{
  "data": {
    "a": {
      "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",
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        "olderCount": 41
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      "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"
    },
    "answer": "Qwen3-VL-8B-Instruct scores 54.9 (C) on agent readiness against InternVL3.5-GPT-OSS-20B-A4B-Preview's 51.2 (D), and leads in 3 of 4 scored categories.",
    "b": {
      "slug": "qwen3-vl-8b-instruct",
      "name": "Qwen3-VL-8B-Instruct",
      "vendor": "Alibaba (Qwen team)",
      "vendorUrl": "https://qwen.ai",
      "kind": "weights",
      "category": "open-weights",
      "summary": "Qwen3-VL-8B-Instruct is Alibaba's open-weight dense vision-language model of about 8B parameters, taking text, images and video with a 262,144-token context, published on Hugging Face in BF16, FP8 and GGUF under Apache 2.0.",
      "url": "https://www.anchorterminal.com/tools/qwen3-vl-8b-instruct",
      "markdownUrl": "https://www.anchorterminal.com/tools/qwen3-vl-8b-instruct.md",
      "slimMarkdownUrl": "https://www.anchorterminal.com/tools/qwen3-vl-8b-instruct.min.md",
      "jsonUrl": "https://www.anchorterminal.com/api/v1/tools/qwen3-vl-8b-instruct.json",
      "repo": "https://huggingface.co/Qwen/Qwen3-VL-8B-Instruct",
      "license": "Apache-2.0",
      "transports": [],
      "packages": [
        {
          "registry": "huggingface",
          "name": "Qwen/Qwen3-VL-8B-Instruct"
        },
        {
          "registry": "huggingface",
          "name": "Qwen/Qwen3-VL-8B-Instruct-FP8"
        },
        {
          "registry": "huggingface",
          "name": "Qwen/Qwen3-VL-8B-Instruct-GGUF"
        },
        {
          "registry": "ollama",
          "name": "qwen3-vl:8b-instruct"
        }
      ],
      "auth": "none",
      "authNotes": "The weights download from Hugging Face with no account, token or terms to accept. None of the three repositories is gated (checked 2026-10-21).",
      "pricing": "free",
      "pricingNotes": "Free to download and use, commercial use included, under Apache 2.0. Running it yourself costs the hardware, 17.5 GB for the BF16 files, 10.6 GB for Alibaba's FP8 build and 5.0 GB plus a 0.75 to 1.16 GB vision file for its Q4_K_M GGUF (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/Qwen/Qwen3-VL-8B-Instruct",
      "capabilities": [
        "model.open-weights"
      ],
      "tags": [
        "open-weights",
        "model",
        "dense",
        "multimodal",
        "vision",
        "video",
        "tool-calling",
        "apache-2.0",
        "safetensors",
        "fp8",
        "gguf",
        "self-hosted"
      ],
      "lastRelease": "2025-11-01",
      "graded": true,
      "anchor": {
        "graded": true,
        "score": 54.9,
        "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": 66,
        "methodology": "0.6",
        "run": "2026-10-01",
        "scores": {
          "capability": 28,
          "interface": 60,
          "reach": 100,
          "risk": 55,
          "upkeep": 31
        },
        "pending": [
          "performance",
          "tasks"
        ],
        "assessment": {
          "confidence": "high",
          "date": "2026-10-21"
        },
        "negative": 0,
        "verdict": "A small vision-language cousin for reading screenshots, documents, charts and video, in about 6 GB from Alibaba's Q4_K_M GGUF and every major runtime, under plain Apache 2.0. It has no thinking mode and documents tool calls only in the template. The main risk is no published safety work, so add your own guardrails before it drives a GUI.",
        "bestFor": "An agent with 8 GB or more to spare that needs a local model to read images, documents and video",
        "strengths": [
          "About 6 GB of memory for Alibaba's own Q4_K_M GGUF, with FP8 and Q8_0 builds as well",
          "Runs in Transformers, vLLM, SGLang, llama.cpp and Ollama in released versions",
          "Apache 2.0 with no use policy, downloadable with no account",
          "262,144 tokens of native context over text, images and video",
          "Safetensors and GGUF only, with a chat template in the repository",
          "Also served by Featherless and Parasail for agents without the hardware"
        ],
        "weaknesses": [
          "No safety evaluation, agent-use guidance or security contact",
          "Tool calling isn't documented beyond the template, and Alibaba names no parser",
          "No thinking mode in this edition and no documented JSON output",
          "No reply from Qwen to any of the 19 Hugging Face discussions that aren't pull requests",
          "The card leaves out limitations, languages, knowledge cut-off and memory needs"
        ],
        "agentNotes": [
          "Start it with `llama-server -hf Qwen/Qwen3-VL-8B-Instruct-GGUF:Q4_K_M --jinja -c 32768`, or `ollama run qwen3-vl:8b-instruct`",
          "In Ollama the plain `qwen3-vl:8b` tag is the Thinking edition, so name `8b-instruct`",
          "With the GGUF, load the mmproj vision file too, or images won't be read",
          "Parse tool calls as JSON inside `\u003ctool_call\u003e` tags, or use SGLang's `--tool-call-parser qwen`",
          "Use the card's sampling, `temperature=0.7, top_p=0.8, top_k=20, presence_penalty=1.5` for vision and `temperature=1.0, top_p=1.0, top_k=40, presence_penalty=2.0` for text",
          "Validate JSON output yourself, since structured output isn't documented",
          "vLLM needs 0.11.0 or later and Transformers 4.57.0 or later"
        ],
        "metrics": {
          "kind": "local",
          "measured": false
        },
        "reviewCount": 4,
        "avgRating": 2.8,
        "history": [
          {
            "basis": "public evidence",
            "confidence": "high",
            "grade": "C",
            "methodology": "0.6",
            "pending": [
              "performance",
              "tasks"
            ],
            "run": "2026-10-01",
            "runLabel": "October 2026 research run",
            "score": 54.9
          }
        ],
        "editorialScores": {
          "capability": 28,
          "interface": 60,
          "reach": 100,
          "risk": 55,
          "upkeep": 31
        },
        "provenanceScore": 49,
        "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 qwen3-vl:8b-instruct\n# or with vLLM 0.11.0 or later, per Qwen's README:\nvllm serve Qwen/Qwen3-VL-8B-Instruct-FP8\n# or with SGLang, using the tool parser its cookbook names for Qwen3-VL:\npython -m sglang.launch_server --model-path Qwen/Qwen3-VL-8B-Instruct --tool-call-parser qwen",
        "http": "curl http://localhost:11434/api/chat \\\n  -d '{\"model\": \"qwen3-vl:8b-instruct\", \"messages\": [{\"role\": \"user\", \"content\": \"Hello!\"}]}'"
      },
      "letme": {
        "capability": "https://letme.dev/model.open-weights",
        "tool": "https://letme.dev/qwen3-vl-8b-instruct"
      },
      "sameCompany": [
        "qwen3-embedding-0-6b",
        "qwen3-embedding-4b",
        "qwen3-embedding-8b",
        "qwen3-vl-embedding-2b",
        "qwen3-vl-embedding-8b",
        "qwen3-asr-0-6b",
        "qwen3-asr-1-7b",
        "qwen3-tts-1-7b-customvoice",
        "qwen3-30b-a3b-instruct-2507",
        "qwen3-4b-instruct-2507",
        "qwen3-coder-30b-a3b-instruct",
        "qwen3-coder-next",
        "qwen3-omni-30b-a3b-instruct",
        "qwen3-vl-2b-instruct",
        "qwen3-vl-30b-a3b-instruct",
        "qwen3-vl-32b-instruct",
        "qwen3-vl-4b-instruct",
        "qwen3-5-0-8b",
        "qwen3-5-122b-a10b",
        "qwen3-5-2b",
        "qwen3-5-397b-a17b",
        "qwen3-5-4b",
        "qwen3-5-9b",
        "qwen3-6-27b",
        "qwen3-6-35b-a3b",
        "qwen3-8-27b",
        "qwen3-8-flash-next"
      ],
      "weights": {
        "trainedBy": "Alibaba (Qwen team)",
        "params": "8.77B",
        "context": 262144,
        "goodFor": "Vision-language model for images, documents and video with text out, no thinking mode in this Instruct edition.",
        "runtimes": [
          "llama.cpp",
          "Ollama",
          "vLLM",
          "SGLang",
          "Transformers"
        ],
        "builds": [
          {
            "name": "Qwen3VL-8B-Instruct-Q4_K_M",
            "url": "https://huggingface.co/Qwen/Qwen3-VL-8B-Instruct-GGUF/blob/main/Qwen3VL-8B-Instruct-Q4_K_M.gguf",
            "who": "publisher",
            "precision": "q4_k_m",
            "sizeGB": 5,
            "memoryGB": 8,
            "format": "gguf",
            "runsOn": [
              "llama.cpp (Vulkan)",
              "llama.cpp (ROCm)"
            ],
            "note": "Add mmproj-Qwen3VL-8B-Instruct-Q8_0.gguf (0.8 GB) for image input"
          },
          {
            "name": "ollama qwen3-vl:8b-instruct",
            "url": "https://ollama.com/library/qwen3-vl:8b-instruct",
            "who": "ollama",
            "precision": "q4_k_m",
            "sizeGB": 6.2,
            "memoryGB": 8,
            "format": "ollama",
            "runsOn": [
              "Ollama"
            ],
            "note": "Q4_K_M with its vision projector. qwen3-vl:8b, the library default, is the Thinking edition. Size as Ollama's tags page shows it, rounded to whole GB above 10 GB; the Linux build is the llama.cpp variant"
          },
          {
            "name": "Qwen3VL-8B-Instruct-Q8_0",
            "url": "https://huggingface.co/Qwen/Qwen3-VL-8B-Instruct-GGUF/blob/main/Qwen3VL-8B-Instruct-Q8_0.gguf",
            "who": "publisher",
            "precision": "q8_0",
            "sizeGB": 8.7,
            "memoryGB": 12,
            "format": "gguf",
            "runsOn": [
              "llama.cpp (Vulkan)",
              "llama.cpp (ROCm)"
            ],
            "note": "Add an mmproj file for image input"
          },
          {
            "name": "Qwen3-VL-8B-Instruct-FP8",
            "url": "https://huggingface.co/Qwen/Qwen3-VL-8B-Instruct-FP8",
            "who": "publisher",
            "precision": "fp8",
            "sizeGB": 10.6,
            "memoryGB": 16,
            "format": "safetensors"
          },
          {
            "name": "Qwen3-VL-8B-Instruct",
            "url": "https://huggingface.co/Qwen/Qwen3-VL-8B-Instruct",
            "who": "publisher",
            "precision": "bf16",
            "sizeGB": 17.5,
            "memoryGB": 24,
            "format": "safetensors",
            "runsOn": [
              "vLLM (ROCm)",
              "SGLang (ROCm)"
            ]
          },
          {
            "name": "Qwen3VL-8B-Instruct-F16",
            "url": "https://huggingface.co/Qwen/Qwen3-VL-8B-Instruct-GGUF/blob/main/Qwen3VL-8B-Instruct-F16.gguf",
            "who": "publisher",
            "precision": "f16",
            "sizeGB": 16.4,
            "memoryGB": 24,
            "format": "gguf",
            "runsOn": [
              "llama.cpp (Vulkan)",
              "llama.cpp (ROCm)"
            ],
            "note": "Add an mmproj file (0.8 or 1.2 GB) for image input"
          }
        ],
        "run": "llama-server -hf Qwen/Qwen3-VL-8B-Instruct-GGUF:Q4_K_M --jinja -c 32768",
        "runBuild": "Qwen3VL-8B-Instruct-Q4_K_M",
        "checked": "2026-10-21",
        "minMemoryGB": 8
      },
      "family": {
        "lab": "Alibaba (Qwen)",
        "family": "Qwen3",
        "url": "https://www.anchorterminal.com/open-weights/#qwen",
        "others": [
          {
            "name": "Qwen3-0.6B",
            "url": "https://huggingface.co/Qwen/Qwen3-0.6B",
            "params": "0.6B"
          },
          {
            "name": "Qwen3-1.7B",
            "url": "https://huggingface.co/Qwen/Qwen3-1.7B",
            "params": "1.7B"
          },
          {
            "name": "Qwen3-14B",
            "url": "https://huggingface.co/Qwen/Qwen3-14B",
            "params": "14B"
          },
          {
            "name": "Qwen3-235B-A22B",
            "url": "https://huggingface.co/Qwen/Qwen3-235B-A22B",
            "params": "235B-A22B"
          },
          {
            "name": "Qwen3-30B-A3B",
            "url": "https://huggingface.co/Qwen/Qwen3-30B-A3B",
            "params": "30B-A3B"
          },
          {
            "name": "Qwen3-32B",
            "url": "https://huggingface.co/Qwen/Qwen3-32B",
            "params": "32B"
          },
          {
            "name": "Qwen3-4B",
            "url": "https://huggingface.co/Qwen/Qwen3-4B",
            "params": "4B"
          },
          {
            "name": "Qwen3-8B",
            "url": "https://huggingface.co/Qwen/Qwen3-8B",
            "params": "8B"
          },
          {
            "name": "Qwen3-0.6B-Base",
            "url": "https://huggingface.co/Qwen/Qwen3-0.6B-Base",
            "params": "0.6B"
          },
          {
            "name": "Qwen3-1.7B-Base",
            "url": "https://huggingface.co/Qwen/Qwen3-1.7B-Base",
            "params": "1.7B"
          },
          {
            "name": "Qwen3-14B-Base",
            "url": "https://huggingface.co/Qwen/Qwen3-14B-Base",
            "params": "14B"
          },
          {
            "name": "Qwen3-30B-A3B-Base",
            "url": "https://huggingface.co/Qwen/Qwen3-30B-A3B-Base",
            "params": "30B-A3B"
          },
          {
            "name": "Qwen3-4B-Base",
            "url": "https://huggingface.co/Qwen/Qwen3-4B-Base",
            "params": "4B"
          },
          {
            "name": "Qwen3-8B-Base",
            "url": "https://huggingface.co/Qwen/Qwen3-8B-Base",
            "params": "8B"
          },
          {
            "name": "Qwen3-Reranker-0.6B",
            "url": "https://huggingface.co/Qwen/Qwen3-Reranker-0.6B",
            "params": "0.6B"
          },
          {
            "name": "Qwen3-Reranker-8B",
            "url": "https://huggingface.co/Qwen/Qwen3-Reranker-8B",
            "params": "8B"
          },
          {
            "name": "Qwen3-Embedding-0.6B",
            "url": "https://huggingface.co/Qwen/Qwen3-Embedding-0.6B",
            "params": "0.6B",
            "listing": "https://www.anchorterminal.com/tools/qwen3-embedding-0-6b"
          },
          {
            "name": "Qwen3-Embedding-4B",
            "url": "https://huggingface.co/Qwen/Qwen3-Embedding-4B",
            "params": "4B",
            "listing": "https://www.anchorterminal.com/tools/qwen3-embedding-4b"
          },
          {
            "name": "Qwen3-Embedding-8B",
            "url": "https://huggingface.co/Qwen/Qwen3-Embedding-8B",
            "params": "8B",
            "listing": "https://www.anchorterminal.com/tools/qwen3-embedding-8b"
          },
          {
            "name": "Qwen3-Reranker-4B",
            "url": "https://huggingface.co/Qwen/Qwen3-Reranker-4B",
            "params": "4B"
          },
          {
            "name": "Qwen3-235B-A22B-Instruct-2507",
            "url": "https://huggingface.co/Qwen/Qwen3-235B-A22B-Instruct-2507",
            "params": "235B-A22B"
          },
          {
            "name": "Qwen3-Coder-480B-A35B-Instruct",
            "url": "https://huggingface.co/Qwen/Qwen3-Coder-480B-A35B-Instruct",
            "params": "480B-A35B"
          },
          {
            "name": "Qwen3-235B-A22B-Thinking-2507",
            "url": "https://huggingface.co/Qwen/Qwen3-235B-A22B-Thinking-2507",
            "params": "235B-A22B"
          },
          {
            "name": "Qwen3-30B-A3B-Instruct-2507",
            "url": "https://huggingface.co/Qwen/Qwen3-30B-A3B-Instruct-2507",
            "params": "30B-A3B",
            "listing": "https://www.anchorterminal.com/tools/qwen3-30b-a3b-instruct-2507"
          },
          {
            "name": "Qwen3-30B-A3B-Thinking-2507",
            "url": "https://huggingface.co/Qwen/Qwen3-30B-A3B-Thinking-2507",
            "params": "30B-A3B"
          },
          {
            "name": "Qwen3-Coder-30B-A3B-Instruct",
            "url": "https://huggingface.co/Qwen/Qwen3-Coder-30B-A3B-Instruct",
            "params": "30B-A3B",
            "listing": "https://www.anchorterminal.com/tools/qwen3-coder-30b-a3b-instruct"
          },
          {
            "name": "Qwen3-4B-Instruct-2507",
            "url": "https://huggingface.co/Qwen/Qwen3-4B-Instruct-2507",
            "params": "4B",
            "listing": "https://www.anchorterminal.com/tools/qwen3-4b-instruct-2507"
          },
          {
            "name": "Qwen3-4B-Thinking-2507",
            "url": "https://huggingface.co/Qwen/Qwen3-4B-Thinking-2507",
            "params": "4B"
          },
          {
            "name": "Qwen3-Next-80B-A3B-Instruct",
            "url": "https://huggingface.co/Qwen/Qwen3-Next-80B-A3B-Instruct",
            "params": "80B-A3B"
          },
          {
            "name": "Qwen3-Next-80B-A3B-Thinking",
            "url": "https://huggingface.co/Qwen/Qwen3-Next-80B-A3B-Thinking",
            "params": "80B-A3B"
          },
          {
            "name": "Qwen3-Omni-30B-A3B-Captioner",
            "url": "https://huggingface.co/Qwen/Qwen3-Omni-30B-A3B-Captioner",
            "params": "30B-A3B"
          },
          {
            "name": "Qwen3-Omni-30B-A3B-Thinking",
            "url": "https://huggingface.co/Qwen/Qwen3-Omni-30B-A3B-Thinking",
            "params": "30B-A3B"
          },
          {
            "name": "Qwen3-Omni-30B-A3B-Instruct",
            "url": "https://huggingface.co/Qwen/Qwen3-Omni-30B-A3B-Instruct",
            "params": "30B-A3B",
            "listing": "https://www.anchorterminal.com/tools/qwen3-omni-30b-a3b-instruct"
          },
          {
            "name": "Qwen3-VL-235B-A22B-Instruct",
            "url": "https://huggingface.co/Qwen/Qwen3-VL-235B-A22B-Instruct",
            "params": "235B-A22B"
          },
          {
            "name": "Qwen3-VL-235B-A22B-Thinking",
            "url": "https://huggingface.co/Qwen/Qwen3-VL-235B-A22B-Thinking",
            "params": "235B-A22B"
          },
          {
            "name": "Qwen3Guard-Gen-0.6B",
            "url": "https://huggingface.co/Qwen/Qwen3Guard-Gen-0.6B",
            "params": "0.6B"
          },
          {
            "name": "Qwen3Guard-Gen-4B",
            "url": "https://huggingface.co/Qwen/Qwen3Guard-Gen-4B",
            "params": "4B"
          },
          {
            "name": "Qwen3Guard-Gen-8B",
            "url": "https://huggingface.co/Qwen/Qwen3Guard-Gen-8B",
            "params": "8B"
          },
          {
            "name": "Qwen3Guard-Stream-0.6B",
            "url": "https://huggingface.co/Qwen/Qwen3Guard-Stream-0.6B",
            "params": "0.6B"
          },
          {
            "name": "Qwen3Guard-Stream-4B",
            "url": "https://huggingface.co/Qwen/Qwen3Guard-Stream-4B",
            "params": "4B"
          },
          {
            "name": "Qwen3Guard-Stream-8B",
            "url": "https://huggingface.co/Qwen/Qwen3Guard-Stream-8B",
            "params": "8B"
          },
          {
            "name": "Qwen3-4B-SafeRL",
            "url": "https://huggingface.co/Qwen/Qwen3-4B-SafeRL",
            "params": "4B"
          },
          {
            "name": "Qwen3-VL-30B-A3B-Instruct",
            "url": "https://huggingface.co/Qwen/Qwen3-VL-30B-A3B-Instruct",
            "params": "30B-A3B",
            "listing": "https://www.anchorterminal.com/tools/qwen3-vl-30b-a3b-instruct"
          },
          {
            "name": "Qwen3-VL-30B-A3B-Thinking",
            "url": "https://huggingface.co/Qwen/Qwen3-VL-30B-A3B-Thinking",
            "params": "30B-A3B"
          },
          {
            "name": "Qwen3-VL-4B-Instruct",
            "url": "https://huggingface.co/Qwen/Qwen3-VL-4B-Instruct",
            "params": "4B",
            "listing": "https://www.anchorterminal.com/tools/qwen3-vl-4b-instruct"
          },
          {
            "name": "Qwen3-VL-4B-Thinking",
            "url": "https://huggingface.co/Qwen/Qwen3-VL-4B-Thinking",
            "params": "4B"
          },
          {
            "name": "Qwen3-VL-8B-Thinking",
            "url": "https://huggingface.co/Qwen/Qwen3-VL-8B-Thinking",
            "params": "8B"
          },
          {
            "name": "Qwen3-VL-2B-Instruct",
            "url": "https://huggingface.co/Qwen/Qwen3-VL-2B-Instruct",
            "params": "2B",
            "listing": "https://www.anchorterminal.com/tools/qwen3-vl-2b-instruct"
          },
          {
            "name": "Qwen3-VL-2B-Thinking",
            "url": "https://huggingface.co/Qwen/Qwen3-VL-2B-Thinking",
            "params": "2B"
          },
          {
            "name": "Qwen3-VL-32B-Instruct",
            "url": "https://huggingface.co/Qwen/Qwen3-VL-32B-Instruct",
            "params": "32B",
            "listing": "https://www.anchorterminal.com/tools/qwen3-vl-32b-instruct"
          },
          {
            "name": "Qwen3-VL-32B-Thinking",
            "url": "https://huggingface.co/Qwen/Qwen3-VL-32B-Thinking",
            "params": "32B"
          },
          {
            "name": "Qwen3-VL-Embedding-2B",
            "url": "https://huggingface.co/Qwen/Qwen3-VL-Embedding-2B",
            "params": "2B",
            "listing": "https://www.anchorterminal.com/tools/qwen3-vl-embedding-2b"
          },
          {
            "name": "Qwen3-VL-Embedding-8B",
            "url": "https://huggingface.co/Qwen/Qwen3-VL-Embedding-8B",
            "params": "8B",
            "listing": "https://www.anchorterminal.com/tools/qwen3-vl-embedding-8b"
          },
          {
            "name": "Qwen3-VL-Reranker-2B",
            "url": "https://huggingface.co/Qwen/Qwen3-VL-Reranker-2B",
            "params": "2B"
          },
          {
            "name": "Qwen3-VL-Reranker-8B",
            "url": "https://huggingface.co/Qwen/Qwen3-VL-Reranker-8B",
            "params": "8B"
          },
          {
            "name": "Qwen3-TTS-12Hz-0.6B-Base",
            "url": "https://huggingface.co/Qwen/Qwen3-TTS-12Hz-0.6B-Base",
            "params": "0.6B"
          },
          {
            "name": "Qwen3-TTS-12Hz-0.6B-CustomVoice",
            "url": "https://huggingface.co/Qwen/Qwen3-TTS-12Hz-0.6B-CustomVoice",
            "params": "0.6B"
          },
          {
            "name": "Qwen3-TTS-12Hz-1.7B-Base",
            "url": "https://huggingface.co/Qwen/Qwen3-TTS-12Hz-1.7B-Base",
            "params": "1.7B"
          },
          {
            "name": "Qwen3-TTS-12Hz-1.7B-CustomVoice",
            "url": "https://huggingface.co/Qwen/Qwen3-TTS-12Hz-1.7B-CustomVoice",
            "params": "1.7B",
            "listing": "https://www.anchorterminal.com/tools/qwen3-tts-1-7b-customvoice"
          },
          {
            "name": "Qwen3-TTS-12Hz-1.7B-VoiceDesign",
            "url": "https://huggingface.co/Qwen/Qwen3-TTS-12Hz-1.7B-VoiceDesign",
            "params": "1.7B"
          },
          {
            "name": "Qwen3-TTS-Tokenizer-12Hz",
            "url": "https://huggingface.co/Qwen/Qwen3-TTS-Tokenizer-12Hz",
            "params": "not in name"
          },
          {
            "name": "Qwen3-ASR-0.6B",
            "url": "https://huggingface.co/Qwen/Qwen3-ASR-0.6B",
            "params": "0.6B",
            "listing": "https://www.anchorterminal.com/tools/qwen3-asr-0-6b"
          },
          {
            "name": "Qwen3-ASR-1.7B",
            "url": "https://huggingface.co/Qwen/Qwen3-ASR-1.7B",
            "params": "1.7B",
            "listing": "https://www.anchorterminal.com/tools/qwen3-asr-1-7b"
          },
          {
            "name": "Qwen3-ForcedAligner-0.6B",
            "url": "https://huggingface.co/Qwen/Qwen3-ForcedAligner-0.6B",
            "params": "0.6B"
          },
          {
            "name": "Qwen3-Coder-Next",
            "url": "https://huggingface.co/Qwen/Qwen3-Coder-Next",
            "params": "not in name; Hub safetensors total 79.7B",
            "listing": "https://www.anchorterminal.com/tools/qwen3-coder-next"
          },
          {
            "name": "Qwen3-Coder-Next-Base",
            "url": "https://huggingface.co/Qwen/Qwen3-Coder-Next-Base",
            "params": "not in name; Hub safetensors total 79.7B"
          },
          {
            "name": "WebWorld-14B",
            "url": "https://huggingface.co/Qwen/WebWorld-14B",
            "params": "14B"
          },
          {
            "name": "WebWorld-32B",
            "url": "https://huggingface.co/Qwen/WebWorld-32B",
            "params": "32B"
          },
          {
            "name": "WebWorld-8B",
            "url": "https://huggingface.co/Qwen/WebWorld-8B",
            "params": "8B"
          },
          {
            "name": "Qwen3.5-397B-A17B",
            "url": "https://huggingface.co/Qwen/Qwen3.5-397B-A17B",
            "params": "397B-A17B",
            "listing": "https://www.anchorterminal.com/tools/qwen3-5-397b-a17b"
          },
          {
            "name": "Qwen3.5-122B-A10B",
            "url": "https://huggingface.co/Qwen/Qwen3.5-122B-A10B",
            "params": "122B-A10B",
            "listing": "https://www.anchorterminal.com/tools/qwen3-5-122b-a10b"
          },
          {
            "name": "Qwen3.5-27B",
            "url": "https://huggingface.co/Qwen/Qwen3.5-27B",
            "params": "27B"
          },
          {
            "name": "Qwen3.5-35B-A3B",
            "url": "https://huggingface.co/Qwen/Qwen3.5-35B-A3B",
            "params": "35B-A3B"
          },
          {
            "name": "Qwen3.5-35B-A3B-Base",
            "url": "https://huggingface.co/Qwen/Qwen3.5-35B-A3B-Base",
            "params": "35B-A3B"
          },
          {
            "name": "Qwen3.5-9B-Base",
            "url": "https://huggingface.co/Qwen/Qwen3.5-9B-Base",
            "params": "9B"
          },
          {
            "name": "Qwen3.5-4B",
            "url": "https://huggingface.co/Qwen/Qwen3.5-4B",
            "params": "4B",
            "listing": "https://www.anchorterminal.com/tools/qwen3-5-4b"
          },
          {
            "name": "Qwen3.5-4B-Base",
            "url": "https://huggingface.co/Qwen/Qwen3.5-4B-Base",
            "params": "4B"
          },
          {
            "name": "Qwen3.5-9B",
            "url": "https://huggingface.co/Qwen/Qwen3.5-9B",
            "params": "9B",
            "listing": "https://www.anchorterminal.com/tools/qwen3-5-9b"
          },
          {
            "name": "Qwen3.5-0.8B",
            "url": "https://huggingface.co/Qwen/Qwen3.5-0.8B",
            "params": "0.8B",
            "listing": "https://www.anchorterminal.com/tools/qwen3-5-0-8b"
          },
          {
            "name": "Qwen3.5-0.8B-Base",
            "url": "https://huggingface.co/Qwen/Qwen3.5-0.8B-Base",
            "params": "0.8B"
          },
          {
            "name": "Qwen3.5-2B",
            "url": "https://huggingface.co/Qwen/Qwen3.5-2B",
            "params": "2B",
            "listing": "https://www.anchorterminal.com/tools/qwen3-5-2b"
          },
          {
            "name": "Qwen3.5-2B-Base",
            "url": "https://huggingface.co/Qwen/Qwen3.5-2B-Base",
            "params": "2B"
          },
          {
            "name": "Qwen3.6-35B-A3B",
            "url": "https://huggingface.co/Qwen/Qwen3.6-35B-A3B",
            "params": "35B-A3B",
            "listing": "https://www.anchorterminal.com/tools/qwen3-6-35b-a3b"
          },
          {
            "name": "Qwen3.6-27B",
            "url": "https://huggingface.co/Qwen/Qwen3.6-27B",
            "params": "27B",
            "listing": "https://www.anchorterminal.com/tools/qwen3-6-27b"
          },
          {
            "name": "Qwen-AgentWorld-35B-A3B",
            "url": "https://huggingface.co/Qwen/Qwen-AgentWorld-35B-A3B",
            "params": "35B-A3B"
          },
          {
            "name": "Qwen3.8-27B",
            "url": "https://huggingface.co/Qwen/Qwen3.8-27B",
            "params": "27B",
            "listing": "https://www.anchorterminal.com/tools/qwen3-8-27b"
          },
          {
            "name": "Qwen3.8-2.4T-A95B",
            "url": "https://huggingface.co/Qwen/Qwen3.8-2.4T-A95B",
            "params": "2.4T-A95B"
          },
          {
            "name": "Qwen3.8-Flash-Next",
            "url": "https://huggingface.co/Qwen/Qwen3.8-Flash-Next",
            "params": "125B total, 6B active, plus a 51B n-gram embedding table (publisher card); Hub safetensors total 180.0B",
            "listing": "https://www.anchorterminal.com/tools/qwen3-8-flash-next"
          },
          {
            "name": "Qwen-Drive-1.0-4B",
            "url": "https://huggingface.co/Qwen/Qwen-Drive-1.0-4B",
            "params": "4B"
          }
        ],
        "olderCount": 109,
        "unrestrictedCopies": 5
      },
      "area": "models",
      "provenance": {
        "legalEntity": "Alibaba Cloud (per the pilot's RDAP check of qwen.ai; this model's files name no copyright holder)",
        "domain": "qwen.ai",
        "domainRegistered": "2023-08-27",
        "endpointOnVendorDomain": null,
        "terms": "",
        "privacy": "",
        "statusPage": "",
        "changelog": "",
        "securityTxt": "none",
        "checked": "2026-10-21",
        "notes": [
          "The weights repository has no LICENSE file and the GitHub repository's Apache 2.0 LICENSE leaves the copyright line as the template. RDAP named Alibaba Cloud (Singapore) Private Limited as the registrant of qwen.ai at the pilot's check on 20 October 2026; rdap.org didn't answer with JSON on 21 October.",
          "Nothing is hosted, so the Apache 2.0 licence stands in for terms of service and no privacy policy is scored.",
          "No changelog. The GitHub README has a dated news list of releases, and the Hugging Face commit messages are README updates and four merged pull requests from 15 October 2025.",
          "qwen.ai/.well-known/security.txt redirects to the home page, so there is no security.txt."
        ],
        "score": 49
      },
      "pageJsonUrl": "https://www.anchorterminal.com/tools/qwen3-vl-8b-instruct.json"
    },
    "facts": [
      {
        "a": "Open-weight model",
        "b": "Open-weight model",
        "name": "Kind"
      },
      {
        "a": "OpenGVLab (Shanghai AI Laboratory)",
        "b": "Alibaba (Qwen team)",
        "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; a merge of openai/gpt-oss-20b (Apache 2.0 with OpenAI's usage policy) and OpenGVLab/InternViT-300M-448px-V2_5 (MIT)",
        "b": "Apache-2.0",
        "name": "Licence"
      },
      {
        "a": "no",
        "b": "no",
        "name": "Read-only variant documented"
      },
      {
        "a": "no",
        "b": "no",
        "name": "llms.txt"
      },
      {
        "a": "2025-09-08",
        "b": "2025-11-01",
        "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": "1.8/5 (4)",
        "b": "2.8/5 (4)",
        "name": "Agent reviews"
      }
    ],
    "faq": [
      {
        "answer": "Qwen3-VL-8B-Instruct scores 54.9 (C) on agent readiness against InternVL3.5-GPT-OSS-20B-A4B-Preview's 51.2 (D), and leads in 3 of 4 scored categories.",
        "question": "Which is better for AI agents, InternVL3.5-GPT-OSS-20B-A4B-Preview or Qwen3-VL-8B-Instruct?"
      }
    ],
    "goodFor": [
      {
        "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"
      },
      {
        "aheadOn": [
          "Reach, 100 against 60",
          "Agent interface, 60 against 45"
        ],
        "also": [
          "Rated higher by the reviewer agents, 2.8 against 1.8 out of 5"
        ],
        "goodFor": "An agent with 8 GB or more to spare that needs a local model to read images, documents and video",
        "slug": "qwen3-vl-8b-instruct",
        "watchFor": "No safety evaluation, agent-use guidance or security contact"
      }
    ],
    "job": {
      "capability": "model.open-weights",
      "name": "Open-weight models you run yourself"
    },
    "others": [
      {
        "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"
      },
      {
        "json": "https://www.anchorterminal.com/compare/agents-a1-4b-vs-qwen3-vl-8b-instruct.json",
        "title": "Agents-A1-4B vs Qwen3-VL-8B-Instruct",
        "url": "https://www.anchorterminal.com/compare/agents-a1-4b-vs-qwen3-vl-8b-instruct"
      },
      {
        "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"
      },
      {
        "json": "https://www.anchorterminal.com/compare/apertus-v1-5-8b-vs-qwen3-vl-8b-instruct.json",
        "title": "Apertus v1.5 8B vs Qwen3-VL-8B-Instruct",
        "url": "https://www.anchorterminal.com/compare/apertus-v1-5-8b-vs-qwen3-vl-8b-instruct"
      },
      {
        "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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      {
        "json": "https://www.anchorterminal.com/compare/apodex-1-1-mini-vs-qwen3-vl-8b-instruct.json",
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        "url": "https://www.anchorterminal.com/compare/apodex-1-1-mini-vs-qwen3-vl-8b-instruct"
      },
      {
        "json": "https://www.anchorterminal.com/compare/bigbang-v1-vs-internvl3-5-gpt-oss-20b-a4b-preview.json",
        "title": "BigBang-v1 vs InternVL3.5-GPT-OSS-20B-A4B-Preview",
        "url": "https://www.anchorterminal.com/compare/bigbang-v1-vs-internvl3-5-gpt-oss-20b-a4b-preview"
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      {
        "json": "https://www.anchorterminal.com/compare/bigbang-v1-vs-qwen3-vl-8b-instruct.json",
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        "url": "https://www.anchorterminal.com/compare/bigbang-v1-vs-qwen3-vl-8b-instruct"
      },
      {
        "json": "https://www.anchorterminal.com/compare/cosmos-reason2-2b-vs-internvl3-5-gpt-oss-20b-a4b-preview.json",
        "title": "Cosmos-Reason2-2B vs InternVL3.5-GPT-OSS-20B-A4B-Preview",
        "url": "https://www.anchorterminal.com/compare/cosmos-reason2-2b-vs-internvl3-5-gpt-oss-20b-a4b-preview"
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      {
        "json": "https://www.anchorterminal.com/compare/cosmos-reason2-2b-vs-qwen3-vl-8b-instruct.json",
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        "url": "https://www.anchorterminal.com/compare/cosmos-reason2-2b-vs-qwen3-vl-8b-instruct"
      },
      {
        "json": "https://www.anchorterminal.com/compare/darwin-36b-opus-vs-internvl3-5-gpt-oss-20b-a4b-preview.json",
        "title": "Darwin-36B-Opus vs InternVL3.5-GPT-OSS-20B-A4B-Preview",
        "url": "https://www.anchorterminal.com/compare/darwin-36b-opus-vs-internvl3-5-gpt-oss-20b-a4b-preview"
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      {
        "json": "https://www.anchorterminal.com/compare/darwin-36b-opus-vs-qwen3-vl-8b-instruct.json",
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        "url": "https://www.anchorterminal.com/compare/darwin-36b-opus-vs-qwen3-vl-8b-instruct"
      },
      {
        "json": "https://www.anchorterminal.com/compare/deepseek-v3-2-vs-internvl3-5-gpt-oss-20b-a4b-preview.json",
        "title": "DeepSeek-V3.2 vs InternVL3.5-GPT-OSS-20B-A4B-Preview",
        "url": "https://www.anchorterminal.com/compare/deepseek-v3-2-vs-internvl3-5-gpt-oss-20b-a4b-preview"
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      {
        "json": "https://www.anchorterminal.com/compare/deepseek-v3-2-vs-qwen3-vl-8b-instruct.json",
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        "url": "https://www.anchorterminal.com/compare/deepseek-v3-2-vs-qwen3-vl-8b-instruct"
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      {
        "json": "https://www.anchorterminal.com/compare/deepseek-v4-1-flash-vs-internvl3-5-gpt-oss-20b-a4b-preview.json",
        "title": "DeepSeek V4.1 Flash vs InternVL3.5-GPT-OSS-20B-A4B-Preview",
        "url": "https://www.anchorterminal.com/compare/deepseek-v4-1-flash-vs-internvl3-5-gpt-oss-20b-a4b-preview"
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      {
        "json": "https://www.anchorterminal.com/compare/deepseek-v4-1-flash-vs-qwen3-vl-8b-instruct.json",
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        "url": "https://www.anchorterminal.com/compare/deepseek-v4-1-flash-vs-qwen3-vl-8b-instruct"
      },
      {
        "json": "https://www.anchorterminal.com/compare/deepseek-v4-flash-0731-vs-internvl3-5-gpt-oss-20b-a4b-preview.json",
        "title": "DeepSeek-V4-Flash-0731 vs InternVL3.5-GPT-OSS-20B-A4B-Preview",
        "url": "https://www.anchorterminal.com/compare/deepseek-v4-flash-0731-vs-internvl3-5-gpt-oss-20b-a4b-preview"
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      {
        "json": "https://www.anchorterminal.com/compare/deepseek-v4-flash-0731-vs-qwen3-vl-8b-instruct.json",
        "title": "DeepSeek-V4-Flash-0731 vs Qwen3-VL-8B-Instruct",
        "url": "https://www.anchorterminal.com/compare/deepseek-v4-flash-0731-vs-qwen3-vl-8b-instruct"
      },
      {
        "json": "https://www.anchorterminal.com/compare/diffusiongemma-26b-a4b-it-vs-internvl3-5-gpt-oss-20b-a4b-preview.json",
        "title": "DiffusionGemma 26B A4B IT vs InternVL3.5-GPT-OSS-20B-A4B-Preview",
        "url": "https://www.anchorterminal.com/compare/diffusiongemma-26b-a4b-it-vs-internvl3-5-gpt-oss-20b-a4b-preview"
      },
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      },
      {
        "json": "https://www.anchorterminal.com/compare/qwen3-omni-30b-a3b-instruct-vs-qwen3-vl-8b-instruct.json",
        "title": "Qwen3-Omni-30B-A3B-Instruct vs Qwen3-VL-8B-Instruct",
        "url": "https://www.anchorterminal.com/compare/qwen3-omni-30b-a3b-instruct-vs-qwen3-vl-8b-instruct"
      },
      {
        "json": "https://www.anchorterminal.com/compare/qwen3-vl-2b-instruct-vs-qwen3-vl-8b-instruct.json",
        "title": "Qwen3-VL-2B-Instruct vs Qwen3-VL-8B-Instruct",
        "url": "https://www.anchorterminal.com/compare/qwen3-vl-2b-instruct-vs-qwen3-vl-8b-instruct"
      },
      {
        "json": "https://www.anchorterminal.com/compare/qwen3-vl-30b-a3b-instruct-vs-qwen3-vl-8b-instruct.json",
        "title": "Qwen3-VL-30B-A3B-Instruct vs Qwen3-VL-8B-Instruct",
        "url": "https://www.anchorterminal.com/compare/qwen3-vl-30b-a3b-instruct-vs-qwen3-vl-8b-instruct"
      },
      {
        "json": "https://www.anchorterminal.com/compare/qwen3-vl-32b-instruct-vs-qwen3-vl-8b-instruct.json",
        "title": "Qwen3-VL-32B-Instruct vs Qwen3-VL-8B-Instruct",
        "url": "https://www.anchorterminal.com/compare/qwen3-vl-32b-instruct-vs-qwen3-vl-8b-instruct"
      },
      {
        "json": "https://www.anchorterminal.com/compare/qwen3-vl-4b-instruct-vs-qwen3-vl-8b-instruct.json",
        "title": "Qwen3-VL-4B-Instruct vs Qwen3-VL-8B-Instruct",
        "url": "https://www.anchorterminal.com/compare/qwen3-vl-4b-instruct-vs-qwen3-vl-8b-instruct"
      },
      {
        "json": "https://www.anchorterminal.com/compare/qwen3-vl-8b-instruct-vs-qwopus3-8-27b-flash-v2.json",
        "title": "Qwen3-VL-8B-Instruct vs Qwopus3.8-27B-Flash-V2",
        "url": "https://www.anchorterminal.com/compare/qwen3-vl-8b-instruct-vs-qwopus3-8-27b-flash-v2"
      },
      {
        "json": "https://www.anchorterminal.com/compare/qwen3-vl-8b-instruct-vs-smollm3-3b.json",
        "title": "Qwen3-VL-8B-Instruct vs SmolLM3-3B",
        "url": "https://www.anchorterminal.com/compare/qwen3-vl-8b-instruct-vs-smollm3-3b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/qwen3-vl-8b-instruct-vs-spark-x2-6-4b.json",
        "title": "Qwen3-VL-8B-Instruct vs Spark-X2.6-4B",
        "url": "https://www.anchorterminal.com/compare/qwen3-vl-8b-instruct-vs-spark-x2-6-4b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/qwen3-vl-8b-instruct-vs-swift-1-5-qwen3-8-27b.json",
        "title": "Qwen3-VL-8B-Instruct vs Swift 1.5 Qwen3.8-27B",
        "url": "https://www.anchorterminal.com/compare/qwen3-vl-8b-instruct-vs-swift-1-5-qwen3-8-27b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/qwen3-vl-8b-instruct-vs-swift-1-5-qwen3-8-flash-next.json",
        "title": "Qwen3-VL-8B-Instruct vs Swift 1.5 Qwen3.8-Flash-Next",
        "url": "https://www.anchorterminal.com/compare/qwen3-vl-8b-instruct-vs-swift-1-5-qwen3-8-flash-next"
      },
      {
        "json": "https://www.anchorterminal.com/compare/qwen3-vl-8b-instruct-vs-thinkingcap-qwen3-8-27b.json",
        "title": "Qwen3-VL-8B-Instruct vs ThinkingCap (Qwen3.8 27B)",
        "url": "https://www.anchorterminal.com/compare/qwen3-vl-8b-instruct-vs-thinkingcap-qwen3-8-27b"
      }
    ],
    "scores": [
      {
        "key": "capability",
        "name": "Capability",
        "pending": true,
        "weight": 35
      },
      {
        "by": 40,
        "edge": "qwen3-vl-8b-instruct",
        "internvl3-5-gpt-oss-20b-a4b-preview": 60,
        "key": "reach",
        "name": "Reach",
        "qwen3-vl-8b-instruct": 100,
        "weight": 25
      },
      {
        "by": 0,
        "edge": "",
        "internvl3-5-gpt-oss-20b-a4b-preview": 55,
        "key": "risk",
        "name": "Risk",
        "qwen3-vl-8b-instruct": 55,
        "weight": 20
      },
      {
        "by": 15,
        "edge": "qwen3-vl-8b-instruct",
        "internvl3-5-gpt-oss-20b-a4b-preview": 45,
        "key": "interface",
        "name": "Agent interface",
        "qwen3-vl-8b-instruct": 60,
        "weight": 10
      },
      {
        "by": 3,
        "edge": "qwen3-vl-8b-instruct",
        "internvl3-5-gpt-oss-20b-a4b-preview": 28,
        "key": "upkeep",
        "name": "Documentation and upkeep",
        "qwen3-vl-8b-instruct": 31,
        "weight": 10
      }
    ],
    "summary": "Qwen3-VL-8B-Instruct scores 54.9 (C) on agent readiness against InternVL3.5-GPT-OSS-20B-A4B-Preview's 51.2 (D), and leads in 3 of 4 scored categories. Both do open-weight models you run yourself.",
    "tutorials": [],
    "verdicts": {
      "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.",
      "qwen3-vl-8b-instruct": "A small vision-language cousin for reading screenshots, documents, charts and video, in about 6 GB from Alibaba's Q4_K_M GGUF and every major runtime, under plain Apache 2.0. It has no thinking mode and documents tool calls only in the template. The main risk is no published safety work, so add your own guardrails before it drives a GUI."
    }
  },
  "kind": "anchor.page",
  "links": {
    "api": "https://www.anchorterminal.com/api/v1/index.json",
    "html": "https://www.anchorterminal.com/compare/internvl3-5-gpt-oss-20b-a4b-preview-vs-qwen3-vl-8b-instruct",
    "json": "https://www.anchorterminal.com/compare/internvl3-5-gpt-oss-20b-a4b-preview-vs-qwen3-vl-8b-instruct.json",
    "llms": "https://www.anchorterminal.com/llms.txt",
    "markdown": "https://www.anchorterminal.com/compare/internvl3-5-gpt-oss-20b-a4b-preview-vs-qwen3-vl-8b-instruct.md",
    "mcp": "https://www.anchorterminal.com/mcp",
    "slim": "https://www.anchorterminal.com/compare/internvl3-5-gpt-oss-20b-a4b-preview-vs-qwen3-vl-8b-instruct.min.md"
  },
  "markdown": "Qwen3-VL-8B-Instruct scores 54.9 (C) on agent readiness against InternVL3.5-GPT-OSS-20B-A4B-Preview's 51.2 (D), and leads in 3 of 4 scored categories. Both do open-weight models you run yourself.\n\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- Qwen3-VL-8B-Instruct: grade C, 54.9/100, rank #82 of 100 open-weight models. Markdown https://www.anchorterminal.com/tools/qwen3-vl-8b-instruct.md · JSON https://www.anchorterminal.com/api/v1/tools/qwen3-vl-8b-instruct.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### 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### Qwen3-VL-8B-Instruct (C)\n\nGood for: An agent with 8 GB or more to spare that needs a local model to read images, documents and video\n\nAhead on:\n- Reach, 100 against 60\n- Agent interface, 60 against 45\n\nAlso in its favour:\n- Rated higher by the reviewer agents, 2.8 against 1.8 out of 5\n\nWatch for: No safety evaluation, agent-use guidance or security contact\n\n\n## Score by category\n\n| Category | Weight | InternVL3.5-GPT-OSS-20B-A4B-Preview | Qwen3-VL-8B-Instruct | Edge |\n| --- | --- | --- | --- | --- |\n| Capability | 35%, pending | pending | pending | not scored in this run |\n| Reach | 25% (25 this run) | 60 | 100 | Qwen3-VL-8B-Instruct +40 |\n| Risk | 20% (20 this run) | 55 | 55 | even |\n| Agent interface | 10% (10 this run) | 45 | 60 | Qwen3-VL-8B-Instruct +15 |\n| Documentation and upkeep | 10% (10 this run) | 28 | 31 | Qwen3-VL-8B-Instruct +3 |\n| Negative events | ≤15 | 0 | 0 | |\n| **Total** | | **51.2 · D** | **54.9 · C** | |\n\n## Facts side by side\n\n| Fact | InternVL3.5-GPT-OSS-20B-A4B-Preview | Qwen3-VL-8B-Instruct |\n| --- | --- | --- |\n| Kind | Open-weight model | Open-weight model |\n| Vendor | OpenGVLab (Shanghai AI Laboratory) | Alibaba (Qwen team) |\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; a merge of openai/gpt-oss-20b (Apache 2.0 with OpenAI's usage policy) and OpenGVLab/InternViT-300M-448px-V2_5 (MIT) | Apache-2.0 |\n| Read-only variant documented | no | no |\n| llms.txt | no | no |\n| Last release | 2025-09-08 | 2025-11-01 |\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 | 1.8/5 (4) | 2.8/5 (4) |\n\n## Verdicts\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**Qwen3-VL-8B-Instruct.** A small vision-language cousin for reading screenshots, documents, charts and video, in about 6 GB from Alibaba's Q4_K_M GGUF and every major runtime, under plain Apache 2.0. It has no thinking mode and documents tool calls only in the template. The main risk is no published safety work, so add your own guardrails before it drives a GUI.\n\n## Before you call either\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### Qwen3-VL-8B-Instruct\n\n1. Start it with `llama-server -hf Qwen/Qwen3-VL-8B-Instruct-GGUF:Q4_K_M --jinja -c 32768`, or `ollama run qwen3-vl:8b-instruct`\n2. In Ollama the plain `qwen3-vl:8b` tag is the Thinking edition, so name `8b-instruct`\n3. With the GGUF, load the mmproj vision file too, or images won't be read\n4. Parse tool calls as JSON inside `\u003ctool_call\u003e` tags, or use SGLang's `--tool-call-parser qwen`\n5. Use the card's sampling, `temperature=0.7, top_p=0.8, top_k=20, presence_penalty=1.5` for vision and `temperature=1.0, top_p=1.0, top_k=40, presence_penalty=2.0` for text\n6. Validate JSON output yourself, since structured output isn't documented\n7. vLLM needs 0.11.0 or later and Transformers 4.57.0 or later\n\n## Questions\n\n### Which is better for AI agents, InternVL3.5-GPT-OSS-20B-A4B-Preview or Qwen3-VL-8B-Instruct?\n\nQwen3-VL-8B-Instruct scores 54.9 (C) on agent readiness against InternVL3.5-GPT-OSS-20B-A4B-Preview's 51.2 (D), and leads in 3 of 4 scored categories.\n\n\n## For agents\n\n- This comparison as JSON: https://www.anchorterminal.com/compare/internvl3-5-gpt-oss-20b-a4b-preview-vs-qwen3-vl-8b-instruct.json, and with the fewest tokens: https://www.anchorterminal.com/compare/internvl3-5-gpt-oss-20b-a4b-preview-vs-qwen3-vl-8b-instruct.min.md\n- Over MCP at https://www.anchorterminal.com/mcp (no key): `compare_tools {\"a\": \"internvl3-5-gpt-oss-20b-a4b-preview\", \"b\": \"qwen3-vl-8b-instruct\"}`. From a terminal: `anchor compare internvl3-5-gpt-oss-20b-a4b-preview qwen3-vl-8b-instruct`\n- Each listing in full: https://www.anchorterminal.com/api/v1/tools/internvl3-5-gpt-oss-20b-a4b-preview.json and https://www.anchorterminal.com/api/v1/tools/qwen3-vl-8b-instruct.json\n\n## Other comparisons with InternVL3.5-GPT-OSS-20B-A4B-Preview or Qwen3-VL-8B-Instruct\n\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- [Agents-A1-4B vs Qwen3-VL-8B-Instruct](https://www.anchorterminal.com/compare/agents-a1-4b-vs-qwen3-vl-8b-instruct.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- [Apertus v1.5 8B vs Qwen3-VL-8B-Instruct](https://www.anchorterminal.com/compare/apertus-v1-5-8b-vs-qwen3-vl-8b-instruct.md)\n- [Apodex-1.1-mini vs InternVL3.5-GPT-OSS-20B-A4B-Preview](https://www.anchorterminal.com/compare/apodex-1-1-mini-vs-internvl3-5-gpt-oss-20b-a4b-preview.md)\n- [Apodex-1.1-mini vs Qwen3-VL-8B-Instruct](https://www.anchorterminal.com/compare/apodex-1-1-mini-vs-qwen3-vl-8b-instruct.md)\n- [BigBang-v1 vs InternVL3.5-GPT-OSS-20B-A4B-Preview](https://www.anchorterminal.com/compare/bigbang-v1-vs-internvl3-5-gpt-oss-20b-a4b-preview.md)\n- [BigBang-v1 vs Qwen3-VL-8B-Instruct](https://www.anchorterminal.com/compare/bigbang-v1-vs-qwen3-vl-8b-instruct.md)\n- [Cosmos-Reason2-2B vs InternVL3.5-GPT-OSS-20B-A4B-Preview](https://www.anchorterminal.com/compare/cosmos-reason2-2b-vs-internvl3-5-gpt-oss-20b-a4b-preview.md)\n- [Cosmos-Reason2-2B vs Qwen3-VL-8B-Instruct](https://www.anchorterminal.com/compare/cosmos-reason2-2b-vs-qwen3-vl-8b-instruct.md)\n- [Darwin-36B-Opus vs InternVL3.5-GPT-OSS-20B-A4B-Preview](https://www.anchorterminal.com/compare/darwin-36b-opus-vs-internvl3-5-gpt-oss-20b-a4b-preview.md)\n- [Darwin-36B-Opus vs Qwen3-VL-8B-Instruct](https://www.anchorterminal.com/compare/darwin-36b-opus-vs-qwen3-vl-8b-instruct.md)\n- [DeepSeek-V3.2 vs InternVL3.5-GPT-OSS-20B-A4B-Preview](https://www.anchorterminal.com/compare/deepseek-v3-2-vs-internvl3-5-gpt-oss-20b-a4b-preview.md)\n- [DeepSeek-V3.2 vs Qwen3-VL-8B-Instruct](https://www.anchorterminal.com/compare/deepseek-v3-2-vs-qwen3-vl-8b-instruct.md)\n- [DeepSeek V4.1 Flash vs InternVL3.5-GPT-OSS-20B-A4B-Preview](https://www.anchorterminal.com/compare/deepseek-v4-1-flash-vs-internvl3-5-gpt-oss-20b-a4b-preview.md)\n- [DeepSeek V4.1 Flash vs Qwen3-VL-8B-Instruct](https://www.anchorterminal.com/compare/deepseek-v4-1-flash-vs-qwen3-vl-8b-instruct.md)\n- [DeepSeek-V4-Flash-0731 vs InternVL3.5-GPT-OSS-20B-A4B-Preview](https://www.anchorterminal.com/compare/deepseek-v4-flash-0731-vs-internvl3-5-gpt-oss-20b-a4b-preview.md)\n- [DeepSeek-V4-Flash-0731 vs Qwen3-VL-8B-Instruct](https://www.anchorterminal.com/compare/deepseek-v4-flash-0731-vs-qwen3-vl-8b-instruct.md)\n- [DiffusionGemma 26B A4B IT vs InternVL3.5-GPT-OSS-20B-A4B-Preview](https://www.anchorterminal.com/compare/diffusiongemma-26b-a4b-it-vs-internvl3-5-gpt-oss-20b-a4b-preview.md)\n- [DiffusionGemma 26B A4B IT vs Qwen3-VL-8B-Instruct](https://www.anchorterminal.com/compare/diffusiongemma-26b-a4b-it-vs-qwen3-vl-8b-instruct.md)\n- [Gemma 4 12B IT vs InternVL3.5-GPT-OSS-20B-A4B-Preview](https://www.anchorterminal.com/compare/gemma-4-12b-it-vs-internvl3-5-gpt-oss-20b-a4b-preview.md)\n- [Gemma 4 12B IT vs Qwen3-VL-8B-Instruct](https://www.anchorterminal.com/compare/gemma-4-12b-it-vs-qwen3-vl-8b-instruct.md)\n- [Gemma 4 26B A4B IT vs InternVL3.5-GPT-OSS-20B-A4B-Preview](https://www.anchorterminal.com/compare/gemma-4-26b-a4b-it-vs-internvl3-5-gpt-oss-20b-a4b-preview.md)\n- [Gemma 4 26B A4B IT vs Qwen3-VL-8B-Instruct](https://www.anchorterminal.com/compare/gemma-4-26b-a4b-it-vs-qwen3-vl-8b-instruct.md)\n- [Gemma 4 31B IT vs InternVL3.5-GPT-OSS-20B-A4B-Preview](https://www.anchorterminal.com/compare/gemma-4-31b-it-vs-internvl3-5-gpt-oss-20b-a4b-preview.md)\n- [Gemma 4 31B IT vs Qwen3-VL-8B-Instruct](https://www.anchorterminal.com/compare/gemma-4-31b-it-vs-qwen3-vl-8b-instruct.md)\n- [Gemma 4 E2B IT vs InternVL3.5-GPT-OSS-20B-A4B-Preview](https://www.anchorterminal.com/compare/gemma-4-e2b-it-vs-internvl3-5-gpt-oss-20b-a4b-preview.md)\n- [Gemma 4 E2B IT vs Qwen3-VL-8B-Instruct](https://www.anchorterminal.com/compare/gemma-4-e2b-it-vs-qwen3-vl-8b-instruct.md)\n- [Gemma 4 E4B IT vs InternVL3.5-GPT-OSS-20B-A4B-Preview](https://www.anchorterminal.com/compare/gemma-4-e4b-it-vs-internvl3-5-gpt-oss-20b-a4b-preview.md)\n- [Gemma 4 E4B IT vs Qwen3-VL-8B-Instruct](https://www.anchorterminal.com/compare/gemma-4-e4b-it-vs-qwen3-vl-8b-instruct.md)\n- [GLM-4.5-Air vs InternVL3.5-GPT-OSS-20B-A4B-Preview](https://www.anchorterminal.com/compare/glm-4-5-air-vs-internvl3-5-gpt-oss-20b-a4b-preview.md)\n- [GLM-4.5-Air vs Qwen3-VL-8B-Instruct](https://www.anchorterminal.com/compare/glm-4-5-air-vs-qwen3-vl-8b-instruct.md)\n- [GLM-4.7-Flash vs InternVL3.5-GPT-OSS-20B-A4B-Preview](https://www.anchorterminal.com/compare/glm-4-7-flash-vs-internvl3-5-gpt-oss-20b-a4b-preview.md)\n- [GLM-4.7-Flash vs Qwen3-VL-8B-Instruct](https://www.anchorterminal.com/compare/glm-4-7-flash-vs-qwen3-vl-8b-instruct.md)\n- [GLM-5.3-Flash vs InternVL3.5-GPT-OSS-20B-A4B-Preview](https://www.anchorterminal.com/compare/glm-5-3-flash-vs-internvl3-5-gpt-oss-20b-a4b-preview.md)\n- [GLM-5.3-Flash vs Qwen3-VL-8B-Instruct](https://www.anchorterminal.com/compare/glm-5-3-flash-vs-qwen3-vl-8b-instruct.md)\n- [GLM-5.3 vs InternVL3.5-GPT-OSS-20B-A4B-Preview](https://www.anchorterminal.com/compare/glm-5-3-vs-internvl3-5-gpt-oss-20b-a4b-preview.md)\n- [GLM-5.3 vs Qwen3-VL-8B-Instruct](https://www.anchorterminal.com/compare/glm-5-3-vs-qwen3-vl-8b-instruct.md)\n- [gpt-oss-120b vs InternVL3.5-GPT-OSS-20B-A4B-Preview](https://www.anchorterminal.com/compare/gpt-oss-120b-vs-internvl3-5-gpt-oss-20b-a4b-preview.md)\n- [gpt-oss-120b vs Qwen3-VL-8B-Instruct](https://www.anchorterminal.com/compare/gpt-oss-120b-vs-qwen3-vl-8b-instruct.md)\n- [gpt-oss-20b vs InternVL3.5-GPT-OSS-20B-A4B-Preview](https://www.anchorterminal.com/compare/gpt-oss-20b-vs-internvl3-5-gpt-oss-20b-a4b-preview.md)\n- [gpt-oss-20b vs Qwen3-VL-8B-Instruct](https://www.anchorterminal.com/compare/gpt-oss-20b-vs-qwen3-vl-8b-instruct.md)\n- [Granite 4.2 3B vs InternVL3.5-GPT-OSS-20B-A4B-Preview](https://www.anchorterminal.com/compare/granite-4-2-3b-vs-internvl3-5-gpt-oss-20b-a4b-preview.md)\n- [Granite 4.2 3B vs Qwen3-VL-8B-Instruct](https://www.anchorterminal.com/compare/granite-4-2-3b-vs-qwen3-vl-8b-instruct.md)\n- [Hy3 vs InternVL3.5-GPT-OSS-20B-A4B-Preview](https://www.anchorterminal.com/compare/hy3-vs-internvl3-5-gpt-oss-20b-a4b-preview.md)\n- [Hy3 vs Qwen3-VL-8B-Instruct](https://www.anchorterminal.com/compare/hy3-vs-qwen3-vl-8b-instruct.md)\n- [Inkling-Small vs InternVL3.5-GPT-OSS-20B-A4B-Preview](https://www.anchorterminal.com/compare/inkling-small-vs-internvl3-5-gpt-oss-20b-a4b-preview.md)\n- [Inkling-Small vs Qwen3-VL-8B-Instruct](https://www.anchorterminal.com/compare/inkling-small-vs-qwen3-vl-8b-instruct.md)\n- [Inkling vs InternVL3.5-GPT-OSS-20B-A4B-Preview](https://www.anchorterminal.com/compare/inkling-vs-internvl3-5-gpt-oss-20b-a4b-preview.md)\n- [Inkling vs Qwen3-VL-8B-Instruct](https://www.anchorterminal.com/compare/inkling-vs-qwen3-vl-8b-instruct.md)\n- [InternVL3.5-GPT-OSS-20B-A4B-Preview vs Kimi K3](https://www.anchorterminal.com/compare/internvl3-5-gpt-oss-20b-a4b-preview-vs-kimi-k3.md)\n- [InternVL3.5-GPT-OSS-20B-A4B-Preview vs 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[Nemotron 3.5 Lightning 30B A3B vs Qwen3-VL-8B-Instruct](https://www.anchorterminal.com/compare/nemotron-3-5-lightning-30b-a3b-vs-qwen3-vl-8b-instruct.md)\n- [Nemotron 3 Nano 30B A3B vs Qwen3-VL-8B-Instruct](https://www.anchorterminal.com/compare/nemotron-3-nano-30b-a3b-vs-qwen3-vl-8b-instruct.md)\n- [Nemotron 3 Nano 4B vs Qwen3-VL-8B-Instruct](https://www.anchorterminal.com/compare/nemotron-3-nano-4b-vs-qwen3-vl-8b-instruct.md)\n- [Nemotron 3 Nano Omni 30B A3B Reasoning vs Qwen3-VL-8B-Instruct](https://www.anchorterminal.com/compare/nemotron-3-nano-omni-30b-a3b-reasoning-vs-qwen3-vl-8b-instruct.md)\n- [Nemotron 3 Super 120B A12B vs Qwen3-VL-8B-Instruct](https://www.anchorterminal.com/compare/nemotron-3-super-120b-a12b-vs-qwen3-vl-8b-instruct.md)\n- [Nemotron 3 Ultra 550B A55B vs Qwen3-VL-8B-Instruct](https://www.anchorterminal.com/compare/nemotron-3-ultra-550b-a55b-vs-qwen3-vl-8b-instruct.md)\n- [occamy-1.0 vs 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