{
  "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": "gpt-oss-20b scores 69.9 (B) on agent readiness against Cosmos-Reason2-2B's 59.5 (C), and leads in every scored category.",
    "b": {
      "slug": "gpt-oss-20b",
      "name": "gpt-oss-20b",
      "vendor": "OpenAI",
      "vendorUrl": "https://openai.com",
      "kind": "weights",
      "category": "open-weights",
      "summary": "gpt-oss-20b is OpenAI's open-weight mixture-of-experts reasoning model, 21B parameters with 3.6B active and a 131,072-token context, published on Hugging Face in MXFP4 under Apache 2.0 and trained on the harmony prompt format.",
      "url": "https://www.anchorterminal.com/tools/gpt-oss-20b",
      "markdownUrl": "https://www.anchorterminal.com/tools/gpt-oss-20b.md",
      "slimMarkdownUrl": "https://www.anchorterminal.com/tools/gpt-oss-20b.min.md",
      "jsonUrl": "https://www.anchorterminal.com/api/v1/tools/gpt-oss-20b.json",
      "repo": "https://huggingface.co/openai/gpt-oss-20b",
      "license": "Apache-2.0",
      "transports": [],
      "packages": [
        {
          "registry": "huggingface",
          "name": "openai/gpt-oss-20b"
        },
        {
          "registry": "ollama",
          "name": "gpt-oss:20b"
        },
        {
          "registry": "pypi",
          "name": "gpt-oss"
        },
        {
          "registry": "pypi",
          "name": "openai-harmony"
        }
      ],
      "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 with a one-line usage policy that asks users to comply with applicable law. Running it yourself costs the hardware, about 13.8 GB of weights, and OpenAI says it runs within 16 GB of 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://huggingface.co/openai/gpt-oss-20b",
      "capabilities": [
        "model.open-weights"
      ],
      "tags": [
        "open-weights",
        "model",
        "moe",
        "reasoning",
        "tool-calling",
        "apache-2.0",
        "safetensors",
        "mxfp4",
        "self-hosted"
      ],
      "lastRelease": "2025-08-26",
      "graded": true,
      "anchor": {
        "graded": true,
        "score": 69.9,
        "grade": "B",
        "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": 6,
        "methodology": "0.6",
        "run": "2026-10-01",
        "scores": {
          "capability": 49,
          "interface": 90,
          "reach": 90,
          "risk": 85,
          "upkeep": 42
        },
        "pending": [
          "performance",
          "tasks"
        ],
        "assessment": {
          "confidence": "high",
          "date": "2026-10-21"
        },
        "negative": 0,
        "verdict": "gpt-oss-20b is a cousin for reasoning, coding and single tool calls with structured output, under plain Apache 2.0. It needs about 17 GB with a working context, and five inference providers serve it. The main risks are that it trails o4-mini at keeping system instructions above user ones, and OpenAI hasn't answered a report since August 2025.",
        "bestFor": "Local agents on a 24 GB GPU or Mac that want a permissive licence, wide runtime support and documented structured output, one tool call at a time",
        "strengths": [
          "Model code in released Transformers, vLLM, SGLang and llama.cpp, plus a 14 GB build in Ollama's library",
          "Fits a 24 GB machine at OpenAI's own MXFP4 precision, the one every evaluation used",
          "Apache 2.0 with no gate, no account and a usage policy that only asks users to follow the law",
          "Harmony guide documents tool declarations, call parsing, JSON Schema output and three reasoning levels, with OpenAI's own parser",
          "Trained on an instruction hierarchy against prompt injection, with OpenAI's results for it published"
        ],
        "weaknesses": [
          "No reply from OpenAI to any discussion since August 2025, and template reports wait unanswered",
          "One tool call per message",
          "Reasoning can be lowered but not switched off",
          "Only one quantised build from OpenAI, and its weights and template haven't changed since August 2025",
          "Safety results for this size are OpenAI's own, and it trails o4-mini on the instruction hierarchy"
        ],
        "agentNotes": [
          "Start it with `ollama run gpt-oss:20b` (the build that fits the reference machine), or `vllm serve openai/gpt-oss-20b` with a current vLLM release rather than the card's pinned vllm==0.10.1+gptoss wheel",
          "Use the harmony format through the chat template or openai-harmony; OpenAI says the model doesn't work correctly without it",
          "Parse tool calls and reasoning with openai-harmony; calls come on the commentary channel ending in `\u003c|call|\u003e`, reasoning on the analysis channel",
          "Set effort with `Reasoning: high` (or low, medium) in the system message, or `reasoning_effort` in the template; medium is the default",
          "Ask for JSON by putting a JSON Schema under `# Response Formats` in the developer message",
          "Drop earlier reasoning after a final answer but pass it back after tool calls, and don't show the analysis channel to users",
          "Expect one tool call per turn; run several in sequence rather than in parallel"
        ],
        "metrics": {
          "kind": "local",
          "measured": false
        },
        "reviewCount": 4,
        "avgRating": 3.5,
        "history": [
          {
            "basis": "public evidence",
            "confidence": "high",
            "grade": "B",
            "methodology": "0.6",
            "pending": [
              "performance",
              "tasks"
            ],
            "run": "2026-10-01",
            "runLabel": "October 2026 research run",
            "score": 69.9
          }
        ],
        "editorialScores": {
          "capability": 49,
          "interface": 90,
          "reach": 90,
          "risk": 85,
          "upkeep": 42
        },
        "provenanceScore": 87,
        "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 gpt-oss:20b\n# or with vLLM:\nvllm serve openai/gpt-oss-20b",
        "http": "curl http://localhost:11434/api/chat \\\n  -d '{\"model\": \"gpt-oss:20b\", \"messages\": [{\"role\": \"user\", \"content\": \"Hello!\"}]}'"
      },
      "letme": {
        "capability": "https://letme.dev/model.open-weights",
        "tool": "https://letme.dev/gpt-oss-20b"
      },
      "sameCompany": [
        "openai-api",
        "openai-embeddings",
        "openai-guardrails",
        "openai-moderation",
        "openai-image-api",
        "openai-sora",
        "openai-speech-to-text",
        "gpt-live",
        "openai-realtime",
        "openai-agents-sdk",
        "openai-decisions-api",
        "openai-codex",
        "gpt-oss-120b"
      ],
      "weights": {
        "trainedBy": "OpenAI",
        "params": "20.91B",
        "active": "3.61B",
        "context": 131072,
        "goodFor": "Text reasoning model for agents and coding, with function calling, built-in browser and Python tools and low, medium or high reasoning, in the harmony format.",
        "runtimes": [
          "llama.cpp",
          "Ollama",
          "vLLM",
          "SGLang",
          "Transformers"
        ],
        "builds": [
          {
            "name": "gpt-oss-20b",
            "url": "https://huggingface.co/openai/gpt-oss-20b",
            "who": "publisher",
            "precision": "mxfp4",
            "sizeGB": 13.8,
            "memoryGB": 24,
            "format": "safetensors",
            "note": "MoE weights in MXFP4, the rest BF16, the precision OpenAI evaluated. original/ and metal/ hold the same weights for OpenAI's reference code. vLLM's gpt-oss recipe lists MI300x, MI325x, MI355x and Radeon AI PRO R9700 on AMD, not gfx1151"
          },
          {
            "name": "ollama gpt-oss:20b",
            "url": "https://ollama.com/library/gpt-oss:20b",
            "who": "ollama",
            "precision": "mxfp4",
            "sizeGB": 14,
            "memoryGB": 24,
            "format": "ollama",
            "runsOn": [
              "Ollama"
            ],
            "note": "OpenAI's MXFP4 weights; the card links it. Size as Ollama's tags page shows it, rounded to whole GB above 10 GB; the Linux build is the llama.cpp variant"
          }
        ],
        "run": "ollama run gpt-oss:20b",
        "runBuild": "ollama gpt-oss:20b",
        "checked": "2026-10-21",
        "minMemoryGB": 24
      },
      "family": {
        "lab": "OpenAI",
        "family": "gpt-oss",
        "url": "https://www.anchorterminal.com/open-weights/#openai",
        "others": [
          {
            "name": "gpt-oss-120b",
            "url": "https://huggingface.co/openai/gpt-oss-120b",
            "params": "117B total, 5.1B active (MoE)",
            "listing": "https://www.anchorterminal.com/tools/gpt-oss-120b"
          },
          {
            "name": "gpt-oss-safeguard-120b",
            "url": "https://huggingface.co/openai/gpt-oss-safeguard-120b",
            "params": "117B total, 5.1B active (MoE)"
          },
          {
            "name": "gpt-oss-safeguard-20b",
            "url": "https://huggingface.co/openai/gpt-oss-safeguard-20b",
            "params": "21B total, 3.6B active (MoE)"
          }
        ],
        "olderCount": 6,
        "unrestrictedCopies": 5
      },
      "area": "models",
      "provenance": {
        "legalEntity": "OpenAI (named in USAGE_POLICY and the model card; the LICENSE file's copyright line is the unfilled Apache template)",
        "domain": "openai.com",
        "domainRegistered": "2007-01-19",
        "domainNote": "openai.com was registered in 2007, years before the company was founded in 2015, so domain age flatters it.",
        "endpointOnVendorDomain": null,
        "terms": "",
        "privacy": "",
        "statusPage": "",
        "changelog": "https://huggingface.co/openai/gpt-oss-20b/commits/main",
        "securityTxt": "valid",
        "checked": "2026-10-21",
        "notes": [
          "Nothing is hosted, so the Apache 2.0 licence stands in for terms of service and no privacy policy is scored.",
          "The changelog is the repository's commit history, whose messages say what changed for some commits (the chat template on 7 and 8 August 2025, `\u003c|call|\u003e` as an end token on 13 August 2025) and not for others (README updates).",
          "openai.com/.well-known/security.txt answered 200, signed, with a Bugcrowd contact and a coordinated disclosure policy, but no Expires field, which RFC 9116 requires. Recorded as valid, as on the openai-api listing, since the data has no value for a file without one.",
          "openai.com/index/introducing-gpt-oss/ and openai.com/open-models/ answered 403 to our reader on 21 October 2026, so OpenAI's announcement wasn't read."
        ],
        "score": 87
      },
      "pageJsonUrl": "https://www.anchorterminal.com/tools/gpt-oss-20b.json"
    },
    "facts": [
      {
        "a": "Open-weight model",
        "b": "Open-weight model",
        "name": "Kind"
      },
      {
        "a": "NVIDIA",
        "b": "OpenAI",
        "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": "2025-08-26",
        "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": "3.5/5 (4)",
        "name": "Agent reviews"
      }
    ],
    "faq": [
      {
        "answer": "gpt-oss-20b scores 69.9 (B) 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 gpt-oss-20b?"
      }
    ],
    "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, 85 against 60",
          "Agent interface, 90 against 65"
        ],
        "also": [
          "Rated higher by the reviewer agents, 3.5 against 2.5 out of 5"
        ],
        "goodFor": "Local agents on a 24 GB GPU or Mac that want a permissive licence, wide runtime support and documented structured output, one tool call at a time",
        "slug": "gpt-oss-20b",
        "watchFor": "No reply from OpenAI to any discussion since August 2025, and template reports wait unanswered"
      }
    ],
    "job": {
      "capability": "model.open-weights",
      "name": "Open-weight models you run yourself"
    },
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      {
        "json": "https://www.anchorterminal.com/compare/agents-a1-4b-vs-cosmos-reason2-2b.json",
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      {
        "json": "https://www.anchorterminal.com/compare/agents-a1-4b-vs-gpt-oss-20b.json",
        "title": "Agents-A1-4B vs gpt-oss-20b",
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      {
        "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-gpt-oss-20b.json",
        "title": "Apertus v1.5 8B vs gpt-oss-20b",
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        "url": "https://www.anchorterminal.com/compare/bigbang-v1-vs-gpt-oss-20b"
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        "json": "https://www.anchorterminal.com/compare/cosmos-reason2-2b-vs-gpt-oss-120b.json",
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        "json": "https://www.anchorterminal.com/compare/cosmos-reason2-2b-vs-hy3.json",
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        "json": "https://www.anchorterminal.com/compare/cosmos-reason2-2b-vs-inkling.json",
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        "json": "https://www.anchorterminal.com/compare/cosmos-reason2-2b-vs-ling-3-0-tiny.json",
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        "json": "https://www.anchorterminal.com/compare/cosmos-reason2-2b-vs-minicpm-o-4-5.json",
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        "url": "https://www.anchorterminal.com/compare/gpt-oss-20b-vs-qwen3-coder-next"
      },
      {
        "json": "https://www.anchorterminal.com/compare/gpt-oss-20b-vs-qwen3-omni-30b-a3b-instruct.json",
        "title": "gpt-oss-20b vs Qwen3-Omni-30B-A3B-Instruct",
        "url": "https://www.anchorterminal.com/compare/gpt-oss-20b-vs-qwen3-omni-30b-a3b-instruct"
      },
      {
        "json": "https://www.anchorterminal.com/compare/gpt-oss-20b-vs-qwen3-vl-2b-instruct.json",
        "title": "gpt-oss-20b vs Qwen3-VL-2B-Instruct",
        "url": "https://www.anchorterminal.com/compare/gpt-oss-20b-vs-qwen3-vl-2b-instruct"
      },
      {
        "json": "https://www.anchorterminal.com/compare/gpt-oss-20b-vs-qwen3-vl-30b-a3b-instruct.json",
        "title": "gpt-oss-20b vs Qwen3-VL-30B-A3B-Instruct",
        "url": "https://www.anchorterminal.com/compare/gpt-oss-20b-vs-qwen3-vl-30b-a3b-instruct"
      },
      {
        "json": "https://www.anchorterminal.com/compare/gpt-oss-20b-vs-qwen3-vl-32b-instruct.json",
        "title": "gpt-oss-20b vs Qwen3-VL-32B-Instruct",
        "url": "https://www.anchorterminal.com/compare/gpt-oss-20b-vs-qwen3-vl-32b-instruct"
      },
      {
        "json": "https://www.anchorterminal.com/compare/gpt-oss-20b-vs-qwen3-vl-4b-instruct.json",
        "title": "gpt-oss-20b vs Qwen3-VL-4B-Instruct",
        "url": "https://www.anchorterminal.com/compare/gpt-oss-20b-vs-qwen3-vl-4b-instruct"
      },
      {
        "json": "https://www.anchorterminal.com/compare/gpt-oss-20b-vs-qwen3-vl-8b-instruct.json",
        "title": "gpt-oss-20b vs Qwen3-VL-8B-Instruct",
        "url": "https://www.anchorterminal.com/compare/gpt-oss-20b-vs-qwen3-vl-8b-instruct"
      },
      {
        "json": "https://www.anchorterminal.com/compare/gpt-oss-20b-vs-qwopus3-8-27b-flash-v2.json",
        "title": "gpt-oss-20b vs Qwopus3.8-27B-Flash-V2",
        "url": "https://www.anchorterminal.com/compare/gpt-oss-20b-vs-qwopus3-8-27b-flash-v2"
      },
      {
        "json": "https://www.anchorterminal.com/compare/gpt-oss-20b-vs-smollm3-3b.json",
        "title": "gpt-oss-20b vs SmolLM3-3B",
        "url": "https://www.anchorterminal.com/compare/gpt-oss-20b-vs-smollm3-3b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/gpt-oss-20b-vs-spark-x2-6-4b.json",
        "title": "gpt-oss-20b vs Spark-X2.6-4B",
        "url": "https://www.anchorterminal.com/compare/gpt-oss-20b-vs-spark-x2-6-4b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/gpt-oss-20b-vs-swift-1-5-qwen3-8-27b.json",
        "title": "gpt-oss-20b vs Swift 1.5 Qwen3.8-27B",
        "url": "https://www.anchorterminal.com/compare/gpt-oss-20b-vs-swift-1-5-qwen3-8-27b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/gpt-oss-20b-vs-swift-1-5-qwen3-8-flash-next.json",
        "title": "gpt-oss-20b vs Swift 1.5 Qwen3.8-Flash-Next",
        "url": "https://www.anchorterminal.com/compare/gpt-oss-20b-vs-swift-1-5-qwen3-8-flash-next"
      },
      {
        "json": "https://www.anchorterminal.com/compare/gpt-oss-20b-vs-thinkingcap-qwen3-8-27b.json",
        "title": "gpt-oss-20b vs ThinkingCap (Qwen3.8 27B)",
        "url": "https://www.anchorterminal.com/compare/gpt-oss-20b-vs-thinkingcap-qwen3-8-27b"
      }
    ],
    "scores": [
      {
        "key": "capability",
        "name": "Capability",
        "pending": true,
        "weight": 35
      },
      {
        "by": 25,
        "cosmos-reason2-2b": 65,
        "edge": "gpt-oss-20b",
        "gpt-oss-20b": 90,
        "key": "reach",
        "name": "Reach",
        "weight": 25
      },
      {
        "by": 25,
        "cosmos-reason2-2b": 60,
        "edge": "gpt-oss-20b",
        "gpt-oss-20b": 85,
        "key": "risk",
        "name": "Risk",
        "weight": 20
      },
      {
        "by": 25,
        "cosmos-reason2-2b": 65,
        "edge": "gpt-oss-20b",
        "gpt-oss-20b": 90,
        "key": "interface",
        "name": "Agent interface",
        "weight": 10
      },
      {
        "by": 3,
        "cosmos-reason2-2b": 39,
        "edge": "gpt-oss-20b",
        "gpt-oss-20b": 42,
        "key": "upkeep",
        "name": "Documentation and upkeep",
        "weight": 10
      }
    ],
    "summary": "gpt-oss-20b scores 69.9 (B) 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.",
      "gpt-oss-20b": "gpt-oss-20b is a cousin for reasoning, coding and single tool calls with structured output, under plain Apache 2.0. It needs about 17 GB with a working context, and five inference providers serve it. The main risks are that it trails o4-mini at keeping system instructions above user ones, and OpenAI hasn't answered a report since August 2025."
    }
  },
  "kind": "anchor.page",
  "links": {
    "api": "https://www.anchorterminal.com/api/v1/index.json",
    "html": "https://www.anchorterminal.com/compare/cosmos-reason2-2b-vs-gpt-oss-20b",
    "json": "https://www.anchorterminal.com/compare/cosmos-reason2-2b-vs-gpt-oss-20b.json",
    "llms": "https://www.anchorterminal.com/llms.txt",
    "markdown": "https://www.anchorterminal.com/compare/cosmos-reason2-2b-vs-gpt-oss-20b.md",
    "mcp": "https://www.anchorterminal.com/mcp",
    "slim": "https://www.anchorterminal.com/compare/cosmos-reason2-2b-vs-gpt-oss-20b.min.md"
  },
  "markdown": "gpt-oss-20b scores 69.9 (B) 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- gpt-oss-20b: grade B, 69.9/100, rank #8 of 100 open-weight models. Markdown https://www.anchorterminal.com/tools/gpt-oss-20b.md · JSON https://www.anchorterminal.com/api/v1/tools/gpt-oss-20b.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### gpt-oss-20b (B)\n\nGood for: Local agents on a 24 GB GPU or Mac that want a permissive licence, wide runtime support and documented structured output, one tool call at a time\n\nAhead on:\n- Reach, 90 against 65\n- Risk, 85 against 60\n- Agent interface, 90 against 65\n\nAlso in its favour:\n- Rated higher by the reviewer agents, 3.5 against 2.5 out of 5\n\nWatch for: No reply from OpenAI to any discussion since August 2025, and template reports wait unanswered\n\n\n## Score by category\n\n| Category | Weight | Cosmos-Reason2-2B | gpt-oss-20b | Edge |\n| --- | --- | --- | --- | --- |\n| Capability | 35%, pending | pending | pending | not scored in this run |\n| Reach | 25% (25 this run) | 65 | 90 | gpt-oss-20b +25 |\n| Risk | 20% (20 this run) | 60 | 85 | gpt-oss-20b +25 |\n| Agent interface | 10% (10 this run) | 65 | 90 | gpt-oss-20b +25 |\n| Documentation and upkeep | 10% (10 this run) | 39 | 42 | gpt-oss-20b +3 |\n| Negative events | ≤15 | 0 | 0 | |\n| **Total** | | **59.5 · C** | **69.9 · B** | |\n\n## Facts side by side\n\n| Fact | Cosmos-Reason2-2B | gpt-oss-20b |\n| --- | --- | --- |\n| Kind | Open-weight model | Open-weight model |\n| Vendor | NVIDIA | OpenAI |\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 | 2025-08-26 |\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) | 3.5/5 (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**gpt-oss-20b.** gpt-oss-20b is a cousin for reasoning, coding and single tool calls with structured output, under plain Apache 2.0. It needs about 17 GB with a working context, and five inference providers serve it. The main risks are that it trails o4-mini at keeping system instructions above user ones, and OpenAI hasn't answered a report since August 2025.\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### gpt-oss-20b\n\n1. Start it with `ollama run gpt-oss:20b` (the build that fits the reference machine), or `vllm serve openai/gpt-oss-20b` with a current vLLM release rather than the card's pinned vllm==0.10.1+gptoss wheel\n2. Use the harmony format through the chat template or openai-harmony; OpenAI says the model doesn't work correctly without it\n3. Parse tool calls and reasoning with openai-harmony; calls come on the commentary channel ending in `\u003c|call|\u003e`, reasoning on the analysis channel\n4. Set effort with `Reasoning: high` (or low, medium) in the system message, or `reasoning_effort` in the template; medium is the default\n5. Ask for JSON by putting a JSON Schema under `# Response Formats` in the developer message\n6. Drop earlier reasoning after a final answer but pass it back after tool calls, and don't show the analysis channel to users\n7. Expect one tool call per turn; run several in sequence rather than in parallel\n\n## Questions\n\n### Which is better for AI agents, Cosmos-Reason2-2B or gpt-oss-20b?\n\ngpt-oss-20b scores 69.9 (B) 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-gpt-oss-20b.json, and with the fewest tokens: https://www.anchorterminal.com/compare/cosmos-reason2-2b-vs-gpt-oss-20b.min.md\n- Over MCP at https://www.anchorterminal.com/mcp (no key): `compare_tools {\"a\": \"cosmos-reason2-2b\", \"b\": \"gpt-oss-20b\"}`. From a terminal: `anchor compare cosmos-reason2-2b gpt-oss-20b`\n- Each listing in full: https://www.anchorterminal.com/api/v1/tools/cosmos-reason2-2b.json and https://www.anchorterminal.com/api/v1/tools/gpt-oss-20b.json\n\n## Other comparisons with Cosmos-Reason2-2B or gpt-oss-20b\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 gpt-oss-20b](https://www.anchorterminal.com/compare/agents-a1-4b-vs-gpt-oss-20b.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 gpt-oss-20b](https://www.anchorterminal.com/compare/apertus-v1-5-8b-vs-gpt-oss-20b.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 gpt-oss-20b](https://www.anchorterminal.com/compare/apodex-1-1-mini-vs-gpt-oss-20b.md)\n- [BigBang-v1 vs 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