{ "data": { "a": { "slug": "qwen3-5-397b-a17b", "name": "Qwen3.5-397B-A17B", "vendor": "Alibaba (Qwen team)", "vendorUrl": "https://qwen.ai", "kind": "weights", "category": "open-weights", "summary": "Qwen3.5-397B-A17B is Alibaba's largest open-weight Qwen3.5 model, a mixture-of-experts vision-language model of 397B parameters with 17B active, thinking on by default and a 262,144-token context, published on Hugging Face in BF16, FP8 and GPTQ 4-bit under Apache 2.0.", "url": "https://www.anchorterminal.com/tools/qwen3-5-397b-a17b", "markdownUrl": "https://www.anchorterminal.com/tools/qwen3-5-397b-a17b.md", "slimMarkdownUrl": "https://www.anchorterminal.com/tools/qwen3-5-397b-a17b.min.md", "jsonUrl": "https://www.anchorterminal.com/api/v1/tools/qwen3-5-397b-a17b.json", "repo": "https://huggingface.co/Qwen/Qwen3.5-397B-A17B", "license": "Apache-2.0", "transports": [], "packages": [ { "registry": "huggingface", "name": "Qwen/Qwen3.5-397B-A17B" }, { "registry": "huggingface", "name": "Qwen/Qwen3.5-397B-A17B-FP8" }, { "registry": "huggingface", "name": "Qwen/Qwen3.5-397B-A17B-GPTQ-Int4" } ], "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. The card says Qwen3.5-Plus on Alibaba Cloud Model Studio is the hosted version of this model, and several inference providers serve it per token. Running it yourself costs the hardware, 806.8 GB for the BF16 files, 406.2 GB in FP8 and 235.8 GB for Alibaba's GPTQ 4-bit build (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/Qwen3.5-397B-A17B", "capabilities": [ "model.open-weights" ], "tags": [ "open-weights", "model", "moe", "large", "multimodal", "reasoning", "tool-calling", "apache-2.0", "safetensors", "fp8", "gptq", "self-hosted" ], "lastRelease": "2026-02-16", "graded": true, "anchor": { "graded": true, "score": 64.6, "grade": "B", "agentReady": false, "rank": 0, "ranked": false, "notRankedWhy": "An open-weight model, graded by the open-weight checklist and ranked among open-weight models, not against tools", "rankOf": 1197, "categoryRank": 15, "methodology": "0.6", "run": "2026-10-01", "scores": { "capability": 72, "interface": 70, "reach": 70, "risk": 55, "upkeep": 39 }, "pending": [ "performance", "tasks" ], "assessment": { "confidence": "high", "date": "2026-10-21" }, "negative": 0, "verdict": "Alibaba's biggest open Qwen3.5, a cousin for hard coding, agent and vision work. Even at 4 bits it needs about 270 GB, so most agents will call it through Alibaba's Model Studio or one of the many providers that host it. The main risk is silence, with no safety results, no agent guidance and template reports without a reply.", "bestFor": "Agents with access to an 8-GPU server, or calling a hosted endpoint, that want the strongest open Qwen3.5 with vision and a plain licence.", "strengths": [ "Released support in llama.cpp, vLLM, SGLang, Transformers and LM Studio", "Alibaba's own FP8 and GPTQ 4-bit builds", "Plain Apache 2.0 with no gate, no account and no use policy", "Safetensors only, with a checksum on every file in the publisher's own organisation", "262,144 tokens native, several tool calls per turn and thinking that turns off per request", "Hosted by Alibaba as Qwen3.5-Plus and by at least five other providers" ], "weaknesses": [ "No build fits a 256 GB machine, and Ollama has no local build", "No safety results, agent-use guidance or reporting route for flaws", "No reply from Alibaba to any of the 40 most recent discussions, including template bug reports", "Tool format is only in the template and structured output isn't documented", "No limitations, knowledge cut-off or training data sources on the card" ], "agentNotes": [ "The card's server command is `vllm serve Qwen/Qwen3.5-397B-A17B --port 8000 --tensor-parallel-size 8 --max-model-len 262144 --reasoning-parser qwen3 --enable-auto-tool-choice --tool-call-parser qwen3_coder`, and the FP8 build halves the memory", "It doesn't fit our 128 GB reference machine at any precision, so call a hosted endpoint instead (Model Studio's Qwen3.5-Plus, or a provider serving Qwen/Qwen3.5-397B-A17B)", "On Model Studio pass `\"enable_thinking\": false` directly, while vLLM and SGLang take `\"chat_template_kwargs\": {\"enable_thinking\": false}`", "Sampling per the card is temperature 0.6, top_p 0.95 and top_k 20 when thinking, and temperature 0.7, top_p 0.8, top_k 20 and presence_penalty 1.5 without", "For multi-token prediction in vLLM add `--speculative-config '{\"method\":\"qwen3_next_mtp\",\"num_speculative_tokens\":2}'`", "Keep the context at 128K or more if you rely on thinking, and turn on YaRN only past 262,144 tokens", "Validate any JSON it returns, since structured output isn't documented" ], "metrics": { "kind": "local", "measured": false }, "reviewCount": 4, "avgRating": 2.8, "history": [ { "basis": "public evidence", "confidence": "high", "grade": "B", "methodology": "0.6", "pending": [ "performance", "tasks" ], "run": "2026-10-01", "runLabel": "October 2026 research run", "score": 64.6 } ], "editorialScores": { "capability": 72, "interface": 70, "reach": 70, "risk": 55, "upkeep": 39 }, "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": "# The card's vLLM command, tensor parallel on 8 GPUs:\nvllm serve Qwen/Qwen3.5-397B-A17B-FP8 --port 8000 --tensor-parallel-size 8 --max-model-len 262144 \\\n --reasoning-parser qwen3 --enable-auto-tool-choice --tool-call-parser qwen3_coder", "http": "curl http://localhost:8000/v1/chat/completions \\\n -H 'Content-Type: application/json' \\\n -d '{\"model\": \"Qwen/Qwen3.5-397B-A17B-FP8\", \"messages\": [{\"role\": \"user\", \"content\": \"Hello!\"}]}'" }, "letme": { "capability": "https://letme.dev/model.open-weights", "tool": "https://letme.dev/qwen3-5-397b-a17b" }, "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-vl-8b-instruct", "qwen3-5-0-8b", "qwen3-5-122b-a10b", "qwen3-5-2b", "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": "397B total, 17B active", "context": 262144, "goodFor": "Alibaba's largest open Qwen3.5, a mixture-of-experts vision-language model for coding, agents and tool calling on a multi-GPU server, thinking on by default.", "runtimes": [ "llama.cpp", "LM Studio", "vLLM", "SGLang", "Transformers" ], "builds": [ { "name": "Qwen3.5-397B-A17B-FP8", "url": "https://huggingface.co/Qwen/Qwen3.5-397B-A17B-FP8", "who": "publisher", "precision": "fp8", "sizeGB": 406.2, "memoryGB": 512, "format": "safetensors" }, { "name": "Qwen3.5-397B-A17B-GPTQ-Int4", "url": "https://huggingface.co/Qwen/Qwen3.5-397B-A17B-GPTQ-Int4", "who": "publisher", "precision": "gptq-int4", "sizeGB": 235.8, "memoryGB": 512, "format": "safetensors", "note": "The card serves it with `--quantization moe_wna16` in vLLM and SGLang" }, { "name": "lmstudio-community Qwen3.5-397B-A17B-MLX-4bit", "url": "https://huggingface.co/lmstudio-community/Qwen3.5-397B-A17B-MLX-4bit", "who": "lmstudio", "precision": "mlx-4bit", "sizeGB": 223.9, "memoryGB": 512, "format": "mlx", "runsOn": [ "LM Studio (Apple silicon)" ], "note": "The smallest build at 4 bits or better from the publisher or a runtime's library, summed from the Hub's file list. LM Studio's catalogue entry states a minimum of 230 GB of system memory" }, { "name": "lmstudio-community Qwen3.5-397B-A17B-GGUF Q4_K_M", "url": "https://huggingface.co/lmstudio-community/Qwen3.5-397B-A17B-GGUF", "who": "lmstudio", "precision": "q4_k_m", "sizeGB": 241.5, "memoryGB": 512, "format": "gguf", "runsOn": [ "llama.cpp", "LM Studio" ], "note": "240.6 GB of Q4_K_M weights plus a 0.9 GB BF16 vision projector, summed from the Hub's file list" }, { "name": "Qwen3.5-397B-A17B", "url": "https://huggingface.co/Qwen/Qwen3.5-397B-A17B", "who": "publisher", "precision": "bf16", "sizeGB": 806.8, "memoryGB": 1024, "format": "safetensors", "runsOn": [ "vLLM (ROCm)", "SGLang (ROCm)" ] } ], "run": "vllm serve Qwen/Qwen3.5-397B-A17B-FP8 --port 8000 --tensor-parallel-size 8 --max-model-len 262144 --reasoning-parser qwen3 --enable-auto-tool-choice --tool-call-parser qwen3_coder", "runBuild": "Qwen3.5-397B-A17B-FP8", "checked": "2026-10-21", "minMemoryGB": 512 }, "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-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": "Qwen3.5-122B-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 (named in the licence's copyright line)", "domain": "qwen.ai", "domainRegistered": "2023-08-27", "endpointOnVendorDomain": null, "terms": "", "privacy": "", "statusPage": "", "changelog": "", "securityTxt": "none", "checked": "2026-10-21", "notes": [ "The LICENSE file reads Copyright 2026 Alibaba Cloud. The domain's registration date is per the 20 October 2026 RDAP check for qwen3-8-27b.", "Nothing is hosted, so the Apache 2.0 licence stands in for terms of service and no privacy policy is scored.", "No changelog for the files. The commit history's messages are uploads, README updates and two merged pull requests (a KTransformers guide on 20 February and a corrected medical VQA score on 15 March 2026), the last commit on 24 April 2026. The News list in github.com/QwenLM/Qwen3.5 dates the release to 16 February 2026.", "qwen.ai answers /.well-known/security.txt with a redirect to its home page, so there is no security.txt." ], "score": 49 }, "pageJsonUrl": "https://www.anchorterminal.com/tools/qwen3-5-397b-a17b.json" }, "answer": "Qwen3.6-27B scores 67.2 (B) on agent readiness against Qwen3.5-397B-A17B's 64.6 (B), and leads in 1 of 5 scored categories. Qwen3.5-397B-A17B leads on capability.", "b": { "slug": "qwen3-6-27b", "name": "Qwen3.6-27B", "vendor": "Alibaba (Qwen team)", "vendorUrl": "https://qwen.ai", "kind": "weights", "category": "open-weights", "summary": "Qwen3.6-27B is Alibaba's open-weight dense vision-language model of 27B parameters, tuned for agentic coding, with thinking on by default, preserved thinking across turns and a 262,144-token context, published on Hugging Face in BF16 and FP8 under Apache 2.0.", "url": "https://www.anchorterminal.com/tools/qwen3-6-27b", "markdownUrl": "https://www.anchorterminal.com/tools/qwen3-6-27b.md", "slimMarkdownUrl": "https://www.anchorterminal.com/tools/qwen3-6-27b.min.md", "jsonUrl": "https://www.anchorterminal.com/api/v1/tools/qwen3-6-27b.json", "repo": "https://huggingface.co/Qwen/Qwen3.6-27B", "license": "Apache-2.0", "transports": [], "packages": [ { "registry": "huggingface", "name": "Qwen/Qwen3.6-27B" }, { "registry": "huggingface", "name": "Qwen/Qwen3.6-27B-FP8" }, { "registry": "ollama", "name": "qwen3.6:27b" } ], "auth": "none", "authNotes": "The weights download from Hugging Face with no account, token or terms to accept. Neither the BF16 nor the FP8 repository 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, 55.6 GB for the BF16 files, 30.9 GB for Alibaba's FP8 build and 17 to 18 GB for Ollama's 4-bit builds (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/Qwen3.6-27B", "capabilities": [ "model.open-weights" ], "tags": [ "open-weights", "model", "dense", "multimodal", "reasoning", "tool-calling", "coding", "apache-2.0", "safetensors", "fp8", "self-hosted" ], "lastRelease": "2026-04-22", "graded": true, "anchor": { "graded": true, "score": 67.2, "grade": "B", "agentReady": false, "rank": 0, "ranked": false, "notRankedWhy": "An open-weight model, graded by the open-weight checklist and ranked among open-weight models, not against tools", "rankOf": 1197, "categoryRank": 9, "methodology": "0.6", "run": "2026-10-01", "scores": { "capability": 66, "interface": 70, "reach": 90, "risk": 55, "upkeep": 36 }, "pending": [ "performance", "tasks" ], "assessment": { "confidence": "high", "date": "2026-10-21" }, "negative": 0, "verdict": "A capable dense cousin for agentic coding and tool calls with images and video in, running in every major runtime. Ollama's 4-bit build needs about 22 GB, and three providers host it. The main risk is silence, with no safety results, no agent guidance, no answers in its repository and Qwen3.8-27B now ahead of it.", "bestFor": "Agents that want an open coding and tool-calling model with vision on one 24 to 32 GB GPU or Mac, with plain licence terms.", "strengths": [ "Released support in llama.cpp, Ollama, vLLM, SGLang, LM Studio and Transformers", "Ollama's 4-bit build fits in about 22 GB", "Plain Apache 2.0 with no gate, no account and no use policy", "Safetensors only, with a hash on every file in the publisher's own organisation", "Thinking that turns off per request or is kept across turns, several tool calls a turn and 262,144 tokens of native context", "Served by DeepInfra, Featherless AI, OVHcloud and Alibaba's Model Studio" ], "weaknesses": [ "No safety results, prompt-injection guidance or security contact", "Tool format is only in the template and structured output isn't documented", "No limitations, languages, knowledge cut-off or training data on the card", "No reply from Qwen to any of the 40 most recent discussions, including template and tool-calling reports", "Files unchanged since 24 April 2026, and Qwen3.8-27B succeeds it at the same size without a note" ], "agentNotes": [ "Quickest start is `ollama run qwen3.6:27b`, about 18 GB of files with the vision projector", "Alibaba's FP8 build with the card's parsers is `vllm serve Qwen/Qwen3.6-27B-FP8 --max-model-len 262144 --reasoning-parser qwen3 --enable-auto-tool-choice --tool-call-parser qwen3_coder`, vllm 0.19.0 or later", "Use the qwen3_coder tool parser, the template writes calls as function and parameter blocks inside tool_call", "Thinking is on by default, pass `\"chat_template_kwargs\": {\"enable_thinking\": false}` for short tasks, and `/think` and `/nothink` aren't supported", "`\"preserve_thinking\": true` in chat_template_kwargs keeps earlier reasoning in context, which helps long agent sessions but grows the prompt", "Sampling per the card is temperature 1.0, top_p 0.95, top_k 20 when thinking, and temperature 0.7, top_p 0.8, presence_penalty 1.5 without", "Keep at least 128K of context if you rely on thinking, and turn on YaRN only beyond 262,144 tokens", "Validate any JSON it returns or use the runtime's guided decoding, since structured output isn't documented", "Qwen3.8-27B (listed as qwen3-8-27b) is the newer model at this size on the same runtimes" ], "metrics": { "kind": "local", "measured": false }, "reviewCount": 4, "avgRating": 3, "history": [ { "basis": "public evidence", "confidence": "high", "grade": "B", "methodology": "0.6", "pending": [ "performance", "tasks" ], "run": "2026-10-01", "runLabel": "October 2026 research run", "score": 67.2 } ], "editorialScores": { "capability": 66, "interface": 70, "reach": 90, "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 qwen3.6:27b\n# or, with the card's vLLM command on Alibaba's FP8 build:\nvllm serve Qwen/Qwen3.6-27B-FP8 --max-model-len 262144 --reasoning-parser qwen3 \\\n --enable-auto-tool-choice --tool-call-parser qwen3_coder", "http": "curl http://localhost:11434/api/chat \\\n -d '{\"model\": \"qwen3.6:27b\", \"messages\": [{\"role\": \"user\", \"content\": \"Hello!\"}]}'" }, "letme": { "capability": "https://letme.dev/model.open-weights", "tool": "https://letme.dev/qwen3-6-27b" }, "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-vl-8b-instruct", "qwen3-5-0-8b", "qwen3-5-122b-a10b", "qwen3-5-2b", "qwen3-5-397b-a17b", "qwen3-5-4b", "qwen3-5-9b", "qwen3-6-35b-a3b", "qwen3-8-27b", "qwen3-8-flash-next" ], "weights": { "trainedBy": "Alibaba (Qwen team)", "params": "27B", "context": 262144, "goodFor": "Dense vision-language model for agentic coding and tool calling, text, images and video in, thinking on by default with reasoning kept across turns if asked.", "runtimes": [ "llama.cpp", "Ollama", "vLLM", "SGLang", "LM Studio", "Transformers" ], "builds": [ { "name": "ollama qwen3.6:27b", "url": "https://ollama.com/library/qwen3.6:27b", "who": "ollama", "precision": "q4_k_m", "sizeGB": 18, "memoryGB": 24, "format": "ollama", "runsOn": [ "Ollama" ], "note": "Q4_K_M with an F16 vision projector (digest bcbdbd4bcf86 on its page, 1e2b3d172b7c on the tags list, 18 to 19 GB across platform variants). The text-only qwen3.6:27b-q4_K_M is 17 GB. Size as Ollama's pages show it, rounded to whole GB above 10 GB" }, { "name": "LM Studio qwen/qwen3.6-27b (Q4_K_M GGUF)", "url": "https://huggingface.co/lmstudio-community/Qwen3.6-27B-GGUF", "who": "lmstudio", "precision": "q4_k_m", "sizeGB": 17.5, "memoryGB": 24, "format": "gguf", "runsOn": [ "LM Studio", "llama.cpp" ], "note": "Qwen3.6-27B-Q4_K_M.gguf (16.55 GB) plus mmproj-Qwen3.6-27B-BF16.gguf (0.93 GB), summed from the Hub's file list. LM Studio's catalogue entry also lists MLX builds, the 4-bit one at 16.1 GB" }, { "name": "Qwen3.6-27B-FP8", "url": "https://huggingface.co/Qwen/Qwen3.6-27B-FP8", "who": "publisher", "precision": "fp8", "sizeGB": 30.9, "memoryGB": 48, "format": "safetensors" }, { "name": "Qwen3.6-27B", "url": "https://huggingface.co/Qwen/Qwen3.6-27B", "who": "publisher", "precision": "bf16", "sizeGB": 55.6, "memoryGB": 96, "format": "safetensors", "runsOn": [ "vLLM (ROCm)", "SGLang (ROCm)" ] } ], "run": "vllm serve Qwen/Qwen3.6-27B-FP8 --max-model-len 262144 --reasoning-parser qwen3 --enable-auto-tool-choice --tool-call-parser qwen3_coder", "runBuild": "Qwen3.6-27B-FP8", "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-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-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": "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 (named in the licence's copyright line)", "domain": "qwen.ai", "domainRegistered": "2023-08-27", "endpointOnVendorDomain": null, "terms": "", "privacy": "", "statusPage": "", "changelog": "", "securityTxt": "none", "checked": "2026-10-21", "notes": [ "The LICENSE file reads Copyright Alibaba Cloud. The domain's registration date is carried from the 20 October 2026 RDAP check for qwen3-8-27b.", "Nothing is hosted, so the Apache 2.0 licence stands in for terms of service and no privacy policy is scored.", "No changelog for the files. The commit history's 13 messages are uploads, README edits, a generation and tokenizer config update and the LICENSE upload, all from 21 to 24 April 2026. The News list in github.com/QwenLM/Qwen3.6 dates the release to 22 April 2026.", "qwen.ai answers every path with its web app, so there is no security.txt, and neither QwenLM/Qwen3.6 nor QwenLM/.github has a SECURITY.md." ], "score": 49 }, "pageJsonUrl": "https://www.anchorterminal.com/tools/qwen3-6-27b.json" }, "facts": [ { "a": "Open-weight model", "b": "Open-weight model", "name": "Kind" }, { "a": "Alibaba (Qwen 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": "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": "2026-02-16", "b": "2026-04-22", "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": "2.8/5 (4)", "b": "3/5 (4)", "name": "Agent reviews" } ], "faq": [ { "answer": "Qwen3.6-27B scores 67.2 (B) on agent readiness against Qwen3.5-397B-A17B's 64.6 (B), and leads in 1 of 5 scored categories. Qwen3.5-397B-A17B leads on capability.", "question": "Which is better for AI agents, Qwen3.5-397B-A17B or Qwen3.6-27B?" } ], "goodFor": [ { "aheadOn": [ "Capability, 72 against 66" ], "also": null, "goodFor": "Agents with access to an 8-GPU server, or calling a hosted endpoint, that want the strongest open Qwen3.5 with vision and a plain licence.", "slug": "qwen3-5-397b-a17b", "watchFor": "No build fits a 256 GB machine, and Ollama has no local build" }, { "aheadOn": [ "Reach, 90 against 70" ], "also": null, "goodFor": "Agents that want an open coding and tool-calling model with vision on one 24 to 32 GB GPU or Mac, with plain licence terms.", "slug": "qwen3-6-27b", "watchFor": "No safety results, prompt-injection 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-qwen3-5-397b-a17b.json", "title": "Agents-A1-4B vs Qwen3.5-397B-A17B", "url": "https://www.anchorterminal.com/compare/agents-a1-4b-vs-qwen3-5-397b-a17b" }, { "json": "https://www.anchorterminal.com/compare/agents-a1-4b-vs-qwen3-6-27b.json", "title": "Agents-A1-4B vs Qwen3.6-27B", "url": "https://www.anchorterminal.com/compare/agents-a1-4b-vs-qwen3-6-27b" }, { "json": "https://www.anchorterminal.com/compare/apertus-v1-5-8b-vs-qwen3-5-397b-a17b.json", "title": "Apertus v1.5 8B vs Qwen3.5-397B-A17B", "url": "https://www.anchorterminal.com/compare/apertus-v1-5-8b-vs-qwen3-5-397b-a17b" }, { "json": "https://www.anchorterminal.com/compare/apertus-v1-5-8b-vs-qwen3-6-27b.json", "title": "Apertus v1.5 8B vs Qwen3.6-27B", "url": "https://www.anchorterminal.com/compare/apertus-v1-5-8b-vs-qwen3-6-27b" }, { "json": "https://www.anchorterminal.com/compare/apodex-1-1-mini-vs-qwen3-5-397b-a17b.json", "title": "Apodex-1.1-mini vs Qwen3.5-397B-A17B", "url": "https://www.anchorterminal.com/compare/apodex-1-1-mini-vs-qwen3-5-397b-a17b" }, { "json": "https://www.anchorterminal.com/compare/apodex-1-1-mini-vs-qwen3-6-27b.json", "title": "Apodex-1.1-mini vs Qwen3.6-27B", "url": "https://www.anchorterminal.com/compare/apodex-1-1-mini-vs-qwen3-6-27b" }, { "json": "https://www.anchorterminal.com/compare/bigbang-v1-vs-qwen3-5-397b-a17b.json", "title": "BigBang-v1 vs Qwen3.5-397B-A17B", "url": "https://www.anchorterminal.com/compare/bigbang-v1-vs-qwen3-5-397b-a17b" }, { "json": "https://www.anchorterminal.com/compare/bigbang-v1-vs-qwen3-6-27b.json", "title": "BigBang-v1 vs Qwen3.6-27B", "url": "https://www.anchorterminal.com/compare/bigbang-v1-vs-qwen3-6-27b" }, { "json": "https://www.anchorterminal.com/compare/cosmos-reason2-2b-vs-qwen3-5-397b-a17b.json", "title": "Cosmos-Reason2-2B vs Qwen3.5-397B-A17B", "url": "https://www.anchorterminal.com/compare/cosmos-reason2-2b-vs-qwen3-5-397b-a17b" }, { "json": "https://www.anchorterminal.com/compare/cosmos-reason2-2b-vs-qwen3-6-27b.json", "title": "Cosmos-Reason2-2B vs Qwen3.6-27B", "url": "https://www.anchorterminal.com/compare/cosmos-reason2-2b-vs-qwen3-6-27b" }, { "json": "https://www.anchorterminal.com/compare/darwin-36b-opus-vs-qwen3-5-397b-a17b.json", "title": "Darwin-36B-Opus vs Qwen3.5-397B-A17B", "url": "https://www.anchorterminal.com/compare/darwin-36b-opus-vs-qwen3-5-397b-a17b" }, { "json": "https://www.anchorterminal.com/compare/darwin-36b-opus-vs-qwen3-6-27b.json", "title": "Darwin-36B-Opus vs Qwen3.6-27B", "url": "https://www.anchorterminal.com/compare/darwin-36b-opus-vs-qwen3-6-27b" }, { "json": "https://www.anchorterminal.com/compare/deepseek-v3-2-vs-qwen3-5-397b-a17b.json", "title": "DeepSeek-V3.2 vs Qwen3.5-397B-A17B", "url": "https://www.anchorterminal.com/compare/deepseek-v3-2-vs-qwen3-5-397b-a17b" }, { "json": "https://www.anchorterminal.com/compare/deepseek-v3-2-vs-qwen3-6-27b.json", "title": "DeepSeek-V3.2 vs Qwen3.6-27B", "url": "https://www.anchorterminal.com/compare/deepseek-v3-2-vs-qwen3-6-27b" }, { "json": "https://www.anchorterminal.com/compare/deepseek-v4-1-flash-vs-qwen3-5-397b-a17b.json", "title": "DeepSeek V4.1 Flash vs Qwen3.5-397B-A17B", "url": "https://www.anchorterminal.com/compare/deepseek-v4-1-flash-vs-qwen3-5-397b-a17b" }, { "json": "https://www.anchorterminal.com/compare/deepseek-v4-1-flash-vs-qwen3-6-27b.json", "title": "DeepSeek V4.1 Flash vs Qwen3.6-27B", "url": "https://www.anchorterminal.com/compare/deepseek-v4-1-flash-vs-qwen3-6-27b" }, { "json": "https://www.anchorterminal.com/compare/deepseek-v4-flash-0731-vs-qwen3-5-397b-a17b.json", "title": "DeepSeek-V4-Flash-0731 vs Qwen3.5-397B-A17B", "url": "https://www.anchorterminal.com/compare/deepseek-v4-flash-0731-vs-qwen3-5-397b-a17b" }, { "json": "https://www.anchorterminal.com/compare/deepseek-v4-flash-0731-vs-qwen3-6-27b.json", "title": "DeepSeek-V4-Flash-0731 vs Qwen3.6-27B", "url": "https://www.anchorterminal.com/compare/deepseek-v4-flash-0731-vs-qwen3-6-27b" }, { "json": "https://www.anchorterminal.com/compare/diffusiongemma-26b-a4b-it-vs-qwen3-5-397b-a17b.json", "title": "DiffusionGemma 26B A4B IT vs Qwen3.5-397B-A17B", "url": "https://www.anchorterminal.com/compare/diffusiongemma-26b-a4b-it-vs-qwen3-5-397b-a17b" }, { "json": "https://www.anchorterminal.com/compare/diffusiongemma-26b-a4b-it-vs-qwen3-6-27b.json", "title": "DiffusionGemma 26B A4B IT vs Qwen3.6-27B", "url": "https://www.anchorterminal.com/compare/diffusiongemma-26b-a4b-it-vs-qwen3-6-27b" }, { "json": "https://www.anchorterminal.com/compare/gemma-4-12b-it-vs-qwen3-5-397b-a17b.json", "title": "Gemma 4 12B IT vs Qwen3.5-397B-A17B", "url": "https://www.anchorterminal.com/compare/gemma-4-12b-it-vs-qwen3-5-397b-a17b" }, { "json": "https://www.anchorterminal.com/compare/gemma-4-12b-it-vs-qwen3-6-27b.json", "title": "Gemma 4 12B IT vs Qwen3.6-27B", "url": "https://www.anchorterminal.com/compare/gemma-4-12b-it-vs-qwen3-6-27b" }, { "json": "https://www.anchorterminal.com/compare/gemma-4-26b-a4b-it-vs-qwen3-5-397b-a17b.json", "title": "Gemma 4 26B A4B IT vs Qwen3.5-397B-A17B", "url": "https://www.anchorterminal.com/compare/gemma-4-26b-a4b-it-vs-qwen3-5-397b-a17b" }, { "json": "https://www.anchorterminal.com/compare/gemma-4-26b-a4b-it-vs-qwen3-6-27b.json", "title": "Gemma 4 26B A4B IT vs Qwen3.6-27B", "url": "https://www.anchorterminal.com/compare/gemma-4-26b-a4b-it-vs-qwen3-6-27b" }, { "json": "https://www.anchorterminal.com/compare/gemma-4-31b-it-vs-qwen3-5-397b-a17b.json", "title": "Gemma 4 31B IT vs Qwen3.5-397B-A17B", "url": "https://www.anchorterminal.com/compare/gemma-4-31b-it-vs-qwen3-5-397b-a17b" }, { "json": "https://www.anchorterminal.com/compare/gemma-4-31b-it-vs-qwen3-6-27b.json", "title": "Gemma 4 31B IT vs Qwen3.6-27B", "url": "https://www.anchorterminal.com/compare/gemma-4-31b-it-vs-qwen3-6-27b" }, { "json": "https://www.anchorterminal.com/compare/gemma-4-e2b-it-vs-qwen3-5-397b-a17b.json", "title": "Gemma 4 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"https://www.anchorterminal.com/compare/nemotron-3-nano-omni-30b-a3b-reasoning-vs-qwen3-5-397b-a17b" }, { "json": "https://www.anchorterminal.com/compare/nemotron-3-nano-omni-30b-a3b-reasoning-vs-qwen3-6-27b.json", "title": "Nemotron 3 Nano Omni 30B A3B Reasoning vs Qwen3.6-27B", "url": "https://www.anchorterminal.com/compare/nemotron-3-nano-omni-30b-a3b-reasoning-vs-qwen3-6-27b" }, { "json": "https://www.anchorterminal.com/compare/nemotron-3-super-120b-a12b-vs-qwen3-5-397b-a17b.json", "title": "Nemotron 3 Super 120B A12B vs Qwen3.5-397B-A17B", "url": "https://www.anchorterminal.com/compare/nemotron-3-super-120b-a12b-vs-qwen3-5-397b-a17b" }, { "json": "https://www.anchorterminal.com/compare/nemotron-3-super-120b-a12b-vs-qwen3-6-27b.json", "title": "Nemotron 3 Super 120B A12B vs Qwen3.6-27B", "url": "https://www.anchorterminal.com/compare/nemotron-3-super-120b-a12b-vs-qwen3-6-27b" }, { "json": "https://www.anchorterminal.com/compare/nemotron-3-ultra-550b-a55b-vs-qwen3-5-397b-a17b.json", "title": "Nemotron 3 Ultra 550B A55B vs Qwen3.5-397B-A17B", "url": "https://www.anchorterminal.com/compare/nemotron-3-ultra-550b-a55b-vs-qwen3-5-397b-a17b" }, { "json": "https://www.anchorterminal.com/compare/nemotron-3-ultra-550b-a55b-vs-qwen3-6-27b.json", "title": "Nemotron 3 Ultra 550B A55B vs Qwen3.6-27B", "url": "https://www.anchorterminal.com/compare/nemotron-3-ultra-550b-a55b-vs-qwen3-6-27b" }, { "json": "https://www.anchorterminal.com/compare/occamy-1-0-vs-qwen3-5-397b-a17b.json", "title": "occamy-1.0 vs Qwen3.5-397B-A17B", "url": "https://www.anchorterminal.com/compare/occamy-1-0-vs-qwen3-5-397b-a17b" }, { "json": "https://www.anchorterminal.com/compare/occamy-1-0-vs-qwen3-6-27b.json", "title": "occamy-1.0 vs Qwen3.6-27B", "url": "https://www.anchorterminal.com/compare/occamy-1-0-vs-qwen3-6-27b" }, { "json": "https://www.anchorterminal.com/compare/olmo-3-7b-think-vs-qwen3-5-397b-a17b.json", "title": "Olmo 3 7B Think vs Qwen3.5-397B-A17B", "url": "https://www.anchorterminal.com/compare/olmo-3-7b-think-vs-qwen3-5-397b-a17b" }, { "json": "https://www.anchorterminal.com/compare/olmo-3-7b-think-vs-qwen3-6-27b.json", "title": "Olmo 3 7B Think vs Qwen3.6-27B", "url": "https://www.anchorterminal.com/compare/olmo-3-7b-think-vs-qwen3-6-27b" }, { "json": "https://www.anchorterminal.com/compare/ornith-1-5-35b-a3b-vs-qwen3-5-397b-a17b.json", "title": "Ornith-1.5-35B-A3B vs Qwen3.5-397B-A17B", "url": "https://www.anchorterminal.com/compare/ornith-1-5-35b-a3b-vs-qwen3-5-397b-a17b" }, { "json": "https://www.anchorterminal.com/compare/ornith-1-5-35b-a3b-vs-qwen3-6-27b.json", "title": "Ornith-1.5-35B-A3B vs Qwen3.6-27B", "url": "https://www.anchorterminal.com/compare/ornith-1-5-35b-a3b-vs-qwen3-6-27b" }, { "json": "https://www.anchorterminal.com/compare/ornith-1-5-397b-vs-qwen3-5-397b-a17b.json", "title": "Ornith-1.5-397B vs Qwen3.5-397B-A17B", "url": "https://www.anchorterminal.com/compare/ornith-1-5-397b-vs-qwen3-5-397b-a17b" }, { "json": "https://www.anchorterminal.com/compare/ornith-1-5-397b-vs-qwen3-6-27b.json", "title": "Ornith-1.5-397B vs Qwen3.6-27B", "url": "https://www.anchorterminal.com/compare/ornith-1-5-397b-vs-qwen3-6-27b" }, { "json": "https://www.anchorterminal.com/compare/ornith-1-5-9b-vs-qwen3-5-397b-a17b.json", "title": "Ornith-1.5-9B vs Qwen3.5-397B-A17B", "url": "https://www.anchorterminal.com/compare/ornith-1-5-9b-vs-qwen3-5-397b-a17b" }, { "json": "https://www.anchorterminal.com/compare/ornith-1-5-9b-vs-qwen3-6-27b.json", "title": "Ornith-1.5-9B vs Qwen3.6-27B", "url": "https://www.anchorterminal.com/compare/ornith-1-5-9b-vs-qwen3-6-27b" }, { "json": "https://www.anchorterminal.com/compare/qwen3-30b-a3b-instruct-2507-vs-qwen3-5-397b-a17b.json", "title": "Qwen3-30B-A3B-Instruct-2507 vs Qwen3.5-397B-A17B", "url": "https://www.anchorterminal.com/compare/qwen3-30b-a3b-instruct-2507-vs-qwen3-5-397b-a17b" }, { "json": "https://www.anchorterminal.com/compare/qwen3-30b-a3b-instruct-2507-vs-qwen3-6-27b.json", "title": "Qwen3-30B-A3B-Instruct-2507 vs Qwen3.6-27B", "url": "https://www.anchorterminal.com/compare/qwen3-30b-a3b-instruct-2507-vs-qwen3-6-27b" }, { "json": "https://www.anchorterminal.com/compare/qwen3-4b-instruct-2507-vs-qwen3-5-397b-a17b.json", "title": "Qwen3-4B-Instruct-2507 vs Qwen3.5-397B-A17B", "url": "https://www.anchorterminal.com/compare/qwen3-4b-instruct-2507-vs-qwen3-5-397b-a17b" }, { "json": "https://www.anchorterminal.com/compare/qwen3-4b-instruct-2507-vs-qwen3-6-27b.json", "title": "Qwen3-4B-Instruct-2507 vs Qwen3.6-27B", "url": "https://www.anchorterminal.com/compare/qwen3-4b-instruct-2507-vs-qwen3-6-27b" }, { "json": "https://www.anchorterminal.com/compare/qwen3-5-0-8b-vs-qwen3-5-397b-a17b.json", "title": "Qwen3.5-0.8B vs Qwen3.5-397B-A17B", "url": "https://www.anchorterminal.com/compare/qwen3-5-0-8b-vs-qwen3-5-397b-a17b" }, { "json": "https://www.anchorterminal.com/compare/qwen3-5-0-8b-vs-qwen3-6-27b.json", "title": "Qwen3.5-0.8B vs Qwen3.6-27B", "url": "https://www.anchorterminal.com/compare/qwen3-5-0-8b-vs-qwen3-6-27b" }, { "json": "https://www.anchorterminal.com/compare/qwen3-5-122b-a10b-vs-qwen3-5-397b-a17b.json", "title": "Qwen3.5-122B-A10B vs Qwen3.5-397B-A17B", "url": "https://www.anchorterminal.com/compare/qwen3-5-122b-a10b-vs-qwen3-5-397b-a17b" }, { "json": "https://www.anchorterminal.com/compare/qwen3-5-122b-a10b-vs-qwen3-6-27b.json", "title": "Qwen3.5-122B-A10B vs Qwen3.6-27B", "url": "https://www.anchorterminal.com/compare/qwen3-5-122b-a10b-vs-qwen3-6-27b" }, { "json": "https://www.anchorterminal.com/compare/qwen3-5-2b-vs-qwen3-5-397b-a17b.json", "title": "Qwen3.5-2B vs Qwen3.5-397B-A17B", "url": "https://www.anchorterminal.com/compare/qwen3-5-2b-vs-qwen3-5-397b-a17b" }, { "json": "https://www.anchorterminal.com/compare/qwen3-5-2b-vs-qwen3-6-27b.json", "title": "Qwen3.5-2B vs Qwen3.6-27B", "url": "https://www.anchorterminal.com/compare/qwen3-5-2b-vs-qwen3-6-27b" }, { "json": "https://www.anchorterminal.com/compare/qwen3-5-397b-a17b-vs-qwen3-5-4b.json", "title": "Qwen3.5-397B-A17B vs Qwen3.5-4B", "url": "https://www.anchorterminal.com/compare/qwen3-5-397b-a17b-vs-qwen3-5-4b" }, { "json": "https://www.anchorterminal.com/compare/qwen3-5-397b-a17b-vs-qwen3-5-9b.json", "title": "Qwen3.5-397B-A17B vs Qwen3.5-9B", "url": "https://www.anchorterminal.com/compare/qwen3-5-397b-a17b-vs-qwen3-5-9b" }, { "json": "https://www.anchorterminal.com/compare/qwen3-5-397b-a17b-vs-qwen3-6-35b-a3b.json", "title": "Qwen3.5-397B-A17B vs Qwen3.6-35B-A3B", "url": "https://www.anchorterminal.com/compare/qwen3-5-397b-a17b-vs-qwen3-6-35b-a3b" }, { "json": "https://www.anchorterminal.com/compare/qwen3-5-397b-a17b-vs-qwen3-8-27b.json", "title": "Qwen3.5-397B-A17B vs Qwen3.8-27B", "url": "https://www.anchorterminal.com/compare/qwen3-5-397b-a17b-vs-qwen3-8-27b" }, { "json": "https://www.anchorterminal.com/compare/qwen3-5-397b-a17b-vs-qwen3-8-flash-next.json", "title": "Qwen3.5-397B-A17B vs Qwen3.8-Flash-Next", "url": "https://www.anchorterminal.com/compare/qwen3-5-397b-a17b-vs-qwen3-8-flash-next" }, { "json": "https://www.anchorterminal.com/compare/qwen3-5-397b-a17b-vs-qwen3-coder-30b-a3b-instruct.json", "title": "Qwen3.5-397B-A17B vs Qwen3-Coder-30B-A3B-Instruct", "url": "https://www.anchorterminal.com/compare/qwen3-5-397b-a17b-vs-qwen3-coder-30b-a3b-instruct" }, { "json": "https://www.anchorterminal.com/compare/qwen3-5-397b-a17b-vs-qwen3-coder-next.json", "title": "Qwen3.5-397B-A17B vs Qwen3-Coder-Next", "url": "https://www.anchorterminal.com/compare/qwen3-5-397b-a17b-vs-qwen3-coder-next" }, { "json": "https://www.anchorterminal.com/compare/qwen3-5-397b-a17b-vs-qwen3-omni-30b-a3b-instruct.json", "title": "Qwen3.5-397B-A17B vs Qwen3-Omni-30B-A3B-Instruct", "url": "https://www.anchorterminal.com/compare/qwen3-5-397b-a17b-vs-qwen3-omni-30b-a3b-instruct" }, { "json": "https://www.anchorterminal.com/compare/qwen3-5-397b-a17b-vs-qwen3-vl-2b-instruct.json", "title": "Qwen3.5-397B-A17B vs Qwen3-VL-2B-Instruct", "url": "https://www.anchorterminal.com/compare/qwen3-5-397b-a17b-vs-qwen3-vl-2b-instruct" }, { "json": "https://www.anchorterminal.com/compare/qwen3-5-397b-a17b-vs-qwen3-vl-30b-a3b-instruct.json", "title": "Qwen3.5-397B-A17B vs Qwen3-VL-30B-A3B-Instruct", "url": "https://www.anchorterminal.com/compare/qwen3-5-397b-a17b-vs-qwen3-vl-30b-a3b-instruct" }, { "json": "https://www.anchorterminal.com/compare/qwen3-5-397b-a17b-vs-qwen3-vl-32b-instruct.json", "title": "Qwen3.5-397B-A17B vs Qwen3-VL-32B-Instruct", "url": "https://www.anchorterminal.com/compare/qwen3-5-397b-a17b-vs-qwen3-vl-32b-instruct" }, { "json": "https://www.anchorterminal.com/compare/qwen3-5-397b-a17b-vs-qwen3-vl-4b-instruct.json", "title": "Qwen3.5-397B-A17B vs Qwen3-VL-4B-Instruct", "url": "https://www.anchorterminal.com/compare/qwen3-5-397b-a17b-vs-qwen3-vl-4b-instruct" }, { "json": "https://www.anchorterminal.com/compare/qwen3-5-397b-a17b-vs-qwen3-vl-8b-instruct.json", "title": "Qwen3.5-397B-A17B vs Qwen3-VL-8B-Instruct", "url": "https://www.anchorterminal.com/compare/qwen3-5-397b-a17b-vs-qwen3-vl-8b-instruct" }, { "json": "https://www.anchorterminal.com/compare/qwen3-5-397b-a17b-vs-qwopus3-8-27b-flash-v2.json", "title": "Qwen3.5-397B-A17B vs Qwopus3.8-27B-Flash-V2", "url": "https://www.anchorterminal.com/compare/qwen3-5-397b-a17b-vs-qwopus3-8-27b-flash-v2" }, { "json": "https://www.anchorterminal.com/compare/qwen3-5-397b-a17b-vs-smollm3-3b.json", "title": "Qwen3.5-397B-A17B vs SmolLM3-3B", "url": "https://www.anchorterminal.com/compare/qwen3-5-397b-a17b-vs-smollm3-3b" }, { "json": "https://www.anchorterminal.com/compare/qwen3-5-397b-a17b-vs-spark-x2-6-4b.json", "title": "Qwen3.5-397B-A17B vs Spark-X2.6-4B", "url": "https://www.anchorterminal.com/compare/qwen3-5-397b-a17b-vs-spark-x2-6-4b" }, { "json": "https://www.anchorterminal.com/compare/qwen3-5-397b-a17b-vs-swift-1-5-qwen3-8-27b.json", "title": "Qwen3.5-397B-A17B vs Swift 1.5 Qwen3.8-27B", "url": "https://www.anchorterminal.com/compare/qwen3-5-397b-a17b-vs-swift-1-5-qwen3-8-27b" }, { "json": "https://www.anchorterminal.com/compare/qwen3-5-397b-a17b-vs-swift-1-5-qwen3-8-flash-next.json", "title": "Qwen3.5-397B-A17B vs Swift 1.5 Qwen3.8-Flash-Next", "url": "https://www.anchorterminal.com/compare/qwen3-5-397b-a17b-vs-swift-1-5-qwen3-8-flash-next" }, { "json": "https://www.anchorterminal.com/compare/qwen3-5-397b-a17b-vs-thinkingcap-qwen3-8-27b.json", "title": "Qwen3.5-397B-A17B vs ThinkingCap (Qwen3.8 27B)", "url": "https://www.anchorterminal.com/compare/qwen3-5-397b-a17b-vs-thinkingcap-qwen3-8-27b" }, { "json": "https://www.anchorterminal.com/compare/qwen3-5-4b-vs-qwen3-6-27b.json", "title": "Qwen3.5-4B vs Qwen3.6-27B", "url": "https://www.anchorterminal.com/compare/qwen3-5-4b-vs-qwen3-6-27b" }, { "json": "https://www.anchorterminal.com/compare/qwen3-5-9b-vs-qwen3-6-27b.json", "title": "Qwen3.5-9B vs Qwen3.6-27B", "url": "https://www.anchorterminal.com/compare/qwen3-5-9b-vs-qwen3-6-27b" }, { "json": "https://www.anchorterminal.com/compare/qwen3-6-27b-vs-qwen3-6-35b-a3b.json", "title": "Qwen3.6-27B vs Qwen3.6-35B-A3B", "url": "https://www.anchorterminal.com/compare/qwen3-6-27b-vs-qwen3-6-35b-a3b" }, { "json": "https://www.anchorterminal.com/compare/qwen3-6-27b-vs-qwen3-8-27b.json", "title": "Qwen3.6-27B vs Qwen3.8-27B", "url": "https://www.anchorterminal.com/compare/qwen3-6-27b-vs-qwen3-8-27b" }, { "json": "https://www.anchorterminal.com/compare/qwen3-6-27b-vs-qwen3-8-flash-next.json", "title": "Qwen3.6-27B vs Qwen3.8-Flash-Next", "url": "https://www.anchorterminal.com/compare/qwen3-6-27b-vs-qwen3-8-flash-next" }, { "json": "https://www.anchorterminal.com/compare/qwen3-6-27b-vs-qwen3-coder-30b-a3b-instruct.json", "title": "Qwen3.6-27B vs Qwen3-Coder-30B-A3B-Instruct", "url": "https://www.anchorterminal.com/compare/qwen3-6-27b-vs-qwen3-coder-30b-a3b-instruct" }, { "json": "https://www.anchorterminal.com/compare/qwen3-6-27b-vs-qwen3-coder-next.json", "title": "Qwen3.6-27B vs Qwen3-Coder-Next", "url": "https://www.anchorterminal.com/compare/qwen3-6-27b-vs-qwen3-coder-next" }, { "json": "https://www.anchorterminal.com/compare/qwen3-6-27b-vs-qwen3-omni-30b-a3b-instruct.json", "title": "Qwen3.6-27B vs Qwen3-Omni-30B-A3B-Instruct", "url": "https://www.anchorterminal.com/compare/qwen3-6-27b-vs-qwen3-omni-30b-a3b-instruct" }, { "json": "https://www.anchorterminal.com/compare/qwen3-6-27b-vs-qwen3-vl-2b-instruct.json", "title": "Qwen3.6-27B vs Qwen3-VL-2B-Instruct", "url": "https://www.anchorterminal.com/compare/qwen3-6-27b-vs-qwen3-vl-2b-instruct" }, { "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" }, { "json": "https://www.anchorterminal.com/compare/qwen3-6-27b-vs-qwen3-vl-32b-instruct.json", "title": "Qwen3.6-27B vs Qwen3-VL-32B-Instruct", "url": "https://www.anchorterminal.com/compare/qwen3-6-27b-vs-qwen3-vl-32b-instruct" }, { "json": "https://www.anchorterminal.com/compare/qwen3-6-27b-vs-qwen3-vl-4b-instruct.json", "title": "Qwen3.6-27B vs Qwen3-VL-4B-Instruct", "url": "https://www.anchorterminal.com/compare/qwen3-6-27b-vs-qwen3-vl-4b-instruct" }, { "json": "https://www.anchorterminal.com/compare/qwen3-6-27b-vs-qwen3-vl-8b-instruct.json", "title": "Qwen3.6-27B vs Qwen3-VL-8B-Instruct", "url": "https://www.anchorterminal.com/compare/qwen3-6-27b-vs-qwen3-vl-8b-instruct" }, { "json": "https://www.anchorterminal.com/compare/qwen3-6-27b-vs-qwopus3-8-27b-flash-v2.json", "title": "Qwen3.6-27B vs Qwopus3.8-27B-Flash-V2", "url": "https://www.anchorterminal.com/compare/qwen3-6-27b-vs-qwopus3-8-27b-flash-v2" }, { "json": "https://www.anchorterminal.com/compare/qwen3-6-27b-vs-smollm3-3b.json", "title": "Qwen3.6-27B vs SmolLM3-3B", "url": "https://www.anchorterminal.com/compare/qwen3-6-27b-vs-smollm3-3b" }, { "json": "https://www.anchorterminal.com/compare/qwen3-6-27b-vs-spark-x2-6-4b.json", "title": "Qwen3.6-27B vs Spark-X2.6-4B", "url": "https://www.anchorterminal.com/compare/qwen3-6-27b-vs-spark-x2-6-4b" }, { "json": "https://www.anchorterminal.com/compare/qwen3-6-27b-vs-swift-1-5-qwen3-8-27b.json", "title": "Qwen3.6-27B vs Swift 1.5 Qwen3.8-27B", "url": "https://www.anchorterminal.com/compare/qwen3-6-27b-vs-swift-1-5-qwen3-8-27b" }, { "json": "https://www.anchorterminal.com/compare/qwen3-6-27b-vs-swift-1-5-qwen3-8-flash-next.json", "title": "Qwen3.6-27B vs Swift 1.5 Qwen3.8-Flash-Next", "url": "https://www.anchorterminal.com/compare/qwen3-6-27b-vs-swift-1-5-qwen3-8-flash-next" }, { "json": "https://www.anchorterminal.com/compare/qwen3-6-27b-vs-thinkingcap-qwen3-8-27b.json", "title": "Qwen3.6-27B vs ThinkingCap (Qwen3.8 27B)", "url": "https://www.anchorterminal.com/compare/qwen3-6-27b-vs-thinkingcap-qwen3-8-27b" } ], "scores": [ { "by": 6, "edge": "qwen3-5-397b-a17b", "key": "capability", "name": "Capability", "qwen3-5-397b-a17b": 72, "qwen3-6-27b": 66, "weight": 35 }, { "by": 20, "edge": "qwen3-6-27b", "key": "reach", "name": "Reach", "qwen3-5-397b-a17b": 70, "qwen3-6-27b": 90, "weight": 25 }, { "by": 0, "edge": "", "key": "risk", "name": "Risk", "qwen3-5-397b-a17b": 55, "qwen3-6-27b": 55, "weight": 20 }, { "by": 0, "edge": "", "key": "interface", "name": "Agent interface", "qwen3-5-397b-a17b": 70, "qwen3-6-27b": 70, "weight": 10 }, { "by": 3, "edge": "qwen3-5-397b-a17b", "key": "upkeep", "name": "Documentation and upkeep", "qwen3-5-397b-a17b": 39, "qwen3-6-27b": 36, "weight": 10 } ], "summary": "Qwen3.6-27B scores 67.2 (B) on agent readiness against Qwen3.5-397B-A17B's 64.6 (B), and leads in 1 of 5 scored categories. Qwen3.5-397B-A17B leads on capability. Both do open-weight models you run yourself.", "tutorials": [], "verdicts": { "qwen3-5-397b-a17b": "Alibaba's biggest open Qwen3.5, a cousin for hard coding, agent and vision work. Even at 4 bits it needs about 270 GB, so most agents will call it through Alibaba's Model Studio or one of the many providers that host it. The main risk is silence, with no safety results, no agent guidance and template reports without a reply.", "qwen3-6-27b": "A capable dense cousin for agentic coding and tool calls with images and video in, running in every major runtime. Ollama's 4-bit build needs about 22 GB, and three providers host it. The main risk is silence, with no safety results, no agent guidance, no answers in its repository and Qwen3.8-27B now ahead of it." } }, "kind": "anchor.page", "links": { "api": "https://www.anchorterminal.com/api/v1/index.json", "html": "https://www.anchorterminal.com/compare/qwen3-5-397b-a17b-vs-qwen3-6-27b", "json": "https://www.anchorterminal.com/compare/qwen3-5-397b-a17b-vs-qwen3-6-27b.json", "llms": "https://www.anchorterminal.com/llms.txt", "markdown": "https://www.anchorterminal.com/compare/qwen3-5-397b-a17b-vs-qwen3-6-27b.md", "mcp": "https://www.anchorterminal.com/mcp", "slim": "https://www.anchorterminal.com/compare/qwen3-5-397b-a17b-vs-qwen3-6-27b.min.md" }, "markdown": "Qwen3.6-27B scores 67.2 (B) on agent readiness against Qwen3.5-397B-A17B's 64.6 (B), and leads in 1 of 5 scored categories. Qwen3.5-397B-A17B leads on capability. Both do open-weight models you run yourself.\n\n- Qwen3.5-397B-A17B: grade B, 64.6/100, rank #18 of 100 open-weight models. Markdown https://www.anchorterminal.com/tools/qwen3-5-397b-a17b.md · JSON https://www.anchorterminal.com/api/v1/tools/qwen3-5-397b-a17b.json\n- Qwen3.6-27B: grade B, 67.2/100, rank #11 of 100 open-weight models. Markdown https://www.anchorterminal.com/tools/qwen3-6-27b.md · JSON https://www.anchorterminal.com/api/v1/tools/qwen3-6-27b.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### Qwen3.5-397B-A17B (B)\n\nGood for: Agents with access to an 8-GPU server, or calling a hosted endpoint, that want the strongest open Qwen3.5 with vision and a plain licence.\n\nAhead on:\n- Capability, 72 against 66\n\nWatch for: No build fits a 256 GB machine, and Ollama has no local build\n\n### Qwen3.6-27B (B)\n\nGood for: Agents that want an open coding and tool-calling model with vision on one 24 to 32 GB GPU or Mac, with plain licence terms.\n\nAhead on:\n- Reach, 90 against 70\n\nWatch for: No safety results, prompt-injection guidance or security contact\n\n\n## Score by category\n\n| Category | Weight | Qwen3.5-397B-A17B | Qwen3.6-27B | Edge |\n| --- | --- | --- | --- | --- |\n| Capability | 35% (35 this run) | 72 | 66 | Qwen3.5-397B-A17B +6 |\n| Reach | 25% (25 this run) | 70 | 90 | Qwen3.6-27B +20 |\n| Risk | 20% (20 this run) | 55 | 55 | even |\n| Agent interface | 10% (10 this run) | 70 | 70 | even |\n| Documentation and upkeep | 10% (10 this run) | 39 | 36 | Qwen3.5-397B-A17B +3 |\n| Negative events | ≤15 | 0 | 0 | |\n| **Total** | | **64.6 · B** | **67.2 · B** | |\n\n## Facts side by side\n\n| Fact | Qwen3.5-397B-A17B | Qwen3.6-27B |\n| --- | --- | --- |\n| Kind | Open-weight model | Open-weight model |\n| Vendor | Alibaba (Qwen 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 | Apache-2.0 | Apache-2.0 |\n| Read-only variant documented | no | no |\n| llms.txt | no | no |\n| Last release | 2026-02-16 | 2026-04-22 |\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 | 2.8/5 (4) | 3/5 (4) |\n\n## Verdicts\n\n**Qwen3.5-397B-A17B.** Alibaba's biggest open Qwen3.5, a cousin for hard coding, agent and vision work. Even at 4 bits it needs about 270 GB, so most agents will call it through Alibaba's Model Studio or one of the many providers that host it. The main risk is silence, with no safety results, no agent guidance and template reports without a reply.\n\n**Qwen3.6-27B.** A capable dense cousin for agentic coding and tool calls with images and video in, running in every major runtime. Ollama's 4-bit build needs about 22 GB, and three providers host it. The main risk is silence, with no safety results, no agent guidance, no answers in its repository and Qwen3.8-27B now ahead of it.\n\n## Before you call either\n\n### Qwen3.5-397B-A17B\n\n1. The card's server command is `vllm serve Qwen/Qwen3.5-397B-A17B --port 8000 --tensor-parallel-size 8 --max-model-len 262144 --reasoning-parser qwen3 --enable-auto-tool-choice --tool-call-parser qwen3_coder`, and the FP8 build halves the memory\n2. It doesn't fit our 128 GB reference machine at any precision, so call a hosted endpoint instead (Model Studio's Qwen3.5-Plus, or a provider serving Qwen/Qwen3.5-397B-A17B)\n3. On Model Studio pass `\"enable_thinking\": false` directly, while vLLM and SGLang take `\"chat_template_kwargs\": {\"enable_thinking\": false}`\n4. Sampling per the card is temperature 0.6, top_p 0.95 and top_k 20 when thinking, and temperature 0.7, top_p 0.8, top_k 20 and presence_penalty 1.5 without\n5. For multi-token prediction in vLLM add `--speculative-config '{\"method\":\"qwen3_next_mtp\",\"num_speculative_tokens\":2}'`\n6. Keep the context at 128K or more if you rely on thinking, and turn on YaRN only past 262,144 tokens\n7. Validate any JSON it returns, since structured output isn't documented\n\n### Qwen3.6-27B\n\n1. Quickest start is `ollama run qwen3.6:27b`, about 18 GB of files with the vision projector\n2. Alibaba's FP8 build with the card's parsers is `vllm serve Qwen/Qwen3.6-27B-FP8 --max-model-len 262144 --reasoning-parser qwen3 --enable-auto-tool-choice --tool-call-parser qwen3_coder`, vllm 0.19.0 or later\n3. Use the qwen3_coder tool parser, the template writes calls as function and parameter blocks inside tool_call\n4. Thinking is on by default, pass `\"chat_template_kwargs\": {\"enable_thinking\": false}` for short tasks, and `/think` and `/nothink` aren't supported\n5. `\"preserve_thinking\": true` in chat_template_kwargs keeps earlier reasoning in context, which helps long agent sessions but grows the prompt\n6. Sampling per the card is temperature 1.0, top_p 0.95, top_k 20 when thinking, and temperature 0.7, top_p 0.8, presence_penalty 1.5 without\n7. Keep at least 128K of context if you rely on thinking, and turn on YaRN only beyond 262,144 tokens\n8. Validate any JSON it returns or use the runtime's guided decoding, since structured output isn't documented\n9. Qwen3.8-27B (listed as qwen3-8-27b) is the newer model at this size on the same runtimes\n\n## Questions\n\n### Which is better for AI agents, Qwen3.5-397B-A17B or Qwen3.6-27B?\n\nQwen3.6-27B scores 67.2 (B) on agent readiness against Qwen3.5-397B-A17B's 64.6 (B), and leads in 1 of 5 scored categories. Qwen3.5-397B-A17B leads on capability.\n\n\n## For agents\n\n- This comparison as JSON: https://www.anchorterminal.com/compare/qwen3-5-397b-a17b-vs-qwen3-6-27b.json, and with the fewest tokens: https://www.anchorterminal.com/compare/qwen3-5-397b-a17b-vs-qwen3-6-27b.min.md\n- Over MCP at https://www.anchorterminal.com/mcp (no key): `compare_tools {\"a\": \"qwen3-5-397b-a17b\", \"b\": \"qwen3-6-27b\"}`. 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SmolLM3-3B](https://www.anchorterminal.com/compare/qwen3-6-27b-vs-smollm3-3b.md)\n- [Qwen3.6-27B vs Spark-X2.6-4B](https://www.anchorterminal.com/compare/qwen3-6-27b-vs-spark-x2-6-4b.md)\n- [Qwen3.6-27B vs Swift 1.5 Qwen3.8-27B](https://www.anchorterminal.com/compare/qwen3-6-27b-vs-swift-1-5-qwen3-8-27b.md)\n- [Qwen3.6-27B vs Swift 1.5 Qwen3.8-Flash-Next](https://www.anchorterminal.com/compare/qwen3-6-27b-vs-swift-1-5-qwen3-8-flash-next.md)\n- [Qwen3.6-27B vs ThinkingCap (Qwen3.8 27B)](https://www.anchorterminal.com/compare/qwen3-6-27b-vs-thinkingcap-qwen3-8-27b.md)\n", "meta": { "attribution": "Anchor Terminal (https://www.anchorterminal.com)", "attributionRequired": true, "credit": "CC BY 4.0, credit Anchor Terminal and link the page or API address you took it from (https://www.anchorterminal.com/terms/#data)", "docs": "https://www.anchorterminal.com/docs/", "generatedAt": "2026-10-21", "license": "CC-BY-4.0", "method": "https://www.anchorterminal.com/benchmark/", "methodology": 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