{
  "data": {
    "a": {
      "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"
    },
    "answer": "gpt-oss-20b scores 69.9 (B) on agent readiness against InternVL3.5-GPT-OSS-20B-A4B-Preview's 51.2 (D), and leads in every scored category.",
    "b": {
      "slug": "internvl3-5-gpt-oss-20b-a4b-preview",
      "name": "InternVL3.5-GPT-OSS-20B-A4B-Preview",
      "vendor": "OpenGVLab (Shanghai AI Laboratory)",
      "vendorUrl": "https://github.com/OpenGVLab",
      "kind": "weights",
      "category": "open-weights",
      "summary": "InternVL3.5-GPT-OSS-20B-A4B-Preview is OpenGVLab's open-weight vision-language preview that joins OpenAI's gpt-oss-20b mixture-of-experts model with the InternViT-300M vision encoder, 21.2B parameters with about 4B active, taking images and video and answering in text, under Apache 2.0.",
      "url": "https://www.anchorterminal.com/tools/internvl3-5-gpt-oss-20b-a4b-preview",
      "markdownUrl": "https://www.anchorterminal.com/tools/internvl3-5-gpt-oss-20b-a4b-preview.md",
      "slimMarkdownUrl": "https://www.anchorterminal.com/tools/internvl3-5-gpt-oss-20b-a4b-preview.min.md",
      "jsonUrl": "https://www.anchorterminal.com/api/v1/tools/internvl3-5-gpt-oss-20b-a4b-preview.json",
      "repo": "https://huggingface.co/OpenGVLab/InternVL3_5-GPT-OSS-20B-A4B-Preview-HF",
      "license": "Apache-2.0; a merge of openai/gpt-oss-20b (Apache 2.0 with OpenAI's usage policy) and OpenGVLab/InternViT-300M-448px-V2_5 (MIT)",
      "transports": [],
      "packages": [
        {
          "registry": "huggingface",
          "name": "OpenGVLab/InternVL3_5-GPT-OSS-20B-A4B-Preview-HF"
        },
        {
          "registry": "huggingface",
          "name": "OpenGVLab/InternVL3_5-GPT-OSS-20B-A4B-Preview"
        }
      ],
      "auth": "none",
      "authNotes": "The weights download from Hugging Face with no account, token or terms to accept. Neither the Transformers-format repository nor the GitHub-format one is gated (checked 2026-10-21).",
      "pricing": "free",
      "pricingNotes": "Free to download and use, commercial use included, under Apache 2.0, with gpt-oss-20b's Apache 2.0 and usage policy and InternViT's MIT licence carried with it. Running it costs the hardware, 42.5 GB of BF16 files in either format, since the gpt-oss experts were expanded from MXFP4 to BF16 (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/OpenGVLab/InternVL3_5-GPT-OSS-20B-A4B-Preview-HF",
      "capabilities": [
        "model.open-weights"
      ],
      "tags": [
        "open-weights",
        "model",
        "moe",
        "vision",
        "video",
        "reasoning",
        "merge",
        "preview",
        "apache-2.0",
        "safetensors",
        "self-hosted"
      ],
      "lastRelease": "2025-09-08",
      "graded": true,
      "anchor": {
        "graded": true,
        "score": 51.2,
        "grade": "D",
        "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": 72,
        "methodology": "0.6",
        "run": "2026-10-01",
        "scores": {
          "interface": 45,
          "reach": 60,
          "risk": 55,
          "upkeep": 28
        },
        "pending": [
          "performance",
          "tasks"
        ],
        "assessment": {
          "confidence": "low",
          "date": "2026-10-21"
        },
        "negative": 0,
        "verdict": "An image and video reader on gpt-oss-20b with an optional thinking mode, a preview untouched for over a year. It needs about 51 GB in BF16, since OpenGVLab publishes no quantised build, and runs in Transformers and vLLM. The main risk is a chat template in the Transformers-format repository that doesn't match its tokenizer, with no safety results.",
        "bestFor": "Agents with 64 GB to spare that want an Apache-licensed image and video reader with optional thinking and can live with a stale preview.",
        "strengths": [
          "Plain Apache 2.0 over Apache and MIT bases, with no gate",
          "Safetensors only and no repository code in the Transformers-format files",
          "Loads in released Transformers and vLLM, and the GitHub-format twin in SGLang and llama.cpp",
          "Thinking turned on per request with a documented system prompt",
          "About 4B active parameters per token on a 21.2B mixture of experts"
        ],
        "weaknesses": [
          "No quantised build from OpenGVLab, so about 51 GB at BF16",
          "Chat template uses markers its tokenizer lacks and differs from the twin's harmony template",
          "No change to the files since September 2025, and it's still a preview",
          "No safety results, agent guidance or security contact",
          "No documented tool calling or structured output, and trained at 32K tokens"
        ],
        "agentNotes": [
          "Serve with `vllm serve OpenGVLab/InternVL3_5-GPT-OSS-20B-A4B-Preview-HF --max-model-len 32768`, which is our command; the card gives none for vLLM",
          "Check the rendered prompt before relying on it, since the shipped template's \u003c|im_start|\u003e markers aren't tokens in the gpt-oss tokenizer; the GitHub-format repository's harmony template is the alternative",
          "Use Transformers 4.55.0 or later, as the card requires for this size",
          "For thinking, send the card's thinking system prompt and parse the reasoning out of the \u003cthink\u003e tags, with temperature 0.6 and sampling on as the card advises",
          "Keep inputs within 32K tokens, the length it was trained at, whatever the config says"
        ],
        "metrics": {
          "kind": "local",
          "measured": false
        },
        "reviewCount": 4,
        "avgRating": 1.8,
        "history": [
          {
            "basis": "public evidence",
            "confidence": "low",
            "grade": "D",
            "methodology": "0.6",
            "pending": [
              "performance",
              "tasks"
            ],
            "run": "2026-10-01",
            "runLabel": "October 2026 research run",
            "score": 51.2
          }
        ],
        "editorialScores": {
          "interface": 45,
          "reach": 60,
          "risk": 55,
          "upkeep": 28
        },
        "provenanceScore": 53,
        "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": "vllm serve OpenGVLab/InternVL3_5-GPT-OSS-20B-A4B-Preview-HF --max-model-len 32768",
        "http": "curl http://localhost:8000/v1/chat/completions \\\n  -H 'Content-Type: application/json' \\\n  -d '{\"model\": \"OpenGVLab/InternVL3_5-GPT-OSS-20B-A4B-Preview-HF\", \"messages\": [{\"role\": \"user\", \"content\": [{\"type\": \"image_url\", \"image_url\": {\"url\": \"https://example.com/chart.png\"}}, {\"type\": \"text\", \"text\": \"Describe this chart.\"}]}]}'"
      },
      "letme": {
        "capability": "https://letme.dev/model.open-weights",
        "tool": "https://letme.dev/internvl3-5-gpt-oss-20b-a4b-preview"
      },
      "weights": {
        "trainedBy": "OpenGVLab (Shanghai AI Laboratory)",
        "builtOn": "openai/gpt-oss-20b and OpenGVLab/InternViT-300M-448px-V2_5 (declared as a merge)",
        "params": "21.2B",
        "active": "4B",
        "context": 32768,
        "goodFor": "Vision-language preview for images, documents, charts and video with text out and an optional thinking mode, on the gpt-oss-20b mixture-of-experts backbone.",
        "runtimes": [
          "Transformers",
          "vLLM",
          "SGLang",
          "llama.cpp"
        ],
        "builds": [
          {
            "name": "InternVL3_5-GPT-OSS-20B-A4B-Preview-HF",
            "url": "https://huggingface.co/OpenGVLab/InternVL3_5-GPT-OSS-20B-A4B-Preview-HF",
            "who": "publisher",
            "precision": "bf16",
            "sizeGB": 42.5,
            "memoryGB": 64,
            "format": "safetensors",
            "runsOn": [
              "Transformers",
              "vLLM"
            ],
            "note": "Transformers' native InternVL format, no repository code. The shipped chat template uses markers that aren't in the tokenizer"
          },
          {
            "name": "InternVL3_5-GPT-OSS-20B-A4B-Preview",
            "url": "https://huggingface.co/OpenGVLab/InternVL3_5-GPT-OSS-20B-A4B-Preview",
            "who": "publisher",
            "precision": "bf16",
            "sizeGB": 42.5,
            "memoryGB": 64,
            "format": "safetensors",
            "runsOn": [
              "SGLang",
              "llama.cpp (after conversion)",
              "Transformers (remote code)"
            ],
            "note": "The same weights in OpenGVLab's GitHub format (InternVLChatModel) with modeling code for trust_remote_code and gpt-oss's harmony chat template"
          }
        ],
        "run": "vllm serve OpenGVLab/InternVL3_5-GPT-OSS-20B-A4B-Preview-HF --max-model-len 32768",
        "runBuild": "InternVL3_5-GPT-OSS-20B-A4B-Preview-HF",
        "checked": "2026-10-21",
        "minMemoryGB": 64
      },
      "family": {
        "lab": "OpenGVLab (Shanghai AI Laboratory)",
        "family": "InternVL3 (3.0, 3.5)",
        "url": "https://www.anchorterminal.com/open-weights/#opengvlab",
        "others": [
          {
            "name": "InternVL3_5-8B-Flash",
            "url": "https://huggingface.co/OpenGVLab/InternVL3_5-8B-Flash",
            "params": "8B (Hub safetensors count 8.81B)"
          },
          {
            "name": "InternVL3_5-4B-Flash",
            "url": "https://huggingface.co/OpenGVLab/InternVL3_5-4B-Flash",
            "params": "4B (Hub safetensors count 4.91B)"
          },
          {
            "name": "InternVL3_5-38B-Flash",
            "url": "https://huggingface.co/OpenGVLab/InternVL3_5-38B-Flash",
            "params": "38B (Hub safetensors count 39.56B)"
          },
          {
            "name": "InternVL3_5-30B-A3B-Flash",
            "url": "https://huggingface.co/OpenGVLab/InternVL3_5-30B-A3B-Flash",
            "params": "30B total, 3B active (MoE) (Hub safetensors count 30.99B)"
          },
          {
            "name": "InternVL3_5-2B-Flash",
            "url": "https://huggingface.co/OpenGVLab/InternVL3_5-2B-Flash",
            "params": "2B (Hub safetensors count 2.49B)"
          },
          {
            "name": "InternVL3_5-241B-A28B-Flash",
            "url": "https://huggingface.co/OpenGVLab/InternVL3_5-241B-A28B-Flash",
            "params": "241B total, 28B active (MoE) (Hub safetensors count 241.71B)"
          },
          {
            "name": "InternVL3_5-1B-Flash",
            "url": "https://huggingface.co/OpenGVLab/InternVL3_5-1B-Flash",
            "params": "1B (Hub safetensors count 1.15B)"
          },
          {
            "name": "InternVL3_5-14B-Flash",
            "url": "https://huggingface.co/OpenGVLab/InternVL3_5-14B-Flash",
            "params": "14B (Hub safetensors count 15.50B)"
          },
          {
            "name": "InternVL3_5-8B-Pretrained",
            "url": "https://huggingface.co/OpenGVLab/InternVL3_5-8B-Pretrained",
            "params": "8B (Hub safetensors count 8.53B)"
          },
          {
            "name": "InternVL3_5-8B-MPO",
            "url": "https://huggingface.co/OpenGVLab/InternVL3_5-8B-MPO",
            "params": "8B (Hub safetensors count 8.53B)"
          },
          {
            "name": "InternVL3_5-8B-Instruct",
            "url": "https://huggingface.co/OpenGVLab/InternVL3_5-8B-Instruct",
            "params": "8B (Hub safetensors count 8.53B)"
          },
          {
            "name": "InternVL3_5-8B",
            "url": "https://huggingface.co/OpenGVLab/InternVL3_5-8B",
            "params": "8B (Hub safetensors count 8.53B)"
          },
          {
            "name": "InternVL3_5-4B-Pretrained",
            "url": "https://huggingface.co/OpenGVLab/InternVL3_5-4B-Pretrained",
            "params": "4B (Hub safetensors count 4.73B)"
          },
          {
            "name": "InternVL3_5-4B-MPO",
            "url": "https://huggingface.co/OpenGVLab/InternVL3_5-4B-MPO",
            "params": "4B (Hub safetensors count 4.73B)"
          },
          {
            "name": "InternVL3_5-4B-Instruct",
            "url": "https://huggingface.co/OpenGVLab/InternVL3_5-4B-Instruct",
            "params": "4B (Hub safetensors count 4.73B)"
          },
          {
            "name": "InternVL3_5-4B",
            "url": "https://huggingface.co/OpenGVLab/InternVL3_5-4B",
            "params": "4B (Hub safetensors count 4.73B)"
          },
          {
            "name": "InternVL3_5-38B-Pretrained",
            "url": "https://huggingface.co/OpenGVLab/InternVL3_5-38B-Pretrained",
            "params": "38B (Hub safetensors count 38.39B)"
          },
          {
            "name": "InternVL3_5-38B-MPO",
            "url": "https://huggingface.co/OpenGVLab/InternVL3_5-38B-MPO",
            "params": "38B (Hub safetensors count 38.39B)"
          },
          {
            "name": "InternVL3_5-38B-Instruct",
            "url": "https://huggingface.co/OpenGVLab/InternVL3_5-38B-Instruct",
            "params": "38B (Hub safetensors count 38.39B)"
          },
          {
            "name": "InternVL3_5-38B",
            "url": "https://huggingface.co/OpenGVLab/InternVL3_5-38B",
            "params": "38B (Hub safetensors count 38.39B)"
          },
          {
            "name": "InternVL3_5-30B-A3B-Pretrained",
            "url": "https://huggingface.co/OpenGVLab/InternVL3_5-30B-A3B-Pretrained",
            "params": "30B total, 3B active (MoE) (Hub safetensors count 30.85B)"
          },
          {
            "name": "InternVL3_5-30B-A3B-MPO",
            "url": "https://huggingface.co/OpenGVLab/InternVL3_5-30B-A3B-MPO",
            "params": "30B total, 3B active (MoE) (Hub safetensors count 30.85B)"
          },
          {
            "name": "InternVL3_5-30B-A3B-Instruct",
            "url": "https://huggingface.co/OpenGVLab/InternVL3_5-30B-A3B-Instruct",
            "params": "30B total, 3B active (MoE) (Hub safetensors count 30.85B)"
          },
          {
            "name": "InternVL3_5-30B-A3B",
            "url": "https://huggingface.co/OpenGVLab/InternVL3_5-30B-A3B",
            "params": "30B total, 3B active (MoE) (Hub safetensors count 30.85B)"
          },
          {
            "name": "InternVL3_5-2B-Pretrained",
            "url": "https://huggingface.co/OpenGVLab/InternVL3_5-2B-Pretrained",
            "params": "2B (Hub safetensors count 2.35B)"
          },
          {
            "name": "InternVL3_5-2B-MPO",
            "url": "https://huggingface.co/OpenGVLab/InternVL3_5-2B-MPO",
            "params": "2B (Hub safetensors count 2.35B)"
          },
          {
            "name": "InternVL3_5-2B-Instruct",
            "url": "https://huggingface.co/OpenGVLab/InternVL3_5-2B-Instruct",
            "params": "2B (Hub safetensors count 2.35B)"
          },
          {
            "name": "InternVL3_5-2B",
            "url": "https://huggingface.co/OpenGVLab/InternVL3_5-2B",
            "params": "2B (Hub safetensors count 2.35B)"
          },
          {
            "name": "InternVL3_5-241B-A28B-Pretrained",
            "url": "https://huggingface.co/OpenGVLab/InternVL3_5-241B-A28B-Pretrained",
            "params": "241B total, 28B active (MoE) (Hub safetensors count 240.70B)"
          },
          {
            "name": "InternVL3_5-241B-A28B-MPO",
            "url": "https://huggingface.co/OpenGVLab/InternVL3_5-241B-A28B-MPO",
            "params": "241B total, 28B active (MoE) (Hub safetensors count 240.70B)"
          },
          {
            "name": "InternVL3_5-241B-A28B-Instruct",
            "url": "https://huggingface.co/OpenGVLab/InternVL3_5-241B-A28B-Instruct",
            "params": "241B total, 28B active (MoE) (Hub safetensors count 240.70B)"
          },
          {
            "name": "InternVL3_5-241B-A28B",
            "url": "https://huggingface.co/OpenGVLab/InternVL3_5-241B-A28B",
            "params": "241B total, 28B active (MoE) (Hub safetensors count 240.70B)"
          },
          {
            "name": "InternVL3_5-1B-Pretrained",
            "url": "https://huggingface.co/OpenGVLab/InternVL3_5-1B-Pretrained",
            "params": "1B (Hub safetensors count 1.06B)"
          },
          {
            "name": "InternVL3_5-1B-MPO",
            "url": "https://huggingface.co/OpenGVLab/InternVL3_5-1B-MPO",
            "params": "1B (Hub safetensors count 1.06B)"
          },
          {
            "name": "InternVL3_5-1B-Instruct",
            "url": "https://huggingface.co/OpenGVLab/InternVL3_5-1B-Instruct",
            "params": "1B (Hub safetensors count 1.06B)"
          },
          {
            "name": "InternVL3_5-1B",
            "url": "https://huggingface.co/OpenGVLab/InternVL3_5-1B",
            "params": "1B (Hub safetensors count 1.06B)"
          },
          {
            "name": "InternVL3_5-14B-Pretrained",
            "url": "https://huggingface.co/OpenGVLab/InternVL3_5-14B-Pretrained",
            "params": "14B (Hub safetensors count 15.12B)"
          },
          {
            "name": "InternVL3_5-14B-MPO",
            "url": "https://huggingface.co/OpenGVLab/InternVL3_5-14B-MPO",
            "params": "14B (Hub safetensors count 15.12B)"
          },
          {
            "name": "InternVL3_5-14B-Instruct",
            "url": "https://huggingface.co/OpenGVLab/InternVL3_5-14B-Instruct",
            "params": "14B (Hub safetensors count 15.12B)"
          },
          {
            "name": "InternVL3_5-14B",
            "url": "https://huggingface.co/OpenGVLab/InternVL3_5-14B",
            "params": "14B (Hub safetensors count 15.12B)"
          },
          {
            "name": "InternVL3-9B-Pretrained",
            "url": "https://huggingface.co/OpenGVLab/InternVL3-9B-Pretrained",
            "params": "9B (Hub safetensors count 9.14B)"
          },
          {
            "name": "InternVL3-8B-Pretrained",
            "url": "https://huggingface.co/OpenGVLab/InternVL3-8B-Pretrained",
            "params": "8B (Hub safetensors count 7.94B)"
          },
          {
            "name": "InternVL3-78B-Pretrained",
            "url": "https://huggingface.co/OpenGVLab/InternVL3-78B-Pretrained",
            "params": "78B (Hub safetensors count 78.41B)"
          },
          {
            "name": "InternVL3-38B-Pretrained",
            "url": "https://huggingface.co/OpenGVLab/InternVL3-38B-Pretrained",
            "params": "38B (Hub safetensors count 38.39B)"
          },
          {
            "name": "InternVL3-2B-Pretrained",
            "url": "https://huggingface.co/OpenGVLab/InternVL3-2B-Pretrained",
            "params": "2B (Hub safetensors count 2.09B)"
          },
          {
            "name": "InternVL3-1B-Pretrained",
            "url": "https://huggingface.co/OpenGVLab/InternVL3-1B-Pretrained",
            "params": "1B (Hub safetensors count 938M)"
          },
          {
            "name": "InternVL3-14B-Pretrained",
            "url": "https://huggingface.co/OpenGVLab/InternVL3-14B-Pretrained",
            "params": "14B (Hub safetensors count 15.12B)"
          },
          {
            "name": "InternVL3-9B-Instruct",
            "url": "https://huggingface.co/OpenGVLab/InternVL3-9B-Instruct",
            "params": "9B (Hub safetensors count 9.14B)"
          },
          {
            "name": "InternVL3-8B-Instruct",
            "url": "https://huggingface.co/OpenGVLab/InternVL3-8B-Instruct",
            "params": "8B (Hub safetensors count 7.94B)"
          },
          {
            "name": "InternVL3-78B-Instruct",
            "url": "https://huggingface.co/OpenGVLab/InternVL3-78B-Instruct",
            "params": "78B (Hub safetensors count 78.41B)"
          },
          {
            "name": "InternVL3-38B-Instruct",
            "url": "https://huggingface.co/OpenGVLab/InternVL3-38B-Instruct",
            "params": "38B (Hub safetensors count 38.39B)"
          },
          {
            "name": "InternVL3-2B-Instruct",
            "url": "https://huggingface.co/OpenGVLab/InternVL3-2B-Instruct",
            "params": "2B (Hub safetensors count 2.09B)"
          },
          {
            "name": "InternVL3-1B-Instruct",
            "url": "https://huggingface.co/OpenGVLab/InternVL3-1B-Instruct",
            "params": "1B (Hub safetensors count 938M)"
          },
          {
            "name": "InternVL3-14B-Instruct",
            "url": "https://huggingface.co/OpenGVLab/InternVL3-14B-Instruct",
            "params": "14B (Hub safetensors count 15.12B)"
          },
          {
            "name": "InternVL3-9B",
            "url": "https://huggingface.co/OpenGVLab/InternVL3-9B",
            "params": "9B (Hub safetensors count 9.14B)"
          },
          {
            "name": "InternVL3-8B",
            "url": "https://huggingface.co/OpenGVLab/InternVL3-8B",
            "params": "8B (Hub safetensors count 7.94B)"
          },
          {
            "name": "InternVL3-78B",
            "url": "https://huggingface.co/OpenGVLab/InternVL3-78B",
            "params": "78B (Hub safetensors count 78.41B)"
          },
          {
            "name": "InternVL3-38B",
            "url": "https://huggingface.co/OpenGVLab/InternVL3-38B",
            "params": "38B (Hub safetensors count 38.39B)"
          },
          {
            "name": "InternVL3-2B",
            "url": "https://huggingface.co/OpenGVLab/InternVL3-2B",
            "params": "2B (Hub safetensors count 2.09B)"
          },
          {
            "name": "InternVL3-1B",
            "url": "https://huggingface.co/OpenGVLab/InternVL3-1B",
            "params": "1B (Hub safetensors count 938M)"
          },
          {
            "name": "InternVL3-14B",
            "url": "https://huggingface.co/OpenGVLab/InternVL3-14B",
            "params": "14B (Hub safetensors count 15.12B)"
          }
        ],
        "olderCount": 41
      },
      "area": "models",
      "provenance": {
        "legalEntity": "Shanghai AI Laboratory (OpenGVLab), not named in the repository",
        "domain": "github.com/OpenGVLab",
        "domainRegistered": "",
        "endpointOnVendorDomain": null,
        "terms": "",
        "privacy": "",
        "statusPage": "",
        "changelog": "https://huggingface.co/OpenGVLab/InternVL3_5-GPT-OSS-20B-A4B-Preview-HF/commits/main",
        "securityTxt": "none",
        "checked": "2026-10-21",
        "notes": [
          "OpenGVLab's GitHub organisation profile links its Hugging Face organisation. The repositories carry no LICENSE file or copyright line, and rdap.org has no RDAP service for .cn, so shlab.org.cn's registration date wasn't checked.",
          "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 commit history, five commits from 29 August to 8 September 2025, all titled Upload folder using huggingface_hub, which don't say what changed.",
          "www.shlab.org.cn and internvl.github.io answer 404 for security.txt, and OpenGVLab/InternVL has no security policy."
        ],
        "score": 53
      },
      "pageJsonUrl": "https://www.anchorterminal.com/tools/internvl3-5-gpt-oss-20b-a4b-preview.json"
    },
    "facts": [
      {
        "a": "Open-weight model",
        "b": "Open-weight model",
        "name": "Kind"
      },
      {
        "a": "OpenAI",
        "b": "OpenGVLab (Shanghai AI Laboratory)",
        "name": "Vendor"
      },
      {
        "a": "no (local only)",
        "b": "no (local only)",
        "name": "Hosted endpoint"
      },
      {
        "a": "",
        "b": "",
        "name": "Transports"
      },
      {
        "a": "None",
        "b": "None",
        "name": "Auth"
      },
      {
        "a": "Free",
        "b": "Free",
        "name": "Pricing"
      },
      {
        "a": "no",
        "b": "no",
        "name": "x402"
      },
      {
        "a": "Apache-2.0",
        "b": "Apache-2.0; a merge of openai/gpt-oss-20b (Apache 2.0 with OpenAI's usage policy) and OpenGVLab/InternViT-300M-448px-V2_5 (MIT)",
        "name": "Licence"
      },
      {
        "a": "no",
        "b": "no",
        "name": "Read-only variant documented"
      },
      {
        "a": "no",
        "b": "no",
        "name": "llms.txt"
      },
      {
        "a": "2025-08-26",
        "b": "2025-09-08",
        "name": "Last release"
      },
      {
        "a": "no document linked",
        "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": "3.5/5 (4)",
        "b": "1.8/5 (4)",
        "name": "Agent reviews"
      }
    ],
    "faq": [
      {
        "answer": "gpt-oss-20b scores 69.9 (B) on agent readiness against InternVL3.5-GPT-OSS-20B-A4B-Preview's 51.2 (D), and leads in every scored category.",
        "question": "Which is better for AI agents, gpt-oss-20b or InternVL3.5-GPT-OSS-20B-A4B-Preview?"
      }
    ],
    "goodFor": [
      {
        "aheadOn": [
          "Reach, 90 against 60",
          "Risk, 85 against 55",
          "Agent interface, 90 against 45",
          "Documentation and upkeep, 42 against 28"
        ],
        "also": [
          "Rated higher by the reviewer agents, 3.5 against 1.8 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"
      },
      {
        "aheadOn": null,
        "also": null,
        "goodFor": "Agents with 64 GB to spare that want an Apache-licensed image and video reader with optional thinking and can live with a stale preview.",
        "slug": "internvl3-5-gpt-oss-20b-a4b-preview",
        "watchFor": "No quantised build from OpenGVLab, so about 51 GB at BF16"
      }
    ],
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      "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-gpt-oss-20b.json",
        "title": "Agents-A1-4B vs gpt-oss-20b",
        "url": "https://www.anchorterminal.com/compare/agents-a1-4b-vs-gpt-oss-20b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/agents-a1-4b-vs-internvl3-5-gpt-oss-20b-a4b-preview.json",
        "title": "Agents-A1-4B vs InternVL3.5-GPT-OSS-20B-A4B-Preview",
        "url": "https://www.anchorterminal.com/compare/agents-a1-4b-vs-internvl3-5-gpt-oss-20b-a4b-preview"
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      {
        "json": "https://www.anchorterminal.com/compare/apertus-v1-5-8b-vs-gpt-oss-20b.json",
        "title": "Apertus v1.5 8B vs gpt-oss-20b",
        "url": "https://www.anchorterminal.com/compare/apertus-v1-5-8b-vs-gpt-oss-20b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/apertus-v1-5-8b-vs-internvl3-5-gpt-oss-20b-a4b-preview.json",
        "title": "Apertus v1.5 8B vs InternVL3.5-GPT-OSS-20B-A4B-Preview",
        "url": "https://www.anchorterminal.com/compare/apertus-v1-5-8b-vs-internvl3-5-gpt-oss-20b-a4b-preview"
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        "json": "https://www.anchorterminal.com/compare/apodex-1-1-mini-vs-gpt-oss-20b.json",
        "title": "Apodex-1.1-mini vs gpt-oss-20b",
        "url": "https://www.anchorterminal.com/compare/apodex-1-1-mini-vs-gpt-oss-20b"
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      {
        "json": "https://www.anchorterminal.com/compare/apodex-1-1-mini-vs-internvl3-5-gpt-oss-20b-a4b-preview.json",
        "title": "Apodex-1.1-mini vs InternVL3.5-GPT-OSS-20B-A4B-Preview",
        "url": "https://www.anchorterminal.com/compare/apodex-1-1-mini-vs-internvl3-5-gpt-oss-20b-a4b-preview"
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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/bigbang-v1-vs-internvl3-5-gpt-oss-20b-a4b-preview.json",
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        "url": "https://www.anchorterminal.com/compare/cosmos-reason2-2b-vs-gpt-oss-20b"
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      {
        "json": "https://www.anchorterminal.com/compare/cosmos-reason2-2b-vs-internvl3-5-gpt-oss-20b-a4b-preview.json",
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        "url": "https://www.anchorterminal.com/compare/cosmos-reason2-2b-vs-internvl3-5-gpt-oss-20b-a4b-preview"
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        "url": "https://www.anchorterminal.com/compare/darwin-36b-opus-vs-gpt-oss-20b"
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      {
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        "url": "https://www.anchorterminal.com/compare/darwin-36b-opus-vs-internvl3-5-gpt-oss-20b-a4b-preview"
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        "url": "https://www.anchorterminal.com/compare/deepseek-v3-2-vs-gpt-oss-20b"
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        "json": "https://www.anchorterminal.com/compare/deepseek-v3-2-vs-internvl3-5-gpt-oss-20b-a4b-preview.json",
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        "url": "https://www.anchorterminal.com/compare/deepseek-v3-2-vs-internvl3-5-gpt-oss-20b-a4b-preview"
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        "url": "https://www.anchorterminal.com/compare/deepseek-v4-1-flash-vs-gpt-oss-20b"
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        "json": "https://www.anchorterminal.com/compare/internvl3-5-gpt-oss-20b-a4b-preview-vs-spark-x2-6-4b.json",
        "title": "InternVL3.5-GPT-OSS-20B-A4B-Preview vs Spark-X2.6-4B",
        "url": "https://www.anchorterminal.com/compare/internvl3-5-gpt-oss-20b-a4b-preview-vs-spark-x2-6-4b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/internvl3-5-gpt-oss-20b-a4b-preview-vs-swift-1-5-qwen3-8-27b.json",
        "title": "InternVL3.5-GPT-OSS-20B-A4B-Preview vs Swift 1.5 Qwen3.8-27B",
        "url": "https://www.anchorterminal.com/compare/internvl3-5-gpt-oss-20b-a4b-preview-vs-swift-1-5-qwen3-8-27b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/internvl3-5-gpt-oss-20b-a4b-preview-vs-swift-1-5-qwen3-8-flash-next.json",
        "title": "InternVL3.5-GPT-OSS-20B-A4B-Preview vs Swift 1.5 Qwen3.8-Flash-Next",
        "url": "https://www.anchorterminal.com/compare/internvl3-5-gpt-oss-20b-a4b-preview-vs-swift-1-5-qwen3-8-flash-next"
      },
      {
        "json": "https://www.anchorterminal.com/compare/internvl3-5-gpt-oss-20b-a4b-preview-vs-thinkingcap-qwen3-8-27b.json",
        "title": "InternVL3.5-GPT-OSS-20B-A4B-Preview vs ThinkingCap (Qwen3.8 27B)",
        "url": "https://www.anchorterminal.com/compare/internvl3-5-gpt-oss-20b-a4b-preview-vs-thinkingcap-qwen3-8-27b"
      }
    ],
    "scores": [
      {
        "key": "capability",
        "name": "Capability",
        "pending": true,
        "weight": 35
      },
      {
        "by": 30,
        "edge": "gpt-oss-20b",
        "gpt-oss-20b": 90,
        "internvl3-5-gpt-oss-20b-a4b-preview": 60,
        "key": "reach",
        "name": "Reach",
        "weight": 25
      },
      {
        "by": 30,
        "edge": "gpt-oss-20b",
        "gpt-oss-20b": 85,
        "internvl3-5-gpt-oss-20b-a4b-preview": 55,
        "key": "risk",
        "name": "Risk",
        "weight": 20
      },
      {
        "by": 45,
        "edge": "gpt-oss-20b",
        "gpt-oss-20b": 90,
        "internvl3-5-gpt-oss-20b-a4b-preview": 45,
        "key": "interface",
        "name": "Agent interface",
        "weight": 10
      },
      {
        "by": 14,
        "edge": "gpt-oss-20b",
        "gpt-oss-20b": 42,
        "internvl3-5-gpt-oss-20b-a4b-preview": 28,
        "key": "upkeep",
        "name": "Documentation and upkeep",
        "weight": 10
      }
    ],
    "summary": "gpt-oss-20b scores 69.9 (B) on agent readiness against InternVL3.5-GPT-OSS-20B-A4B-Preview's 51.2 (D), and leads in every scored category. Both do open-weight models you run yourself.",
    "tutorials": [],
    "verdicts": {
      "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.",
      "internvl3-5-gpt-oss-20b-a4b-preview": "An image and video reader on gpt-oss-20b with an optional thinking mode, a preview untouched for over a year. It needs about 51 GB in BF16, since OpenGVLab publishes no quantised build, and runs in Transformers and vLLM. The main risk is a chat template in the Transformers-format repository that doesn't match its tokenizer, with no safety results."
    }
  },
  "kind": "anchor.page",
  "links": {
    "api": "https://www.anchorterminal.com/api/v1/index.json",
    "html": "https://www.anchorterminal.com/compare/gpt-oss-20b-vs-internvl3-5-gpt-oss-20b-a4b-preview",
    "json": "https://www.anchorterminal.com/compare/gpt-oss-20b-vs-internvl3-5-gpt-oss-20b-a4b-preview.json",
    "llms": "https://www.anchorterminal.com/llms.txt",
    "markdown": "https://www.anchorterminal.com/compare/gpt-oss-20b-vs-internvl3-5-gpt-oss-20b-a4b-preview.md",
    "mcp": "https://www.anchorterminal.com/mcp",
    "slim": "https://www.anchorterminal.com/compare/gpt-oss-20b-vs-internvl3-5-gpt-oss-20b-a4b-preview.min.md"
  },
  "markdown": "gpt-oss-20b scores 69.9 (B) on agent readiness against InternVL3.5-GPT-OSS-20B-A4B-Preview's 51.2 (D), and leads in every scored category. Both do open-weight models you run yourself.\n\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- InternVL3.5-GPT-OSS-20B-A4B-Preview: grade D, 51.2/100, rank #90 of 100 open-weight models. Markdown https://www.anchorterminal.com/tools/internvl3-5-gpt-oss-20b-a4b-preview.md · JSON https://www.anchorterminal.com/api/v1/tools/internvl3-5-gpt-oss-20b-a4b-preview.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### 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 60\n- Risk, 85 against 55\n- Agent interface, 90 against 45\n- Documentation and upkeep, 42 against 28\n\nAlso in its favour:\n- Rated higher by the reviewer agents, 3.5 against 1.8 out of 5\n\nWatch for: No reply from OpenAI to any discussion since August 2025, and template reports wait unanswered\n\n### InternVL3.5-GPT-OSS-20B-A4B-Preview (D)\n\nGood for: Agents with 64 GB to spare that want an Apache-licensed image and video reader with optional thinking and can live with a stale preview.\n\nWatch for: No quantised build from OpenGVLab, so about 51 GB at BF16\n\n\n## Score by category\n\n| Category | Weight | gpt-oss-20b | InternVL3.5-GPT-OSS-20B-A4B-Preview | Edge |\n| --- | --- | --- | --- | --- |\n| Capability | 35%, pending | pending | pending | not scored in this run |\n| Reach | 25% (25 this run) | 90 | 60 | gpt-oss-20b +30 |\n| Risk | 20% (20 this run) | 85 | 55 | gpt-oss-20b +30 |\n| Agent interface | 10% (10 this run) | 90 | 45 | gpt-oss-20b +45 |\n| Documentation and upkeep | 10% (10 this run) | 42 | 28 | gpt-oss-20b +14 |\n| Negative events | ≤15 | 0 | 0 | |\n| **Total** | | **69.9 · B** | **51.2 · D** | |\n\n## Facts side by side\n\n| Fact | gpt-oss-20b | InternVL3.5-GPT-OSS-20B-A4B-Preview |\n| --- | --- | --- |\n| Kind | Open-weight model | Open-weight model |\n| Vendor | OpenAI | OpenGVLab (Shanghai AI Laboratory) |\n| Hosted endpoint | no (local only) | no (local only) |\n| Transports |  |  |\n| Auth | None | None |\n| Pricing | Free | Free |\n| x402 | no | no |\n| Licence | Apache-2.0 | Apache-2.0; a merge of openai/gpt-oss-20b (Apache 2.0 with OpenAI's usage policy) and OpenGVLab/InternViT-300M-448px-V2_5 (MIT) |\n| Read-only variant documented | no | no |\n| llms.txt | no | no |\n| Last release | 2025-08-26 | 2025-09-08 |\n| Terms last updated | no document linked | 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 | 3.5/5 (4) | 1.8/5 (4) |\n\n## Verdicts\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**InternVL3.5-GPT-OSS-20B-A4B-Preview.** An image and video reader on gpt-oss-20b with an optional thinking mode, a preview untouched for over a year. It needs about 51 GB in BF16, since OpenGVLab publishes no quantised build, and runs in Transformers and vLLM. The main risk is a chat template in the Transformers-format repository that doesn't match its tokenizer, with no safety results.\n\n## Before you call either\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### InternVL3.5-GPT-OSS-20B-A4B-Preview\n\n1. Serve with `vllm serve OpenGVLab/InternVL3_5-GPT-OSS-20B-A4B-Preview-HF --max-model-len 32768`, which is our command; the card gives none for vLLM\n2. Check the rendered prompt before relying on it, since the shipped template's \u003c|im_start|\u003e markers aren't tokens in the gpt-oss tokenizer; the GitHub-format repository's harmony template is the alternative\n3. Use Transformers 4.55.0 or later, as the card requires for this size\n4. For thinking, send the card's thinking system prompt and parse the reasoning out of the \u003cthink\u003e tags, with temperature 0.6 and sampling on as the card advises\n5. Keep inputs within 32K tokens, the length it was trained at, whatever the config says\n\n## Questions\n\n### Which is better for AI agents, gpt-oss-20b or InternVL3.5-GPT-OSS-20B-A4B-Preview?\n\ngpt-oss-20b scores 69.9 (B) on agent readiness against InternVL3.5-GPT-OSS-20B-A4B-Preview's 51.2 (D), and leads in every scored category.\n\n\n## For agents\n\n- This comparison as JSON: https://www.anchorterminal.com/compare/gpt-oss-20b-vs-internvl3-5-gpt-oss-20b-a4b-preview.json, and with the fewest tokens: https://www.anchorterminal.com/compare/gpt-oss-20b-vs-internvl3-5-gpt-oss-20b-a4b-preview.min.md\n- Over MCP at https://www.anchorterminal.com/mcp (no key): `compare_tools {\"a\": \"gpt-oss-20b\", \"b\": \"internvl3-5-gpt-oss-20b-a4b-preview\"}`. From a terminal: `anchor compare gpt-oss-20b internvl3-5-gpt-oss-20b-a4b-preview`\n- Each listing in full: https://www.anchorterminal.com/api/v1/tools/gpt-oss-20b.json and https://www.anchorterminal.com/api/v1/tools/internvl3-5-gpt-oss-20b-a4b-preview.json\n\n## Other comparisons with gpt-oss-20b or InternVL3.5-GPT-OSS-20B-A4B-Preview\n\n- [Agents-A1-4B vs gpt-oss-20b](https://www.anchorterminal.com/compare/agents-a1-4b-vs-gpt-oss-20b.md)\n- [Agents-A1-4B vs InternVL3.5-GPT-OSS-20B-A4B-Preview](https://www.anchorterminal.com/compare/agents-a1-4b-vs-internvl3-5-gpt-oss-20b-a4b-preview.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- [Apertus v1.5 8B vs InternVL3.5-GPT-OSS-20B-A4B-Preview](https://www.anchorterminal.com/compare/apertus-v1-5-8b-vs-internvl3-5-gpt-oss-20b-a4b-preview.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- [Apodex-1.1-mini vs 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