{ "data": { "a": { "slug": "cosmos-reason2-2b", "name": "Cosmos-Reason2-2B", "vendor": "NVIDIA", "vendorUrl": "https://github.com/nvidia-cosmos/cosmos-reason2", "kind": "weights", "category": "open-weights", "summary": "Cosmos-Reason2-2B is NVIDIA's open-weight vision language model for physical AI and robotics, a 2.4B-parameter fine-tune of Qwen3-VL-2B-Instruct that reasons over video and images. The repository is gated behind a click-through licence.", "url": "https://www.anchorterminal.com/tools/cosmos-reason2-2b", "markdownUrl": "https://www.anchorterminal.com/tools/cosmos-reason2-2b.md", "slimMarkdownUrl": "https://www.anchorterminal.com/tools/cosmos-reason2-2b.min.md", "jsonUrl": "https://www.anchorterminal.com/api/v1/tools/cosmos-reason2-2b.json", "dns": "cosmos-reason2-2b.grade.anchorterminal.com", "repo": "https://huggingface.co/nvidia/Cosmos-Reason2-2B", "license": "NVIDIA Open Model License (custom, commercial use allowed, not an OSI licence); built on Qwen3-VL-2B-Instruct under Apache 2.0", "transports": [], "packages": [ { "registry": "huggingface", "name": "nvidia/Cosmos-Reason2-2B" } ], "auth": "none", "authNotes": "The repository is gated (gated: auto). Downloading needs a Hugging Face account and token and accepting the NVIDIA Open Model License on the card, which Hugging Face approves automatically. The card, the file list and the licence text are public. We didn't accept the terms (checked 2026-10-21).", "pricing": "free", "pricingNotes": "Free to download and use, commercial use included, under the NVIDIA Open Model License, with a contact for a custom licence. Running it costs the hardware, 4.9 GB of BF16 safetensors by the Hub's file list; NVIDIA states a minimum of 24 GB of GPU memory (checked 2026-10-21).", "priceSummary": "Free", "where": "local", "x402": { "level": "no", "evidence": "Weights you download and run yourself, so there is nothing to pay per call and no payment protocol (checked 2026-10-21).", "endpoints": [] }, "toolCount": null, "popularity": { "githubStars": null, "npmWeekly": null, "pypiWeekly": null, "asOf": "2026-11-04" }, "docsUrl": "https://github.com/nvidia-cosmos/cosmos-reason2", "capabilities": [ "model.open-weights" ], "tags": [ "open-weights", "model", "dense", "vision", "video", "reasoning", "robotics", "physical-ai", "fine-tune", "safetensors", "gated", "self-hosted" ], "lastRelease": "2026-03-10", "graded": true, "anchor": { "graded": true, "score": 59.5, "grade": "C", "agentReady": false, "rank": 0, "ranked": false, "notRankedWhy": "An open-weight model, graded by the open-weight checklist and ranked among open-weight models, not against tools", "rankOf": 1518, "categoryRank": 75, "methodology": "0.7", "run": "2026-10-01", "scores": { "interface": 65, "reach": 65, "risk": 60, "upkeep": 39 }, "pending": [ "performance", "tasks" ], "assessment": { "confidence": "low", "date": "2026-11-04" }, "negative": 0, "verdict": "A small local model for reasoning over video and images in robotics, driving and warehouse scenes, returning points, boxes and timed events as JSON. The 4.9 GB file runs in Transformers or vLLM, though NVIDIA asks for 24 GB of GPU memory. Development has moved to Cosmos 3, and the gated licence is revocable.", "bestFor": "Agents that need a small local model to reason over camera footage and images for robotics, driving or smart spaces", "strengths": [ "4.9 GB of BF16 safetensors with no remote code, loaded by Transformers' own Qwen3-VL class", "Runs on released Transformers, vLLM, SGLang and llama.cpp through the Qwen3-VL architecture", "NVIDIA's prompt files give JSON formats for bounding boxes, timed events and robot trajectories", "Reasoning is prompted with a documented think and answer format and parsed by vLLM's qwen3 parser", "Commercial use allowed, files in NVIDIA's own organisation with hashes" ], "weaknesses": [ "Gated behind a click-through licence that needs a Hugging Face account", "The licence is revocable, can be updated by NVIDIA and ends if a guardrail is bypassed", "NVIDIA says the repository is no longer under active development and points to Cosmos 3", "No quantised build from NVIDIA, no hosted endpoint for the 2B, and no NVIDIA reply in its discussions", "No documented tool calling, no safety results and no training data sizes or cut-off" ], "agentNotes": [ "Accept the licence on the Hugging Face card with a signed-in account and set HF_TOKEN before downloading", "Serve it with `vllm serve nvidia/Cosmos-Reason2-2B --max-model-len 16384 --media-io-kwargs '{\"video\": {\"num_frames\": -1}}' --reasoning-parser qwen3`, keeping max-model-len between 8,192 and 16,384 as NVIDIA advises", "For local video or images, make a folder for them (`mkdir -p media`) and pass `--allowed-local-media-path \"$(pwd)/media\"`, so the server can read only that folder, not everything under the directory you start it from", "Sample video at 4 fps and allow at least 4,096 output tokens so the reasoning isn't cut off", "For reasoning, add the card's instruction to answer with a think block and then the answer; leave it out for a direct reply", "Use NVIDIA's prompt files (prompts/*.yaml in nvidia-cosmos/cosmos-reason2) when you want JSON boxes, events or trajectories, and validate the JSON yourself", "Check its plans before a robot acts on them, since NVIDIA's own safety card warns of collision and manipulation risks" ], "metrics": { "kind": "local", "measured": false }, "reviewCount": 4, "avgRating": 2.5, "history": [ { "basis": "public evidence", "confidence": "low", "grade": "C", "methodology": "0.7", "pending": [ "performance", "tasks" ], "run": "2026-10-01", "runLabel": "October 2026 research run", "score": 59.5 } ], "editorialScores": { "interface": 65, "reach": 65, "risk": 60, "upkeep": 39 }, "provenanceScore": 70, "checked": { "categories": { "interface": "2026-11-04", "reach": "2026-11-04", "risk": "2026-11-04", "upkeep": "2026-11-04" }, "last": "2026-11-04", "oldest": "2026-11-04", "stale": false, "staleAfterDays": 90 } }, "connect": { "install": "# accept the licence on the Hugging Face card first, then set HF_TOKEN\nvllm serve nvidia/Cosmos-Reason2-2B --max-model-len 16384 \\\n --media-io-kwargs '{\"video\": {\"num_frames\": -1}}' --reasoning-parser qwen3 --port 8000", "http": "curl http://localhost:8000/v1/chat/completions \\\n -H 'Content-Type: application/json' \\\n -d '{\"model\": \"nvidia/Cosmos-Reason2-2B\", \"max_tokens\": 4096, \"messages\": [{\"role\": \"user\", \"content\": [{\"type\": \"image_url\", \"image_url\": {\"url\": \"file:///path/to/frame.jpg\"}}, {\"type\": \"text\", \"text\": \"Is it safe to turn right?\"}]}]}'" }, "letme": { "capability": "https://letme.dev/model.open-weights", "tool": "https://letme.dev/cosmos-reason2-2b" }, "sameCompany": [ "nemotron-3-5-super-vl", "nvidia-nemo-retriever", "nemo-guardrails", "nemotron-3-5-asr-streaming-0-6b", "nemotron-3-5-transcribe-30b-a4b", "parakeet-tdt-0-6b-v3", "parakeet-unified-en-0-6b", "nemotron-3-5-parse", "nemotron-3-5-bolt-e4b-4gb", "nemotron-3-nano-30b-a3b", "nemotron-3-nano-4b", "nemotron-3-nano-omni-30b-a3b-reasoning", "nemotron-3-super-120b-a12b", "nemotron-3-ultra-550b-a55b", "nemotron-3-5-lightning-30b-a3b" ], "weights": { "trainedBy": "NVIDIA", "builtOn": "Qwen/Qwen3-VL-2B-Instruct (fine-tune, Apache 2.0)", "params": "2.44B", "context": 262144, "goodFor": "Small vision language model for physical AI, reasoning over video and images for robots, driving and smart spaces, with point and box outputs.", "runtimes": [ "Transformers", "vLLM", "SGLang", "llama.cpp" ], "builds": [ { "name": "Cosmos-Reason2-2B", "url": "https://huggingface.co/nvidia/Cosmos-Reason2-2B", "who": "publisher", "precision": "bf16", "sizeGB": 4.9, "memoryGB": 8, "format": "safetensors", "note": "Gated (click-through). NVIDIA states a minimum of 24 GB of GPU memory, more than the file size suggests, presumably for video input" } ], "run": "vllm serve nvidia/Cosmos-Reason2-2B --allowed-local-media-path \"$(pwd)/media\" --max-model-len 16384 --media-io-kwargs '{\"video\": {\"num_frames\": -1}}' --reasoning-parser qwen3 --port 8000", "runBuild": "Cosmos-Reason2-2B", "checked": "2026-10-21", "minMemoryGB": 8 }, "family": { "lab": "NVIDIA (Nemotron)", "family": "Cosmos-Reason2", "url": "https://www.anchorterminal.com/open-weights/#nvidia", "others": [ { "name": "Cosmos-Reason2-8B", "url": "https://huggingface.co/nvidia/Cosmos-Reason2-8B", "params": "8B (8.77B per the safetensors count)" }, { "name": "Cosmos-Reason2-32B", "url": "https://huggingface.co/nvidia/Cosmos-Reason2-32B", "params": "32B (33.36B per the safetensors count)" } ], "olderCount": 47, "unrestrictedCopies": 3 }, "area": "models", "provenance": { "legalEntity": "NVIDIA Corporation", "domain": "nvidia.com", "domainRegistered": "1993-04-20", "endpointOnVendorDomain": null, "terms": "https://www.nvidia.com/en-us/agreements/enterprise-software/nvidia-open-model-license/", "privacy": "", "statusPage": "", "changelog": "https://github.com/nvidia-cosmos/cosmos-reason2/commits/main", "securityTxt": "none", "checked": "2026-10-21", "notes": [ "The card names NVIDIA as model developer and the licence names NVIDIA Corporation. The domain registration date is carried from the RDAP check made for nemotron-3-nano-30b-a3b on 21 October 2026.", "Nothing is hosted for this listing, so the NVIDIA Open Model License stands in for terms of service and no privacy policy is scored.", "The Hugging Face commit history is behind the gate, so the changelog is the GitHub repository's, whose README carries dated news entries from 19 December 2025 to 1 June 2026.", "www.nvidia.com/.well-known/security.txt answered 403 at the 21 October 2026 check for nemotron-3-nano-30b-a3b. The card links NVIDIA's security vulnerability form." ], "score": 70 }, "pageJsonUrl": "https://www.anchorterminal.com/tools/cosmos-reason2-2b.json", "live": { "slug": "cosmos-reason2-2b", "securityTxt": { "url": "https://nvidia.com/.well-known/security.txt", "state": "unknown", "checkedAt": "2026-11-10T16:08:00.271598775Z" }, "domain": { "domain": "nvidia.com", "registered": "1993-04-20", "source": "https://rdap.verisign.com/com/v1/domain/nvidia.com", "checkedAt": "2026-11-08T15:03:11.895084282Z" }, "pages": [ { "url": "https://www.nvidia.com/en-us/agreements/enterprise-software/nvidia-open-model-license/", "kind": "terms", "status": 304, "checkedAt": "2026-11-10T16:43:29.102317163Z", "changedAt": "2026-10-31T06:30:16.800317464Z", "fingerprint": "657e4e24049b" } ], "updatedAt": "2026-11-10T16:43:29.102317163Z" } }, "answer": "Granite 4.2 8B scores 61 (C) on agent readiness against Cosmos-Reason2-2B's 59.5 (C), and leads in 3 of 4 scored categories. Cosmos-Reason2-2B leads on risk.", "b": { "slug": "granite-4-2-8b", "name": "Granite 4.2 8B", "vendor": "IBM", "vendorUrl": "https://www.ibm.com/granite", "kind": "weights", "category": "open-weights", "summary": "Granite 4.2 8B is IBM's open-weight dense reasoning model of 8.8B parameters, post-trained from Granite 4.1 8B 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-4-2-8b", "markdownUrl": "https://www.anchorterminal.com/tools/granite-4-2-8b.md", "slimMarkdownUrl": "https://www.anchorterminal.com/tools/granite-4-2-8b.min.md", "jsonUrl": "https://www.anchorterminal.com/api/v1/tools/granite-4-2-8b.json", "dns": "granite-4-2-8b.grade.anchorterminal.com", "repo": "https://huggingface.co/ibm-granite/granite-4.2-8b", "license": "Apache-2.0", "transports": [], "packages": [ { "registry": "huggingface", "name": "ibm-granite/granite-4.2-8b" }, { "registry": "huggingface", "name": "ibm-granite/granite-4.2-8b-GGUF" }, { "registry": "huggingface", "name": "ibm-granite/granite-4.2-8b-fp8" }, { "registry": "huggingface", "name": "ibm-granite/granite-4.2-8b-mxfp4" }, { "registry": "huggingface", "name": "ibm-granite/granite-4.2-8b-nvfp4" }, { "registry": "huggingface", "name": "ibm-granite/granite-4.2-8b-q4-mlx" }, { "registry": "ollama", "name": "granite4.2:8b" } ], "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, 17.6 GB for the BF16 files, 5.3 GB for IBM's Q4_K_M GGUF or 5.0 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-4.2-8b", "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": "2026-10-20", "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": 53, "methodology": "0.7", "run": "2026-10-01", "scores": { "interface": 85, "reach": 95, "risk": 55, "upkeep": 92 }, "pending": [ "performance", "tasks" ], "assessment": { "confidence": "low", "date": "2026-11-10" }, "negative": 0, "verdict": "IBM's mid-size reasoning cousin, with the same strengths as the 3B. It runs in every runtime we count from IBM's own builds on a 16 GB machine, 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 16 GB machine", "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 granite4.2:8b`, or `llama-server -hf ibm-granite/granite-4.2-8b-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": 95, "risk": 55, "upkeep": 92 }, "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 granite4.2:8b\n# or, with llama.cpp and IBM's own GGUF:\nllama-server -hf ibm-granite/granite-4.2-8b-GGUF:Q4_K_M --jinja\n# or, with vLLM 0.32.0 or later:\nvllm serve ibm-granite/granite-4.2-8b --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\": \"granite4.2:8b\", \"messages\": [{\"role\": \"user\", \"content\": \"Hello!\"}]}'" }, "letme": { "capability": "https://letme.dev/model.open-weights", "tool": "https://letme.dev/granite-4-2-8b" }, "sameCompany": [ "granite-embedding-small-english-r2", "granite-guardian", "granite-speech-5-0-2b", "ibm-watson-stt", "granite-switch", "granite-4-2-30b", "granite-4-2-3b" ], "weights": { "trainedBy": "IBM", "builtOn": "ibm-granite/granite-4.1-8b-base (IBM's own base checkpoint, post-trained; named on the card and in its metadata)", "params": "8.79B", "context": 131072, "goodFor": "Mid-size dense reasoning model for tool calling, coding and multilingual chat on a laptop GPU, with thinking that is on, off or short per request.", "runtimes": [ "llama.cpp", "Ollama", "vLLM", "SGLang", "Transformers" ], "builds": [ { "name": "granite-4.2-8b-nvfp4", "url": "https://huggingface.co/ibm-granite/granite-4.2-8b-nvfp4", "who": "publisher", "precision": "nvfp4", "sizeGB": 6.13, "memoryGB": 8, "format": "safetensors", "runsOn": [ "vLLM" ] }, { "name": "granite-4.2-8b-mxfp4", "url": "https://huggingface.co/ibm-granite/granite-4.2-8b-mxfp4", "who": "publisher", "precision": "mxfp4", "sizeGB": 5.88, "memoryGB": 8, "format": "safetensors", "runsOn": [ "vLLM" ] }, { "name": "granite-4.2-8b-Q4_K_M", "url": "https://huggingface.co/ibm-granite/granite-4.2-8b-GGUF", "who": "publisher", "precision": "q4_k_m", "sizeGB": 5.35, "memoryGB": 8, "format": "gguf", "runsOn": [ "llama.cpp" ], "note": "IBM's GGUF repository also holds Q4_0 (5.06 GB), Q6_K and BF16 files among others" }, { "name": "granite-4.2-8b-q4-mlx", "url": "https://huggingface.co/ibm-granite/granite-4.2-8b-q4-mlx", "who": "publisher", "precision": "q4", "sizeGB": 4.95, "memoryGB": 8, "format": "mlx", "runsOn": [ "mlx-lm" ], "note": "The smallest build at 4-bit or better. IBM also publishes q8-mlx (9.34 GB) and bf16-mlx" }, { "name": "ollama granite4.2:8b", "url": "https://ollama.com/library/granite4.2:8b", "who": "ollama", "precision": "q4_k_m", "sizeGB": 5.3, "memoryGB": 8, "format": "ollama", "runsOn": [ "Ollama" ], "note": "Ollama's library build, size as its tags page shows it on 10 November 2026" }, { "name": "granite-4.2-8b-fp8", "url": "https://huggingface.co/ibm-granite/granite-4.2-8b-fp8", "who": "publisher", "precision": "fp8", "sizeGB": 9.62, "memoryGB": 12, "format": "safetensors", "runsOn": [ "vLLM" ] }, { "name": "granite-4.2-8b-Q8_0", "url": "https://huggingface.co/ibm-granite/granite-4.2-8b-GGUF", "who": "publisher", "precision": "q8_0", "sizeGB": 9.35, "memoryGB": 12, "format": "gguf", "runsOn": [ "llama.cpp" ] }, { "name": "granite-4.2-8b", "url": "https://huggingface.co/ibm-granite/granite-4.2-8b", "who": "publisher", "precision": "bf16", "sizeGB": 17.58, "memoryGB": 24, "format": "safetensors", "runsOn": [ "vLLM", "SGLang", "Transformers" ] } ], "run": "ollama run granite4.2:8b", "runBuild": "ollama granite4.2:8b", "checked": "2026-11-10", "minMemoryGB": 8 }, "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-4.2-30b", "url": "https://huggingface.co/ibm-granite/granite-4.2-30b", "params": "30B (Hub safetensors count 29.28B)", "listing": "https://www.anchorterminal.com/tools/granite-4-2-30b" }, { "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-4.2-8b/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-4-2-8b.json" }, "edges": [ { "by": 53, "category": "upkeep", "leads": "granite-4-2-8b", "name": "Documentation and upkeep", "reasons": { "a": "The card misses languages and a cut-off (14). Training data is named by dataset without sizes or a cut-off (5). The Hub repository last changed on 30 April 2026, 188 days before this check, which alone gives 5. NVIDIA's GitHub repository last changed with a README redirect to Cosmos 3 on 7 June 2026, 150 days back, and this run counts the publisher's documentation commits on this line (10). None of its 3 discussions has an NVIDIA reply, counted by author flags on 4 November (0). The 2B's weights were replaced in place in March with a dated line, and the family is now superseded by Cosmos 3 with a dated note (5). The gated files couldn't be checked against the card, which itself mixes float16 and BF16 and links a newer licence than the gate shows (5). 14 + 5 + 10 + 0 + 5 + 5 = 39.", "b": "Model card 17, Intended use (best for), limitations (ethical considerations and limitations), architecture, parameters (8B), context length (128K native) and 12 tested languages are on the card. Training data 20, IBM's disclosure file for the 8B lists the datasets used in pre-training and post-training as machine-readable metadata, and the card describes the three training stages. Last change 20, the last commit, on 20 October 2026, replaced model.safetensors.index.json (titled \"granite-4.2 index file fix\"), 21 days before this check. Responsiveness 20, Of the 5 discussions that aren't pull requests (13 September to 5 November 2026), 4 have a reply from an ibm-granite member. Version policy 5, Granite 4.1 8B 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 + 20 + 20 + 5 + 10 = 92." }, "scores": { "a": 39, "b": 92 } }, { "by": 30, "category": "reach", "leads": "granite-4-2-8b", "name": "Reach", "reasons": { "a": "Memory earns the full 30 because the BF16 file is 4.9 GB, about 5.9 GB with the fifth added, though NVIDIA itself asks for 24 GB of GPU memory. Runtimes get 20 because the model keeps Qwen3-VL's architecture, which Transformers, vLLM, SGLang and llama.cpp run in released versions, while LM Studio's catalogue has only the base. Builds score 0, as NVIDIA publishes no quantised build of the 2B. The NVIDIA Open Model License allows free commercial use under a use policy (10). The gate is an automatic click-through that needs an account (5), and nothing hosts the 2B (0).", "b": "Memory 30, IBM's own 4-bit MLX build granite-4.2-8b-q4-mlx is 4.95 GB, and 4.95 GB × 1.2 = 5.9 GB, within 8 GB. Its Q4_0 GGUF is 5.06 GB and Ollama's library build granite4.2:8b (5.3 GB) fits 8 GB too. 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, 8b 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. 30 + 25 + 15 + 15 + 10 + 0 = 95." }, "scores": { "a": 65, "b": 95 } }, { "by": 20, "category": "interface", "leads": "granite-4-2-8b", "name": "Agent interface", "reasons": { "a": "A Jinja template ships as chat_template.json (20). Tools are declared only by the template it inherits from Qwen3-VL, with no NVIDIA documentation or parser (10), and nothing shows the 2B was trained for tool use (0). NVIDIA's prompt files ask for JSON with named keys for boxes, events and trajectories (15). Reasoning is asked for in the prompt and vLLM's qwen3 parser returns it apart (10). The card states 256K input tokens (10).", "b": "Chat template 20, chat_template.jinja in the repository, with roles, tools, tool responses, the thinking switch and low effort. Tool-calling format 25, the card has tool-calling sections for vLLM and SGLang, declares tools with OpenAI's function schema and names the parser to use, qwen3_coder, which both runtimes ship in the released versions read. Trained tool calling 20, the template loops over every entry in an assistant turn's tool_calls, so it renders several calls in one turn, and the card names tool calling and agentic workflows as what it's best for. Structured output 0, the card doesn't document JSON or JSON Schema output or how to ask for it. Reasoning control 10, the card documents thinking on by default, non-thinking and low-effort modes per request through the template (enable_thinking and low_effort), with the reasoning returned apart from the answer. Context 10, 131,072 tokens natively per the card and config.json. 20 + 25 + 20 + 0 + 10 + 10 = 85." }, "scores": { "a": 65, "b": 85 } }, { "by": 5, "category": "risk", "leads": "cosmos-reason2-2b", "name": "Risk", "reasons": { "a": "File safety gets the full 25, one safetensors file loaded by Transformers' own code with a template, no remote code. Provenance gets 15 for files in NVIDIA's own organisation with hashes. The licence has a use policy and guardrail clause and NVIDIA can revoke or update it, so licence risk keeps 5 of 15. NVIDIA's PSIRT route and bulletins give the security programme 10. Agent guidance gets 5 for general cautions about guardrails and physical risk, and safety evaluation 0, with no safety results.", "b": "File safety 15, safetensors only, no .bin, .pt or .pth files (25). Provenance 15, the files sit in the ibm-granite organisation, which IBM's Granite docs and the GitHub README link to (10). Safety evaluation 0, no safety results on the card. Agent guidance 5, General cautions. Licence risk 15, Apache 2.0 has no use policy, field-of-use limit, threshold or change clause, and the card's licence link resolves. Security programme 5, www.ibm.com/.well-known/security.txt names IBM PSIRT, read for the 3B listing on 4 November 2026 (5). 15 + 15 + 0 + 5 + 15 + 5 = 55." }, "scores": { "a": 60, "b": 55 } } ], "facts": [ { "a": "Open-weight model", "b": "Open-weight model", "name": "Kind" }, { "a": "NVIDIA", "b": "IBM", "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": "NVIDIA Open Model License (custom, commercial use allowed, not an OSI licence); built on Qwen3-VL-2B-Instruct under Apache 2.0", "b": "Apache-2.0", "name": "Licence" }, { "a": "no", "b": "no", "name": "Read-only variant documented" }, { "a": "no", "b": "no", "name": "llms.txt" }, { "a": "2026-03-10", "b": "2026-10-20", "name": "Last release" }, { "a": "2025-10-24", "b": "no document linked", "name": "Terms last updated" }, { "a": "no document linked", "b": "no document linked", "name": "Privacy policy last updated" }, { "a": "yes", "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": "not found in the text", "b": "not read yet", "name": "Terms or service can change without notice" }, { "a": "not found in the text", "b": "not read yet", "name": "Arbitration or class-action waiver" }, { "a": "2.5/5 (4)", "b": "none", "name": "Agent reviews" } ], "faq": [ { "answer": "Granite 4.2 8B scores 61 (C) on agent readiness against Cosmos-Reason2-2B's 59.5 (C), and leads in 3 of 4 scored categories. Cosmos-Reason2-2B leads on risk.", "question": "Which is better for AI agents, Cosmos-Reason2-2B or Granite 4.2 8B?" } ], "goodFor": [ { "aheadOn": [ "Risk, 60 against 55" ], "also": null, "goodFor": "Agents that need a small local model to reason over camera footage and images for robotics, driving or smart spaces", "slug": "cosmos-reason2-2b", "watchFor": "Gated behind a click-through licence that needs a Hugging Face account" }, { "aheadOn": [ "Reach, 95 against 65", "Agent interface, 85 against 65", "Documentation and upkeep, 92 against 39" ], "also": null, "goodFor": "Agents that want a documented, signed, Apache 2.0 reasoning model with tool calling on a 16 GB machine", "slug": "granite-4-2-8b", "watchFor": "No safety results published for it" } ], "history": null, "job": { "capability": "model.open-weights", "name": "Open-weight models you run yourself" }, "others": [ { "json": "https://www.anchorterminal.com/compare/agents-a1-4b-vs-cosmos-reason2-2b.json", "title": "Agents-A1-4B vs Cosmos-Reason2-2B", "url": "https://www.anchorterminal.com/compare/agents-a1-4b-vs-cosmos-reason2-2b" }, { "json": "https://www.anchorterminal.com/compare/agents-a1-4b-vs-granite-4-2-8b.json", "title": "Agents-A1-4B vs Granite 4.2 8B", "url": "https://www.anchorterminal.com/compare/agents-a1-4b-vs-granite-4-2-8b" }, { "json": "https://www.anchorterminal.com/compare/apertus-v1-5-8b-vs-cosmos-reason2-2b.json", "title": "Apertus v1.5 8B vs Cosmos-Reason2-2B", "url": "https://www.anchorterminal.com/compare/apertus-v1-5-8b-vs-cosmos-reason2-2b" }, { "json": "https://www.anchorterminal.com/compare/apertus-v1-5-8b-vs-granite-4-2-8b.json", "title": "Apertus v1.5 8B vs Granite 4.2 8B", "url": "https://www.anchorterminal.com/compare/apertus-v1-5-8b-vs-granite-4-2-8b" }, { "json": "https://www.anchorterminal.com/compare/apodex-1-1-mini-vs-cosmos-reason2-2b.json", "title": "Apodex-1.1-mini vs Cosmos-Reason2-2B", "url": 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4.2 8B vs Laguna S 2.1", "url": "https://www.anchorterminal.com/compare/granite-4-2-8b-vs-laguna-s-2-1" }, { "json": "https://www.anchorterminal.com/compare/granite-4-2-8b-vs-laguna-xs-2-1.json", "title": "Granite 4.2 8B vs Laguna XS 2.1", "url": "https://www.anchorterminal.com/compare/granite-4-2-8b-vs-laguna-xs-2-1" }, { "json": "https://www.anchorterminal.com/compare/granite-4-2-8b-vs-lbs-27b.json", "title": "Granite 4.2 8B vs LBS-27B", "url": "https://www.anchorterminal.com/compare/granite-4-2-8b-vs-lbs-27b" }, { "json": "https://www.anchorterminal.com/compare/granite-4-2-8b-vs-lfm2-5-2-6b.json", "title": "Granite 4.2 8B vs LFM2.5-2.6B", "url": "https://www.anchorterminal.com/compare/granite-4-2-8b-vs-lfm2-5-2-6b" }, { "json": "https://www.anchorterminal.com/compare/granite-4-2-8b-vs-lfm3-1-7b.json", "title": "Granite 4.2 8B vs LFM3-1.7B", "url": "https://www.anchorterminal.com/compare/granite-4-2-8b-vs-lfm3-1-7b" }, { "json": "https://www.anchorterminal.com/compare/granite-4-2-8b-vs-lfm3-audio-2b.json", "title": "Granite 4.2 8B vs LFM3-Audio-2B", "url": "https://www.anchorterminal.com/compare/granite-4-2-8b-vs-lfm3-audio-2b" }, { "json": "https://www.anchorterminal.com/compare/granite-4-2-8b-vs-lfm3-omni-2b.json", "title": "Granite 4.2 8B vs LFM3-Omni-2B", "url": "https://www.anchorterminal.com/compare/granite-4-2-8b-vs-lfm3-omni-2b" }, { "json": "https://www.anchorterminal.com/compare/granite-4-2-8b-vs-lfm3-vl-2b.json", "title": "Granite 4.2 8B vs LFM3-VL-2B", "url": "https://www.anchorterminal.com/compare/granite-4-2-8b-vs-lfm3-vl-2b" }, { "json": "https://www.anchorterminal.com/compare/granite-4-2-8b-vs-ling-3-0-tiny.json", "title": "Granite 4.2 8B vs Ling-3.0-tiny", "url": "https://www.anchorterminal.com/compare/granite-4-2-8b-vs-ling-3-0-tiny" }, { "json": "https://www.anchorterminal.com/compare/granite-4-2-8b-vs-ling-3-1-flash-1019.json", "title": "Granite 4.2 8B vs Ling-3.1-flash-1019", "url": "https://www.anchorterminal.com/compare/granite-4-2-8b-vs-ling-3-1-flash-1019" }, { "json": "https://www.anchorterminal.com/compare/granite-4-2-8b-vs-longcat-2-5.json", "title": "Granite 4.2 8B vs LongCat-2.5", "url": "https://www.anchorterminal.com/compare/granite-4-2-8b-vs-longcat-2-5" }, { "json": "https://www.anchorterminal.com/compare/granite-4-2-8b-vs-mimo-v2-6-distill-qwen-9b.json", "title": "Granite 4.2 8B vs MiMo-V2.6 Distill Qwen 9B", "url": "https://www.anchorterminal.com/compare/granite-4-2-8b-vs-mimo-v2-6-distill-qwen-9b" }, { "json": "https://www.anchorterminal.com/compare/granite-4-2-8b-vs-mimo-v2-6-flash-rl.json", "title": "Granite 4.2 8B vs MiMo-V2.6-Flash-RL", "url": "https://www.anchorterminal.com/compare/granite-4-2-8b-vs-mimo-v2-6-flash-rl" }, { "json": "https://www.anchorterminal.com/compare/granite-4-2-8b-vs-minicpm-o-4-5.json", "title": "Granite 4.2 8B vs MiniCPM-o 4.5", "url": "https://www.anchorterminal.com/compare/granite-4-2-8b-vs-minicpm-o-4-5" }, { "json": "https://www.anchorterminal.com/compare/granite-4-2-8b-vs-minicpm-v-4-7-1b.json", "title": "Granite 4.2 8B vs MiniCPM-V 4.7 1B", "url": "https://www.anchorterminal.com/compare/granite-4-2-8b-vs-minicpm-v-4-7-1b" }, { "json": "https://www.anchorterminal.com/compare/granite-4-2-8b-vs-minicpm-v-4-7-35b-a3b.json", "title": "Granite 4.2 8B vs MiniCPM-V 4.7 35B-A3B", "url": "https://www.anchorterminal.com/compare/granite-4-2-8b-vs-minicpm-v-4-7-35b-a3b" }, { "json": "https://www.anchorterminal.com/compare/granite-4-2-8b-vs-minicpm5-2b.json", "title": "Granite 4.2 8B vs MiniCPM5-2B", "url": "https://www.anchorterminal.com/compare/granite-4-2-8b-vs-minicpm5-2b" }, { "json": "https://www.anchorterminal.com/compare/granite-4-2-8b-vs-minimax-m2-5.json", "title": "Granite 4.2 8B vs MiniMax-M2.5", "url": "https://www.anchorterminal.com/compare/granite-4-2-8b-vs-minimax-m2-5" }, { "json": "https://www.anchorterminal.com/compare/granite-4-2-8b-vs-minimax-m2-7.json", "title": "Granite 4.2 8B vs MiniMax-M2.7", "url": "https://www.anchorterminal.com/compare/granite-4-2-8b-vs-minimax-m2-7" }, { "json": "https://www.anchorterminal.com/compare/granite-4-2-8b-vs-minimax-m3-1-flash.json", "title": "Granite 4.2 8B vs MiniMax-M3.1-Flash", "url": "https://www.anchorterminal.com/compare/granite-4-2-8b-vs-minimax-m3-1-flash" }, { "json": "https://www.anchorterminal.com/compare/granite-4-2-8b-vs-mistral-large-4.json", "title": "Granite 4.2 8B vs Mistral Large 4", "url": "https://www.anchorterminal.com/compare/granite-4-2-8b-vs-mistral-large-4" }, { "json": "https://www.anchorterminal.com/compare/granite-4-2-8b-vs-muse-glimmer-30b.json", "title": "Granite 4.2 8B vs Muse Glimmer 30B", "url": "https://www.anchorterminal.com/compare/granite-4-2-8b-vs-muse-glimmer-30b" }, { "json": "https://www.anchorterminal.com/compare/granite-4-2-8b-vs-nanbeige-4-2-3b.json", "title": "Granite 4.2 8B vs Nanbeige4.2-3B", "url": "https://www.anchorterminal.com/compare/granite-4-2-8b-vs-nanbeige-4-2-3b" }, { "json": "https://www.anchorterminal.com/compare/granite-4-2-8b-vs-nanbeige-4-3-33b.json", "title": "Granite 4.2 8B vs Nanbeige4.3-33B", "url": "https://www.anchorterminal.com/compare/granite-4-2-8b-vs-nanbeige-4-3-33b" }, { "json": "https://www.anchorterminal.com/compare/granite-4-2-8b-vs-nemotron-3-5-bolt-e4b-4gb.json", "title": "Granite 4.2 8B vs NVIDIA Nemotron 3.5 Bolt E4B 4GB", "url": "https://www.anchorterminal.com/compare/granite-4-2-8b-vs-nemotron-3-5-bolt-e4b-4gb" }, { "json": "https://www.anchorterminal.com/compare/granite-4-2-8b-vs-nemotron-3-5-lightning-30b-a3b.json", "title": "Granite 4.2 8B vs Nemotron 3.5 Lightning 30B A3B", "url": "https://www.anchorterminal.com/compare/granite-4-2-8b-vs-nemotron-3-5-lightning-30b-a3b" }, { "json": "https://www.anchorterminal.com/compare/granite-4-2-8b-vs-nemotron-3-nano-30b-a3b.json", "title": "Granite 4.2 8B vs Nemotron 3 Nano 30B A3B", "url": "https://www.anchorterminal.com/compare/granite-4-2-8b-vs-nemotron-3-nano-30b-a3b" }, { "json": "https://www.anchorterminal.com/compare/granite-4-2-8b-vs-nemotron-3-nano-4b.json", "title": "Granite 4.2 8B vs Nemotron 3 Nano 4B", "url": "https://www.anchorterminal.com/compare/granite-4-2-8b-vs-nemotron-3-nano-4b" }, { "json": "https://www.anchorterminal.com/compare/granite-4-2-8b-vs-nemotron-3-nano-omni-30b-a3b-reasoning.json", "title": "Granite 4.2 8B vs Nemotron 3 Nano Omni 30B A3B Reasoning", "url": "https://www.anchorterminal.com/compare/granite-4-2-8b-vs-nemotron-3-nano-omni-30b-a3b-reasoning" }, { "json": "https://www.anchorterminal.com/compare/granite-4-2-8b-vs-nemotron-3-super-120b-a12b.json", "title": "Granite 4.2 8B vs Nemotron 3 Super 120B A12B", "url": "https://www.anchorterminal.com/compare/granite-4-2-8b-vs-nemotron-3-super-120b-a12b" }, { "json": "https://www.anchorterminal.com/compare/granite-4-2-8b-vs-nemotron-3-ultra-550b-a55b.json", "title": "Granite 4.2 8B vs Nemotron 3 Ultra 550B A55B", "url": "https://www.anchorterminal.com/compare/granite-4-2-8b-vs-nemotron-3-ultra-550b-a55b" }, { "json": "https://www.anchorterminal.com/compare/granite-4-2-8b-vs-north-mini-code-1-0.json", "title": "Granite 4.2 8B vs North Mini Code 1.0", "url": "https://www.anchorterminal.com/compare/granite-4-2-8b-vs-north-mini-code-1-0" }, { "json": "https://www.anchorterminal.com/compare/granite-4-2-8b-vs-occamy-1-0.json", "title": "Granite 4.2 8B vs occamy-1.0", "url": "https://www.anchorterminal.com/compare/granite-4-2-8b-vs-occamy-1-0" }, { "json": "https://www.anchorterminal.com/compare/granite-4-2-8b-vs-olmo-3-7b-think.json", "title": "Granite 4.2 8B vs Olmo 3 7B Think", "url": "https://www.anchorterminal.com/compare/granite-4-2-8b-vs-olmo-3-7b-think" }, { "json": "https://www.anchorterminal.com/compare/granite-4-2-8b-vs-ornith-1-5-122b.json", "title": "Granite 4.2 8B vs Ornith-1.5-122B", "url": "https://www.anchorterminal.com/compare/granite-4-2-8b-vs-ornith-1-5-122b" }, { "json": "https://www.anchorterminal.com/compare/granite-4-2-8b-vs-ornith-1-5-35b-a3b.json", "title": "Granite 4.2 8B vs Ornith-1.5-35B-A3B", "url": "https://www.anchorterminal.com/compare/granite-4-2-8b-vs-ornith-1-5-35b-a3b" }, { "json": "https://www.anchorterminal.com/compare/granite-4-2-8b-vs-ornith-1-5-397b.json", "title": "Granite 4.2 8B vs Ornith-1.5-397B", "url": "https://www.anchorterminal.com/compare/granite-4-2-8b-vs-ornith-1-5-397b" }, { "json": "https://www.anchorterminal.com/compare/granite-4-2-8b-vs-ornith-1-5-9b.json", "title": "Granite 4.2 8B vs Ornith-1.5-9B", "url": "https://www.anchorterminal.com/compare/granite-4-2-8b-vs-ornith-1-5-9b" }, { "json": "https://www.anchorterminal.com/compare/granite-4-2-8b-vs-otel-2-0-llm-31b-it.json", "title": "Granite 4.2 8B vs OTel-2.0-LLM-31B-IT", "url": "https://www.anchorterminal.com/compare/granite-4-2-8b-vs-otel-2-0-llm-31b-it" }, { "json": "https://www.anchorterminal.com/compare/granite-4-2-8b-vs-qwen-agentworld-35b-a3b.json", "title": "Granite 4.2 8B vs Qwen-AgentWorld-35B-A3B", "url": "https://www.anchorterminal.com/compare/granite-4-2-8b-vs-qwen-agentworld-35b-a3b" }, { "json": "https://www.anchorterminal.com/compare/granite-4-2-8b-vs-qwen3-30b-a3b-instruct-2507.json", "title": "Granite 4.2 8B vs Qwen3-30B-A3B-Instruct-2507", "url": "https://www.anchorterminal.com/compare/granite-4-2-8b-vs-qwen3-30b-a3b-instruct-2507" }, { "json": "https://www.anchorterminal.com/compare/granite-4-2-8b-vs-qwen3-4b-instruct-2507.json", "title": "Granite 4.2 8B vs Qwen3-4B-Instruct-2507", "url": "https://www.anchorterminal.com/compare/granite-4-2-8b-vs-qwen3-4b-instruct-2507" }, { "json": "https://www.anchorterminal.com/compare/granite-4-2-8b-vs-qwen3-5-0-8b.json", "title": "Granite 4.2 8B vs Qwen3.5-0.8B", "url": "https://www.anchorterminal.com/compare/granite-4-2-8b-vs-qwen3-5-0-8b" }, { "json": "https://www.anchorterminal.com/compare/granite-4-2-8b-vs-qwen3-5-122b-a10b.json", "title": "Granite 4.2 8B vs Qwen3.5-122B-A10B", "url": "https://www.anchorterminal.com/compare/granite-4-2-8b-vs-qwen3-5-122b-a10b" }, { "json": "https://www.anchorterminal.com/compare/granite-4-2-8b-vs-qwen3-5-2b.json", "title": "Granite 4.2 8B vs Qwen3.5-2B", "url": "https://www.anchorterminal.com/compare/granite-4-2-8b-vs-qwen3-5-2b" }, { "json": "https://www.anchorterminal.com/compare/granite-4-2-8b-vs-qwen3-5-397b-a17b.json", "title": "Granite 4.2 8B vs Qwen3.5-397B-A17B", "url": "https://www.anchorterminal.com/compare/granite-4-2-8b-vs-qwen3-5-397b-a17b" }, { "json": "https://www.anchorterminal.com/compare/granite-4-2-8b-vs-qwen3-5-4b.json", "title": "Granite 4.2 8B vs Qwen3.5-4B", "url": "https://www.anchorterminal.com/compare/granite-4-2-8b-vs-qwen3-5-4b" }, { "json": "https://www.anchorterminal.com/compare/granite-4-2-8b-vs-qwen3-5-9b.json", "title": "Granite 4.2 8B vs Qwen3.5-9B", "url": "https://www.anchorterminal.com/compare/granite-4-2-8b-vs-qwen3-5-9b" }, { "json": "https://www.anchorterminal.com/compare/granite-4-2-8b-vs-qwen3-6-27b.json", "title": "Granite 4.2 8B vs Qwen3.6-27B", "url": "https://www.anchorterminal.com/compare/granite-4-2-8b-vs-qwen3-6-27b" }, { "json": "https://www.anchorterminal.com/compare/granite-4-2-8b-vs-qwen3-6-35b-a3b.json", "title": "Granite 4.2 8B vs Qwen3.6-35B-A3B", "url": "https://www.anchorterminal.com/compare/granite-4-2-8b-vs-qwen3-6-35b-a3b" }, { "json": "https://www.anchorterminal.com/compare/granite-4-2-8b-vs-qwen3-8-27b.json", "title": "Granite 4.2 8B vs Qwen3.8-27B", "url": "https://www.anchorterminal.com/compare/granite-4-2-8b-vs-qwen3-8-27b" }, { "json": "https://www.anchorterminal.com/compare/granite-4-2-8b-vs-qwen3-8-flash-next.json", "title": "Granite 4.2 8B vs Qwen3.8-Flash-Next", "url": "https://www.anchorterminal.com/compare/granite-4-2-8b-vs-qwen3-8-flash-next" }, { "json": "https://www.anchorterminal.com/compare/granite-4-2-8b-vs-qwen3-coder-30b-a3b-instruct.json", "title": "Granite 4.2 8B vs Qwen3-Coder-30B-A3B-Instruct", "url": "https://www.anchorterminal.com/compare/granite-4-2-8b-vs-qwen3-coder-30b-a3b-instruct" }, { "json": "https://www.anchorterminal.com/compare/granite-4-2-8b-vs-qwen3-coder-next.json", "title": "Granite 4.2 8B vs Qwen3-Coder-Next", "url": "https://www.anchorterminal.com/compare/granite-4-2-8b-vs-qwen3-coder-next" }, { "json": "https://www.anchorterminal.com/compare/granite-4-2-8b-vs-qwen3-omni-30b-a3b-instruct.json", "title": "Granite 4.2 8B vs Qwen3-Omni-30B-A3B-Instruct", "url": "https://www.anchorterminal.com/compare/granite-4-2-8b-vs-qwen3-omni-30b-a3b-instruct" }, { "json": "https://www.anchorterminal.com/compare/granite-4-2-8b-vs-qwen3-vl-2b-instruct.json", "title": "Granite 4.2 8B vs Qwen3-VL-2B-Instruct", "url": "https://www.anchorterminal.com/compare/granite-4-2-8b-vs-qwen3-vl-2b-instruct" }, { "json": "https://www.anchorterminal.com/compare/granite-4-2-8b-vs-qwen3-vl-30b-a3b-instruct.json", "title": "Granite 4.2 8B vs Qwen3-VL-30B-A3B-Instruct", "url": "https://www.anchorterminal.com/compare/granite-4-2-8b-vs-qwen3-vl-30b-a3b-instruct" }, { "json": "https://www.anchorterminal.com/compare/granite-4-2-8b-vs-qwen3-vl-32b-instruct.json", "title": "Granite 4.2 8B vs Qwen3-VL-32B-Instruct", "url": "https://www.anchorterminal.com/compare/granite-4-2-8b-vs-qwen3-vl-32b-instruct" }, { "json": "https://www.anchorterminal.com/compare/granite-4-2-8b-vs-qwen3-vl-4b-instruct.json", "title": "Granite 4.2 8B vs Qwen3-VL-4B-Instruct", "url": "https://www.anchorterminal.com/compare/granite-4-2-8b-vs-qwen3-vl-4b-instruct" }, { "json": "https://www.anchorterminal.com/compare/granite-4-2-8b-vs-qwen3-vl-8b-instruct.json", "title": "Granite 4.2 8B vs Qwen3-VL-8B-Instruct", "url": "https://www.anchorterminal.com/compare/granite-4-2-8b-vs-qwen3-vl-8b-instruct" }, { "json": "https://www.anchorterminal.com/compare/granite-4-2-8b-vs-qwopus3-8-27b-flash-v2.json", "title": "Granite 4.2 8B vs Qwopus3.8-27B-Flash-V2", "url": "https://www.anchorterminal.com/compare/granite-4-2-8b-vs-qwopus3-8-27b-flash-v2" }, { "json": "https://www.anchorterminal.com/compare/granite-4-2-8b-vs-recursive-flint.json", "title": "Granite 4.2 8B vs Recursive Flint", "url": "https://www.anchorterminal.com/compare/granite-4-2-8b-vs-recursive-flint" }, { "json": "https://www.anchorterminal.com/compare/granite-4-2-8b-vs-ripple-65b-preview.json", "title": "Granite 4.2 8B vs Ripple-65B Preview", "url": "https://www.anchorterminal.com/compare/granite-4-2-8b-vs-ripple-65b-preview" }, { "json": "https://www.anchorterminal.com/compare/granite-4-2-8b-vs-sensenova-loop-9b-preview.json", "title": "Granite 4.2 8B vs SenseNova-Loop-9B-Preview", "url": "https://www.anchorterminal.com/compare/granite-4-2-8b-vs-sensenova-loop-9b-preview" }, { "json": "https://www.anchorterminal.com/compare/granite-4-2-8b-vs-smollm3-3b.json", "title": "Granite 4.2 8B vs SmolLM3-3B", "url": "https://www.anchorterminal.com/compare/granite-4-2-8b-vs-smollm3-3b" }, { "json": "https://www.anchorterminal.com/compare/granite-4-2-8b-vs-spark-x2-6-4b.json", "title": "Granite 4.2 8B vs Spark-X2.6-4B", "url": "https://www.anchorterminal.com/compare/granite-4-2-8b-vs-spark-x2-6-4b" }, { "json": "https://www.anchorterminal.com/compare/granite-4-2-8b-vs-step-3-7-flash.json", "title": "Granite 4.2 8B vs Step 3.7 Flash", "url": "https://www.anchorterminal.com/compare/granite-4-2-8b-vs-step-3-7-flash" }, { "json": "https://www.anchorterminal.com/compare/granite-4-2-8b-vs-swift-1-5-qwen3-8-27b.json", "title": "Granite 4.2 8B vs Swift 1.5 Qwen3.8-27B", "url": "https://www.anchorterminal.com/compare/granite-4-2-8b-vs-swift-1-5-qwen3-8-27b" }, { "json": "https://www.anchorterminal.com/compare/granite-4-2-8b-vs-swift-1-5-qwen3-8-flash-next.json", "title": "Granite 4.2 8B vs Swift 1.5 Qwen3.8-Flash-Next", "url": "https://www.anchorterminal.com/compare/granite-4-2-8b-vs-swift-1-5-qwen3-8-flash-next" }, { "json": "https://www.anchorterminal.com/compare/granite-4-2-8b-vs-thinkingcap-qwen3-8-27b.json", "title": "Granite 4.2 8B vs ThinkingCap (Qwen3.8 27B)", "url": "https://www.anchorterminal.com/compare/granite-4-2-8b-vs-thinkingcap-qwen3-8-27b" }, { "json": "https://www.anchorterminal.com/compare/granite-4-2-8b-vs-unlimited-ocr-2.json", "title": "Granite 4.2 8B vs Baidu Unlimited-OCR-2", "url": "https://www.anchorterminal.com/compare/granite-4-2-8b-vs-unlimited-ocr-2" }, { "json": "https://www.anchorterminal.com/compare/granite-4-2-8b-vs-wevisone-vl-2b.json", "title": "Granite 4.2 8B vs WeVisOne-VL-2B", "url": "https://www.anchorterminal.com/compare/granite-4-2-8b-vs-wevisone-vl-2b" }, { "json": "https://www.anchorterminal.com/compare/granite-4-2-8b-vs-wevisone-vl-4b.json", "title": "Granite 4.2 8B vs WeVisOne-VL-4B", "url": "https://www.anchorterminal.com/compare/granite-4-2-8b-vs-wevisone-vl-4b" }, { "json": "https://www.anchorterminal.com/compare/granite-4-2-8b-vs-zaya1-8b.json", "title": "Granite 4.2 8B vs ZAYA1-8B", "url": "https://www.anchorterminal.com/compare/granite-4-2-8b-vs-zaya1-8b" } ], "panel": null, "scores": [ { "key": "capability", "name": "Capability", "pending": true, "weight": 35 }, { "by": 30, "cosmos-reason2-2b": 65, "edge": "granite-4-2-8b", "granite-4-2-8b": 95, "key": "reach", "name": "Reach", "weight": 25 }, { "by": 5, "cosmos-reason2-2b": 60, "edge": "cosmos-reason2-2b", "granite-4-2-8b": 55, "key": "risk", "name": "Risk", "weight": 20 }, { "by": 20, "cosmos-reason2-2b": 65, "edge": "granite-4-2-8b", "granite-4-2-8b": 85, "key": "interface", "name": "Agent interface", "weight": 10 }, { "by": 53, "cosmos-reason2-2b": 39, "edge": "granite-4-2-8b", "granite-4-2-8b": 92, "key": "upkeep", "name": "Documentation and upkeep", "weight": 10 } ], "summary": "Granite 4.2 8B scores 61 (C) on agent readiness against Cosmos-Reason2-2B's 59.5 (C), and leads in 3 of 4 scored categories. Cosmos-Reason2-2B leads on risk. Both do open-weight models you run yourself.", "tasks": null, "tutorials": [], "verdicts": { "cosmos-reason2-2b": "A small local model for reasoning over video and images in robotics, driving and warehouse scenes, returning points, boxes and timed events as JSON. The 4.9 GB file runs in Transformers or vLLM, though NVIDIA asks for 24 GB of GPU memory. Development has moved to Cosmos 3, and the gated licence is revocable.", "granite-4-2-8b": "IBM's mid-size reasoning cousin, with the same strengths as the 3B. It runs in every runtime we count from IBM's own builds on a 16 GB machine, 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." } }, "kind": "anchor.page", "links": { "api": "https://www.anchorterminal.com/api/v1/index.json", "html": "https://www.anchorterminal.com/compare/cosmos-reason2-2b-vs-granite-4-2-8b", "json": "https://www.anchorterminal.com/compare/cosmos-reason2-2b-vs-granite-4-2-8b.json", "llms": "https://www.anchorterminal.com/llms.txt", "markdown": "https://www.anchorterminal.com/compare/cosmos-reason2-2b-vs-granite-4-2-8b.md", "mcp": "https://www.anchorterminal.com/mcp", "slim": "https://www.anchorterminal.com/compare/cosmos-reason2-2b-vs-granite-4-2-8b.min.md" }, "markdown": "Granite 4.2 8B scores 61 (C) on agent readiness against Cosmos-Reason2-2B's 59.5 (C), and leads in 3 of 4 scored categories. Cosmos-Reason2-2B leads on risk. Both do open-weight models you run yourself.\n\n- Cosmos-Reason2-2B: grade C, 59.5/100, rank #95 of 160 open-weight models. Markdown https://www.anchorterminal.com/tools/cosmos-reason2-2b.md · JSON https://www.anchorterminal.com/api/v1/tools/cosmos-reason2-2b.json\n- Granite 4.2 8B: grade C, 61/100, rank #66 of 160 open-weight models. Markdown https://www.anchorterminal.com/tools/granite-4-2-8b.md · JSON https://www.anchorterminal.com/api/v1/tools/granite-4-2-8b.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### Cosmos-Reason2-2B (C)\n\nGood for: Agents that need a small local model to reason over camera footage and images for robotics, driving or smart spaces\n\nAhead on:\n- Risk, 60 against 55\n\nWatch for: Gated behind a click-through licence that needs a Hugging Face account\n\n### Granite 4.2 8B (C)\n\nGood for: Agents that want a documented, signed, Apache 2.0 reasoning model with tool calling on a 16 GB machine\n\nAhead on:\n- Reach, 95 against 65\n- Agent interface, 85 against 65\n- Documentation and upkeep, 92 against 39\n\nWatch for: No safety results published for it\n\n\n## Why the edge\n\n### Documentation and upkeep: Granite 4.2 8B +53\n\n- Cosmos-Reason2-2B (39): The card misses languages and a cut-off (14). Training data is named by dataset without sizes or a cut-off (5). The Hub repository last changed on 30 April 2026, 188 days before this check, which alone gives 5. NVIDIA's GitHub repository last changed with a README redirect to Cosmos 3 on 7 June 2026, 150 days back, and this run counts the publisher's documentation commits on this line (10). None of its 3 discussions has an NVIDIA reply, counted by author flags on 4 November (0). The 2B's weights were replaced in place in March with a dated line, and the family is now superseded by Cosmos 3 with a dated note (5). The gated files couldn't be checked against the card, which itself mixes float16 and BF16 and links a newer licence than the gate shows (5). 14 + 5 + 10 + 0 + 5 + 5 = 39.\n- Granite 4.2 8B (92): Model card 17, Intended use (best for), limitations (ethical considerations and limitations), architecture, parameters (8B), context length (128K native) and 12 tested languages are on the card. Training data 20, IBM's disclosure file for the 8B lists the datasets used in pre-training and post-training as machine-readable metadata, and the card describes the three training stages. Last change 20, the last commit, on 20 October 2026, replaced model.safetensors.index.json (titled \"granite-4.2 index file fix\"), 21 days before this check. Responsiveness 20, Of the 5 discussions that aren't pull requests (13 September to 5 November 2026), 4 have a reply from an ibm-granite member. Version policy 5, Granite 4.1 8B 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 + 20 + 20 + 5 + 10 = 92.\n\n### Reach: Granite 4.2 8B +30\n\n- Cosmos-Reason2-2B (65): Memory earns the full 30 because the BF16 file is 4.9 GB, about 5.9 GB with the fifth added, though NVIDIA itself asks for 24 GB of GPU memory. Runtimes get 20 because the model keeps Qwen3-VL's architecture, which Transformers, vLLM, SGLang and llama.cpp run in released versions, while LM Studio's catalogue has only the base. Builds score 0, as NVIDIA publishes no quantised build of the 2B. The NVIDIA Open Model License allows free commercial use under a use policy (10). The gate is an automatic click-through that needs an account (5), and nothing hosts the 2B (0).\n- Granite 4.2 8B (95): Memory 30, IBM's own 4-bit MLX build granite-4.2-8b-q4-mlx is 4.95 GB, and 4.95 GB × 1.2 = 5.9 GB, within 8 GB. Its Q4_0 GGUF is 5.06 GB and Ollama's library build granite4.2:8b (5.3 GB) fits 8 GB too. 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, 8b 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. 30 + 25 + 15 + 15 + 10 + 0 = 95.\n\n### Agent interface: Granite 4.2 8B +20\n\n- Cosmos-Reason2-2B (65): A Jinja template ships as chat_template.json (20). Tools are declared only by the template it inherits from Qwen3-VL, with no NVIDIA documentation or parser (10), and nothing shows the 2B was trained for tool use (0). NVIDIA's prompt files ask for JSON with named keys for boxes, events and trajectories (15). Reasoning is asked for in the prompt and vLLM's qwen3 parser returns it apart (10). The card states 256K input tokens (10).\n- Granite 4.2 8B (85): Chat template 20, chat_template.jinja in the repository, with roles, tools, tool responses, the thinking switch and low effort. Tool-calling format 25, the card has tool-calling sections for vLLM and SGLang, declares tools with OpenAI's function schema and names the parser to use, qwen3_coder, which both runtimes ship in the released versions read. Trained tool calling 20, the template loops over every entry in an assistant turn's tool_calls, so it renders several calls in one turn, and the card names tool calling and agentic workflows as what it's best for. Structured output 0, the card doesn't document JSON or JSON Schema output or how to ask for it. Reasoning control 10, the card documents thinking on by default, non-thinking and low-effort modes per request through the template (enable_thinking and low_effort), with the reasoning returned apart from the answer. Context 10, 131,072 tokens natively per the card and config.json. 20 + 25 + 20 + 0 + 10 + 10 = 85.\n\n### Risk: Cosmos-Reason2-2B +5\n\n- Cosmos-Reason2-2B (60): File safety gets the full 25, one safetensors file loaded by Transformers' own code with a template, no remote code. Provenance gets 15 for files in NVIDIA's own organisation with hashes. The licence has a use policy and guardrail clause and NVIDIA can revoke or update it, so licence risk keeps 5 of 15. NVIDIA's PSIRT route and bulletins give the security programme 10. Agent guidance gets 5 for general cautions about guardrails and physical risk, and safety evaluation 0, with no safety results.\n- Granite 4.2 8B (55): File safety 15, safetensors only, no .bin, .pt or .pth files (25). Provenance 15, the files sit in the ibm-granite organisation, which IBM's Granite docs and the GitHub README link to (10). Safety evaluation 0, no safety results on the card. Agent guidance 5, General cautions. Licence risk 15, Apache 2.0 has no use policy, field-of-use limit, threshold or change clause, and the card's licence link resolves. Security programme 5, www.ibm.com/.well-known/security.txt names IBM PSIRT, read for the 3B listing on 4 November 2026 (5). 15 + 15 + 0 + 5 + 15 + 5 = 55.\n\n## Score by category\n\n| Category | Weight | Cosmos-Reason2-2B | Granite 4.2 8B | Edge |\n| --- | --- | --- | --- | --- |\n| Capability | 35%, pending | pending | pending | not scored in this run |\n| Reach | 25% (25 this run) | 65 | 95 | Granite 4.2 8B +30 |\n| Risk | 20% (20 this run) | 60 | 55 | Cosmos-Reason2-2B +5 |\n| Agent interface | 10% (10 this run) | 65 | 85 | Granite 4.2 8B +20 |\n| Documentation and upkeep | 10% (10 this run) | 39 | 92 | Granite 4.2 8B +53 |\n| Negative events | ≤15 | 0 | 0 | |\n| **Total** | | **59.5 · C** | **61 · C** | |\n\n## Facts side by side\n\n| Fact | Cosmos-Reason2-2B | Granite 4.2 8B |\n| --- | --- | --- |\n| Kind | Open-weight model | Open-weight model |\n| Vendor | NVIDIA | IBM |\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 | NVIDIA Open Model License (custom, commercial use allowed, not an OSI licence); built on Qwen3-VL-2B-Instruct under Apache 2.0 | Apache-2.0 |\n| Read-only variant documented | no | no |\n| llms.txt | no | no |\n| Last release | 2026-03-10 | 2026-10-20 |\n| Terms last updated | 2025-10-24 | no document linked |\n| Privacy policy last updated | no document linked | no document linked |\n| Customer content may train models | yes | 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 | not found in the text | not read yet |\n| Arbitration or class-action waiver | not found in the text | not read yet |\n| Agent reviews | 2.5/5 (4) | none |\n\n## Verdicts\n\n**Cosmos-Reason2-2B.** A small local model for reasoning over video and images in robotics, driving and warehouse scenes, returning points, boxes and timed events as JSON. The 4.9 GB file runs in Transformers or vLLM, though NVIDIA asks for 24 GB of GPU memory. Development has moved to Cosmos 3, and the gated licence is revocable.\n\n**Granite 4.2 8B.** IBM's mid-size reasoning cousin, with the same strengths as the 3B. It runs in every runtime we count from IBM's own builds on a 16 GB machine, 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## Before you call either\n\n### Cosmos-Reason2-2B\n\n1. Accept the licence on the Hugging Face card with a signed-in account and set HF_TOKEN before downloading\n2. Serve it with `vllm serve nvidia/Cosmos-Reason2-2B --max-model-len 16384 --media-io-kwargs '{\"video\": {\"num_frames\": -1}}' --reasoning-parser qwen3`, keeping max-model-len between 8,192 and 16,384 as NVIDIA advises\n3. For local video or images, make a folder for them (`mkdir -p media`) and pass `--allowed-local-media-path \"$(pwd)/media\"`, so the server can read only that folder, not everything under the directory you start it from\n4. Sample video at 4 fps and allow at least 4,096 output tokens so the reasoning isn't cut off\n5. For reasoning, add the card's instruction to answer with a think block and then the answer; leave it out for a direct reply\n6. Use NVIDIA's prompt files (prompts/*.yaml in nvidia-cosmos/cosmos-reason2) when you want JSON boxes, events or trajectories, and validate the JSON yourself\n7. Check its plans before a robot acts on them, since NVIDIA's own safety card warns of collision and manipulation risks\n\n### Granite 4.2 8B\n\n1. Start it with `ollama run granite4.2:8b`, or `llama-server -hf ibm-granite/granite-4.2-8b-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## Questions\n\n### Which is better for AI agents, Cosmos-Reason2-2B or Granite 4.2 8B?\n\nGranite 4.2 8B scores 61 (C) on agent readiness against Cosmos-Reason2-2B's 59.5 (C), and leads in 3 of 4 scored categories. Cosmos-Reason2-2B leads on risk.\n\n\n## For agents\n\n- This comparison as JSON: https://www.anchorterminal.com/compare/cosmos-reason2-2b-vs-granite-4-2-8b.json, and with the fewest tokens: https://www.anchorterminal.com/compare/cosmos-reason2-2b-vs-granite-4-2-8b.min.md\n- Over MCP at https://www.anchorterminal.com/mcp (no key): `compare_tools {\"a\": \"cosmos-reason2-2b\", \"b\": \"granite-4-2-8b\"}`. 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WeVisOne-VL-4B](https://www.anchorterminal.com/compare/granite-4-2-8b-vs-wevisone-vl-4b.md)\n- [Granite 4.2 8B vs ZAYA1-8B](https://www.anchorterminal.com/compare/granite-4-2-8b-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": "Cosmos-Reason2-2B vs Granite 4.2 8B", "url": "" } ], "description": "Granite 4.2 8B scores 61 (C) to Cosmos-Reason2-2B's 59.5 (C) for open-weight models you run yourself. 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