenance": { "legalEntity": "International Business Machines Corporation (per IBM's naming guidance, as read for granite-guardian)", "domain": "ibm.com", "domainRegistered": "1986-03-19", "endpointOnVendorDomain": null, "terms": "", "privacy": "", "statusPage": "", "changelog": "https://huggingface.co/ibm-granite/granite-4.2-30b/commits/main", "securityTxt": "valid", "checked": "2026-11-10", "notes": [ "IBM's Granite docs page for 4.2 links the ibm-granite collection on Hugging Face and the GitHub repository, and the docs site says it is no longer updated. The domain date is carried from the granite-guardian check.", "The ibm-granite organisation (209 members) isn't verified on the Hub, which the calibration doesn't require.", "Nothing is hosted for this listing, so the Apache 2.0 licence stands in for terms of service and no privacy policy is scored.", "The changelog is the Hugging Face commit history, 15 commits from 7 August to 20 October 2026, most titled only \"granite-4.2\".", "www.ibm.com/.well-known/security.txt is present with PSIRT contacts and expires on 21 November 2026.", "Released on 25 August 2026 by the card and IBM's blog, which firstReleased uses. The repository and its weight files date from 7 August 2026, the date BATCH.md and the IBM family page used before 21 October." ], "score": 88 }, "pageJsonUrl": "https://www.anchorterminal.com/tools/granite-4-2-30b.json" }, "answer": "Granite 4.2 30B and Laguna XS 2.1 score within a point of each other on agent readiness, 61 (C) and 61 (C).", "b": { "slug": "laguna-xs-2-1", "name": "Laguna XS 2.1", "vendor": "Poolside", "vendorUrl": "https://poolside.ai", "kind": "weights", "category": "open-weights", "summary": "Laguna XS 2.1 is Poolside's open-weight Mixture-of-Experts coding model, 33B total and 3B active parameters, with switchable reasoning and a 262,144-token context, published on Hugging Face under OpenMDW-1.1.", "url": "https://www.anchorterminal.com/tools/laguna-xs-2-1", "markdownUrl": "https://www.anchorterminal.com/tools/laguna-xs-2-1.md", "slimMarkdownUrl": "https://www.anchorterminal.com/tools/laguna-xs-2-1.min.md", "jsonUrl": "https://www.anchorterminal.com/api/v1/tools/laguna-xs-2-1.json", "dns": "laguna-xs-2-1.grade.anchorterminal.com", "repo": "https://huggingface.co/poolside/Laguna-XS-2.1", "license": "OpenMDW-1.1", "transports": [], "packages": [ { "registry": "huggingface", "name": "poolside/Laguna-XS-2.1" }, { "registry": "huggingface", "name": "poolside/Laguna-XS-2.1-FP8" }, { "registry": "huggingface", "name": "poolside/Laguna-XS-2.1-INT4" }, { "registry": "huggingface", "name": "poolside/Laguna-XS-2.1-NVFP4" }, { "registry": "huggingface", "name": "poolside/Laguna-XS-2.1-NVFP4-mlx" }, { "registry": "huggingface", "name": "poolside/Laguna-XS-2.1-GGUF" }, { "registry": "ollama", "name": "laguna-xs-2.1" } ], "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 every build, 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 OpenMDW-1.1. Running it yourself costs the hardware, 66.9 GB for the BF16 files and 20.3 GB for Poolside's Q4_K_M GGUF, which is also Ollama's default build. Poolside's OpenRouter endpoints expired on 31 October 2026 and no other host was found (checked 2026-11-03).", "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-XS-2.1", "capabilities": [ "model.open-weights" ], "tags": [ "open-weights", "model", "moe", "coding", "reasoning", "tool-calling", "openmdw-1.1", "safetensors", "gguf", "fp8", "nvfp4", "self-hosted" ], "lastRelease": "2026-08-19", "graded": true, "anchor": { "graded": true, "score": 61, "grade": "C", "agentReady": false, "rank": 0, "ranked": false, "notRankedWhy": "An open-weight model, graded by the open-weight checklist and ranked among open-weight models, not against tools", "rankOf": 1518, "categoryRank": 36, "methodology": "0.7", "run": "2026-10-01", "scores": { "interface": 85, "reach": 80, "risk": 55, "upkeep": 46 }, "pending": [ "performance", "tasks" ], "assessment": { "confidence": "low", "date": "2026-11-03" }, "negative": 0, "verdict": "A small coding and agent cousin with 3B active parameters, so it's quick on modest hardware. Poolside's 4-bit GGUF, also Ollama's default, needs about 24 GB, and every major runtime runs it. The main risks are that nobody at Poolside answers its discussions, there are no safety results, and the SGLang route runs repository code.", "bestFor": "Agents that want a fast local coding model on a 32 GB GPU or Mac, with tool calling and a permissive licence.", "strengths": [ "Released support in llama.cpp, Ollama, vLLM, SGLang, Transformers and mlx-lm", "Poolside's own Q4_K_M, FP8, INT4, NVFP4 and MLX builds, the Q4_K_M at 20.3 GB", "Permissive OpenMDW-1.1 licence with no gate, account or use policy", "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": [ "No reply from Poolside to any discussion, including reports about the tokenizer and remote code", "No safety results and only general cautions for agent use", "The SGLang and TensorRT-LLM commands run the repository's Python with trust_remote_code", "The template defaults thinking off while generation_config.json turns it on", "No structured output documentation, and no limitations, languages or cut-off on the card", "No hosted endpoint since Poolside's OpenRouter endpoints expired on 31 October 2026, so an agent without the hardware can't call it" ], "agentNotes": [ "Quickest start is `ollama run laguna-xs-2.1`, 20 GB of files, the same Q4_K_M as Poolside's GGUF", "On our reference machine use `llama-server -hf poolside/Laguna-XS-2.1-GGUF:Q4_K_M --jinja -c 131072`, from a llama.cpp release with the laguna architecture (b11772 has it), or BF16 with vLLM (66.9 GB)", "With vLLM use `--tool-call-parser poolside_v1 --reasoning-parser poolside_v1 --enable-auto-tool-choice`, on a build with vllm-project/vllm#47311, or `--tool-call-parser glm47` on older builds", "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 card warns that Ollama on Apple Silicon may return empty output until llama.cpp#25389 ships", "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": 2.8, "history": [ { "basis": "public evidence", "confidence": "low", "grade": "C", "methodology": "0.7", "pending": [ "performance", "tasks" ], "run": "2026-10-01", "runLabel": "October 2026 research run", "score": 61 } ], "editorialScores": { "interface": 85, "reach": 80, "risk": 55, "upkeep": 46 }, "provenanceScore": 69, "checked": { "categories": { "interface": "2026-11-03", "reach": "2026-11-03", "risk": "2026-11-03", "upkeep": "2026-11-03" }, "last": "2026-11-03", "lastMoved": "2026-11-03", "oldest": "2026-11-03", "stale": false, "staleAfterDays": 90 } }, "connect": { "install": "ollama run laguna-xs-2.1\n# or, with vLLM 0.21.0 or later (a build with vllm-project/vllm#47311):\nvllm serve poolside/Laguna-XS-2.1 --tool-call-parser poolside_v1 --reasoning-parser poolside_v1 \\\n --enable-auto-tool-choice --default-chat-template-kwargs '{\"enable_thinking\": true}'", "http": "curl http://localhost:11434/api/chat \\\n -d '{\"model\": \"laguna-xs-2.1\", \"messages\": [{\"role\": \"user\", \"content\": \"Hello!\"}]}'" }, "letme": { "capability": "https://letme.dev/model.open-weights", "tool": "https://letme.dev/laguna-xs-2-1" }, "sameCompany": [ "laguna-m-1", "laguna-s-2-1" ], "weights": { "trainedBy": "Poolside", "params": "33.4B total, 3B active", "context": 262144, "goodFor": "Agentic coding and long-horizon terminal work on one GPU or a 32 GB machine, with tool calling and reasoning that turns on or off per request.", "runtimes": [ "llama.cpp", "Ollama", "vLLM", "SGLang", "LM Studio", "Transformers" ], "builds": [ { "name": "Laguna-XS-2.1-INT4", "url": "https://huggingface.co/poolside/Laguna-XS-2.1-INT4", "who": "publisher", "precision": "int4 (w4a16)", "sizeGB": 23.9, "memoryGB": 32, "format": "safetensors" }, { "name": "Laguna-XS-2.1-NVFP4", "url": "https://huggingface.co/poolside/Laguna-XS-2.1-NVFP4", "who": "publisher", "precision": "nvfp4", "sizeGB": 21.6, "memoryGB": 32, "format": "safetensors", "note": "For NVIDIA Blackwell GPUs" }, { "name": "Laguna-XS-2.1-NVFP4-mlx", "url": "https://huggingface.co/poolside/Laguna-XS-2.1-NVFP4-mlx", "who": "publisher", "precision": "nvfp4", "sizeGB": 21.6, "memoryGB": 32, "format": "mlx", "runsOn": [ "MLX" ] }, { "name": "Laguna-XS-2.1-GGUF Q4_K_M", "url": "https://huggingface.co/poolside/Laguna-XS-2.1-GGUF", "who": "publisher", "precision": "q4_k_m", "sizeGB": 20.3, "memoryGB": 32, "format": "gguf", "runsOn": [ "llama.cpp", "Ollama" ], "note": "Laguna-XS-2.1-Q4_K_M.gguf, 20,274,300,032 bytes. The repository also holds a BF16 GGUF of 66.9 GB (96 GB of memory)" }, { "name": "ollama laguna-xs-2.1:latest", "url": "https://ollama.com/library/laguna-xs-2.1:latest", "who": "ollama", "precision": "q4_k_m", "sizeGB": 20.3, "memoryGB": 32, "format": "ollama", "runsOn": [ "Ollama" ], "note": "Ollama shows 20 GB. Its model blob (sha256 1ac7079101fc) is Poolside's Q4_K_M GGUF, so the exact size is Poolside's. The library also has q8_0 (36 GB), bf16 (67 GB) and MLX tags (nvfp4 shown as 20 GB, exact size unpublished, mxfp8 40 GB, mlx-bf16 68 GB). The card warns that ollama run may return empty output on Apple Silicon until llama.cpp#25389 ships" }, { "name": "Laguna-XS-2.1-FP8", "url": "https://huggingface.co/poolside/Laguna-XS-2.1-FP8", "who": "publisher", "precision": "fp8", "sizeGB": 35.3, "memoryGB": 48, "format": "safetensors" }, { "name": "Laguna-XS-2.1", "url": "https://huggingface.co/poolside/Laguna-XS-2.1", "who": "publisher", "precision": "bf16", "sizeGB": 66.9, "memoryGB": 96, "format": "safetensors", "runsOn": [ "vLLM", "SGLang", "Transformers" ] } ], "run": "llama-server -hf poolside/Laguna-XS-2.1-GGUF:Q4_K_M --jinja -c 131072 --port 8000", "runBuild": "Laguna-XS-2.1-GGUF Q4_K_M", "checked": "2026-10-21", "minMemoryGB": 32 }, "family": { "lab": "Poolside", "family": "Laguna 2 (XS.2, XS 2.1, S 2.1)", "url": "https://www.anchorterminal.com/open-weights/#poolside", "others": [ { "name": "Laguna-S-2.1", "url": "https://huggingface.co/poolside/Laguna-S-2.1", "params": "117.56B (Hub safetensors count; the name gives only the size class S)", "listing": "https://www.anchorterminal.com/tools/laguna-s-2-1" }, { "name": "Laguna-S-2.1-base", "url": "https://huggingface.co/poolside/Laguna-S-2.1-base", "params": "not stated (no safetensors count on the Hub; the instruct model is 117.56B)" }, { "name": "Laguna-XS.2", "url": "https://huggingface.co/poolside/Laguna-XS.2", "params": "33.44B (Hub safetensors count; the name gives only the size class XS)" } ], "unrestrictedCopies": 1 }, "area": "models", "provenance": { "legalEntity": "Poolside, Inc. (named in Poolside's Terms of Use)", "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 blog post for this release links its collection there.", "Nothing is hosted for this listing, so the OpenMDW-1.1 licence stands in for terms of service and no privacy policy is scored.", "Poolside's docs keep dated model release notes. The June 2026 entry calls XS 2.1 an incremental update to Laguna XS.2.", "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-xs-2-1.json", "live": { "slug": "laguna-xs-2-1", "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" }, "updatedAt": "2026-11-10T16:09:25.614312659Z" } }, "edges": [ { "by": 41, "category": "upkeep", "leads": "granite-4-2-30b", "name": "Documentation and upkeep", "reasons": { "a": "Model card 17, Intended use (best for), limitations (ethical considerations and limitations), architecture, parameters (30B), context length (128K native) and 12 tested languages are on the card. Training data 20, IBM's disclosure file for the 30B lists the datasets used in pre-training and post-training as machine-readable metadata, and the card describes the three training stages. Last change 15, the last commit to the repository was on 4 September 2026, 67 days before this check. Responsiveness 20, Of the 4 discussions that aren't pull requests (28 August to 3 November 2026), 3 have a reply from an ibm-granite member. Version policy 5, Granite 4.1 30B stays in its own repository and 4.2 came out in new ones. File health 10, Config, template and card agree on the architecture, the 131,072-token context and the thinking switch. 17 + 20 + 15 + 20 + 5 + 10 = 87.", "b": "Model card 11 of 20, intended use, architecture, parameters and context are there, limitations, languages and a cut-off aren't. Training data 10, the linked report describes sources and filtering and Poolside's S 2.1 post gives the shared November 2025 cut-off. Last change 15, 19 August 2026, 76 days back. Responsiveness 0, Poolside answered none of the 6 discussions. Version policy 5, XS.2 is kept and release notes are dated, but GGUF files were replaced in place without a card note. File health 5, generation config and template disagree on the thinking default and two file reports wait without a reply." }, "scores": { "a": 87, "b": 46 } }, { "by": 10, "category": "reach", "leads": "granite-4-2-30b", "name": "Reach", "reasons": { "a": "Memory 25, IBM's own 4-bit MLX build granite-4.2-30b-q4-mlx is 16.47 GB, and 16.47 GB × 1.2 = 19.8 GB, which fits 24 GB but not 16 GB. Its Q4_0 GGUF is 16.58 GB and Ollama's library build granite4.2:30b 18 GB, the same band. Runtimes 25, Released versions run the granite architecture in llama.cpp (granite, b12242), vLLM (GraniteForCausalLM in the v0.33.0 registry), SGLang (granite.py at v0.5.23), Transformers (v5.22.2) and Ollama (its own granite4.2 library entry, 30b tag). Builds 15, IBM publishes FP8, MXFP4 and NVFP4 safetensors builds, a GGUF repository with Q4_0 to Q8_0 and BF16 files, and 4-bit, 8-bit and BF16 MLX builds, so quantised builds at two precisions or more. Terms 15, Apache 2.0, an OSI-approved licence, with no use policy or other terms added on the card. Download 10, the Hub API reports gated false for the BF16, FP8, MXFP4, NVFP4, GGUF and MLX repositories, so the files download with no account and nothing to accept. Hosted 0, Hugging Face maps one inference provider (DeepInfra, live), short of the two the line needs. 25 + 25 + 15 + 15 + 10 + 0 = 90.", "b": "Memory 20 of 30, the smallest 4-bit build with an exact size is Poolside's Q4_K_M GGUF at 20.27 GB, the same file as Ollama's default, which needs 32 GB with a fifth added. Runtimes 25, released llama.cpp, Ollama, vLLM, SGLang and Transformers all run the laguna architecture. Builds 15, Poolside publishes FP8, INT4, NVFP4, MLX and GGUF builds. Terms 10, OpenMDW-1.1 is permissive but not OSI-approved. Download 10, nothing is gated. Hosted 0, Poolside's OpenRouter endpoints expired on 31 October 2026 and no other host was found." }, "scores": { "a": 90, "b": 80 } } ], "facts": [ { "a": "Open-weight model", "b": "Open-weight model", "name": "Kind" }, { "a": "IBM", "b": "Poolside", "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": "OpenMDW-1.1", "name": "Licence" }, { "a": "no", "b": "no", "name": "Read-only variant documented" }, { "a": "no", "b": "no", "name": "llms.txt" }, { "a": "2026-09-04", "b": "2026-08-19", "name": "Last release" }, { "a": "no document linked", "b": "2026-07-21", "name": "Terms last updated" }, { "a": "no document linked", "b": "2026-07-21", "name": "Privacy policy last updated" }, { "a": "not read yet", "b": "yes, with an opt-out", "name": "Customer content may train models" }, { "a": "not read yet", "b": "not found in the text", "name": "Terms restrict automated access" }, { "a": "not read yet", "b": "not found in the text", "name": "Terms restrict benchmarking" }, { "a": "not read yet", "b": "yes", "name": "Terms or service can change without notice" }, { "a": "not read yet", "b": "yes", "name": "Arbitration or class-action waiver" }, { "a": "none", "b": "2.8/5 (4)", "name": "Agent reviews" } ], "faq": [ { "answer": "Granite 4.2 30B and Laguna XS 2.1 score within a point of each other on agent readiness, 61 (C) and 61 (C).", "question": "Which is better for AI agents, Granite 4.2 30B or Laguna XS 2.1?" } ], "goodFor": [ { "aheadOn": [ "Reach, 90 against 80", "Documentation and upkeep, 87 against 46" ], "also": null, "goodFor": "Agents that want a documented, signed, Apache 2.0 reasoning model with tool calling on a 24 GB card", "slug": "granite-4-2-30b", "watchFor": "No safety results published for it" }, { "aheadOn": null, "also": null, "goodFor": "Agents that want a fast local coding model on a 32 GB GPU or Mac, with tool calling and a permissive licence.", "slug": "laguna-xs-2-1", "watchFor": "No reply from Poolside to any discussion, including reports about the tokenizer and remote code" } ], "history": { "granite-4-2-30b": null, "laguna-xs-2-1": [ { "causes": [ "product" ], "date": "2026-11-03", "delta": 0, "from": 61, "fromGrade": "C", "to": 61, "toGrade": "C" } ] }, "job": { "capability": "model.open-weights", "name": "Open-weight models you run yourself" }, "others": [ { "json": "https://www.anchorterminal.com/compare/agents-a1-4b-vs-granite-4-2-30b.json", "title": "Agents-A1-4B vs Granite 4.2 30B", "url": "https://www.anchorterminal.com/compare/agents-a1-4b-vs-granite-4-2-30b" }, { "json": "https://www.anchorterminal.com/compare/agents-a1-4b-vs-laguna-xs-2-1.json", "title": "Agents-A1-4B vs Laguna XS 2.1", "url": "https://www.anchorterminal.com/compare/agents-a1-4b-vs-laguna-xs-2-1" }, { "json": "https://www.anchorterminal.com/compare/apertus-v1-5-8b-vs-granite-4-2-30b.json", "title": "Apertus v1.5 8B vs Granite 4.2 30B", "url": "https://www.anchorterminal.com/compare/apertus-v1-5-8b-vs-granite-4-2-30b" }, { "json": "https://www.anchorterminal.com/compare/apertus-v1-5-8b-vs-laguna-xs-2-1.json", "title": "Apertus v1.5 8B vs Laguna XS 2.1", "url": "https://www.anchorterminal.com/compare/apertus-v1-5-8b-vs-laguna-xs-2-1" }, { "json": "https://www.anchorterminal.com/compare/apodex-1-1-mini-vs-granite-4-2-30b.json", "title": "Apodex-1.1-mini vs Granite 4.2 30B", "url": "https://www.anchorterminal.com/compare/apodex-1-1-mini-vs-granite-4-2-30b" }, { "json": "https://www.anchorterminal.com/compare/apodex-1-1-mini-vs-laguna-xs-2-1.json", "title": "Apodex-1.1-mini vs Laguna XS 2.1", "url": "https://www.anchorterminal.com/compare/apodex-1-1-mini-vs-laguna-xs-2-1" }, { "json": "https://www.anchorterminal.com/compare/arete-27b-vs-granite-4-2-30b.json", "title": "Arete-27B vs Granite 4.2 30B", "url": "https://www.anchorterminal.com/compare/arete-27b-vs-granite-4-2-30b" }, { "json": "https://www.anchorterminal.com/compare/arete-27b-vs-laguna-xs-2-1.json", "title": "Arete-27B vs Laguna XS 2.1", "url": "https://www.anchorterminal.com/compare/arete-27b-vs-laguna-xs-2-1" }, { "json": "https://www.anchorterminal.com/compare/bigbang-v1-vs-granite-4-2-30b.json", "title": "BigBang-v1 vs Granite 4.2 30B", "url": "https://www.anchorterminal.com/compare/bigbang-v1-vs-granite-4-2-30b" }, { "json": "https://www.anchorterminal.com/compare/bigbang-v1-vs-laguna-xs-2-1.json", "title": "BigBang-v1 vs Laguna XS 2.1", "url": "https://www.anchorterminal.com/compare/bigbang-v1-vs-laguna-xs-2-1" }, { "json": "https://www.anchorterminal.com/compare/carbon-x-vs-granite-4-2-30b.json", "title": "Carbon-X vs Granite 4.2 30B", "url": "https://www.anchorterminal.com/compare/carbon-x-vs-granite-4-2-30b" }, { "json": "https://www.anchorterminal.com/compare/carbon-x-vs-laguna-xs-2-1.json", "title": "Carbon-X vs Laguna XS 2.1", "url": "https://www.anchorterminal.com/compare/carbon-x-vs-laguna-xs-2-1" }, { "json": "https://www.anchorterminal.com/compare/cola2-vs-granite-4-2-30b.json", "title": "Cola2 vs Granite 4.2 30B", "url": "https://www.anchorterminal.com/compare/cola2-vs-granite-4-2-30b" }, { "json": "https://www.anchorterminal.com/compare/cola2-vs-laguna-xs-2-1.json", "title": "Cola2 vs Laguna XS 2.1", "url": "https://www.anchorterminal.com/compare/cola2-vs-laguna-xs-2-1" }, { "json": "https://www.anchorterminal.com/compare/cosmos-reason2-2b-vs-granite-4-2-30b.json", "title": "Cosmos-Reason2-2B vs Granite 4.2 30B", "url": "https://www.anchorterminal.com/compare/cosmos-reason2-2b-vs-granite-4-2-30b" }, { "json": "https://www.anchorterminal.com/compare/cosmos-reason2-2b-vs-laguna-xs-2-1.json", "title": "Cosmos-Reason2-2B vs Laguna XS 2.1", "url": "https://www.anchorterminal.com/compare/cosmos-reason2-2b-vs-laguna-xs-2-1" }, { "json": "https://www.anchorterminal.com/compare/darwin-36b-opus-vs-granite-4-2-30b.json", "title": "Darwin-36B-Opus vs Granite 4.2 30B", "url": "https://www.anchorterminal.com/compare/darwin-36b-opus-vs-granite-4-2-30b" }, { "json": "https://www.anchorterminal.com/compare/darwin-36b-opus-vs-laguna-xs-2-1.json", "title": "Darwin-36B-Opus vs Laguna XS 2.1", "url": "https://www.anchorterminal.com/compare/darwin-36b-opus-vs-laguna-xs-2-1" }, { "json": "https://www.anchorterminal.com/compare/deepseek-v3-2-vs-granite-4-2-30b.json", "title": "DeepSeek-V3.2 vs Granite 4.2 30B", "url": "https://www.anchorterminal.com/compare/deepseek-v3-2-vs-granite-4-2-30b" }, { "json": "https://www.anchorterminal.com/compare/deepseek-v3-2-vs-laguna-xs-2-1.json", "title": "DeepSeek-V3.2 vs Laguna XS 2.1", "url": "https://www.anchorterminal.com/compare/deepseek-v3-2-vs-laguna-xs-2-1" }, { "json": "https://www.anchorterminal.com/compare/deepseek-v4-1-flash-vs-granite-4-2-30b.json", "title": "DeepSeek V4.1 Flash vs Granite 4.2 30B", "url": "https://www.anchorterminal.com/compare/deepseek-v4-1-flash-vs-granite-4-2-30b" }, { "json": "https://www.anchorterminal.com/compare/deepseek-v4-1-flash-vs-laguna-xs-2-1.json", "title": "DeepSeek V4.1 Flash vs Laguna XS 2.1", "url": "https://www.anchorterminal.com/compare/deepseek-v4-1-flash-vs-laguna-xs-2-1" }, { "json": "https://www.anchorterminal.com/compare/deepseek-v4-flash-0731-vs-granite-4-2-30b.json", "title": "DeepSeek-V4-Flash-0731 vs Granite 4.2 30B", "url": "https://www.anchorterminal.com/compare/deepseek-v4-flash-0731-vs-granite-4-2-30b" }, { "json": "https://www.anchorterminal.com/compare/deepseek-v4-flash-0731-vs-laguna-xs-2-1.json", "title": "DeepSeek-V4-Flash-0731 vs Laguna XS 2.1", "url": "https://www.anchorterminal.com/compare/deepseek-v4-flash-0731-vs-laguna-xs-2-1" }, { "json": "https://www.anchorterminal.com/compare/devstral-small-2-vs-granite-4-2-30b.json", "title": "Devstral Small 2 vs Granite 4.2 30B", "url": 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"https://www.anchorterminal.com/compare/laguna-xs-2-1-vs-mimo-v2-6-distill-qwen-9b.json", "title": "Laguna XS 2.1 vs MiMo-V2.6 Distill Qwen 9B", "url": "https://www.anchorterminal.com/compare/laguna-xs-2-1-vs-mimo-v2-6-distill-qwen-9b" }, { "json": "https://www.anchorterminal.com/compare/laguna-xs-2-1-vs-mimo-v2-6-flash-rl.json", "title": "Laguna XS 2.1 vs MiMo-V2.6-Flash-RL", "url": "https://www.anchorterminal.com/compare/laguna-xs-2-1-vs-mimo-v2-6-flash-rl" }, { "json": "https://www.anchorterminal.com/compare/laguna-xs-2-1-vs-minicpm-o-4-5.json", "title": "Laguna XS 2.1 vs MiniCPM-o 4.5", "url": "https://www.anchorterminal.com/compare/laguna-xs-2-1-vs-minicpm-o-4-5" }, { "json": "https://www.anchorterminal.com/compare/laguna-xs-2-1-vs-minicpm-v-4-7-1b.json", "title": "Laguna XS 2.1 vs MiniCPM-V 4.7 1B", "url": "https://www.anchorterminal.com/compare/laguna-xs-2-1-vs-minicpm-v-4-7-1b" }, { "json": "https://www.anchorterminal.com/compare/laguna-xs-2-1-vs-minicpm-v-4-7-35b-a3b.json", "title": "Laguna XS 2.1 vs MiniCPM-V 4.7 35B-A3B", "url": "https://www.anchorterminal.com/compare/laguna-xs-2-1-vs-minicpm-v-4-7-35b-a3b" }, { "json": "https://www.anchorterminal.com/compare/laguna-xs-2-1-vs-minicpm5-2b.json", "title": "Laguna XS 2.1 vs MiniCPM5-2B", "url": "https://www.anchorterminal.com/compare/laguna-xs-2-1-vs-minicpm5-2b" }, { "json": "https://www.anchorterminal.com/compare/laguna-xs-2-1-vs-minimax-m2-5.json", "title": "Laguna XS 2.1 vs MiniMax-M2.5", "url": "https://www.anchorterminal.com/compare/laguna-xs-2-1-vs-minimax-m2-5" }, { "json": "https://www.anchorterminal.com/compare/laguna-xs-2-1-vs-minimax-m2-7.json", "title": "Laguna XS 2.1 vs MiniMax-M2.7", "url": "https://www.anchorterminal.com/compare/laguna-xs-2-1-vs-minimax-m2-7" }, { "json": "https://www.anchorterminal.com/compare/laguna-xs-2-1-vs-minimax-m3-1-flash.json", "title": "Laguna XS 2.1 vs MiniMax-M3.1-Flash", "url": "https://www.anchorterminal.com/compare/laguna-xs-2-1-vs-minimax-m3-1-flash" }, { "json": "https://www.anchorterminal.com/compare/laguna-xs-2-1-vs-mistral-large-4.json", "title": "Laguna XS 2.1 vs Mistral Large 4", "url": "https://www.anchorterminal.com/compare/laguna-xs-2-1-vs-mistral-large-4" }, { "json": "https://www.anchorterminal.com/compare/laguna-xs-2-1-vs-muse-glimmer-30b.json", "title": "Laguna XS 2.1 vs Muse Glimmer 30B", "url": "https://www.anchorterminal.com/compare/laguna-xs-2-1-vs-muse-glimmer-30b" }, { "json": "https://www.anchorterminal.com/compare/laguna-xs-2-1-vs-nanbeige-4-2-3b.json", "title": "Laguna XS 2.1 vs Nanbeige4.2-3B", "url": "https://www.anchorterminal.com/compare/laguna-xs-2-1-vs-nanbeige-4-2-3b" }, { "json": "https://www.anchorterminal.com/compare/laguna-xs-2-1-vs-nanbeige-4-3-33b.json", "title": "Laguna XS 2.1 vs Nanbeige4.3-33B", "url": "https://www.anchorterminal.com/compare/laguna-xs-2-1-vs-nanbeige-4-3-33b" }, { "json": "https://www.anchorterminal.com/compare/laguna-xs-2-1-vs-nemotron-3-5-bolt-e4b-4gb.json", "title": "Laguna XS 2.1 vs NVIDIA Nemotron 3.5 Bolt E4B 4GB", "url": "https://www.anchorterminal.com/compare/laguna-xs-2-1-vs-nemotron-3-5-bolt-e4b-4gb" }, { "json": "https://www.anchorterminal.com/compare/laguna-xs-2-1-vs-nemotron-3-5-lightning-30b-a3b.json", "title": "Laguna XS 2.1 vs Nemotron 3.5 Lightning 30B A3B", "url": "https://www.anchorterminal.com/compare/laguna-xs-2-1-vs-nemotron-3-5-lightning-30b-a3b" }, { "json": "https://www.anchorterminal.com/compare/laguna-xs-2-1-vs-nemotron-3-nano-30b-a3b.json", "title": "Laguna XS 2.1 vs Nemotron 3 Nano 30B A3B", "url": "https://www.anchorterminal.com/compare/laguna-xs-2-1-vs-nemotron-3-nano-30b-a3b" }, { "json": "https://www.anchorterminal.com/compare/laguna-xs-2-1-vs-nemotron-3-nano-4b.json", "title": "Laguna XS 2.1 vs Nemotron 3 Nano 4B", "url": "https://www.anchorterminal.com/compare/laguna-xs-2-1-vs-nemotron-3-nano-4b" }, { "json": "https://www.anchorterminal.com/compare/laguna-xs-2-1-vs-nemotron-3-nano-omni-30b-a3b-reasoning.json", "title": "Laguna XS 2.1 vs Nemotron 3 Nano Omni 30B A3B Reasoning", "url": "https://www.anchorterminal.com/compare/laguna-xs-2-1-vs-nemotron-3-nano-omni-30b-a3b-reasoning" }, { "json": "https://www.anchorterminal.com/compare/laguna-xs-2-1-vs-nemotron-3-super-120b-a12b.json", "title": "Laguna XS 2.1 vs Nemotron 3 Super 120B A12B", "url": "https://www.anchorterminal.com/compare/laguna-xs-2-1-vs-nemotron-3-super-120b-a12b" }, { "json": "https://www.anchorterminal.com/compare/laguna-xs-2-1-vs-nemotron-3-ultra-550b-a55b.json", "title": "Laguna XS 2.1 vs Nemotron 3 Ultra 550B A55B", "url": "https://www.anchorterminal.com/compare/laguna-xs-2-1-vs-nemotron-3-ultra-550b-a55b" }, { "json": "https://www.anchorterminal.com/compare/laguna-xs-2-1-vs-north-mini-code-1-0.json", "title": "Laguna XS 2.1 vs North Mini Code 1.0", "url": "https://www.anchorterminal.com/compare/laguna-xs-2-1-vs-north-mini-code-1-0" }, { "json": "https://www.anchorterminal.com/compare/laguna-xs-2-1-vs-occamy-1-0.json", "title": "Laguna XS 2.1 vs occamy-1.0", "url": "https://www.anchorterminal.com/compare/laguna-xs-2-1-vs-occamy-1-0" }, { "json": "https://www.anchorterminal.com/compare/laguna-xs-2-1-vs-olmo-3-7b-think.json", "title": "Laguna XS 2.1 vs Olmo 3 7B Think", "url": "https://www.anchorterminal.com/compare/laguna-xs-2-1-vs-olmo-3-7b-think" }, { "json": "https://www.anchorterminal.com/compare/laguna-xs-2-1-vs-ornith-1-5-122b.json", "title": "Laguna XS 2.1 vs Ornith-1.5-122B", "url": "https://www.anchorterminal.com/compare/laguna-xs-2-1-vs-ornith-1-5-122b" }, { "json": "https://www.anchorterminal.com/compare/laguna-xs-2-1-vs-ornith-1-5-35b-a3b.json", "title": "Laguna XS 2.1 vs Ornith-1.5-35B-A3B", "url": "https://www.anchorterminal.com/compare/laguna-xs-2-1-vs-ornith-1-5-35b-a3b" }, { "json": "https://www.anchorterminal.com/compare/laguna-xs-2-1-vs-ornith-1-5-397b.json", "title": "Laguna XS 2.1 vs Ornith-1.5-397B", "url": "https://www.anchorterminal.com/compare/laguna-xs-2-1-vs-ornith-1-5-397b" }, { "json": "https://www.anchorterminal.com/compare/laguna-xs-2-1-vs-ornith-1-5-9b.json", "title": "Laguna XS 2.1 vs Ornith-1.5-9B", "url": "https://www.anchorterminal.com/compare/laguna-xs-2-1-vs-ornith-1-5-9b" }, { "json": "https://www.anchorterminal.com/compare/laguna-xs-2-1-vs-otel-2-0-llm-31b-it.json", "title": "Laguna XS 2.1 vs OTel-2.0-LLM-31B-IT", "url": "https://www.anchorterminal.com/compare/laguna-xs-2-1-vs-otel-2-0-llm-31b-it" }, { "json": "https://www.anchorterminal.com/compare/laguna-xs-2-1-vs-qwen-agentworld-35b-a3b.json", "title": "Laguna XS 2.1 vs Qwen-AgentWorld-35B-A3B", "url": "https://www.anchorterminal.com/compare/laguna-xs-2-1-vs-qwen-agentworld-35b-a3b" }, { "json": "https://www.anchorterminal.com/compare/laguna-xs-2-1-vs-qwen3-30b-a3b-instruct-2507.json", "title": "Laguna XS 2.1 vs Qwen3-30B-A3B-Instruct-2507", "url": "https://www.anchorterminal.com/compare/laguna-xs-2-1-vs-qwen3-30b-a3b-instruct-2507" }, { "json": "https://www.anchorterminal.com/compare/laguna-xs-2-1-vs-qwen3-4b-instruct-2507.json", "title": "Laguna XS 2.1 vs Qwen3-4B-Instruct-2507", "url": "https://www.anchorterminal.com/compare/laguna-xs-2-1-vs-qwen3-4b-instruct-2507" }, { "json": "https://www.anchorterminal.com/compare/laguna-xs-2-1-vs-qwen3-5-0-8b.json", "title": "Laguna XS 2.1 vs Qwen3.5-0.8B", "url": "https://www.anchorterminal.com/compare/laguna-xs-2-1-vs-qwen3-5-0-8b" }, { "json": "https://www.anchorterminal.com/compare/laguna-xs-2-1-vs-qwen3-5-122b-a10b.json", "title": "Laguna XS 2.1 vs Qwen3.5-122B-A10B", "url": "https://www.anchorterminal.com/compare/laguna-xs-2-1-vs-qwen3-5-122b-a10b" }, { "json": "https://www.anchorterminal.com/compare/laguna-xs-2-1-vs-qwen3-5-2b.json", "title": "Laguna XS 2.1 vs Qwen3.5-2B", "url": "https://www.anchorterminal.com/compare/laguna-xs-2-1-vs-qwen3-5-2b" }, { "json": "https://www.anchorterminal.com/compare/laguna-xs-2-1-vs-qwen3-5-397b-a17b.json", "title": "Laguna XS 2.1 vs Qwen3.5-397B-A17B", "url": "https://www.anchorterminal.com/compare/laguna-xs-2-1-vs-qwen3-5-397b-a17b" }, { "json": "https://www.anchorterminal.com/compare/laguna-xs-2-1-vs-qwen3-5-4b.json", "title": "Laguna XS 2.1 vs Qwen3.5-4B", "url": "https://www.anchorterminal.com/compare/laguna-xs-2-1-vs-qwen3-5-4b" }, { "json": "https://www.anchorterminal.com/compare/laguna-xs-2-1-vs-qwen3-5-9b.json", "title": "Laguna XS 2.1 vs Qwen3.5-9B", "url": "https://www.anchorterminal.com/compare/laguna-xs-2-1-vs-qwen3-5-9b" }, { "json": "https://www.anchorterminal.com/compare/laguna-xs-2-1-vs-qwen3-6-27b.json", "title": "Laguna XS 2.1 vs Qwen3.6-27B", "url": "https://www.anchorterminal.com/compare/laguna-xs-2-1-vs-qwen3-6-27b" }, { "json": "https://www.anchorterminal.com/compare/laguna-xs-2-1-vs-qwen3-6-35b-a3b.json", "title": "Laguna XS 2.1 vs Qwen3.6-35B-A3B", "url": "https://www.anchorterminal.com/compare/laguna-xs-2-1-vs-qwen3-6-35b-a3b" }, { "json": "https://www.anchorterminal.com/compare/laguna-xs-2-1-vs-qwen3-8-27b.json", "title": "Laguna XS 2.1 vs Qwen3.8-27B", "url": "https://www.anchorterminal.com/compare/laguna-xs-2-1-vs-qwen3-8-27b" }, { "json": "https://www.anchorterminal.com/compare/laguna-xs-2-1-vs-qwen3-8-flash-next.json", "title": "Laguna XS 2.1 vs Qwen3.8-Flash-Next", "url": "https://www.anchorterminal.com/compare/laguna-xs-2-1-vs-qwen3-8-flash-next" }, { "json": "https://www.anchorterminal.com/compare/laguna-xs-2-1-vs-qwen3-coder-30b-a3b-instruct.json", "title": "Laguna XS 2.1 vs Qwen3-Coder-30B-A3B-Instruct", "url": "https://www.anchorterminal.com/compare/laguna-xs-2-1-vs-qwen3-coder-30b-a3b-instruct" }, { "json": "https://www.anchorterminal.com/compare/laguna-xs-2-1-vs-qwen3-coder-next.json", "title": "Laguna XS 2.1 vs Qwen3-Coder-Next", "url": "https://www.anchorterminal.com/compare/laguna-xs-2-1-vs-qwen3-coder-next" }, { "json": "https://www.anchorterminal.com/compare/laguna-xs-2-1-vs-qwen3-omni-30b-a3b-instruct.json", "title": "Laguna XS 2.1 vs Qwen3-Omni-30B-A3B-Instruct", "url": "https://www.anchorterminal.com/compare/laguna-xs-2-1-vs-qwen3-omni-30b-a3b-instruct" }, { "json": "https://www.anchorterminal.com/compare/laguna-xs-2-1-vs-qwen3-vl-2b-instruct.json", "title": "Laguna XS 2.1 vs Qwen3-VL-2B-Instruct", "url": "https://www.anchorterminal.com/compare/laguna-xs-2-1-vs-qwen3-vl-2b-instruct" }, { "json": "https://www.anchorterminal.com/compare/laguna-xs-2-1-vs-qwen3-vl-30b-a3b-instruct.json", "title": "Laguna XS 2.1 vs Qwen3-VL-30B-A3B-Instruct", "url": "https://www.anchorterminal.com/compare/laguna-xs-2-1-vs-qwen3-vl-30b-a3b-instruct" }, { "json": "https://www.anchorterminal.com/compare/laguna-xs-2-1-vs-qwen3-vl-32b-instruct.json", "title": "Laguna XS 2.1 vs Qwen3-VL-32B-Instruct", "url": "https://www.anchorterminal.com/compare/laguna-xs-2-1-vs-qwen3-vl-32b-instruct" }, { "json": "https://www.anchorterminal.com/compare/laguna-xs-2-1-vs-qwen3-vl-4b-instruct.json", "title": "Laguna XS 2.1 vs Qwen3-VL-4B-Instruct", "url": "https://www.anchorterminal.com/compare/laguna-xs-2-1-vs-qwen3-vl-4b-instruct" }, { "json": "https://www.anchorterminal.com/compare/laguna-xs-2-1-vs-qwen3-vl-8b-instruct.json", "title": "Laguna XS 2.1 vs Qwen3-VL-8B-Instruct", "url": "https://www.anchorterminal.com/compare/laguna-xs-2-1-vs-qwen3-vl-8b-instruct" }, { "json": "https://www.anchorterminal.com/compare/laguna-xs-2-1-vs-qwopus3-8-27b-flash-v2.json", "title": "Laguna XS 2.1 vs Qwopus3.8-27B-Flash-V2", "url": "https://www.anchorterminal.com/compare/laguna-xs-2-1-vs-qwopus3-8-27b-flash-v2" }, { "json": "https://www.anchorterminal.com/compare/laguna-xs-2-1-vs-recursive-flint.json", "title": "Laguna XS 2.1 vs Recursive Flint", "url": "https://www.anchorterminal.com/compare/laguna-xs-2-1-vs-recursive-flint" }, { "json": "https://www.anchorterminal.com/compare/laguna-xs-2-1-vs-ripple-65b-preview.json", "title": "Laguna XS 2.1 vs Ripple-65B Preview", "url": "https://www.anchorterminal.com/compare/laguna-xs-2-1-vs-ripple-65b-preview" }, { "json": "https://www.anchorterminal.com/compare/laguna-xs-2-1-vs-sensenova-loop-9b-preview.json", "title": "Laguna XS 2.1 vs SenseNova-Loop-9B-Preview", "url": "https://www.anchorterminal.com/compare/laguna-xs-2-1-vs-sensenova-loop-9b-preview" }, { "json": "https://www.anchorterminal.com/compare/laguna-xs-2-1-vs-smollm3-3b.json", "title": "Laguna XS 2.1 vs SmolLM3-3B", "url": "https://www.anchorterminal.com/compare/laguna-xs-2-1-vs-smollm3-3b" }, { "json": "https://www.anchorterminal.com/compare/laguna-xs-2-1-vs-spark-x2-6-4b.json", "title": "Laguna XS 2.1 vs Spark-X2.6-4B", "url": "https://www.anchorterminal.com/compare/laguna-xs-2-1-vs-spark-x2-6-4b" }, { "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/laguna-xs-2-1-vs-swift-1-5-qwen3-8-27b.json", "title": "Laguna XS 2.1 vs Swift 1.5 Qwen3.8-27B", "url": "https://www.anchorterminal.com/compare/laguna-xs-2-1-vs-swift-1-5-qwen3-8-27b" }, { "json": "https://www.anchorterminal.com/compare/laguna-xs-2-1-vs-swift-1-5-qwen3-8-flash-next.json", "title": "Laguna XS 2.1 vs Swift 1.5 Qwen3.8-Flash-Next", "url": "https://www.anchorterminal.com/compare/laguna-xs-2-1-vs-swift-1-5-qwen3-8-flash-next" }, { "json": "https://www.anchorterminal.com/compare/laguna-xs-2-1-vs-thinkingcap-qwen3-8-27b.json", "title": "Laguna XS 2.1 vs ThinkingCap (Qwen3.8 27B)", "url": "https://www.anchorterminal.com/compare/laguna-xs-2-1-vs-thinkingcap-qwen3-8-27b" }, { "json": "https://www.anchorterminal.com/compare/laguna-xs-2-1-vs-unlimited-ocr-2.json", "title": "Laguna XS 2.1 vs Baidu Unlimited-OCR-2", "url": "https://www.anchorterminal.com/compare/laguna-xs-2-1-vs-unlimited-ocr-2" }, { "json": "https://www.anchorterminal.com/compare/laguna-xs-2-1-vs-wevisone-vl-2b.json", "title": "Laguna XS 2.1 vs WeVisOne-VL-2B", "url": "https://www.anchorterminal.com/compare/laguna-xs-2-1-vs-wevisone-vl-2b" }, { "json": "https://www.anchorterminal.com/compare/laguna-xs-2-1-vs-wevisone-vl-4b.json", "title": "Laguna XS 2.1 vs WeVisOne-VL-4B", "url": "https://www.anchorterminal.com/compare/laguna-xs-2-1-vs-wevisone-vl-4b" }, { "json": "https://www.anchorterminal.com/compare/laguna-xs-2-1-vs-zaya1-8b.json", "title": "Laguna XS 2.1 vs ZAYA1-8B", "url": "https://www.anchorterminal.com/compare/laguna-xs-2-1-vs-zaya1-8b" } ], "panel": null, "scores": [ { "key": "capability", "name": "Capability", "pending": true, "weight": 35 }, { "by": 10, "edge": "granite-4-2-30b", "granite-4-2-30b": 90, "key": "reach", "laguna-xs-2-1": 80, "name": "Reach", "weight": 25 }, { "by": 0, "edge": "", "granite-4-2-30b": 55, "key": "risk", "laguna-xs-2-1": 55, "name": "Risk", "weight": 20 }, { "by": 0, "edge": "", "granite-4-2-30b": 85, "key": "interface", "laguna-xs-2-1": 85, "name": "Agent interface", "weight": 10 }, { "by": 41, "edge": "granite-4-2-30b", "granite-4-2-30b": 87, "key": "upkeep", "laguna-xs-2-1": 46, "name": "Documentation and upkeep", "weight": 10 } ], "summary": "Granite 4.2 30B and Laguna XS 2.1 score within a point of each other on agent readiness, 61 (C) and 61 (C). Both do open-weight models you run yourself.", "tasks": null, "tutorials": [], "verdicts": { "granite-4-2-30b": "IBM's largest reasoning cousin, with the same strengths as the 3B. It runs in every runtime we count from IBM's own builds on a 24 GB card, is signed, plain Apache 2.0, and comes with a disclosure of its training data. No safety results are published and structured output isn't documented.", "laguna-xs-2-1": "A small coding and agent cousin with 3B active parameters, so it's quick on modest hardware. Poolside's 4-bit GGUF, also Ollama's default, needs about 24 GB, and every major runtime runs it. The main risks are that nobody at Poolside answers its discussions, there are no safety results, and the SGLang route runs repository code." } }, "kind": "anchor.page", "links": { "api": "https://www.anchorterminal.com/api/v1/index.json", "html": "https://www.anchorterminal.com/compare/granite-4-2-30b-vs-laguna-xs-2-1", "json": "https://www.anchorterminal.com/compare/granite-4-2-30b-vs-laguna-xs-2-1.json", "llms": "https://www.anchorterminal.com/llms.txt", "markdown": "https://www.anchorterminal.com/compare/granite-4-2-30b-vs-laguna-xs-2-1.md", "mcp": "https://www.anchorterminal.com/mcp", "slim": "https://www.anchorterminal.com/compare/granite-4-2-30b-vs-laguna-xs-2-1.min.md" }, "markdown": "Granite 4.2 30B and Laguna XS 2.1 score within a point of each other on agent readiness, 61 (C) and 61 (C). Both do open-weight models you run yourself.\n\n- Granite 4.2 30B: grade C, 61/100, rank #65 of 160 open-weight models. Markdown https://www.anchorterminal.com/tools/granite-4-2-30b.md · JSON https://www.anchorterminal.com/api/v1/tools/granite-4-2-30b.json\n- Laguna XS 2.1: grade C, 61/100, rank #46 of 160 open-weight models. Markdown https://www.anchorterminal.com/tools/laguna-xs-2-1.md · JSON https://www.anchorterminal.com/api/v1/tools/laguna-xs-2-1.json\n- Best open-weight models you download and run yourself for AI agents: https://www.anchorterminal.com/best/open-weights/index.md\n- All 6359 open weights comparisons: https://www.anchorterminal.com/compare/open-weights/index.md\n\n## Which one, for what\n\n### Granite 4.2 30B (C)\n\nGood for: Agents that want a documented, signed, Apache 2.0 reasoning model with tool calling on a 24 GB card\n\nAhead on:\n- Reach, 90 against 80\n- Documentation and upkeep, 87 against 46\n\nWatch for: No safety results published for it\n\n### Laguna XS 2.1 (C)\n\nGood for: Agents that want a fast local coding model on a 32 GB GPU or Mac, with tool calling and a permissive licence.\n\nWatch for: No reply from Poolside to any discussion, including reports about the tokenizer and remote code\n\n\n## Why the edge\n\n### Documentation and upkeep: Granite 4.2 30B +41\n\n- Granite 4.2 30B (87): Model card 17, Intended use (best for), limitations (ethical considerations and limitations), architecture, parameters (30B), context length (128K native) and 12 tested languages are on the card. Training data 20, IBM's disclosure file for the 30B lists the datasets used in pre-training and post-training as machine-readable metadata, and the card describes the three training stages. Last change 15, the last commit to the repository was on 4 September 2026, 67 days before this check. Responsiveness 20, Of the 4 discussions that aren't pull requests (28 August to 3 November 2026), 3 have a reply from an ibm-granite member. Version policy 5, Granite 4.1 30B stays in its own repository and 4.2 came out in new ones. File health 10, Config, template and card agree on the architecture, the 131,072-token context and the thinking switch. 17 + 20 + 15 + 20 + 5 + 10 = 87.\n- Laguna XS 2.1 (46): Model card 11 of 20, intended use, architecture, parameters and context are there, limitations, languages and a cut-off aren't. Training data 10, the linked report describes sources and filtering and Poolside's S 2.1 post gives the shared November 2025 cut-off. Last change 15, 19 August 2026, 76 days back. Responsiveness 0, Poolside answered none of the 6 discussions. Version policy 5, XS.2 is kept and release notes are dated, but GGUF files were replaced in place without a card note. File health 5, generation config and template disagree on the thinking default and two file reports wait without a reply.\n\n### Reach: Granite 4.2 30B +10\n\n- Granite 4.2 30B (90): Memory 25, IBM's own 4-bit MLX build granite-4.2-30b-q4-mlx is 16.47 GB, and 16.47 GB × 1.2 = 19.8 GB, which fits 24 GB but not 16 GB. Its Q4_0 GGUF is 16.58 GB and Ollama's library build granite4.2:30b 18 GB, the same band. Runtimes 25, Released versions run the granite architecture in llama.cpp (granite, b12242), vLLM (GraniteForCausalLM in the v0.33.0 registry), SGLang (granite.py at v0.5.23), Transformers (v5.22.2) and Ollama (its own granite4.2 library entry, 30b tag). Builds 15, IBM publishes FP8, MXFP4 and NVFP4 safetensors builds, a GGUF repository with Q4_0 to Q8_0 and BF16 files, and 4-bit, 8-bit and BF16 MLX builds, so quantised builds at two precisions or more. Terms 15, Apache 2.0, an OSI-approved licence, with no use policy or other terms added on the card. Download 10, the Hub API reports gated false for the BF16, FP8, MXFP4, NVFP4, GGUF and MLX repositories, so the files download with no account and nothing to accept. Hosted 0, Hugging Face maps one inference provider (DeepInfra, live), short of the two the line needs. 25 + 25 + 15 + 15 + 10 + 0 = 90.\n- Laguna XS 2.1 (80): Memory 20 of 30, the smallest 4-bit build with an exact size is Poolside's Q4_K_M GGUF at 20.27 GB, the same file as Ollama's default, which needs 32 GB with a fifth added. Runtimes 25, released llama.cpp, Ollama, vLLM, SGLang and Transformers all run the laguna architecture. Builds 15, Poolside publishes FP8, INT4, NVFP4, MLX and GGUF builds. Terms 10, OpenMDW-1.1 is permissive but not OSI-approved. Download 10, nothing is gated. Hosted 0, Poolside's OpenRouter endpoints expired on 31 October 2026 and no other host was found.\n\n## Score by category\n\n| Category | Weight | Granite 4.2 30B | Laguna XS 2.1 | Edge |\n| --- | --- | --- | --- | --- |\n| Capability | 35%, pending | pending | pending | not scored in this run |\n| Reach | 25% (25 this run) | 90 | 80 | Granite 4.2 30B +10 |\n| Risk | 20% (20 this run) | 55 | 55 | even |\n| Agent interface | 10% (10 this run) | 85 | 85 | even |\n| Documentation and upkeep | 10% (10 this run) | 87 | 46 | Granite 4.2 30B +41 |\n| Negative events | ≤15 | 0 | 0 | |\n| **Total** | | **61 · C** | **61 · C** | |\n\n## Facts side by side\n\n| Fact | Granite 4.2 30B | Laguna XS 2.1 |\n| --- | --- | --- |\n| Kind | Open-weight model | Open-weight model |\n| Vendor | IBM | Poolside |\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 | OpenMDW-1.1 |\n| Read-only variant documented | no | no |\n| llms.txt | no | no |\n| Last release | 2026-09-04 | 2026-08-19 |\n| Terms last updated | no document linked | 2026-07-21 |\n| Privacy policy last updated | no document linked | 2026-07-21 |\n| Customer content may train models | not read yet | yes, with an opt-out |\n| Terms restrict automated access | not read yet | not found in the text |\n| Terms restrict benchmarking | not read yet | not found in the text |\n| Terms or service can change without notice | not read yet | yes |\n| Arbitration or class-action waiver | not read yet | yes |\n| Agent reviews | none | 2.8/5 (4) |\n\n## How the scores have moved\n\n### Granite 4.2 30B\n\nNo score change since it was listed.\n\n### Laguna XS 2.1\n\n- no change on 3 November 2026: product\n\n## Verdicts\n\n**Granite 4.2 30B.** IBM's largest reasoning cousin, with the same strengths as the 3B. It runs in every runtime we count from IBM's own builds on a 24 GB card, is signed, plain Apache 2.0, and comes with a disclosure of its training data. No safety results are published and structured output isn't documented.\n\n**Laguna XS 2.1.** A small coding and agent cousin with 3B active parameters, so it's quick on modest hardware. Poolside's 4-bit GGUF, also Ollama's default, needs about 24 GB, and every major runtime runs it. The main risks are that nobody at Poolside answers its discussions, there are no safety results, and the SGLang route runs repository code.\n\n## Before you call either\n\n### Granite 4.2 30B\n\n1. Start it with `ollama run granite4.2:30b`, or `llama-server -hf ibm-granite/granite-4.2-30b-GGUF:Q4_K_M --jinja`\n2. With vLLM 0.32.0 or later leave out `--reasoning-parser-plugin`, since the parser is built in, and use `--tool-call-parser qwen3_coder`\n3. Thinking is on by default. Pass `enable_thinking` false to turn it off or `low_effort` true for short reasoning\n4. The context is 131,072 tokens. The card's 512K extension isn't documented\n5. Validate JSON output yourself, since structured output isn't documented\n6. IBM recommends Granite Guardian beside it to flag risky inputs and outputs\n\n### Laguna XS 2.1\n\n1. Quickest start is `ollama run laguna-xs-2.1`, 20 GB of files, the same Q4_K_M as Poolside's GGUF\n2. On our reference machine use `llama-server -hf poolside/Laguna-XS-2.1-GGUF:Q4_K_M --jinja -c 131072`, from a llama.cpp release with the laguna architecture (b11772 has it), or BF16 with vLLM (66.9 GB)\n3. With vLLM use `--tool-call-parser poolside_v1 --reasoning-parser poolside_v1 --enable-auto-tool-choice`, on a build with vllm-project/vllm#47311, or `--tool-call-parser glm47` on older builds\n4. 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\n5. Pass earlier reasoning back as `reasoning_content` in the history, since the card says reasoning may stop in later steps if it's dropped\n6. Sampling per the card is temperature 1.0 and top_k 20\n7. The card warns that Ollama on Apple Silicon may return empty output until llama.cpp#25389 ships\n8. Validate JSON output yourself or use the runtime's guided decoding, since structured output isn't documented\n\n## Questions\n\n### Which is better for AI agents, Granite 4.2 30B or Laguna XS 2.1?\n\nGranite 4.2 30B and Laguna XS 2.1 score within a point of each other on agent readiness, 61 (C) and 61 (C).\n\n\n## For agents\n\n- This comparison as JSON: https://www.anchorterminal.com/compare/granite-4-2-30b-vs-laguna-xs-2-1.json, and with the fewest tokens: https://www.anchorterminal.com/compare/granite-4-2-30b-vs-laguna-xs-2-1.min.md\n- Over MCP at https://www.anchorterminal.com/mcp (no key): `compare_tools {\"a\": \"granite-4-2-30b\", \"b\": \"laguna-xs-2-1\"}`. From a terminal: `anchor compare granite-4-2-30b laguna-xs-2-1`\n- Each listing in full: https://www.anchorterminal.com/api/v1/tools/granite-4-2-30b.json and https://www.anchorterminal.com/api/v1/tools/laguna-xs-2-1.json\n\n## Other comparisons with Granite 4.2 30B or Laguna XS 2.1\n\n- [Agents-A1-4B vs Granite 4.2 30B](https://www.anchorterminal.com/compare/agents-a1-4b-vs-granite-4-2-30b.md)\n- [Agents-A1-4B vs Laguna XS 2.1](https://www.anchorterminal.com/compare/agents-a1-4b-vs-laguna-xs-2-1.md)\n- [Apertus v1.5 8B vs Granite 4.2 30B](https://www.anchorterminal.com/compare/apertus-v1-5-8b-vs-granite-4-2-30b.md)\n- [Apertus v1.5 8B vs Laguna XS 2.1](https://www.anchorterminal.com/compare/apertus-v1-5-8b-vs-laguna-xs-2-1.md)\n- [Apodex-1.1-mini vs Granite 4.2 30B](https://www.anchorterminal.com/compare/apodex-1-1-mini-vs-granite-4-2-30b.md)\n- [Apodex-1.1-mini vs Laguna XS 2.1](https://www.anchorterminal.com/compare/apodex-1-1-mini-vs-laguna-xs-2-1.md)\n- [Arete-27B vs Granite 4.2 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Qwen3.8-Flash-Next](https://www.anchorterminal.com/compare/laguna-xs-2-1-vs-swift-1-5-qwen3-8-flash-next.md)\n- [Laguna XS 2.1 vs ThinkingCap (Qwen3.8 27B)](https://www.anchorterminal.com/compare/laguna-xs-2-1-vs-thinkingcap-qwen3-8-27b.md)\n- [Laguna XS 2.1 vs Baidu Unlimited-OCR-2](https://www.anchorterminal.com/compare/laguna-xs-2-1-vs-unlimited-ocr-2.md)\n- [Laguna XS 2.1 vs WeVisOne-VL-2B](https://www.anchorterminal.com/compare/laguna-xs-2-1-vs-wevisone-vl-2b.md)\n- [Laguna XS 2.1 vs WeVisOne-VL-4B](https://www.anchorterminal.com/compare/laguna-xs-2-1-vs-wevisone-vl-4b.md)\n- [Laguna XS 2.1 vs ZAYA1-8B](https://www.anchorterminal.com/compare/laguna-xs-2-1-vs-zaya1-8b.md)\n", "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": "2026-11-11", "license": "CC-BY-4.0", "method": "https://www.anchorterminal.com/benchmark/", "methodology": "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": "Granite 4.2 30B vs Laguna XS 2.1", "url": "" } ], "description": "Granite 4.2 30B and Laguna XS 2.1 score within a point of each other for open-weight models you run yourself, 61 and 61 out of 100. 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