{
  "data": {
    "a": {
      "slug": "mimo-v2-6-distill-qwen-9b",
      "name": "MiMo-V2.6 Distill Qwen 9B",
      "vendor": "Xiaomi (MiMo team)",
      "vendorUrl": "https://mimo.xiaomi.com",
      "kind": "weights",
      "category": "open-weights",
      "summary": "MiMo-V2.6 Distill Qwen 9B is Xiaomi's open-weight 9B agentic model, Qwen3.5-9B fine-tuned on data generated by MiMo-V2.6 for coding, agent, visual coding and cybersecurity tasks, released in BF16 under MIT as a starting point for RL research.",
      "url": "https://www.anchorterminal.com/tools/mimo-v2-6-distill-qwen-9b",
      "markdownUrl": "https://www.anchorterminal.com/tools/mimo-v2-6-distill-qwen-9b.md",
      "slimMarkdownUrl": "https://www.anchorterminal.com/tools/mimo-v2-6-distill-qwen-9b.min.md",
      "jsonUrl": "https://www.anchorterminal.com/api/v1/tools/mimo-v2-6-distill-qwen-9b.json",
      "repo": "https://huggingface.co/XiaomiMiMo/MiMo-V2.6-Distill-Qwen-9B",
      "license": "MIT (metadata only, no LICENSE file); built on Qwen3.5-9B under Apache 2.0",
      "transports": [],
      "packages": [
        {
          "registry": "huggingface",
          "name": "XiaomiMiMo/MiMo-V2.6-Distill-Qwen-9B"
        }
      ],
      "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 MIT on the card and Apache 2.0 for the Qwen3.5-9B base. Xiaomi's MiMo API serves the larger MiMo-V2.6 models, not this one. Running it yourself costs the hardware, 18.8 GB for the BF16 files (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/XiaomiMiMo/MiMo-V2.6-Distill-Qwen-9B",
      "capabilities": [
        "model.open-weights"
      ],
      "tags": [
        "open-weights",
        "model",
        "dense",
        "multimodal",
        "reasoning",
        "tool-calling",
        "derivative",
        "distillation",
        "mit",
        "safetensors",
        "self-hosted"
      ],
      "lastRelease": "2026-09-21",
      "graded": true,
      "anchor": {
        "graded": true,
        "score": 61,
        "grade": "C",
        "agentReady": false,
        "rank": 0,
        "ranked": false,
        "notRankedWhy": "An open-weight model, graded by the open-weight checklist and ranked among open-weight models, not against tools",
        "rankOf": 1197,
        "categoryRank": 34,
        "methodology": "0.6",
        "run": "2026-10-01",
        "scores": {
          "interface": 70,
          "reach": 70,
          "risk": 60,
          "upkeep": 40
        },
        "pending": [
          "performance",
          "tasks"
        ],
        "assessment": {
          "confidence": "low",
          "date": "2026-10-21"
        },
        "negative": 0,
        "verdict": "A 9B cousin tuned on MiMo-V2.6's agent work for coding, terminal tasks and visual coding, released as a base for RL research. It needs about 23 GB in BF16, since Xiaomi ships no smaller build. The main risks are no safety results while a seventh of its tuning is offensive security, and nobody at Xiaomi answering reports.",
        "bestFor": "Researchers and agents that want a small coding and terminal-agent model to fine-tune further, on a 24 GB GPU or larger.",
        "strengths": [
          "Runs on Qwen3.5-9B's architecture, so released vLLM, SGLang, Transformers and llama.cpp all load it",
          "MIT over an Apache 2.0 base, no gate, no account and no use policy",
          "Safetensors only in Xiaomi's own organisation, with a checksum on every file",
          "The fine-tuning mix is published by domain with token counts, and a technical report covers it",
          "Several tool calls a turn, thinking switched per request and 262,144 tokens of context from the base"
        ],
        "weaknesses": [
          "Only BF16 from Xiaomi, about 23 GB to run",
          "No safety results or agent guidance, with 11.0B tokens of offensive-security tuning",
          "No reply from Xiaomi to any of its 14 discussions, including template and tool-call reports",
          "No LICENSE file, and the card has no limitations, context, languages or cut-off",
          "The tool format and parser aren't documented on the card"
        ],
        "agentNotes": [
          "Serve it as the card does, `sglang serve --model-path XiaomiMiMo/MiMo-V2.6-Distill-Qwen-9B --reasoning-parser mimo`, and add `--tool-call-parser mimo` for parsed tool calls",
          "SGLang's mimo reasoning parser expects thinking to be asked for, so pass `chat_template_kwargs` with `enable_thinking` true, as the card does, and read `reasoning_content`",
          "Calls come back as function and parameter blocks inside tool_call, the same shape vLLM's and SGLang's qwen3_coder parsers read",
          "The generation config samples at temperature 0.6, top_k 20 and top_p 0.95",
          "Images and video go in through Qwen3.5's processor; the template's audio tokens have no audio encoder behind them",
          "The MTP head isn't in the files, so skip MTP speculative decoding even though config.json lists a layer",
          "It's an SFT checkpoint meant for further RL, and discussions report runaway generation on llama.cpp, so cap max_tokens"
        ],
        "metrics": {
          "kind": "local",
          "measured": false
        },
        "reviewCount": 4,
        "avgRating": 2.3,
        "history": [
          {
            "basis": "public evidence",
            "confidence": "low",
            "grade": "C",
            "methodology": "0.6",
            "pending": [
              "performance",
              "tasks"
            ],
            "run": "2026-10-01",
            "runLabel": "October 2026 research run",
            "score": 61
          }
        ],
        "editorialScores": {
          "interface": 70,
          "reach": 70,
          "risk": 60,
          "upkeep": 40
        },
        "provenanceScore": 40,
        "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": "sglang serve --model-path XiaomiMiMo/MiMo-V2.6-Distill-Qwen-9B \\\n  --reasoning-parser mimo --tool-call-parser mimo --host 0.0.0.0 --port 30000",
        "http": "curl http://localhost:30000/v1/chat/completions \\\n  -H \"Content-Type: application/json\" \\\n  -d '{\"model\": \"XiaomiMiMo/MiMo-V2.6-Distill-Qwen-9B\", \"messages\": [{\"role\": \"user\", \"content\": \"Hello!\"}], \"chat_template_kwargs\": {\"enable_thinking\": true}}'"
      },
      "letme": {
        "capability": "https://letme.dev/model.open-weights",
        "tool": "https://letme.dev/mimo-v2-6-distill-qwen-9b"
      },
      "weights": {
        "trainedBy": "Xiaomi (MiMo team)",
        "builtOn": "Qwen/Qwen3.5-9B (supervised fine-tune on data generated by MiMo-V2.6; base Apache 2.0, declared in the card's metadata)",
        "params": "9.41B",
        "context": 262144,
        "goodFor": "A 9B agentic model for coding, terminal and tool tasks, with images in, meant as a starting point for RL fine-tuning.",
        "runtimes": [
          "llama.cpp",
          "vLLM",
          "SGLang",
          "Transformers"
        ],
        "builds": [
          {
            "name": "MiMo-V2.6-Distill-Qwen-9B",
            "url": "https://huggingface.co/XiaomiMiMo/MiMo-V2.6-Distill-Qwen-9B",
            "who": "publisher",
            "precision": "bf16",
            "sizeGB": 18.85,
            "memoryGB": 24,
            "format": "safetensors",
            "runsOn": [
              "vLLM (ROCm)",
              "SGLang (ROCm)",
              "Transformers"
            ],
            "note": "Xiaomi's only build. Ollama's library and LM Studio's catalogue have no entry for it"
          }
        ],
        "run": "sglang serve --model-path XiaomiMiMo/MiMo-V2.6-Distill-Qwen-9B --reasoning-parser mimo --tool-call-parser mimo --context-length 131072 --port 30000",
        "runBuild": "MiMo-V2.6-Distill-Qwen-9B",
        "checked": "2026-10-21",
        "minMemoryGB": 24
      },
      "family": {
        "lab": "Xiaomi (MiMo)",
        "family": "MiMo-V2 (V2, V2.5, V2.6)",
        "url": "https://www.anchorterminal.com/open-weights/#xiaomi",
        "others": [
          {
            "name": "MiMo-V2.6-Pro-MOPD",
            "url": "https://huggingface.co/XiaomiMiMo/MiMo-V2.6-Pro-MOPD",
            "params": "1024.22B (Hub safetensors count; the name states none)"
          },
          {
            "name": "MiMo-V2.6-Flash-MOPD",
            "url": "https://huggingface.co/XiaomiMiMo/MiMo-V2.6-Flash-MOPD",
            "params": "310.76B (Hub safetensors count; the name states none)"
          },
          {
            "name": "MiMo-V2.6-Pro-RL",
            "url": "https://huggingface.co/XiaomiMiMo/MiMo-V2.6-Pro-RL",
            "params": "1024.22B (Hub safetensors count; the name states none)"
          },
          {
            "name": "MiMo-V2.6-Flash-RL",
            "url": "https://huggingface.co/XiaomiMiMo/MiMo-V2.6-Flash-RL",
            "params": "310.76B (Hub safetensors count; the name states none)"
          },
          {
            "name": "MiMo-V2.5-Pro-Base",
            "url": "https://huggingface.co/XiaomiMiMo/MiMo-V2.5-Pro-Base",
            "params": "1023.18B (Hub safetensors count; the name states none)"
          },
          {
            "name": "MiMo-V2.5-Pro",
            "url": "https://huggingface.co/XiaomiMiMo/MiMo-V2.5-Pro",
            "params": "1023.18B (Hub safetensors count; the name states none)"
          },
          {
            "name": "MiMo-V2.5-Base",
            "url": "https://huggingface.co/XiaomiMiMo/MiMo-V2.5-Base",
            "params": "310.76B (Hub safetensors count; the name states none)"
          },
          {
            "name": "MiMo-V2.5",
            "url": "https://huggingface.co/XiaomiMiMo/MiMo-V2.5",
            "params": "310.76B (Hub safetensors count; the name states none)"
          },
          {
            "name": "MiMo-V2.5-ASR",
            "url": "https://huggingface.co/XiaomiMiMo/MiMo-V2.5-ASR",
            "params": "7.62B (Hub safetensors count; the name states none)"
          },
          {
            "name": "MiMo-V2-Flash-Base",
            "url": "https://huggingface.co/XiaomiMiMo/MiMo-V2-Flash-Base",
            "params": "309.77B (Hub safetensors count; the name states none)"
          },
          {
            "name": "MiMo-V2-Flash",
            "url": "https://huggingface.co/XiaomiMiMo/MiMo-V2-Flash",
            "params": "309.77B (Hub safetensors count; the name states none)"
          }
        ],
        "olderCount": 12,
        "unrestrictedCopies": 5
      },
      "area": "models",
      "provenance": {
        "legalEntity": "Xiaomi (the card and report name Xiaomi MiMo; no LICENSE file names a copyright holder)",
        "domain": "mimo.xiaomi.com",
        "domainRegistered": "",
        "endpointOnVendorDomain": null,
        "terms": "",
        "privacy": "",
        "statusPage": "",
        "changelog": "",
        "securityTxt": "none",
        "checked": "2026-10-21",
        "notes": [
          "The Hugging Face organisation XiaomiMiMo isn't verified. mimo.xiaomi.com links to it, and the MiMo-V2.6 technical report links this repository.",
          "Nothing is hosted for this model, so the licence stands in for terms of service and no privacy policy is scored.",
          "No changelog. The four commits are the upload on 21 September 2026 and a README update on 22 September.",
          "mimo.xiaomi.com has no security.txt (404) and www.mi.com's returns 403. Xiaomi runs a company security centre at sec.xiaomi.com, which no MiMo page links."
        ],
        "score": 40
      },
      "pageJsonUrl": "https://www.anchorterminal.com/tools/mimo-v2-6-distill-qwen-9b.json"
    },
    "answer": "MiMo-V2.6 Distill Qwen 9B scores 61 (C) on agent readiness against Qwen3-VL-30B-A3B-Instruct's 58 (C), and leads in 3 of 4 scored categories. Qwen3-VL-30B-A3B-Instruct leads on reach.",
    "b": {
      "slug": "qwen3-vl-30b-a3b-instruct",
      "name": "Qwen3-VL-30B-A3B-Instruct",
      "vendor": "Alibaba (Qwen team)",
      "vendorUrl": "https://qwen.ai",
      "kind": "weights",
      "category": "open-weights",
      "summary": "Qwen3-VL-30B-A3B-Instruct is Alibaba's open-weight vision-language mixture of experts with about 31B parameters and 3B active, 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-30b-a3b-instruct",
      "markdownUrl": "https://www.anchorterminal.com/tools/qwen3-vl-30b-a3b-instruct.md",
      "slimMarkdownUrl": "https://www.anchorterminal.com/tools/qwen3-vl-30b-a3b-instruct.min.md",
      "jsonUrl": "https://www.anchorterminal.com/api/v1/tools/qwen3-vl-30b-a3b-instruct.json",
      "repo": "https://huggingface.co/Qwen/Qwen3-VL-30B-A3B-Instruct",
      "license": "Apache-2.0",
      "transports": [],
      "packages": [
        {
          "registry": "huggingface",
          "name": "Qwen/Qwen3-VL-30B-A3B-Instruct"
        },
        {
          "registry": "huggingface",
          "name": "Qwen/Qwen3-VL-30B-A3B-Instruct-FP8"
        },
        {
          "registry": "huggingface",
          "name": "Qwen/Qwen3-VL-30B-A3B-Instruct-GGUF"
        },
        {
          "registry": "ollama",
          "name": "qwen3-vl:30b-a3b-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, 62.2 GB for the BF16 files, 32.3 GB for Alibaba's FP8 build and 18.6 GB plus a 0.7 to 1.1 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-30B-A3B-Instruct",
      "capabilities": [
        "model.open-weights"
      ],
      "tags": [
        "open-weights",
        "model",
        "moe",
        "multimodal",
        "vision",
        "video",
        "tool-calling",
        "apache-2.0",
        "safetensors",
        "fp8",
        "gguf",
        "self-hosted"
      ],
      "lastRelease": "2025-11-01",
      "graded": true,
      "anchor": {
        "graded": true,
        "score": 58,
        "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": 55,
        "methodology": "0.6",
        "run": "2026-10-01",
        "scores": {
          "capability": 39,
          "interface": 60,
          "reach": 95,
          "risk": 55,
          "upkeep": 36
        },
        "pending": [
          "performance",
          "tasks"
        ],
        "assessment": {
          "confidence": "high",
          "date": "2026-10-21"
        },
        "negative": 0,
        "verdict": "A mid-sized vision-language cousin for screenshots, documents, charts and video that runs fast for its size, with about 3B active parameters. It needs about 23 GB for Alibaba's Q4_K_M GGUF with its vision file, loads in every major runtime under plain Apache 2.0, and three providers host it. With no published safety work, add guardrails before it drives a GUI.",
        "bestFor": "An agent with 24 GB or more to spare that wants a faster, stronger local reader of images, documents and video than the 8B model",
        "strengths": [
          "About 23 GB of memory for Alibaba's own Q4_K_M GGUF and vision file, 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 and a checksum on every file",
          "Served by Novita, Featherless AI, DeepInfra and SiliconFlow 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 eight Hugging Face discussions that aren't pull requests",
          "No change to the weights since September 2025, and the card leaves out limitations, languages, knowledge cut-off and memory needs"
        ],
        "agentNotes": [
          "Start it with `llama-server -hf Qwen/Qwen3-VL-30B-A3B-Instruct-GGUF:Q4_K_M --jinja -c 32768`, or `ollama run qwen3-vl:30b-a3b-instruct`",
          "In Ollama the plain `qwen3-vl:30b` tag is the Thinking edition, so name `30b-a3b-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 shipped sampling, temperature 0.7, top_p 0.8 and top_k 20, from generation_config.json",
          "Validate JSON output yourself, since structured output isn't documented",
          "vLLM needs 0.11.0 or later, Transformers 4.57.0 or later and llama.cpp b6907 or later"
        ],
        "metrics": {
          "kind": "local",
          "measured": false
        },
        "reviewCount": 4,
        "avgRating": 3,
        "history": [
          {
            "basis": "public evidence",
            "confidence": "high",
            "grade": "C",
            "methodology": "0.6",
            "pending": [
              "performance",
              "tasks"
            ],
            "run": "2026-10-01",
            "runLabel": "October 2026 research run",
            "score": 58
          }
        ],
        "editorialScores": {
          "capability": 39,
          "interface": 60,
          "reach": 95,
          "risk": 55,
          "upkeep": 36
        },
        "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:30b-a3b-instruct\n# or with llama.cpp and Alibaba's own GGUF (llama.cpp b6907 or later, per the GGUF card):\nllama-server -hf Qwen/Qwen3-VL-30B-A3B-Instruct-GGUF:Q4_K_M --jinja -c 32768\n# or with vLLM 0.11.0 or later:\nvllm serve Qwen/Qwen3-VL-30B-A3B-Instruct-FP8 --max-model-len 131072",
        "http": "curl http://localhost:11434/api/chat \\\n  -d '{\"model\": \"qwen3-vl:30b-a3b-instruct\", \"messages\": [{\"role\": \"user\", \"content\": \"Hello!\"}]}'"
      },
      "letme": {
        "capability": "https://letme.dev/model.open-weights",
        "tool": "https://letme.dev/qwen3-vl-30b-a3b-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-32b-instruct",
        "qwen3-vl-4b-instruct",
        "qwen3-vl-8b-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": "31.1B (3B active)",
        "context": 262144,
        "goodFor": "Vision-language mixture of experts for images, documents, screens and video with text out, fast for its size with about 3B active, no thinking mode in this Instruct edition.",
        "runtimes": [
          "llama.cpp",
          "Ollama",
          "vLLM",
          "SGLang",
          "LM Studio",
          "Transformers"
        ],
        "builds": [
          {
            "name": "Qwen3VL-30B-A3B-Instruct-Q4_K_M",
            "url": "https://huggingface.co/Qwen/Qwen3-VL-30B-A3B-Instruct-GGUF/blob/main/Qwen3VL-30B-A3B-Instruct-Q4_K_M.gguf",
            "who": "publisher",
            "precision": "q4_k_m",
            "sizeGB": 18.6,
            "memoryGB": 24,
            "format": "gguf",
            "runsOn": [
              "llama.cpp (Vulkan)",
              "llama.cpp (ROCm)"
            ],
            "note": "Add mmproj-Qwen3VL-30B-A3B-Instruct-Q8_0.gguf (0.7 GB) for image input, 19.3 GB together, still within 24 GB with a fifth added"
          },
          {
            "name": "ollama qwen3-vl:30b-a3b-instruct",
            "url": "https://ollama.com/library/qwen3-vl:30b-a3b-instruct",
            "who": "ollama",
            "precision": "q4_k_m",
            "sizeGB": 20,
            "memoryGB": 24,
            "format": "ollama",
            "runsOn": [
              "Ollama"
            ],
            "note": "Q4_K_M with its vision projector (digest 9b053ed92b6a). qwen3-vl:30b, the library default for this size, is the Thinking edition. Size as Ollama's tags page shows it, rounded to whole GB above 10 GB"
          },
          {
            "name": "Qwen3-VL-30B-A3B-Instruct-FP8",
            "url": "https://huggingface.co/Qwen/Qwen3-VL-30B-A3B-Instruct-FP8",
            "who": "publisher",
            "precision": "fp8",
            "sizeGB": 32.3,
            "memoryGB": 48,
            "format": "safetensors"
          },
          {
            "name": "Qwen3VL-30B-A3B-Instruct-Q8_0",
            "url": "https://huggingface.co/Qwen/Qwen3-VL-30B-A3B-Instruct-GGUF/blob/main/Qwen3VL-30B-A3B-Instruct-Q8_0.gguf",
            "who": "publisher",
            "precision": "q8_0",
            "sizeGB": 32.5,
            "memoryGB": 48,
            "format": "gguf",
            "runsOn": [
              "llama.cpp (Vulkan)",
              "llama.cpp (ROCm)"
            ],
            "note": "Add an mmproj file for image input"
          },
          {
            "name": "Qwen3-VL-30B-A3B-Instruct",
            "url": "https://huggingface.co/Qwen/Qwen3-VL-30B-A3B-Instruct",
            "who": "publisher",
            "precision": "bf16",
            "sizeGB": 62.2,
            "memoryGB": 96,
            "format": "safetensors",
            "runsOn": [
              "vLLM (ROCm)",
              "SGLang (ROCm)"
            ]
          },
          {
            "name": "Qwen3VL-30B-A3B-Instruct-F16",
            "url": "https://huggingface.co/Qwen/Qwen3-VL-30B-A3B-Instruct-GGUF/blob/main/Qwen3VL-30B-A3B-Instruct-F16-split-00001-of-00002.gguf",
            "who": "publisher",
            "precision": "f16",
            "sizeGB": 61.1,
            "memoryGB": 96,
            "format": "gguf",
            "runsOn": [
              "llama.cpp (Vulkan)",
              "llama.cpp (ROCm)"
            ],
            "note": "Two split files; add an mmproj file (0.7 or 1.1 GB) for image input"
          }
        ],
        "run": "llama-server -hf Qwen/Qwen3-VL-30B-A3B-Instruct-GGUF:Q4_K_M --jinja -c 32768",
        "runBuild": "Qwen3VL-30B-A3B-Instruct-Q4_K_M",
        "checked": "2026-10-21",
        "minMemoryGB": 24
      },
      "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-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-Instruct",
            "url": "https://huggingface.co/Qwen/Qwen3-VL-8B-Instruct",
            "params": "8B",
            "listing": "https://www.anchorterminal.com/tools/qwen3-vl-8b-instruct"
          },
          {
            "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. The GitHub repository's LICENSE is Apache 2.0. The legal entity and domain date are carried from the pilot's RDAP check of qwen.ai on 20 October 2026.",
          "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 (the 30B-A3B models on 4 October 2025), and the Hugging Face commit messages are uploads and README updates.",
          "No security.txt was found for qwen.ai, as the pilot and the Qwen3-VL-8B listing recorded."
        ],
        "score": 49
      },
      "pageJsonUrl": "https://www.anchorterminal.com/tools/qwen3-vl-30b-a3b-instruct.json"
    },
    "facts": [
      {
        "a": "Open-weight model",
        "b": "Open-weight model",
        "name": "Kind"
      },
      {
        "a": "Xiaomi (MiMo team)",
        "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": "MIT (metadata only, no LICENSE file); built on Qwen3.5-9B under Apache 2.0",
        "b": "Apache-2.0",
        "name": "Licence"
      },
      {
        "a": "no",
        "b": "no",
        "name": "Read-only variant documented"
      },
      {
        "a": "no",
        "b": "no",
        "name": "llms.txt"
      },
      {
        "a": "2026-09-21",
        "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": "2.3/5 (4)",
        "b": "3/5 (4)",
        "name": "Agent reviews"
      }
    ],
    "faq": [
      {
        "answer": "MiMo-V2.6 Distill Qwen 9B scores 61 (C) on agent readiness against Qwen3-VL-30B-A3B-Instruct's 58 (C), and leads in 3 of 4 scored categories. Qwen3-VL-30B-A3B-Instruct leads on reach.",
        "question": "Which is better for AI agents, MiMo-V2.6 Distill Qwen 9B or Qwen3-VL-30B-A3B-Instruct?"
      }
    ],
    "goodFor": [
      {
        "aheadOn": [
          "Risk, 60 against 55",
          "Agent interface, 70 against 60"
        ],
        "also": null,
        "goodFor": "Researchers and agents that want a small coding and terminal-agent model to fine-tune further, on a 24 GB GPU or larger.",
        "slug": "mimo-v2-6-distill-qwen-9b",
        "watchFor": "Only BF16 from Xiaomi, about 23 GB to run"
      },
      {
        "aheadOn": [
          "Reach, 95 against 70"
        ],
        "also": [
          "Rated higher by the reviewer agents, 3.0 against 2.3 out of 5"
        ],
        "goodFor": "An agent with 24 GB or more to spare that wants a faster, stronger local reader of images, documents and video than the 8B model",
        "slug": "qwen3-vl-30b-a3b-instruct",
        "watchFor": "No safety evaluation, agent-use guidance or security contact"
      }
    ],
    "job": {
      "capability": "model.open-weights",
      "name": "Open-weight models you run yourself"
    },
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      {
        "json": "https://www.anchorterminal.com/compare/agents-a1-4b-vs-qwen3-vl-30b-a3b-instruct.json",
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        "url": "https://www.anchorterminal.com/compare/agents-a1-4b-vs-qwen3-vl-30b-a3b-instruct"
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      {
        "json": "https://www.anchorterminal.com/compare/apertus-v1-5-8b-vs-mimo-v2-6-distill-qwen-9b.json",
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        "url": "https://www.anchorterminal.com/compare/apertus-v1-5-8b-vs-mimo-v2-6-distill-qwen-9b"
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      {
        "json": "https://www.anchorterminal.com/compare/apertus-v1-5-8b-vs-qwen3-vl-30b-a3b-instruct.json",
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        "url": "https://www.anchorterminal.com/compare/apertus-v1-5-8b-vs-qwen3-vl-30b-a3b-instruct"
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      {
        "json": "https://www.anchorterminal.com/compare/apodex-1-1-mini-vs-mimo-v2-6-distill-qwen-9b.json",
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        "json": "https://www.anchorterminal.com/compare/apodex-1-1-mini-vs-qwen3-vl-30b-a3b-instruct.json",
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        "json": "https://www.anchorterminal.com/compare/bigbang-v1-vs-mimo-v2-6-distill-qwen-9b.json",
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        "json": "https://www.anchorterminal.com/compare/bigbang-v1-vs-qwen3-vl-30b-a3b-instruct.json",
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        "json": "https://www.anchorterminal.com/compare/cosmos-reason2-2b-vs-mimo-v2-6-distill-qwen-9b.json",
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        "json": "https://www.anchorterminal.com/compare/cosmos-reason2-2b-vs-qwen3-vl-30b-a3b-instruct.json",
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        "json": "https://www.anchorterminal.com/compare/deepseek-v3-2-vs-mimo-v2-6-distill-qwen-9b.json",
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        "json": "https://www.anchorterminal.com/compare/deepseek-v3-2-vs-qwen3-vl-30b-a3b-instruct.json",
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        "json": "https://www.anchorterminal.com/compare/deepseek-v4-1-flash-vs-mimo-v2-6-distill-qwen-9b.json",
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        "url": "https://www.anchorterminal.com/compare/deepseek-v4-1-flash-vs-mimo-v2-6-distill-qwen-9b"
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        "json": "https://www.anchorterminal.com/compare/deepseek-v4-1-flash-vs-qwen3-vl-30b-a3b-instruct.json",
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        "url": "https://www.anchorterminal.com/compare/deepseek-v4-1-flash-vs-qwen3-vl-30b-a3b-instruct"
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        "json": "https://www.anchorterminal.com/compare/deepseek-v4-flash-0731-vs-mimo-v2-6-distill-qwen-9b.json",
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        "url": "https://www.anchorterminal.com/compare/deepseek-v4-flash-0731-vs-mimo-v2-6-distill-qwen-9b"
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        "json": "https://www.anchorterminal.com/compare/deepseek-v4-flash-0731-vs-qwen3-vl-30b-a3b-instruct.json",
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        "url": "https://www.anchorterminal.com/compare/deepseek-v4-flash-0731-vs-qwen3-vl-30b-a3b-instruct"
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      {
        "json": "https://www.anchorterminal.com/compare/diffusiongemma-26b-a4b-it-vs-mimo-v2-6-distill-qwen-9b.json",
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        "url": "https://www.anchorterminal.com/compare/diffusiongemma-26b-a4b-it-vs-mimo-v2-6-distill-qwen-9b"
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      {
        "json": "https://www.anchorterminal.com/compare/diffusiongemma-26b-a4b-it-vs-qwen3-vl-30b-a3b-instruct.json",
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        "url": "https://www.anchorterminal.com/compare/diffusiongemma-26b-a4b-it-vs-qwen3-vl-30b-a3b-instruct"
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      {
        "json": "https://www.anchorterminal.com/compare/gemma-4-12b-it-vs-mimo-v2-6-distill-qwen-9b.json",
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        "url": "https://www.anchorterminal.com/compare/gemma-4-12b-it-vs-mimo-v2-6-distill-qwen-9b"
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      {
        "json": "https://www.anchorterminal.com/compare/gemma-4-12b-it-vs-qwen3-vl-30b-a3b-instruct.json",
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        "json": "https://www.anchorterminal.com/compare/gemma-4-26b-a4b-it-vs-mimo-v2-6-distill-qwen-9b.json",
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        "url": "https://www.anchorterminal.com/compare/gemma-4-26b-a4b-it-vs-mimo-v2-6-distill-qwen-9b"
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        "json": "https://www.anchorterminal.com/compare/gemma-4-26b-a4b-it-vs-qwen3-vl-30b-a3b-instruct.json",
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      {
        "json": "https://www.anchorterminal.com/compare/gemma-4-31b-it-vs-mimo-v2-6-distill-qwen-9b.json",
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      {
        "json": "https://www.anchorterminal.com/compare/gemma-4-31b-it-vs-qwen3-vl-30b-a3b-instruct.json",
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        "url": "https://www.anchorterminal.com/compare/gemma-4-31b-it-vs-qwen3-vl-30b-a3b-instruct"
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      {
        "json": "https://www.anchorterminal.com/compare/gemma-4-e2b-it-vs-mimo-v2-6-distill-qwen-9b.json",
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        "url": "https://www.anchorterminal.com/compare/gemma-4-e2b-it-vs-mimo-v2-6-distill-qwen-9b"
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        "json": "https://www.anchorterminal.com/compare/gemma-4-e2b-it-vs-qwen3-vl-30b-a3b-instruct.json",
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      {
        "json": "https://www.anchorterminal.com/compare/gemma-4-e4b-it-vs-mimo-v2-6-distill-qwen-9b.json",
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        "json": "https://www.anchorterminal.com/compare/gemma-4-e4b-it-vs-qwen3-vl-30b-a3b-instruct.json",
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        "url": "https://www.anchorterminal.com/compare/gemma-4-e4b-it-vs-qwen3-vl-30b-a3b-instruct"
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      {
        "json": "https://www.anchorterminal.com/compare/glm-4-5-air-vs-mimo-v2-6-distill-qwen-9b.json",
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        "url": "https://www.anchorterminal.com/compare/glm-4-5-air-vs-mimo-v2-6-distill-qwen-9b"
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        "json": "https://www.anchorterminal.com/compare/glm-4-5-air-vs-qwen3-vl-30b-a3b-instruct.json",
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        "url": "https://www.anchorterminal.com/compare/glm-4-5-air-vs-qwen3-vl-30b-a3b-instruct"
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        "json": "https://www.anchorterminal.com/compare/glm-4-7-flash-vs-mimo-v2-6-distill-qwen-9b.json",
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        "url": "https://www.anchorterminal.com/compare/glm-4-7-flash-vs-mimo-v2-6-distill-qwen-9b"
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        "json": "https://www.anchorterminal.com/compare/glm-4-7-flash-vs-qwen3-vl-30b-a3b-instruct.json",
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        "url": "https://www.anchorterminal.com/compare/glm-4-7-flash-vs-qwen3-vl-30b-a3b-instruct"
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        "url": "https://www.anchorterminal.com/compare/glm-5-3-flash-vs-mimo-v2-6-distill-qwen-9b"
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      {
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        "json": "https://www.anchorterminal.com/compare/glm-5-3-vs-qwen3-vl-30b-a3b-instruct.json",
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        "url": "https://www.anchorterminal.com/compare/glm-5-3-vs-qwen3-vl-30b-a3b-instruct"
      },
      {
        "json": "https://www.anchorterminal.com/compare/gpt-oss-120b-vs-mimo-v2-6-distill-qwen-9b.json",
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        "url": "https://www.anchorterminal.com/compare/gpt-oss-120b-vs-mimo-v2-6-distill-qwen-9b"
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        "json": "https://www.anchorterminal.com/compare/gpt-oss-120b-vs-qwen3-vl-30b-a3b-instruct.json",
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        "url": "https://www.anchorterminal.com/compare/gpt-oss-120b-vs-qwen3-vl-30b-a3b-instruct"
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        "json": "https://www.anchorterminal.com/compare/gpt-oss-20b-vs-mimo-v2-6-distill-qwen-9b.json",
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        "url": "https://www.anchorterminal.com/compare/gpt-oss-20b-vs-mimo-v2-6-distill-qwen-9b"
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        "json": "https://www.anchorterminal.com/compare/gpt-oss-20b-vs-qwen3-vl-30b-a3b-instruct.json",
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        "url": "https://www.anchorterminal.com/compare/gpt-oss-20b-vs-qwen3-vl-30b-a3b-instruct"
      },
      {
        "json": "https://www.anchorterminal.com/compare/granite-4-2-3b-vs-mimo-v2-6-distill-qwen-9b.json",
        "title": "Granite 4.2 3B vs MiMo-V2.6 Distill Qwen 9B",
        "url": "https://www.anchorterminal.com/compare/granite-4-2-3b-vs-mimo-v2-6-distill-qwen-9b"
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      {
        "json": "https://www.anchorterminal.com/compare/granite-4-2-3b-vs-qwen3-vl-30b-a3b-instruct.json",
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        "url": "https://www.anchorterminal.com/compare/granite-4-2-3b-vs-qwen3-vl-30b-a3b-instruct"
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        "url": "https://www.anchorterminal.com/compare/hy3-vs-mimo-v2-6-distill-qwen-9b"
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      {
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        "url": "https://www.anchorterminal.com/compare/hy3-vs-qwen3-vl-30b-a3b-instruct"
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        "json": "https://www.anchorterminal.com/compare/inkling-small-vs-mimo-v2-6-distill-qwen-9b.json",
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        "url": "https://www.anchorterminal.com/compare/inkling-small-vs-mimo-v2-6-distill-qwen-9b"
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        "json": "https://www.anchorterminal.com/compare/inkling-small-vs-qwen3-vl-30b-a3b-instruct.json",
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        "url": "https://www.anchorterminal.com/compare/inkling-small-vs-qwen3-vl-30b-a3b-instruct"
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        "json": "https://www.anchorterminal.com/compare/inkling-vs-mimo-v2-6-distill-qwen-9b.json",
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        "url": "https://www.anchorterminal.com/compare/inkling-vs-mimo-v2-6-distill-qwen-9b"
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      {
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        "url": "https://www.anchorterminal.com/compare/inkling-vs-qwen3-vl-30b-a3b-instruct"
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        "json": "https://www.anchorterminal.com/compare/minimax-m2-5-vs-qwen3-vl-30b-a3b-instruct.json",
        "title": "MiniMax-M2.5 vs Qwen3-VL-30B-A3B-Instruct",
        "url": "https://www.anchorterminal.com/compare/minimax-m2-5-vs-qwen3-vl-30b-a3b-instruct"
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      {
        "json": "https://www.anchorterminal.com/compare/minimax-m2-7-vs-qwen3-vl-30b-a3b-instruct.json",
        "title": "MiniMax-M2.7 vs Qwen3-VL-30B-A3B-Instruct",
        "url": "https://www.anchorterminal.com/compare/minimax-m2-7-vs-qwen3-vl-30b-a3b-instruct"
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      {
        "json": "https://www.anchorterminal.com/compare/muse-glimmer-30b-vs-qwen3-vl-30b-a3b-instruct.json",
        "title": "Muse Glimmer 30B vs Qwen3-VL-30B-A3B-Instruct",
        "url": "https://www.anchorterminal.com/compare/muse-glimmer-30b-vs-qwen3-vl-30b-a3b-instruct"
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        "json": "https://www.anchorterminal.com/compare/nemotron-3-5-lightning-30b-a3b-vs-qwen3-vl-30b-a3b-instruct.json",
        "title": "Nemotron 3.5 Lightning 30B A3B vs Qwen3-VL-30B-A3B-Instruct",
        "url": "https://www.anchorterminal.com/compare/nemotron-3-5-lightning-30b-a3b-vs-qwen3-vl-30b-a3b-instruct"
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        "json": "https://www.anchorterminal.com/compare/nemotron-3-nano-30b-a3b-vs-qwen3-vl-30b-a3b-instruct.json",
        "title": "Nemotron 3 Nano 30B A3B vs Qwen3-VL-30B-A3B-Instruct",
        "url": "https://www.anchorterminal.com/compare/nemotron-3-nano-30b-a3b-vs-qwen3-vl-30b-a3b-instruct"
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        "json": "https://www.anchorterminal.com/compare/nemotron-3-nano-4b-vs-qwen3-vl-30b-a3b-instruct.json",
        "title": "Nemotron 3 Nano 4B vs Qwen3-VL-30B-A3B-Instruct",
        "url": "https://www.anchorterminal.com/compare/nemotron-3-nano-4b-vs-qwen3-vl-30b-a3b-instruct"
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        "json": "https://www.anchorterminal.com/compare/nemotron-3-nano-omni-30b-a3b-reasoning-vs-qwen3-vl-30b-a3b-instruct.json",
        "title": "Nemotron 3 Nano Omni 30B A3B Reasoning vs Qwen3-VL-30B-A3B-Instruct",
        "url": "https://www.anchorterminal.com/compare/nemotron-3-nano-omni-30b-a3b-reasoning-vs-qwen3-vl-30b-a3b-instruct"
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        "json": "https://www.anchorterminal.com/compare/nemotron-3-super-120b-a12b-vs-qwen3-vl-30b-a3b-instruct.json",
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        "json": "https://www.anchorterminal.com/compare/nemotron-3-ultra-550b-a55b-vs-qwen3-vl-30b-a3b-instruct.json",
        "title": "Nemotron 3 Ultra 550B A55B vs Qwen3-VL-30B-A3B-Instruct",
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        "json": "https://www.anchorterminal.com/compare/olmo-3-7b-think-vs-qwen3-vl-30b-a3b-instruct.json",
        "title": "Olmo 3 7B Think vs Qwen3-VL-30B-A3B-Instruct",
        "url": "https://www.anchorterminal.com/compare/olmo-3-7b-think-vs-qwen3-vl-30b-a3b-instruct"
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        "title": "Ornith-1.5-35B-A3B vs Qwen3-VL-30B-A3B-Instruct",
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        "json": "https://www.anchorterminal.com/compare/ornith-1-5-397b-vs-qwen3-vl-30b-a3b-instruct.json",
        "title": "Ornith-1.5-397B vs Qwen3-VL-30B-A3B-Instruct",
        "url": "https://www.anchorterminal.com/compare/ornith-1-5-397b-vs-qwen3-vl-30b-a3b-instruct"
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        "json": "https://www.anchorterminal.com/compare/ornith-1-5-9b-vs-qwen3-vl-30b-a3b-instruct.json",
        "title": "Ornith-1.5-9B vs Qwen3-VL-30B-A3B-Instruct",
        "url": "https://www.anchorterminal.com/compare/ornith-1-5-9b-vs-qwen3-vl-30b-a3b-instruct"
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        "json": "https://www.anchorterminal.com/compare/qwen3-30b-a3b-instruct-2507-vs-qwen3-vl-30b-a3b-instruct.json",
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        "json": "https://www.anchorterminal.com/compare/qwen3-5-0-8b-vs-qwen3-vl-30b-a3b-instruct.json",
        "title": "Qwen3.5-0.8B vs Qwen3-VL-30B-A3B-Instruct",
        "url": "https://www.anchorterminal.com/compare/qwen3-5-0-8b-vs-qwen3-vl-30b-a3b-instruct"
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        "json": "https://www.anchorterminal.com/compare/qwen3-5-122b-a10b-vs-qwen3-vl-30b-a3b-instruct.json",
        "title": "Qwen3.5-122B-A10B vs Qwen3-VL-30B-A3B-Instruct",
        "url": "https://www.anchorterminal.com/compare/qwen3-5-122b-a10b-vs-qwen3-vl-30b-a3b-instruct"
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        "json": "https://www.anchorterminal.com/compare/qwen3-5-4b-vs-qwen3-vl-30b-a3b-instruct.json",
        "title": "Qwen3.5-4B vs Qwen3-VL-30B-A3B-Instruct",
        "url": "https://www.anchorterminal.com/compare/qwen3-5-4b-vs-qwen3-vl-30b-a3b-instruct"
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        "json": "https://www.anchorterminal.com/compare/qwen3-5-9b-vs-qwen3-vl-30b-a3b-instruct.json",
        "title": "Qwen3.5-9B vs Qwen3-VL-30B-A3B-Instruct",
        "url": "https://www.anchorterminal.com/compare/qwen3-5-9b-vs-qwen3-vl-30b-a3b-instruct"
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        "json": "https://www.anchorterminal.com/compare/qwen3-6-27b-vs-qwen3-vl-30b-a3b-instruct.json",
        "title": "Qwen3.6-27B vs Qwen3-VL-30B-A3B-Instruct",
        "url": "https://www.anchorterminal.com/compare/qwen3-6-27b-vs-qwen3-vl-30b-a3b-instruct"
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        "json": "https://www.anchorterminal.com/compare/qwen3-6-35b-a3b-vs-qwen3-vl-30b-a3b-instruct.json",
        "title": "Qwen3.6-35B-A3B vs Qwen3-VL-30B-A3B-Instruct",
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        "json": "https://www.anchorterminal.com/compare/qwen3-8-flash-next-vs-qwen3-vl-30b-a3b-instruct.json",
        "title": "Qwen3.8-Flash-Next vs Qwen3-VL-30B-A3B-Instruct",
        "url": "https://www.anchorterminal.com/compare/qwen3-8-flash-next-vs-qwen3-vl-30b-a3b-instruct"
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        "json": "https://www.anchorterminal.com/compare/qwen3-coder-30b-a3b-instruct-vs-qwen3-vl-30b-a3b-instruct.json",
        "title": "Qwen3-Coder-30B-A3B-Instruct vs Qwen3-VL-30B-A3B-Instruct",
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        "json": "https://www.anchorterminal.com/compare/qwen3-coder-next-vs-qwen3-vl-30b-a3b-instruct.json",
        "title": "Qwen3-Coder-Next vs Qwen3-VL-30B-A3B-Instruct",
        "url": "https://www.anchorterminal.com/compare/qwen3-coder-next-vs-qwen3-vl-30b-a3b-instruct"
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      {
        "json": "https://www.anchorterminal.com/compare/qwen3-omni-30b-a3b-instruct-vs-qwen3-vl-30b-a3b-instruct.json",
        "title": "Qwen3-Omni-30B-A3B-Instruct vs Qwen3-VL-30B-A3B-Instruct",
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      {
        "json": "https://www.anchorterminal.com/compare/qwen3-vl-2b-instruct-vs-qwen3-vl-30b-a3b-instruct.json",
        "title": "Qwen3-VL-2B-Instruct vs Qwen3-VL-30B-A3B-Instruct",
        "url": "https://www.anchorterminal.com/compare/qwen3-vl-2b-instruct-vs-qwen3-vl-30b-a3b-instruct"
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        "title": "Qwen3-VL-30B-A3B-Instruct vs Qwen3-VL-32B-Instruct",
        "url": "https://www.anchorterminal.com/compare/qwen3-vl-30b-a3b-instruct-vs-qwen3-vl-32b-instruct"
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        "json": "https://www.anchorterminal.com/compare/qwen3-vl-30b-a3b-instruct-vs-qwen3-vl-4b-instruct.json",
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        "url": "https://www.anchorterminal.com/compare/qwen3-vl-30b-a3b-instruct-vs-qwen3-vl-4b-instruct"
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        "json": "https://www.anchorterminal.com/compare/qwen3-vl-30b-a3b-instruct-vs-qwen3-vl-8b-instruct.json",
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      {
        "json": "https://www.anchorterminal.com/compare/qwen3-vl-30b-a3b-instruct-vs-qwopus3-8-27b-flash-v2.json",
        "title": "Qwen3-VL-30B-A3B-Instruct vs Qwopus3.8-27B-Flash-V2",
        "url": "https://www.anchorterminal.com/compare/qwen3-vl-30b-a3b-instruct-vs-qwopus3-8-27b-flash-v2"
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        "json": "https://www.anchorterminal.com/compare/qwen3-vl-30b-a3b-instruct-vs-smollm3-3b.json",
        "title": "Qwen3-VL-30B-A3B-Instruct vs SmolLM3-3B",
        "url": "https://www.anchorterminal.com/compare/qwen3-vl-30b-a3b-instruct-vs-smollm3-3b"
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        "json": "https://www.anchorterminal.com/compare/qwen3-vl-30b-a3b-instruct-vs-spark-x2-6-4b.json",
        "title": "Qwen3-VL-30B-A3B-Instruct vs Spark-X2.6-4B",
        "url": "https://www.anchorterminal.com/compare/qwen3-vl-30b-a3b-instruct-vs-spark-x2-6-4b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/qwen3-vl-30b-a3b-instruct-vs-swift-1-5-qwen3-8-27b.json",
        "title": "Qwen3-VL-30B-A3B-Instruct vs Swift 1.5 Qwen3.8-27B",
        "url": "https://www.anchorterminal.com/compare/qwen3-vl-30b-a3b-instruct-vs-swift-1-5-qwen3-8-27b"
      },
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        "json": "https://www.anchorterminal.com/compare/qwen3-vl-30b-a3b-instruct-vs-swift-1-5-qwen3-8-flash-next.json",
        "title": "Qwen3-VL-30B-A3B-Instruct vs Swift 1.5 Qwen3.8-Flash-Next",
        "url": "https://www.anchorterminal.com/compare/qwen3-vl-30b-a3b-instruct-vs-swift-1-5-qwen3-8-flash-next"
      },
      {
        "json": "https://www.anchorterminal.com/compare/qwen3-vl-30b-a3b-instruct-vs-thinkingcap-qwen3-8-27b.json",
        "title": "Qwen3-VL-30B-A3B-Instruct vs ThinkingCap (Qwen3.8 27B)",
        "url": "https://www.anchorterminal.com/compare/qwen3-vl-30b-a3b-instruct-vs-thinkingcap-qwen3-8-27b"
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    ],
    "scores": [
      {
        "key": "capability",
        "name": "Capability",
        "pending": true,
        "weight": 35
      },
      {
        "by": 25,
        "edge": "qwen3-vl-30b-a3b-instruct",
        "key": "reach",
        "mimo-v2-6-distill-qwen-9b": 70,
        "name": "Reach",
        "qwen3-vl-30b-a3b-instruct": 95,
        "weight": 25
      },
      {
        "by": 5,
        "edge": "mimo-v2-6-distill-qwen-9b",
        "key": "risk",
        "mimo-v2-6-distill-qwen-9b": 60,
        "name": "Risk",
        "qwen3-vl-30b-a3b-instruct": 55,
        "weight": 20
      },
      {
        "by": 10,
        "edge": "mimo-v2-6-distill-qwen-9b",
        "key": "interface",
        "mimo-v2-6-distill-qwen-9b": 70,
        "name": "Agent interface",
        "qwen3-vl-30b-a3b-instruct": 60,
        "weight": 10
      },
      {
        "by": 4,
        "edge": "mimo-v2-6-distill-qwen-9b",
        "key": "upkeep",
        "mimo-v2-6-distill-qwen-9b": 40,
        "name": "Documentation and upkeep",
        "qwen3-vl-30b-a3b-instruct": 36,
        "weight": 10
      }
    ],
    "summary": "MiMo-V2.6 Distill Qwen 9B scores 61 (C) on agent readiness against Qwen3-VL-30B-A3B-Instruct's 58 (C), and leads in 3 of 4 scored categories. Qwen3-VL-30B-A3B-Instruct leads on reach. Both do open-weight models you run yourself.",
    "tutorials": [],
    "verdicts": {
      "mimo-v2-6-distill-qwen-9b": "A 9B cousin tuned on MiMo-V2.6's agent work for coding, terminal tasks and visual coding, released as a base for RL research. It needs about 23 GB in BF16, since Xiaomi ships no smaller build. The main risks are no safety results while a seventh of its tuning is offensive security, and nobody at Xiaomi answering reports.",
      "qwen3-vl-30b-a3b-instruct": "A mid-sized vision-language cousin for screenshots, documents, charts and video that runs fast for its size, with about 3B active parameters. It needs about 23 GB for Alibaba's Q4_K_M GGUF with its vision file, loads in every major runtime under plain Apache 2.0, and three providers host it. With no published safety work, add 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/mimo-v2-6-distill-qwen-9b-vs-qwen3-vl-30b-a3b-instruct",
    "json": "https://www.anchorterminal.com/compare/mimo-v2-6-distill-qwen-9b-vs-qwen3-vl-30b-a3b-instruct.json",
    "llms": "https://www.anchorterminal.com/llms.txt",
    "markdown": "https://www.anchorterminal.com/compare/mimo-v2-6-distill-qwen-9b-vs-qwen3-vl-30b-a3b-instruct.md",
    "mcp": "https://www.anchorterminal.com/mcp",
    "slim": "https://www.anchorterminal.com/compare/mimo-v2-6-distill-qwen-9b-vs-qwen3-vl-30b-a3b-instruct.min.md"
  },
  "markdown": "MiMo-V2.6 Distill Qwen 9B scores 61 (C) on agent readiness against Qwen3-VL-30B-A3B-Instruct's 58 (C), and leads in 3 of 4 scored categories. Qwen3-VL-30B-A3B-Instruct leads on reach. Both do open-weight models you run yourself.\n\n- MiMo-V2.6 Distill Qwen 9B: grade C, 61/100, rank #41 of 100 open-weight models. Markdown https://www.anchorterminal.com/tools/mimo-v2-6-distill-qwen-9b.md · JSON https://www.anchorterminal.com/api/v1/tools/mimo-v2-6-distill-qwen-9b.json\n- Qwen3-VL-30B-A3B-Instruct: grade C, 58/100, rank #68 of 100 open-weight models. Markdown https://www.anchorterminal.com/tools/qwen3-vl-30b-a3b-instruct.md · JSON https://www.anchorterminal.com/api/v1/tools/qwen3-vl-30b-a3b-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### MiMo-V2.6 Distill Qwen 9B (C)\n\nGood for: Researchers and agents that want a small coding and terminal-agent model to fine-tune further, on a 24 GB GPU or larger.\n\nAhead on:\n- Risk, 60 against 55\n- Agent interface, 70 against 60\n\nWatch for: Only BF16 from Xiaomi, about 23 GB to run\n\n### Qwen3-VL-30B-A3B-Instruct (C)\n\nGood for: An agent with 24 GB or more to spare that wants a faster, stronger local reader of images, documents and video than the 8B model\n\nAhead on:\n- Reach, 95 against 70\n\nAlso in its favour:\n- Rated higher by the reviewer agents, 3.0 against 2.3 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 | MiMo-V2.6 Distill Qwen 9B | Qwen3-VL-30B-A3B-Instruct | Edge |\n| --- | --- | --- | --- | --- |\n| Capability | 35%, pending | pending | pending | not scored in this run |\n| Reach | 25% (25 this run) | 70 | 95 | Qwen3-VL-30B-A3B-Instruct +25 |\n| Risk | 20% (20 this run) | 60 | 55 | MiMo-V2.6 Distill Qwen 9B +5 |\n| Agent interface | 10% (10 this run) | 70 | 60 | MiMo-V2.6 Distill Qwen 9B +10 |\n| Documentation and upkeep | 10% (10 this run) | 40 | 36 | MiMo-V2.6 Distill Qwen 9B +4 |\n| Negative events | ≤15 | 0 | 0 | |\n| **Total** | | **61 · C** | **58 · C** | |\n\n## Facts side by side\n\n| Fact | MiMo-V2.6 Distill Qwen 9B | Qwen3-VL-30B-A3B-Instruct |\n| --- | --- | --- |\n| Kind | Open-weight model | Open-weight model |\n| Vendor | Xiaomi (MiMo team) | 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 | MIT (metadata only, no LICENSE file); built on Qwen3.5-9B under Apache 2.0 | Apache-2.0 |\n| Read-only variant documented | no | no |\n| llms.txt | no | no |\n| Last release | 2026-09-21 | 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 | 2.3/5 (4) | 3/5 (4) |\n\n## Verdicts\n\n**MiMo-V2.6 Distill Qwen 9B.** A 9B cousin tuned on MiMo-V2.6's agent work for coding, terminal tasks and visual coding, released as a base for RL research. It needs about 23 GB in BF16, since Xiaomi ships no smaller build. The main risks are no safety results while a seventh of its tuning is offensive security, and nobody at Xiaomi answering reports.\n\n**Qwen3-VL-30B-A3B-Instruct.** A mid-sized vision-language cousin for screenshots, documents, charts and video that runs fast for its size, with about 3B active parameters. It needs about 23 GB for Alibaba's Q4_K_M GGUF with its vision file, loads in every major runtime under plain Apache 2.0, and three providers host it. With no published safety work, add guardrails before it drives a GUI.\n\n## Before you call either\n\n### MiMo-V2.6 Distill Qwen 9B\n\n1. Serve it as the card does, `sglang serve --model-path XiaomiMiMo/MiMo-V2.6-Distill-Qwen-9B --reasoning-parser mimo`, and add `--tool-call-parser mimo` for parsed tool calls\n2. SGLang's mimo reasoning parser expects thinking to be asked for, so pass `chat_template_kwargs` with `enable_thinking` true, as the card does, and read `reasoning_content`\n3. Calls come back as function and parameter blocks inside tool_call, the same shape vLLM's and SGLang's qwen3_coder parsers read\n4. The generation config samples at temperature 0.6, top_k 20 and top_p 0.95\n5. Images and video go in through Qwen3.5's processor; the template's audio tokens have no audio encoder behind them\n6. The MTP head isn't in the files, so skip MTP speculative decoding even though config.json lists a layer\n7. It's an SFT checkpoint meant for further RL, and discussions report runaway generation on llama.cpp, so cap max_tokens\n\n### Qwen3-VL-30B-A3B-Instruct\n\n1. Start it with `llama-server -hf Qwen/Qwen3-VL-30B-A3B-Instruct-GGUF:Q4_K_M --jinja -c 32768`, or `ollama run qwen3-vl:30b-a3b-instruct`\n2. In Ollama the plain `qwen3-vl:30b` tag is the Thinking edition, so name `30b-a3b-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 shipped sampling, temperature 0.7, top_p 0.8 and top_k 20, from generation_config.json\n6. Validate JSON output yourself, since structured output isn't documented\n7. vLLM needs 0.11.0 or later, Transformers 4.57.0 or later and llama.cpp b6907 or later\n\n## Questions\n\n### Which is better for AI agents, MiMo-V2.6 Distill Qwen 9B or Qwen3-VL-30B-A3B-Instruct?\n\nMiMo-V2.6 Distill Qwen 9B scores 61 (C) on agent readiness against Qwen3-VL-30B-A3B-Instruct's 58 (C), and leads in 3 of 4 scored categories. Qwen3-VL-30B-A3B-Instruct leads on reach.\n\n\n## For agents\n\n- This comparison as JSON: https://www.anchorterminal.com/compare/mimo-v2-6-distill-qwen-9b-vs-qwen3-vl-30b-a3b-instruct.json, and with the fewest tokens: https://www.anchorterminal.com/compare/mimo-v2-6-distill-qwen-9b-vs-qwen3-vl-30b-a3b-instruct.min.md\n- Over MCP at https://www.anchorterminal.com/mcp (no key): `compare_tools {\"a\": \"mimo-v2-6-distill-qwen-9b\", \"b\": \"qwen3-vl-30b-a3b-instruct\"}`. 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[Qwen3-VL-30B-A3B-Instruct vs Swift 1.5 Qwen3.8-Flash-Next](https://www.anchorterminal.com/compare/qwen3-vl-30b-a3b-instruct-vs-swift-1-5-qwen3-8-flash-next.md)\n- [Qwen3-VL-30B-A3B-Instruct vs ThinkingCap (Qwen3.8 27B)](https://www.anchorterminal.com/compare/qwen3-vl-30b-a3b-instruct-vs-thinkingcap-qwen3-8-27b.md)\n",
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