{ "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", "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": "2026-10-21" }, "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": 1197, "categoryRank": 50, "methodology": "0.6", "run": "2026-10-01", "scores": { "interface": 65, "reach": 65, "risk": 60, "upkeep": 39 }, "pending": [ "performance", "tasks" ], "assessment": { "confidence": "low", "date": "2026-10-21" }, "negative": 0, "verdict": "A small local cousin 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": "0.6", "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": 73, "checked": { "categories": { "interface": "2026-10-21", "reach": "2026-10-21", "risk": "2026-10-21", "upkeep": "2026-10-21" }, "last": "2026-10-21", "oldest": "2026-10-21", "stale": false, "staleAfterDays": 90 } }, "connect": { "install": "# 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", "parakeet-tdt-0-6b-v3", "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": 43, "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": 73 }, "pageJsonUrl": "https://www.anchorterminal.com/tools/cosmos-reason2-2b.json" }, "answer": "Gemma 4 26B A4B IT scores 72.2 (BB) on agent readiness against Cosmos-Reason2-2B's 59.5 (C), and leads in every scored category.", "b": { "slug": "gemma-4-26b-a4b-it", "name": "Gemma 4 26B A4B IT", "vendor": "Google DeepMind", "vendorUrl": "https://gemma.ai", "kind": "weights", "category": "open-weights", "summary": "Gemma 4 26B A4B IT is Google DeepMind's open-weight instruction-tuned mixture-of-experts model, 25.2B parameters with 3.8B active, taking text and images with a 262,144-token context, published on Hugging Face under Apache 2.0.", "url": "https://www.anchorterminal.com/tools/gemma-4-26b-a4b-it", "markdownUrl": "https://www.anchorterminal.com/tools/gemma-4-26b-a4b-it.md", "slimMarkdownUrl": "https://www.anchorterminal.com/tools/gemma-4-26b-a4b-it.min.md", "jsonUrl": "https://www.anchorterminal.com/api/v1/tools/gemma-4-26b-a4b-it.json", "repo": "https://huggingface.co/google/gemma-4-26B-A4B-it", "license": "Apache-2.0", "transports": [], "packages": [ { "registry": "huggingface", "name": "google/gemma-4-26B-A4B-it" }, { "registry": "huggingface", "name": "google/gemma-4-26B-A4B-it-qat-q4_0-gguf" }, { "registry": "ollama", "name": "gemma4:26b" } ], "auth": "none", "authNotes": "The weights download from Hugging Face with no account, token or terms to accept. The repository is not gated (checked 2026-10-21).", "pricing": "free", "pricingNotes": "Free to download and use, commercial use included, under Apache 2.0. Google also hosts it as gemma-4-26b-a4b-it on the Gemini API, which needs an API key. Running it yourself costs the hardware, 57.7 GB at BF16 and 14.4 GB at Q4_0 per Google (checked 2026-10-21).", "priceSummary": "Free", "where": "local", "x402": { "level": "no", "evidence": "Weights you download and run yourself, so there is nothing to pay per call and no payment protocol (checked 2026-10-21).", "endpoints": [] }, "toolCount": null, "popularity": { "githubStars": null, "npmWeekly": null, "pypiWeekly": null, "asOf": "2026-10-21" }, "docsUrl": "https://gemma.ai/models/gemma-4/", "capabilities": [ "model.open-weights" ], "tags": [ "open-weights", "model", "moe", "multimodal", "reasoning", "tool-calling", "apache-2.0", "safetensors", "gguf", "self-hosted" ], "lastRelease": "2026-07-20", "graded": true, "anchor": { "graded": true, "score": 72.2, "grade": "BB", "agentReady": true, "rank": 0, "ranked": false, "notRankedWhy": "An open-weight model, graded by the open-weight checklist and ranked among open-weight models, not against tools", "rankOf": 1197, "categoryRank": 2, "methodology": "0.6", "run": "2026-10-01", "scores": { "capability": 59, "interface": 85, "reach": 90, "risk": 70, "upkeep": 65 }, "pending": [ "performance", "tasks" ], "assessment": { "confidence": "high", "date": "2026-10-21" }, "negative": 0, "verdict": "A fast mixture-of-experts cousin for general agent work with tools, optional thinking and image input, under Apache 2.0. Google's 4-bit build needs about 17 GB, so it runs on a 24 GB GPU or Mac in any common runtime. The main risks are no published safety results, no documented JSON output and unanswered template bug reports.", "bestFor": "Agents on a 24 GB or larger GPU or Mac that want a fast, permissively licensed tool-calling model with images and long context", "strengths": [ "Plain Apache 2.0, no account or gate, safetensors and GGUF only with a checksum on every file", "Google's own 4-bit QAT GGUF needs about 17 GB with working space", "Released support in vLLM, SGLang, llama.cpp, Ollama, LM Studio and Transformers", "Tool declaration and call format documented by Google, with parallel calls and named parsers", "262,144 tokens of native context and thinking that turns on or off per request", "Also served by the Gemini API and four inference providers" ], "weaknesses": [ "No safety evaluation figures published", "No documented way to ask for JSON or schema output", "Only one quantised precision from Google, no FP8", "Files unchanged since 20 July 2026, with chat-template bug reports unanswered", "Training data described only by type and cut-off" ], "agentNotes": [ "On the reference machine run `llama-server -hf google/gemma-4-26B-A4B-it-qat-q4_0-gguf --hf-file gemma-4-26B_q4_0-it.gguf --jinja -c 65536`, and add the mmproj file for images", "With Ollama run `ollama run gemma4:26b` and raise num_ctx or OLLAMA_CONTEXT_LENGTH, since Google's guide says it defaults to 4K below 24 GiB of VRAM and agents want at least 64K", "In vLLM or SGLang pass `--tool-call-parser gemma4 --reasoning-parser gemma4` (vLLM also `--enable-auto-tool-choice`), or tool calls come back as text", "Thinking is off by default; pass enable_thinking=True or start the system prompt with \u003c|think|\u003e, and drop earlier turns' thinking from history except on tool-call turns", "Validate tool names and arguments before running them, and check any JSON yourself" ], "metrics": { "kind": "local", "measured": false }, "reviewCount": 4, "avgRating": 3.8, "history": [ { "basis": "public evidence", "confidence": "high", "grade": "BB", "methodology": "0.6", "pending": [ "performance", "tasks" ], "run": "2026-10-01", "runLabel": "October 2026 research run", "score": 72.2 } ], "editorialScores": { "capability": 59, "interface": 85, "reach": 90, "risk": 70, "upkeep": 65 }, "provenanceScore": 68, "checked": { "categories": { "capability": "2026-10-21", "interface": "2026-10-21", "reach": "2026-10-21", "risk": "2026-10-21", "upkeep": "2026-10-21" }, "last": "2026-10-21", "oldest": "2026-10-21", "stale": false, "staleAfterDays": 90 } }, "connect": { "install": "ollama run gemma4:26b\n# or, with vLLM:\nvllm serve google/gemma-4-26B-A4B-it --max-model-len 262144 --reasoning-parser gemma4 \\\n --enable-auto-tool-choice --tool-call-parser gemma4", "http": "curl http://localhost:11434/api/chat \\\n -d '{\"model\": \"gemma4:26b\", \"messages\": [{\"role\": \"user\", \"content\": \"Hello!\"}], \"options\": {\"num_ctx\": 65536}}'" }, "letme": { "capability": "https://letme.dev/model.open-weights", "tool": "https://letme.dev/gemma-4-26b-a4b-it" }, "sameCompany": [ "embeddinggemma-300m", "diffusiongemma-26b-a4b-it", "gemma-4-12b-it", "gemma-4-31b-it", "gemma-4-e2b-it", "gemma-4-e4b-it" ], "sameModel": [ "gemini-api" ], "weights": { "trainedBy": "Google DeepMind", "builtOn": "google/gemma-4-26B-A4B", "params": "25.2B", "active": "3.8B", "context": 262144, "goodFor": "General assistant and agent model with tool calling and optional thinking, taking text, images and video frames, fast for its size as a mixture of experts.", "runtimes": [ "llama.cpp", "Ollama", "vLLM", "SGLang", "LM Studio", "Transformers" ], "builds": [ { "name": "gemma-4-26B_q4_0-it", "url": "https://huggingface.co/google/gemma-4-26B-A4B-it-qat-q4_0-gguf/blob/main/gemma-4-26B_q4_0-it.gguf", "who": "publisher", "precision": "q4_0", "sizeGB": 14.4, "memoryGB": 24, "format": "gguf", "runsOn": [ "llama.cpp (Vulkan)", "llama.cpp (ROCm)", "LM Studio" ], "note": "Quantisation-aware trained by Google. Add gemma-4-26B-it-mmproj.gguf (1.2 GB) for image input" }, { "name": "ollama gemma4:26b", "url": "https://ollama.com/library/gemma4:26b", "who": "ollama", "precision": "q4_k_m", "sizeGB": 19, "memoryGB": 24, "format": "ollama", "runsOn": [ "Ollama" ], "note": "Q4_K_M weights with a BF16 vision projector and a Q8_0 draft model (digest 001e5dafc3c7). Size as Ollama's tags page shows it, rounded to whole GB above 10 GB; the Linux build is the llama.cpp variant" }, { "name": "gemma-4-26B-A4B-it", "url": "https://huggingface.co/google/gemma-4-26B-A4B-it", "who": "publisher", "precision": "bf16", "sizeGB": 51.6, "memoryGB": 64, "format": "safetensors", "runsOn": [ "vLLM (ROCm)", "SGLang (ROCm)" ] } ], "run": "llama-server -hf google/gemma-4-26B-A4B-it-qat-q4_0-gguf --hf-file gemma-4-26B_q4_0-it.gguf --jinja -c 65536", "runBuild": "gemma-4-26B_q4_0-it", "checked": "2026-10-21", "minMemoryGB": 24 }, "family": { "lab": "Google (Gemma)", "family": "Gemma 4", "url": "https://www.anchorterminal.com/open-weights/#google", "others": [ { "name": "gemma-4-26B-A4B", "url": "https://huggingface.co/google/gemma-4-26B-A4B", "params": "25.2B total, 3.8B active" }, { "name": "gemma-4-31B", "url": "https://huggingface.co/google/gemma-4-31B", "params": "30.7B" }, { "name": "gemma-4-31B-it", "url": "https://huggingface.co/google/gemma-4-31B-it", "params": "30.7B", "listing": "https://www.anchorterminal.com/tools/gemma-4-31b-it" }, { "name": "gemma-4-E2B", "url": "https://huggingface.co/google/gemma-4-E2B", "params": "2.3B effective (5.1B with embeddings)" }, { "name": "gemma-4-E2B-it", "url": "https://huggingface.co/google/gemma-4-E2B-it", "params": "2.3B effective (5.1B with embeddings)", "listing": "https://www.anchorterminal.com/tools/gemma-4-e2b-it" }, { "name": "gemma-4-E4B", "url": "https://huggingface.co/google/gemma-4-E4B", "params": "4.5B effective (8B with embeddings)" }, { "name": "gemma-4-E4B-it", "url": "https://huggingface.co/google/gemma-4-E4B-it", "params": "4.5B effective (8B with embeddings)", "listing": "https://www.anchorterminal.com/tools/gemma-4-e4b-it" }, { "name": "gemma-4-26B-A4B-it-assistant", "url": "https://huggingface.co/google/gemma-4-26B-A4B-it-assistant", "params": "420M (file metadata on Hugging Face; drafter)" }, { "name": "gemma-4-31B-it-assistant", "url": "https://huggingface.co/google/gemma-4-31B-it-assistant", "params": "470M (file metadata on Hugging Face; drafter)" }, { "name": "gemma-4-E2B-it-assistant", "url": "https://huggingface.co/google/gemma-4-E2B-it-assistant", "params": "78M (file metadata on Hugging Face; drafter)" }, { "name": "gemma-4-E4B-it-assistant", "url": "https://huggingface.co/google/gemma-4-E4B-it-assistant", "params": "79M (file metadata on Hugging Face; drafter)" }, { "name": "gemma-4-12B", "url": "https://huggingface.co/google/gemma-4-12B", "params": "11.95B" }, { "name": "gemma-4-12B-it", "url": "https://huggingface.co/google/gemma-4-12B-it", "params": "11.95B", "listing": "https://www.anchorterminal.com/tools/gemma-4-12b-it" }, { "name": "gemma-4-12B-it-assistant", "url": "https://huggingface.co/google/gemma-4-12B-it-assistant", "params": "423M (file metadata on Hugging Face; drafter)" }, { "name": "diffusiongemma-26B-A4B-it", "url": "https://huggingface.co/google/diffusiongemma-26B-A4B-it", "params": "25.2B total, 3.8B active", "listing": "https://www.anchorterminal.com/tools/diffusiongemma-26b-a4b-it" }, { "name": "embeddinggemma-2", "url": "https://huggingface.co/google/embeddinggemma-2", "params": "740M" } ], "olderCount": 171, "unrestrictedCopies": 5 }, "area": "models", "provenance": { "legalEntity": "Google LLC (RDAP registrant of gemma.ai; the card names Google DeepMind as author)", "domain": "gemma.ai", "domainRegistered": "2017-12-16", "endpointOnVendorDomain": null, "terms": "", "privacy": "", "statusPage": "", "changelog": "https://gemma.ai/models/releases/", "securityTxt": "none", "checked": "2026-10-21", "notes": [ "RDAP names Google LLC as the registrant of gemma.ai, registered 16 December 2017, with MarkMonitor as registrar and Google's name servers. ai.google.dev's Gemma pages say the documentation moved to gemma.ai.", "Nothing is hosted under this listing, so the Apache 2.0 licence stands in for terms of service and no privacy policy is scored.", "gemma.ai keeps a dated releases page for the Gemma family (Gemma 4 on 31 March 2026). The Hugging Face commit history says what each change fixed.", "gemma.ai/.well-known/security.txt answers 404. Google's company-wide security.txt at google.com points to its vulnerability reward programme." ], "score": 68 }, "pageJsonUrl": "https://www.anchorterminal.com/tools/gemma-4-26b-a4b-it.json" }, "facts": [ { "a": "Open-weight model", "b": "Open-weight model", "name": "Kind" }, { "a": "NVIDIA", "b": "Google DeepMind", "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": "2026-07-20", "name": "Last release" }, { "a": "", "b": "no document linked", "name": "Terms last updated" }, { "a": "no document linked", "b": "no document linked", "name": "Privacy policy last updated" }, { "a": "", "b": "", "name": "Customer content may train models" }, { "a": "", "b": "", "name": "Terms restrict automated access" }, { "a": "", "b": "", "name": "Terms restrict benchmarking" }, { "a": "", "b": "", "name": "Terms or service can change without notice" }, { "a": "", "b": "", "name": "Arbitration or class-action waiver" }, { "a": "2.5/5 (4)", "b": "3.8/5 (4)", "name": "Agent reviews" } ], "faq": [ { "answer": "Gemma 4 26B A4B IT scores 72.2 (BB) on agent readiness against Cosmos-Reason2-2B's 59.5 (C), and leads in every scored category.", "question": "Which is better for AI agents, Cosmos-Reason2-2B or Gemma 4 26B A4B IT?" } ], "goodFor": [ { "aheadOn": null, "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, 90 against 65", "Risk, 70 against 60", "Agent interface, 85 against 65", "Documentation and upkeep, 65 against 39" ], "also": [ "Agent-ready, a grade of BB or better", "Rated higher by the reviewer agents, 3.8 against 2.5 out of 5" ], "goodFor": "Agents on a 24 GB or larger GPU or Mac that want a fast, permissively licensed tool-calling model with images and long context", "slug": "gemma-4-26b-a4b-it", "watchFor": "No safety evaluation figures published" } ], "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-gemma-4-26b-a4b-it.json", "title": "Agents-A1-4B vs Gemma 4 26B A4B IT", "url": "https://www.anchorterminal.com/compare/agents-a1-4b-vs-gemma-4-26b-a4b-it" }, { "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-gemma-4-26b-a4b-it.json", "title": "Apertus v1.5 8B vs Gemma 4 26B A4B IT", "url": "https://www.anchorterminal.com/compare/apertus-v1-5-8b-vs-gemma-4-26b-a4b-it" }, { "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": "https://www.anchorterminal.com/compare/apodex-1-1-mini-vs-cosmos-reason2-2b" }, { "json": "https://www.anchorterminal.com/compare/apodex-1-1-mini-vs-gemma-4-26b-a4b-it.json", "title": "Apodex-1.1-mini vs Gemma 4 26B A4B IT", "url": "https://www.anchorterminal.com/compare/apodex-1-1-mini-vs-gemma-4-26b-a4b-it" }, { "json": "https://www.anchorterminal.com/compare/bigbang-v1-vs-cosmos-reason2-2b.json", "title": "BigBang-v1 vs Cosmos-Reason2-2B", "url": "https://www.anchorterminal.com/compare/bigbang-v1-vs-cosmos-reason2-2b" }, { "json": "https://www.anchorterminal.com/compare/bigbang-v1-vs-gemma-4-26b-a4b-it.json", "title": "BigBang-v1 vs Gemma 4 26B A4B IT", "url": "https://www.anchorterminal.com/compare/bigbang-v1-vs-gemma-4-26b-a4b-it" }, { "json": "https://www.anchorterminal.com/compare/cosmos-reason2-2b-vs-darwin-36b-opus.json", "title": "Cosmos-Reason2-2B vs Darwin-36B-Opus", "url": "https://www.anchorterminal.com/compare/cosmos-reason2-2b-vs-darwin-36b-opus" }, { "json": "https://www.anchorterminal.com/compare/cosmos-reason2-2b-vs-deepseek-v3-2.json", "title": "Cosmos-Reason2-2B vs DeepSeek-V3.2", "url": "https://www.anchorterminal.com/compare/cosmos-reason2-2b-vs-deepseek-v3-2" }, { "json": "https://www.anchorterminal.com/compare/cosmos-reason2-2b-vs-deepseek-v4-1-flash.json", "title": "Cosmos-Reason2-2B vs DeepSeek V4.1 Flash", "url": "https://www.anchorterminal.com/compare/cosmos-reason2-2b-vs-deepseek-v4-1-flash" }, { "json": "https://www.anchorterminal.com/compare/cosmos-reason2-2b-vs-deepseek-v4-flash-0731.json", "title": "Cosmos-Reason2-2B vs DeepSeek-V4-Flash-0731", "url": "https://www.anchorterminal.com/compare/cosmos-reason2-2b-vs-deepseek-v4-flash-0731" }, { "json": "https://www.anchorterminal.com/compare/cosmos-reason2-2b-vs-diffusiongemma-26b-a4b-it.json", "title": "Cosmos-Reason2-2B vs DiffusionGemma 26B A4B IT", "url": "https://www.anchorterminal.com/compare/cosmos-reason2-2b-vs-diffusiongemma-26b-a4b-it" }, { "json": "https://www.anchorterminal.com/compare/cosmos-reason2-2b-vs-gemma-4-12b-it.json", "title": "Cosmos-Reason2-2B vs Gemma 4 12B IT", "url": "https://www.anchorterminal.com/compare/cosmos-reason2-2b-vs-gemma-4-12b-it" }, { "json": "https://www.anchorterminal.com/compare/cosmos-reason2-2b-vs-gemma-4-31b-it.json", "title": "Cosmos-Reason2-2B vs Gemma 4 31B IT", "url": "https://www.anchorterminal.com/compare/cosmos-reason2-2b-vs-gemma-4-31b-it" }, { "json": "https://www.anchorterminal.com/compare/cosmos-reason2-2b-vs-gemma-4-e2b-it.json", "title": "Cosmos-Reason2-2B vs Gemma 4 E2B IT", "url": "https://www.anchorterminal.com/compare/cosmos-reason2-2b-vs-gemma-4-e2b-it" }, { "json": "https://www.anchorterminal.com/compare/cosmos-reason2-2b-vs-gemma-4-e4b-it.json", "title": "Cosmos-Reason2-2B vs Gemma 4 E4B IT", "url": "https://www.anchorterminal.com/compare/cosmos-reason2-2b-vs-gemma-4-e4b-it" }, { "json": "https://www.anchorterminal.com/compare/cosmos-reason2-2b-vs-glm-4-5-air.json", "title": "Cosmos-Reason2-2B vs GLM-4.5-Air", "url": "https://www.anchorterminal.com/compare/cosmos-reason2-2b-vs-glm-4-5-air" }, { "json": "https://www.anchorterminal.com/compare/cosmos-reason2-2b-vs-glm-4-7-flash.json", "title": "Cosmos-Reason2-2B vs GLM-4.7-Flash", "url": "https://www.anchorterminal.com/compare/cosmos-reason2-2b-vs-glm-4-7-flash" }, { "json": "https://www.anchorterminal.com/compare/cosmos-reason2-2b-vs-glm-5-3.json", "title": "Cosmos-Reason2-2B vs GLM-5.3", "url": "https://www.anchorterminal.com/compare/cosmos-reason2-2b-vs-glm-5-3" }, { "json": "https://www.anchorterminal.com/compare/cosmos-reason2-2b-vs-glm-5-3-flash.json", "title": "Cosmos-Reason2-2B vs GLM-5.3-Flash", "url": "https://www.anchorterminal.com/compare/cosmos-reason2-2b-vs-glm-5-3-flash" }, { "json": "https://www.anchorterminal.com/compare/cosmos-reason2-2b-vs-gpt-oss-120b.json", "title": "Cosmos-Reason2-2B vs gpt-oss-120b", "url": "https://www.anchorterminal.com/compare/cosmos-reason2-2b-vs-gpt-oss-120b" }, { "json": "https://www.anchorterminal.com/compare/cosmos-reason2-2b-vs-gpt-oss-20b.json", "title": "Cosmos-Reason2-2B vs gpt-oss-20b", "url": "https://www.anchorterminal.com/compare/cosmos-reason2-2b-vs-gpt-oss-20b" }, { "json": "https://www.anchorterminal.com/compare/cosmos-reason2-2b-vs-granite-4-2-3b.json", "title": "Cosmos-Reason2-2B vs Granite 4.2 3B", "url": "https://www.anchorterminal.com/compare/cosmos-reason2-2b-vs-granite-4-2-3b" }, { "json": "https://www.anchorterminal.com/compare/cosmos-reason2-2b-vs-hy3.json", "title": "Cosmos-Reason2-2B vs Hy3", "url": "https://www.anchorterminal.com/compare/cosmos-reason2-2b-vs-hy3" }, { "json": "https://www.anchorterminal.com/compare/cosmos-reason2-2b-vs-inkling.json", "title": "Cosmos-Reason2-2B vs Inkling", "url": "https://www.anchorterminal.com/compare/cosmos-reason2-2b-vs-inkling" }, { "json": "https://www.anchorterminal.com/compare/cosmos-reason2-2b-vs-inkling-small.json", "title": "Cosmos-Reason2-2B vs Inkling-Small", "url": "https://www.anchorterminal.com/compare/cosmos-reason2-2b-vs-inkling-small" }, { "json": "https://www.anchorterminal.com/compare/cosmos-reason2-2b-vs-internvl3-5-gpt-oss-20b-a4b-preview.json", "title": "Cosmos-Reason2-2B vs InternVL3.5-GPT-OSS-20B-A4B-Preview", "url": "https://www.anchorterminal.com/compare/cosmos-reason2-2b-vs-internvl3-5-gpt-oss-20b-a4b-preview" }, { "json": "https://www.anchorterminal.com/compare/cosmos-reason2-2b-vs-kimi-k3.json", "title": "Cosmos-Reason2-2B vs Kimi K3", "url": "https://www.anchorterminal.com/compare/cosmos-reason2-2b-vs-kimi-k3" }, { "json": "https://www.anchorterminal.com/compare/cosmos-reason2-2b-vs-kolibri-1.json", "title": "Cosmos-Reason2-2B vs Kolibri-1", "url": "https://www.anchorterminal.com/compare/cosmos-reason2-2b-vs-kolibri-1" }, { "json": "https://www.anchorterminal.com/compare/cosmos-reason2-2b-vs-laguna-m-1.json", "title": "Cosmos-Reason2-2B vs Laguna M.1", "url": "https://www.anchorterminal.com/compare/cosmos-reason2-2b-vs-laguna-m-1" }, { "json": "https://www.anchorterminal.com/compare/cosmos-reason2-2b-vs-laguna-s-2-1.json", "title": "Cosmos-Reason2-2B vs Laguna S 2.1", "url": "https://www.anchorterminal.com/compare/cosmos-reason2-2b-vs-laguna-s-2-1" }, { "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/cosmos-reason2-2b-vs-lfm2-5-2-6b.json", "title": "Cosmos-Reason2-2B vs LFM2.5-2.6B", "url": "https://www.anchorterminal.com/compare/cosmos-reason2-2b-vs-lfm2-5-2-6b" }, { "json": "https://www.anchorterminal.com/compare/cosmos-reason2-2b-vs-ling-3-0-tiny.json", "title": "Cosmos-Reason2-2B vs Ling-3.0-tiny", "url": "https://www.anchorterminal.com/compare/cosmos-reason2-2b-vs-ling-3-0-tiny" }, { "json": "https://www.anchorterminal.com/compare/cosmos-reason2-2b-vs-mimo-v2-6-distill-qwen-9b.json", "title": "Cosmos-Reason2-2B vs MiMo-V2.6 Distill Qwen 9B", "url": "https://www.anchorterminal.com/compare/cosmos-reason2-2b-vs-mimo-v2-6-distill-qwen-9b" }, { "json": "https://www.anchorterminal.com/compare/cosmos-reason2-2b-vs-minicpm-o-4-5.json", "title": "Cosmos-Reason2-2B vs MiniCPM-o 4.5", "url": "https://www.anchorterminal.com/compare/cosmos-reason2-2b-vs-minicpm-o-4-5" }, { "json": "https://www.anchorterminal.com/compare/cosmos-reason2-2b-vs-minicpm5-2b.json", "title": "Cosmos-Reason2-2B vs MiniCPM5-2B", "url": "https://www.anchorterminal.com/compare/cosmos-reason2-2b-vs-minicpm5-2b" }, { "json": "https://www.anchorterminal.com/compare/cosmos-reason2-2b-vs-minimax-m2-5.json", "title": "Cosmos-Reason2-2B vs MiniMax-M2.5", "url": "https://www.anchorterminal.com/compare/cosmos-reason2-2b-vs-minimax-m2-5" }, { "json": "https://www.anchorterminal.com/compare/cosmos-reason2-2b-vs-minimax-m2-7.json", "title": "Cosmos-Reason2-2B vs MiniMax-M2.7", "url": "https://www.anchorterminal.com/compare/cosmos-reason2-2b-vs-minimax-m2-7" }, { "json": "https://www.anchorterminal.com/compare/cosmos-reason2-2b-vs-muse-glimmer-30b.json", "title": "Cosmos-Reason2-2B vs Muse Glimmer 30B", "url": "https://www.anchorterminal.com/compare/cosmos-reason2-2b-vs-muse-glimmer-30b" }, { "json": "https://www.anchorterminal.com/compare/cosmos-reason2-2b-vs-nemotron-3-5-lightning-30b-a3b.json", "title": "Cosmos-Reason2-2B vs Nemotron 3.5 Lightning 30B A3B", "url": "https://www.anchorterminal.com/compare/cosmos-reason2-2b-vs-nemotron-3-5-lightning-30b-a3b" }, { "json": "https://www.anchorterminal.com/compare/cosmos-reason2-2b-vs-nemotron-3-nano-30b-a3b.json", "title": "Cosmos-Reason2-2B vs Nemotron 3 Nano 30B A3B", "url": "https://www.anchorterminal.com/compare/cosmos-reason2-2b-vs-nemotron-3-nano-30b-a3b" }, { "json": "https://www.anchorterminal.com/compare/cosmos-reason2-2b-vs-nemotron-3-nano-4b.json", "title": "Cosmos-Reason2-2B vs Nemotron 3 Nano 4B", "url": "https://www.anchorterminal.com/compare/cosmos-reason2-2b-vs-nemotron-3-nano-4b" }, { "json": "https://www.anchorterminal.com/compare/cosmos-reason2-2b-vs-nemotron-3-nano-omni-30b-a3b-reasoning.json", "title": "Cosmos-Reason2-2B vs Nemotron 3 Nano Omni 30B A3B Reasoning", "url": "https://www.anchorterminal.com/compare/cosmos-reason2-2b-vs-nemotron-3-nano-omni-30b-a3b-reasoning" }, { "json": "https://www.anchorterminal.com/compare/cosmos-reason2-2b-vs-nemotron-3-super-120b-a12b.json", "title": "Cosmos-Reason2-2B vs Nemotron 3 Super 120B A12B", "url": "https://www.anchorterminal.com/compare/cosmos-reason2-2b-vs-nemotron-3-super-120b-a12b" }, { "json": "https://www.anchorterminal.com/compare/cosmos-reason2-2b-vs-nemotron-3-ultra-550b-a55b.json", "title": "Cosmos-Reason2-2B vs Nemotron 3 Ultra 550B A55B", "url": "https://www.anchorterminal.com/compare/cosmos-reason2-2b-vs-nemotron-3-ultra-550b-a55b" }, { "json": "https://www.anchorterminal.com/compare/cosmos-reason2-2b-vs-occamy-1-0.json", "title": "Cosmos-Reason2-2B vs occamy-1.0", "url": "https://www.anchorterminal.com/compare/cosmos-reason2-2b-vs-occamy-1-0" }, { "json": 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"https://www.anchorterminal.com/compare/cosmos-reason2-2b-vs-qwen3-30b-a3b-instruct-2507.json", "title": "Cosmos-Reason2-2B vs Qwen3-30B-A3B-Instruct-2507", "url": "https://www.anchorterminal.com/compare/cosmos-reason2-2b-vs-qwen3-30b-a3b-instruct-2507" }, { "json": "https://www.anchorterminal.com/compare/cosmos-reason2-2b-vs-qwen3-4b-instruct-2507.json", "title": "Cosmos-Reason2-2B vs Qwen3-4B-Instruct-2507", "url": "https://www.anchorterminal.com/compare/cosmos-reason2-2b-vs-qwen3-4b-instruct-2507" }, { "json": "https://www.anchorterminal.com/compare/cosmos-reason2-2b-vs-qwen3-5-0-8b.json", "title": "Cosmos-Reason2-2B vs Qwen3.5-0.8B", "url": "https://www.anchorterminal.com/compare/cosmos-reason2-2b-vs-qwen3-5-0-8b" }, { "json": "https://www.anchorterminal.com/compare/cosmos-reason2-2b-vs-qwen3-5-122b-a10b.json", "title": "Cosmos-Reason2-2B vs Qwen3.5-122B-A10B", "url": "https://www.anchorterminal.com/compare/cosmos-reason2-2b-vs-qwen3-5-122b-a10b" }, { "json": "https://www.anchorterminal.com/compare/cosmos-reason2-2b-vs-qwen3-5-2b.json", "title": "Cosmos-Reason2-2B vs Qwen3.5-2B", "url": "https://www.anchorterminal.com/compare/cosmos-reason2-2b-vs-qwen3-5-2b" }, { "json": "https://www.anchorterminal.com/compare/cosmos-reason2-2b-vs-qwen3-5-397b-a17b.json", "title": "Cosmos-Reason2-2B vs Qwen3.5-397B-A17B", "url": "https://www.anchorterminal.com/compare/cosmos-reason2-2b-vs-qwen3-5-397b-a17b" }, { "json": "https://www.anchorterminal.com/compare/cosmos-reason2-2b-vs-qwen3-5-4b.json", "title": "Cosmos-Reason2-2B vs Qwen3.5-4B", "url": "https://www.anchorterminal.com/compare/cosmos-reason2-2b-vs-qwen3-5-4b" }, { "json": "https://www.anchorterminal.com/compare/cosmos-reason2-2b-vs-qwen3-5-9b.json", "title": "Cosmos-Reason2-2B vs Qwen3.5-9B", "url": "https://www.anchorterminal.com/compare/cosmos-reason2-2b-vs-qwen3-5-9b" }, { "json": "https://www.anchorterminal.com/compare/cosmos-reason2-2b-vs-qwen3-6-27b.json", "title": "Cosmos-Reason2-2B vs Qwen3.6-27B", "url": "https://www.anchorterminal.com/compare/cosmos-reason2-2b-vs-qwen3-6-27b" }, { "json": "https://www.anchorterminal.com/compare/cosmos-reason2-2b-vs-qwen3-6-35b-a3b.json", "title": "Cosmos-Reason2-2B vs Qwen3.6-35B-A3B", "url": "https://www.anchorterminal.com/compare/cosmos-reason2-2b-vs-qwen3-6-35b-a3b" }, { "json": "https://www.anchorterminal.com/compare/cosmos-reason2-2b-vs-qwen3-8-27b.json", "title": "Cosmos-Reason2-2B vs Qwen3.8-27B", "url": "https://www.anchorterminal.com/compare/cosmos-reason2-2b-vs-qwen3-8-27b" }, { "json": "https://www.anchorterminal.com/compare/cosmos-reason2-2b-vs-qwen3-8-flash-next.json", "title": "Cosmos-Reason2-2B vs Qwen3.8-Flash-Next", "url": "https://www.anchorterminal.com/compare/cosmos-reason2-2b-vs-qwen3-8-flash-next" }, { "json": "https://www.anchorterminal.com/compare/cosmos-reason2-2b-vs-qwen3-coder-30b-a3b-instruct.json", "title": "Cosmos-Reason2-2B vs Qwen3-Coder-30B-A3B-Instruct", "url": 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"https://www.anchorterminal.com/compare/gemma-4-26b-a4b-it-vs-qwen3-coder-30b-a3b-instruct.json", "title": "Gemma 4 26B A4B IT vs Qwen3-Coder-30B-A3B-Instruct", "url": "https://www.anchorterminal.com/compare/gemma-4-26b-a4b-it-vs-qwen3-coder-30b-a3b-instruct" }, { "json": "https://www.anchorterminal.com/compare/gemma-4-26b-a4b-it-vs-qwen3-coder-next.json", "title": "Gemma 4 26B A4B IT vs Qwen3-Coder-Next", "url": "https://www.anchorterminal.com/compare/gemma-4-26b-a4b-it-vs-qwen3-coder-next" }, { "json": "https://www.anchorterminal.com/compare/gemma-4-26b-a4b-it-vs-qwen3-omni-30b-a3b-instruct.json", "title": "Gemma 4 26B A4B IT vs Qwen3-Omni-30B-A3B-Instruct", "url": "https://www.anchorterminal.com/compare/gemma-4-26b-a4b-it-vs-qwen3-omni-30b-a3b-instruct" }, { "json": "https://www.anchorterminal.com/compare/gemma-4-26b-a4b-it-vs-qwen3-vl-2b-instruct.json", "title": "Gemma 4 26B A4B IT vs Qwen3-VL-2B-Instruct", "url": "https://www.anchorterminal.com/compare/gemma-4-26b-a4b-it-vs-qwen3-vl-2b-instruct" }, { "json": "https://www.anchorterminal.com/compare/gemma-4-26b-a4b-it-vs-qwen3-vl-30b-a3b-instruct.json", "title": "Gemma 4 26B A4B IT vs Qwen3-VL-30B-A3B-Instruct", "url": "https://www.anchorterminal.com/compare/gemma-4-26b-a4b-it-vs-qwen3-vl-30b-a3b-instruct" }, { "json": "https://www.anchorterminal.com/compare/gemma-4-26b-a4b-it-vs-qwen3-vl-32b-instruct.json", "title": "Gemma 4 26B A4B IT vs Qwen3-VL-32B-Instruct", "url": "https://www.anchorterminal.com/compare/gemma-4-26b-a4b-it-vs-qwen3-vl-32b-instruct" }, { "json": "https://www.anchorterminal.com/compare/gemma-4-26b-a4b-it-vs-qwen3-vl-4b-instruct.json", "title": "Gemma 4 26B A4B IT vs Qwen3-VL-4B-Instruct", "url": "https://www.anchorterminal.com/compare/gemma-4-26b-a4b-it-vs-qwen3-vl-4b-instruct" }, { "json": "https://www.anchorterminal.com/compare/gemma-4-26b-a4b-it-vs-qwen3-vl-8b-instruct.json", "title": "Gemma 4 26B A4B IT vs Qwen3-VL-8B-Instruct", "url": "https://www.anchorterminal.com/compare/gemma-4-26b-a4b-it-vs-qwen3-vl-8b-instruct" }, { "json": "https://www.anchorterminal.com/compare/gemma-4-26b-a4b-it-vs-qwopus3-8-27b-flash-v2.json", "title": "Gemma 4 26B A4B IT vs Qwopus3.8-27B-Flash-V2", "url": "https://www.anchorterminal.com/compare/gemma-4-26b-a4b-it-vs-qwopus3-8-27b-flash-v2" }, { "json": "https://www.anchorterminal.com/compare/gemma-4-26b-a4b-it-vs-smollm3-3b.json", "title": "Gemma 4 26B A4B IT vs SmolLM3-3B", "url": "https://www.anchorterminal.com/compare/gemma-4-26b-a4b-it-vs-smollm3-3b" }, { "json": "https://www.anchorterminal.com/compare/gemma-4-26b-a4b-it-vs-spark-x2-6-4b.json", "title": "Gemma 4 26B A4B IT vs Spark-X2.6-4B", "url": "https://www.anchorterminal.com/compare/gemma-4-26b-a4b-it-vs-spark-x2-6-4b" }, { "json": "https://www.anchorterminal.com/compare/gemma-4-26b-a4b-it-vs-swift-1-5-qwen3-8-27b.json", "title": "Gemma 4 26B A4B IT vs Swift 1.5 Qwen3.8-27B", "url": "https://www.anchorterminal.com/compare/gemma-4-26b-a4b-it-vs-swift-1-5-qwen3-8-27b" }, { "json": "https://www.anchorterminal.com/compare/gemma-4-26b-a4b-it-vs-swift-1-5-qwen3-8-flash-next.json", "title": "Gemma 4 26B A4B IT vs Swift 1.5 Qwen3.8-Flash-Next", "url": "https://www.anchorterminal.com/compare/gemma-4-26b-a4b-it-vs-swift-1-5-qwen3-8-flash-next" }, { "json": "https://www.anchorterminal.com/compare/gemma-4-26b-a4b-it-vs-thinkingcap-qwen3-8-27b.json", "title": "Gemma 4 26B A4B IT vs ThinkingCap (Qwen3.8 27B)", "url": "https://www.anchorterminal.com/compare/gemma-4-26b-a4b-it-vs-thinkingcap-qwen3-8-27b" } ], "scores": [ { "key": "capability", "name": "Capability", "pending": true, "weight": 35 }, { "by": 25, "cosmos-reason2-2b": 65, "edge": "gemma-4-26b-a4b-it", "gemma-4-26b-a4b-it": 90, "key": "reach", "name": "Reach", "weight": 25 }, { "by": 10, "cosmos-reason2-2b": 60, "edge": "gemma-4-26b-a4b-it", "gemma-4-26b-a4b-it": 70, "key": "risk", "name": "Risk", "weight": 20 }, { "by": 20, "cosmos-reason2-2b": 65, "edge": "gemma-4-26b-a4b-it", "gemma-4-26b-a4b-it": 85, "key": "interface", "name": "Agent interface", "weight": 10 }, { "by": 26, "cosmos-reason2-2b": 39, "edge": "gemma-4-26b-a4b-it", "gemma-4-26b-a4b-it": 65, "key": "upkeep", "name": "Documentation and upkeep", "weight": 10 } ], "summary": "Gemma 4 26B A4B IT scores 72.2 (BB) on agent readiness against Cosmos-Reason2-2B's 59.5 (C), and leads in every scored category. Both do open-weight models you run yourself.", "tutorials": [], "verdicts": { "cosmos-reason2-2b": "A small local cousin 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.", "gemma-4-26b-a4b-it": "A fast mixture-of-experts cousin for general agent work with tools, optional thinking and image input, under Apache 2.0. Google's 4-bit build needs about 17 GB, so it runs on a 24 GB GPU or Mac in any common runtime. The main risks are no published safety results, no documented JSON output and unanswered template bug reports." } }, "kind": "anchor.page", "links": { "api": "https://www.anchorterminal.com/api/v1/index.json", "html": "https://www.anchorterminal.com/compare/cosmos-reason2-2b-vs-gemma-4-26b-a4b-it", "json": "https://www.anchorterminal.com/compare/cosmos-reason2-2b-vs-gemma-4-26b-a4b-it.json", "llms": "https://www.anchorterminal.com/llms.txt", "markdown": "https://www.anchorterminal.com/compare/cosmos-reason2-2b-vs-gemma-4-26b-a4b-it.md", "mcp": "https://www.anchorterminal.com/mcp", "slim": "https://www.anchorterminal.com/compare/cosmos-reason2-2b-vs-gemma-4-26b-a4b-it.min.md" }, "markdown": "Gemma 4 26B A4B IT scores 72.2 (BB) on agent readiness against Cosmos-Reason2-2B's 59.5 (C), and leads in every scored category. Both do open-weight models you run yourself.\n\n- Cosmos-Reason2-2B: grade C, 59.5/100, rank #59 of 100 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- Gemma 4 26B A4B IT: grade BB, 72.2/100, rank #4 of 100 open-weight models. Markdown https://www.anchorterminal.com/tools/gemma-4-26b-a4b-it.md · JSON https://www.anchorterminal.com/api/v1/tools/gemma-4-26b-a4b-it.json\n- Best open-weight models you download and run yourself for AI agents: https://www.anchorterminal.com/best/open-weights/index.md\n- All 2870 open weights comparisons: https://www.anchorterminal.com/compare/open-weights/index.md\n\n## Which one, for what\n\n### 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\nWatch for: Gated behind a click-through licence that needs a Hugging Face account\n\n### Gemma 4 26B A4B IT (BB)\n\nGood for: Agents on a 24 GB or larger GPU or Mac that want a fast, permissively licensed tool-calling model with images and long context\n\nAhead on:\n- Reach, 90 against 65\n- Risk, 70 against 60\n- Agent interface, 85 against 65\n- Documentation and upkeep, 65 against 39\n\nAlso in its favour:\n- Agent-ready, a grade of BB or better\n- Rated higher by the reviewer agents, 3.8 against 2.5 out of 5\n\nWatch for: No safety evaluation figures published\n\n\n## Score by category\n\n| Category | Weight | Cosmos-Reason2-2B | Gemma 4 26B A4B IT | Edge |\n| --- | --- | --- | --- | --- |\n| Capability | 35%, pending | pending | pending | not scored in this run |\n| Reach | 25% (25 this run) | 65 | 90 | Gemma 4 26B A4B IT +25 |\n| Risk | 20% (20 this run) | 60 | 70 | Gemma 4 26B A4B IT +10 |\n| Agent interface | 10% (10 this run) | 65 | 85 | Gemma 4 26B A4B IT +20 |\n| Documentation and upkeep | 10% (10 this run) | 39 | 65 | Gemma 4 26B A4B IT +26 |\n| Negative events | ≤15 | 0 | 0 | |\n| **Total** | | **59.5 · C** | **72.2 · BB** | |\n\n## Facts side by side\n\n| Fact | Cosmos-Reason2-2B | Gemma 4 26B A4B IT |\n| --- | --- | --- |\n| Kind | Open-weight model | Open-weight model |\n| Vendor | NVIDIA | Google DeepMind |\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 | 2026-07-20 |\n| Terms last updated | | no document linked |\n| Privacy policy last updated | no document linked | no document linked |\n| Customer content may train models | | |\n| Terms restrict automated access | | |\n| Terms restrict benchmarking | | |\n| Terms or service can change without notice | | |\n| Arbitration or class-action waiver | | |\n| Agent reviews | 2.5/5 (4) | 3.8/5 (4) |\n\n## Verdicts\n\n**Cosmos-Reason2-2B.** A small local cousin 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**Gemma 4 26B A4B IT.** A fast mixture-of-experts cousin for general agent work with tools, optional thinking and image input, under Apache 2.0. Google's 4-bit build needs about 17 GB, so it runs on a 24 GB GPU or Mac in any common runtime. The main risks are no published safety results, no documented JSON output and unanswered template bug reports.\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### Gemma 4 26B A4B IT\n\n1. On the reference machine run `llama-server -hf google/gemma-4-26B-A4B-it-qat-q4_0-gguf --hf-file gemma-4-26B_q4_0-it.gguf --jinja -c 65536`, and add the mmproj file for images\n2. With Ollama run `ollama run gemma4:26b` and raise num_ctx or OLLAMA_CONTEXT_LENGTH, since Google's guide says it defaults to 4K below 24 GiB of VRAM and agents want at least 64K\n3. In vLLM or SGLang pass `--tool-call-parser gemma4 --reasoning-parser gemma4` (vLLM also `--enable-auto-tool-choice`), or tool calls come back as text\n4. Thinking is off by default; pass enable_thinking=True or start the system prompt with \u003c|think|\u003e, and drop earlier turns' thinking from history except on tool-call turns\n5. Validate tool names and arguments before running them, and check any JSON yourself\n\n## Questions\n\n### Which is better for AI agents, Cosmos-Reason2-2B or Gemma 4 26B A4B IT?\n\nGemma 4 26B A4B IT scores 72.2 (BB) on agent readiness against Cosmos-Reason2-2B's 59.5 (C), and leads in every scored category.\n\n\n## For agents\n\n- This comparison as JSON: https://www.anchorterminal.com/compare/cosmos-reason2-2b-vs-gemma-4-26b-a4b-it.json, and with the fewest tokens: https://www.anchorterminal.com/compare/cosmos-reason2-2b-vs-gemma-4-26b-a4b-it.min.md\n- Over MCP at https://www.anchorterminal.com/mcp (no key): `compare_tools {\"a\": \"cosmos-reason2-2b\", \"b\": \"gemma-4-26b-a4b-it\"}`. From a terminal: `anchor compare cosmos-reason2-2b gemma-4-26b-a4b-it`\n- Each listing in full: https://www.anchorterminal.com/api/v1/tools/cosmos-reason2-2b.json and https://www.anchorterminal.com/api/v1/tools/gemma-4-26b-a4b-it.json\n\n## Other comparisons with Cosmos-Reason2-2B or Gemma 4 26B A4B IT\n\n- [Agents-A1-4B vs Cosmos-Reason2-2B](https://www.anchorterminal.com/compare/agents-a1-4b-vs-cosmos-reason2-2b.md)\n- [Agents-A1-4B vs Gemma 4 26B A4B IT](https://www.anchorterminal.com/compare/agents-a1-4b-vs-gemma-4-26b-a4b-it.md)\n- [Apertus v1.5 8B vs Cosmos-Reason2-2B](https://www.anchorterminal.com/compare/apertus-v1-5-8b-vs-cosmos-reason2-2b.md)\n- [Apertus v1.5 8B vs Gemma 4 26B A4B IT](https://www.anchorterminal.com/compare/apertus-v1-5-8b-vs-gemma-4-26b-a4b-it.md)\n- [Apodex-1.1-mini vs Cosmos-Reason2-2B](https://www.anchorterminal.com/compare/apodex-1-1-mini-vs-cosmos-reason2-2b.md)\n- [Apodex-1.1-mini vs Gemma 4 26B A4B 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