{ "data": { "a": { "slug": "qwen3-coder-30b-a3b-instruct", "name": "Qwen3-Coder-30B-A3B-Instruct", "vendor": "Alibaba (Qwen team)", "vendorUrl": "https://qwen.ai", "kind": "weights", "category": "open-weights", "summary": "Qwen3-Coder-30B-A3B-Instruct is Alibaba's open-weight mixture-of-experts coding model, 30.5B parameters with 3.3B active, for agentic coding and tool use, with a 262,144-token context, published in BF16 and FP8 under Apache 2.0.", "url": "https://www.anchorterminal.com/tools/qwen3-coder-30b-a3b-instruct", "markdownUrl": "https://www.anchorterminal.com/tools/qwen3-coder-30b-a3b-instruct.md", "slimMarkdownUrl": "https://www.anchorterminal.com/tools/qwen3-coder-30b-a3b-instruct.min.md", "jsonUrl": "https://www.anchorterminal.com/api/v1/tools/qwen3-coder-30b-a3b-instruct.json", "repo": "https://huggingface.co/Qwen/Qwen3-Coder-30B-A3B-Instruct", "license": "Apache-2.0", "transports": [], "packages": [ { "registry": "huggingface", "name": "Qwen/Qwen3-Coder-30B-A3B-Instruct" }, { "registry": "huggingface", "name": "Qwen/Qwen3-Coder-30B-A3B-Instruct-FP8" }, { "registry": "ollama", "name": "qwen3-coder:30b" } ], "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, 61.1 GB for the BF16 files, 31.2 GB for Alibaba's FP8 build and 19 GB for Ollama's 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-Coder-30B-A3B-Instruct", "capabilities": [ "model.open-weights" ], "tags": [ "open-weights", "model", "moe", "coding", "tool-calling", "long-context", "apache-2.0", "safetensors", "fp8", "self-hosted" ], "lastRelease": "2025-12-03", "graded": true, "anchor": { "graded": true, "score": 55.7, "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": 63, "methodology": "0.6", "run": "2026-10-01", "scores": { "capability": 33, "interface": 75, "reach": 90, "risk": 55, "upkeep": 31 }, "pending": [ "performance", "tasks" ], "assessment": { "confidence": "high", "date": "2026-10-21" }, "negative": 0, "verdict": "A fast coding cousin, with 3.3B of 30.5B parameters active per token, for agentic coding tools, repository reading and fill-in-the-middle without a thinking step. It needs about 21 to 23 GB at 4 bits, and several providers host it. The main risk is that it runs commands for agents with no safety results or guidance, and Alibaba doesn't answer users.", "bestFor": "Coding agents and local coding tools that want a fast, capable open model on one 24 GB GPU or a 32 GB Mac, with a plain licence.", "strengths": [ "Only 3.3B parameters active per token, so it runs fast for its size", "4-bit builds from Ollama and LM Studio fit 24 GB", "Its own qwen3_coder tool parser shipped in the repository and carried by released vLLM and SGLang", "Plain Apache 2.0 with no gate, no account and no use policy, and a checksum on every file", "262,144 tokens of native context and fill-in-the-middle support" ], "weaknesses": [ "No safety results, prompt-injection guidance or security contact, though it's meant to run commands", "config.json was corrected in place in December 2025 with no note, and older GGUF copies may predate it", "No reply from Alibaba in 26 discussions, and parser reports wait", "No thinking mode and no documented structured output", "Alibaba's only quantised build is FP8" ], "agentNotes": [ "Quickest start is `ollama run qwen3-coder:30b`, 19 GB", "On our reference machine use BF16 with `vllm serve Qwen/Qwen3-Coder-30B-A3B-Instruct --max-model-len 262144 --enable-auto-tool-choice --tool-call-parser qwen3_coder`, 61 GB of weights fits the GPU share", "Use the qwen3_coder parser in vLLM or SGLang, not hermes, since calls come back as function and parameter blocks rather than JSON", "Pass tool-call arguments in the history as objects, the template iterates them as a mapping", "Sampling per the card is temperature 0.7, top_p 0.8, top_k 20 and repetition_penalty 1.05, with up to 65,536 output tokens", "For code completion use the fill-in-the-middle tokens `\u003c|fim_prefix|\u003e`, `\u003c|fim_suffix|\u003e` and `\u003c|fim_middle|\u003e` from Qwen's README", "Sandbox the commands and files it touches, since nothing from Alibaba covers prompt injection" ], "metrics": { "kind": "local", "measured": false }, "reviewCount": 4, "avgRating": 2.8, "history": [ { "basis": "public evidence", "confidence": "high", "grade": "C", "methodology": "0.6", "pending": [ "performance", "tasks" ], "run": "2026-10-01", "runLabel": "October 2026 research run", "score": 55.7 } ], "editorialScores": { "capability": 33, "interface": 75, "reach": 90, "risk": 55, "upkeep": 31 }, "provenanceScore": 49, "checked": { "categories": { "capability": "2026-10-21", "interface": "2026-10-21", "reach": "2026-10-21", "risk": "2026-10-21", "upkeep": "2026-10-21" }, "last": "2026-10-21", "oldest": "2026-10-21", "stale": false, "staleAfterDays": 90 } }, "connect": { "install": "ollama run qwen3-coder:30b\n# or, with vLLM:\nvllm serve Qwen/Qwen3-Coder-30B-A3B-Instruct --max-model-len 262144 \\\n --enable-auto-tool-choice --tool-call-parser qwen3_coder", "http": "curl http://localhost:11434/api/chat \\\n -d '{\"model\": \"qwen3-coder:30b\", \"messages\": [{\"role\": \"user\", \"content\": \"Write a quick sort in Go.\"}]}'" }, "letme": { "capability": "https://letme.dev/model.open-weights", "tool": "https://letme.dev/qwen3-coder-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-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", "qwen3-6-27b", "qwen3-6-35b-a3b", "qwen3-8-27b", "qwen3-8-flash-next" ], "weights": { "trainedBy": "Alibaba (Qwen team)", "params": "30.5B (3.3B active)", "context": 262144, "goodFor": "Mixture-of-experts coding model for agentic coding tools, repository-scale code reading, tool calls and fill-in-the-middle, fast for its size and with no thinking step.", "runtimes": [ "llama.cpp", "Ollama", "vLLM", "SGLang", "LM Studio", "Transformers" ], "builds": [ { "name": "ollama qwen3-coder:30b", "url": "https://ollama.com/library/qwen3-coder:30b", "who": "ollama", "precision": "q4_k_m", "sizeGB": 19, "memoryGB": 24, "format": "ollama", "runsOn": [ "Ollama" ], "note": "Digest 06c1097efce0, also tagged latest and 30b-a3b-q4_K_M. Size as Ollama's tags page shows it, rounded to whole GB above 10 GB" }, { "name": "LM Studio qwen/qwen3-coder-30b (Q4_K_M GGUF)", "url": "https://huggingface.co/lmstudio-community/Qwen3-Coder-30B-A3B-Instruct-GGUF", "who": "lmstudio", "precision": "q4_k_m", "sizeGB": 18.63, "memoryGB": 24, "format": "gguf", "runsOn": [ "LM Studio", "llama.cpp" ], "note": "LM Studio's catalogue entry qwen/qwen3-coder-30b draws on this repository (Q3_K_L, Q4_K_M, Q6_K and Q8_0) and on MLX builds at 4 to 8 bits. The MLX 4-bit repository is 17.19 GB, also in the 24 GB band" }, { "name": "Qwen3-Coder-30B-A3B-Instruct-FP8", "url": "https://huggingface.co/Qwen/Qwen3-Coder-30B-A3B-Instruct-FP8", "who": "publisher", "precision": "fp8", "sizeGB": 31.2, "memoryGB": 48, "format": "safetensors", "note": "Block-wise FP8 with 128-wide blocks, per its card" }, { "name": "Qwen3-Coder-30B-A3B-Instruct", "url": "https://huggingface.co/Qwen/Qwen3-Coder-30B-A3B-Instruct", "who": "publisher", "precision": "bf16", "sizeGB": 61.08, "memoryGB": 96, "format": "safetensors", "runsOn": [ "vLLM (ROCm)", "SGLang (ROCm)" ] } ], "run": "vllm serve Qwen/Qwen3-Coder-30B-A3B-Instruct --max-model-len 262144 --enable-auto-tool-choice --tool-call-parser qwen3_coder", "runBuild": "Qwen3-Coder-30B-A3B-Instruct", "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": 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"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": "Qwen3-4B-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": 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"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 (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 2024 Alibaba Cloud. The registration date of qwen.ai is carried from the 20 October 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. Commit titles name the template, parser and config updates of 7 and 21 August and 3 December 2025, without saying what changed.", "qwen.ai/.well-known/security.txt redirects to the home page, so there is no security.txt." ], "score": 49 }, "pageJsonUrl": "https://www.anchorterminal.com/tools/qwen3-coder-30b-a3b-instruct.json" }, "answer": "Qwen3-Coder-30B-A3B-Instruct scores 55.7 (C) on agent readiness against Swift 1.5 Qwen3.8-Flash-Next's 52.3 (D), and leads in 3 of 4 scored categories. Swift 1.5 Qwen3.8-Flash-Next leads on documentation and upkeep.", "b": { "slug": "swift-1-5-qwen3-8-flash-next", "name": "Swift 1.5 Qwen3.8-Flash-Next", "vendor": "UkisAI", "vendorUrl": "https://ukisai.com", "kind": "weights", "category": "open-weights", "summary": "Swift 1.5 Qwen3.8-Flash-Next is UkisAI's post-trained Qwen3.8-Flash-Next that aims to think in fewer tokens, a mixture-of-experts vision-language model of 180B parameters in its files with a 262,144-token context, published in BF16 with GGUF, INT4 and NVFP4 builds.", "url": "https://www.anchorterminal.com/tools/swift-1-5-qwen3-8-flash-next", "markdownUrl": "https://www.anchorterminal.com/tools/swift-1-5-qwen3-8-flash-next.md", "slimMarkdownUrl": "https://www.anchorterminal.com/tools/swift-1-5-qwen3-8-flash-next.min.md", "jsonUrl": "https://www.anchorterminal.com/api/v1/tools/swift-1-5-qwen3-8-flash-next.json", "repo": "https://huggingface.co/ukisai/Swift1.5-Qwen3.8-Flash-Next", "license": "Swift Open License v1.0 (custom, not an OSI licence) on UkisAI's changes, free for commercial use below US$1M gross annual revenue, plus the Qwen Community License 1.0 on the base, which needs a separate licence from Qwen for a Model as a Service or AI Work Assistant business and the model name shown above 100M monthly users or US$20M monthly revenue", "transports": [], "packages": [ { "registry": "huggingface", "name": "ukisai/Swift1.5-Qwen3.8-Flash-Next" }, { "registry": "huggingface", "name": "ukisai/Swift-1.5-Qwen3.8-Flash-Next-GGUF" } ], "auth": "none", "authNotes": "The weights download from Hugging Face with no account, token or terms to accept. The Hub reports the repository as not gated, though the card's metadata says gated true (checked 2026-10-21).", "pricing": "free", "pricingNotes": "Free to download. Commercial use of UkisAI's contribution is free below US$1,000,000 gross annual revenue, affiliates included, and needs a Swift Enterprise License above it. The base's Qwen Community License 1.0 also applies, with a separate licence from Qwen for Model as a Service or AI Work Assistant businesses. UkisAI's card lists a free API for research at ukisai.com/api/flash-next/v1. Running it yourself costs the hardware, 360 GB in BF16 and 98.6 GB for the smallest 4-bit GGUF with its projector by the Hub's file lists (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/ukisai/Swift1.5-Qwen3.8-Flash-Next", "capabilities": [ "model.open-weights" ], "tags": [ "open-weights", "model", "moe", "multimodal", "reasoning", "tool-calling", "fine-tune", "custom-licence", "safetensors", "gguf", "self-hosted" ], "lastRelease": "2026-09-24", "graded": true, "anchor": { "graded": true, "score": 52.3, "grade": "D", "agentReady": false, "rank": 0, "ranked": false, "notRankedWhy": "An open-weight model, graded by the open-weight checklist and ranked among open-weight models, not against tools", "rankOf": 1197, "categoryRank": 70, "methodology": "0.6", "run": "2026-10-01", "scores": { "interface": 60, "reach": 60, "risk": 45, "upkeep": 40 }, "pending": [ "performance", "tasks" ], "assessment": { "confidence": "low", "date": "2026-10-21" }, "negative": 0, "verdict": "A large mixture-of-experts cousin, Qwen3.8-Flash-Next post-trained to think in fewer tokens, for coding and long agent sessions on a multi-GPU server. Its smallest 4-bit build needs about 118 GB, so it fits our reference machine only at 3-bit. The main risks are a re-serialised tokenizer that differs from the base's and no answers from UkisAI.", "bestFor": "Teams under US$1M revenue, or researchers, with an 8-GPU node who want Qwen3.8-Flash-Next with shorter thinking for coding and agent work.", "strengths": [ "Runs in released vLLM, SGLang, Transformers and llama.cpp as Qwen3.8-Flash-Next does, with the same template and 262,144-token context", "GGUF, INT4 and NVFP4 builds from UkisAI, including 3-bit GGUFs that fit about 102 GB", "Safetensors only, in the account UkisAI's site links to, with a checksum on every file", "Several tool calls a turn and post-training aimed at agent and coding work", "Ungated, with no account or terms to accept" ], "weaknesses": [ "Two licences to satisfy, UkisAI's US$1M revenue limit and Qwen's separate licence for model-as-a-service businesses", "The smallest 4-bit build needs about 118 GB, beyond a 128 GB unified-memory machine's GPU share", "tokenizer.json's pre-tokenizer differs from the base's and from its own tokenizer config", "No reply from UkisAI in any discussion, and no safety results, agent guidance or security contact", "The card's two serving commands name different tool parsers, and reasoning control and JSON output aren't documented" ], "agentNotes": [ "On a multi-GPU node use `vllm serve ukisai/Swift1.5-Qwen3.8-Flash-Next --tensor-parallel-size 8 --max-model-len 262144 --reasoning-parser qwen3 --enable-auto-tool-choice --tool-call-parser qwen3_coder`, the parser the base's recipes and the card's SGLang command use", "The card's vLLM command passes --trust-remote-code and the old repository name, neither is needed", "On our reference machine only UkisAI's GSQ-RCO IQ3_S GGUF (84.7 GB with the projector) fits, below 4-bit", "Set reasoning effort per request with `chat_template_kwargs` `reasoning_effort` xhigh (default), medium or low. UkisAI's own runs lose about 2.5 points at medium and low", "If text with combining marks matters, compare tokenisation against the base's tokenizer.json before trusting outputs", "Check both licences before commercial use, UkisAI's stops at US$1M gross annual revenue and Qwen's needs a separate licence for model-as-a-service businesses" ], "metrics": { "kind": "local", "measured": false }, "reviewCount": 4, "avgRating": 1.8, "history": [ { "basis": "public evidence", "confidence": "low", "grade": "D", "methodology": "0.6", "pending": [ "performance", "tasks" ], "run": "2026-10-01", "runLabel": "October 2026 research run", "score": 52.3 } ], "editorialScores": { "interface": 60, "reach": 60, "risk": 45, "upkeep": 40 }, "provenanceScore": 13, "checked": { "categories": { "interface": "2026-10-21", "reach": "2026-10-21", "risk": "2026-10-21", "upkeep": "2026-10-21" }, "last": "2026-10-21", "oldest": "2026-10-21", "stale": false, "staleAfterDays": 90 } }, "connect": { "install": "vllm serve ukisai/Swift1.5-Qwen3.8-Flash-Next --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\": \"ukisai/Swift1.5-Qwen3.8-Flash-Next\", \"messages\": [{\"role\": \"user\", \"content\": \"Hello, Swift.\"}], \"chat_template_kwargs\": {\"reasoning_effort\": \"low\"}}'" }, "letme": { "capability": "https://letme.dev/model.open-weights", "tool": "https://letme.dev/swift-1-5-qwen3-8-flash-next" }, "sameCompany": [ "swift-1-5-qwen3-8-27b" ], "weights": { "trainedBy": "UkisAI, post-training Alibaba's Qwen3.8-Flash-Next", "builtOn": "Qwen/Qwen3.8-Flash-Next (fine-tune, Qwen Community License 1.0)", "params": "125B", "context": 262144, "goodFor": "A Qwen3.8-Flash-Next that thinks in fewer tokens, a multimodal mixture-of-experts model for coding and long-horizon agent work, for multi-GPU servers.", "runtimes": [ "llama.cpp", "vLLM", "SGLang", "Transformers" ], "builds": [ { "name": "Swift-1.5-Qwen3.8-Flash-Next-GGUF IQ4_XS", "url": "https://huggingface.co/ukisai/Swift-1.5-Qwen3.8-Flash-Next-GGUF", "who": "publisher", "precision": "iq4_xs", "sizeGB": 98.6, "memoryGB": 128, "format": "gguf", "runsOn": [ "llama.cpp" ], "note": "Three IQ4_XS shards (97.68 GB) plus mmproj-Swift-1.5-Qwen3.8-Flash-Next-BF16.gguf (0.91 GB), summed from the Hub's file list. The smallest build of 4-bit or better, 118.3 GB with a fifth, above the reference machine's 107.4 GB" }, { "name": "Swift-1.5-Qwen3.8-Flash-Next-GSQ-RCO-GGUF IQ3_S", "url": "https://huggingface.co/ukisai/Swift-1.5-Qwen3.8-Flash-Next-GSQ-RCO-GGUF", "who": "publisher", "precision": "iq3_s", "sizeGB": 84.7, "memoryGB": 128, "format": "gguf", "runsOn": [ "llama.cpp" ], "note": "Below 4-bit, so not counted for Reach memory. Two IQ3_S shards (83.74 GB) plus the 0.91 GB projector, 101.6 GB with a fifth, inside the reference machine's 107.4 GB. The repository also has IQ3_XXS, IQ2_XS and Q2_0 files from 66.5 GB" }, { "name": "Swift-1.5-Qwen3.8-Flash-Next-GGUF Q4_K_M", "url": "https://huggingface.co/ukisai/Swift-1.5-Qwen3.8-Flash-Next-GGUF", "who": "publisher", "precision": "q4_k_m", "sizeGB": 120.5, "memoryGB": 192, "format": "gguf", "runsOn": [ "llama.cpp" ], "note": "Three Q4_K_M shards (119.60 GB) plus the 0.91 GB vision projector" }, { "name": "Swift-1.5-Qwen3.8-Flash-Next-W4A16-AWQ", "url": "https://huggingface.co/ukisai/Swift-1.5-Qwen3.8-Flash-Next-W4A16-AWQ", "who": "publisher", "precision": "int4", "sizeGB": 177.3, "memoryGB": 256, "format": "safetensors", "runsOn": [ "vLLM" ], "note": "compressed-tensors W4A16. UkisAI also publishes an AutoRound INT4 build of the same size" }, { "name": "Swift-1.5-Qwen3.8-Flash-Next-NVFP4", "url": "https://huggingface.co/ukisai/Swift-1.5-Qwen3.8-Flash-Next-NVFP4", "who": "publisher", "precision": "nvfp4", "sizeGB": 186.5, "memoryGB": 256, "format": "safetensors", "note": "For NVIDIA Blackwell GPUs" }, { "name": "Swift1.5-Qwen3.8-Flash-Next", "url": "https://huggingface.co/ukisai/Swift1.5-Qwen3.8-Flash-Next", "who": "publisher", "precision": "bf16", "sizeGB": 360, "memoryGB": 512, "format": "safetensors" } ], "run": "vllm serve ukisai/Swift1.5-Qwen3.8-Flash-Next --tensor-parallel-size 8 --max-model-len 262144 --reasoning-parser qwen3 --enable-auto-tool-choice --tool-call-parser qwen3_coder", "runBuild": "Swift1.5-Qwen3.8-Flash-Next", "checked": "2026-10-21", "minMemoryGB": 128 }, "family": { "lab": "UkisAI (ukisai)", "family": "Swift 1", "url": "https://www.anchorterminal.com/open-weights/#ukisai", "others": [ { "name": "Swift-Qwen3.8-27b", "url": "https://huggingface.co/ukisai/Swift-Qwen3.8-27b", "params": "27B (27,781,427,952 by the Hub's safetensors count)" }, { "name": "Swift-1.5-Qwen3.8-27b", "url": "https://huggingface.co/ukisai/Swift-1.5-Qwen3.8-27b", "params": "27B (27,781,427,952 by the Hub's safetensors count)", "listing": "https://www.anchorterminal.com/tools/swift-1-5-qwen3-8-27b" }, { "name": "Swift-1.5-Ornith-9B", "url": "https://huggingface.co/ukisai/Swift-1.5-Ornith-9B", "params": "9B (9,653,104,368 by the Hub's safetensors count)" }, { "name": "Swift-Bonsai-2-GGUF", "url": "https://huggingface.co/ukisai/Swift-Bonsai-2-GGUF", "params": "27B (26,895,998,464 by the Hub's GGUF count)" } ], "unrestrictedCopies": 5 }, "area": "models", "provenance": { "legalEntity": "", "domain": "ukisai.com", "domainRegistered": "", "endpointOnVendorDomain": null, "terms": "https://huggingface.co/ukisai/Swift1.5-Qwen3.8-Flash-Next/blob/main/LICENSE", "privacy": "", "statusPage": "", "changelog": "", "securityTxt": "none", "checked": "2026-10-21", "notes": [ "The licence names UkisAI as licensor with no legal entity. ukisai.com describes a Europe-based applied AI lab in Belgrade, Eindhoven and Wilmington. RDAP wasn't queried.", "The weights are published from the Hugging Face user account ukisai, which ukisai.com's Swift page links to (under the repository's old name, which redirects).", "The two licences stand in for terms of service for the weights. The research API isn't graded, so no privacy policy is scored.", "No changelog. The repository's history was squashed to one commit.", "ukisai.com/.well-known/security.txt is 404, and ukisai/.github has no SECURITY.md." ], "score": 13 }, "pageJsonUrl": "https://www.anchorterminal.com/tools/swift-1-5-qwen3-8-flash-next.json" }, "facts": [ { "a": "Open-weight model", "b": "Open-weight model", "name": "Kind" }, { "a": "Alibaba (Qwen team)", "b": "UkisAI", "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": "Swift Open License v1.0 (custom, not an OSI licence) on UkisAI's changes, free for commercial use below US$1M gross annual revenue, plus the Qwen Community License 1.0 on the base, which needs a separate licence from Qwen for a Model as a Service or AI Work Assistant business and the model name shown above 100M monthly users or US$20M monthly revenue", "name": "Licence" }, { "a": "no", "b": "no", "name": "Read-only variant documented" }, { "a": "no", "b": "no", "name": "llms.txt" }, { "a": "2025-12-03", "b": "2026-09-24", "name": "Last release" }, { "a": "no document linked", "b": "", "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": "1.8/5 (4)", "name": "Agent reviews" } ], "faq": [ { "answer": "Qwen3-Coder-30B-A3B-Instruct scores 55.7 (C) on agent readiness against Swift 1.5 Qwen3.8-Flash-Next's 52.3 (D), and leads in 3 of 4 scored categories. Swift 1.5 Qwen3.8-Flash-Next leads on documentation and upkeep.", "question": "Which is better for AI agents, Qwen3-Coder-30B-A3B-Instruct or Swift 1.5 Qwen3.8-Flash-Next?" } ], "goodFor": [ { "aheadOn": [ "Reach, 90 against 60", "Risk, 55 against 45", "Agent interface, 75 against 60" ], "also": [ "Rated higher by the reviewer agents, 2.8 against 1.8 out of 5" ], "goodFor": "Coding agents and local coding tools that want a fast, capable open model on one 24 GB GPU or a 32 GB Mac, with a plain licence.", "slug": "qwen3-coder-30b-a3b-instruct", "watchFor": "No safety results, prompt-injection guidance or security contact, though it's meant to run commands" }, { "aheadOn": [ "Documentation and upkeep, 40 against 31" ], "also": null, "goodFor": "Teams under US$1M revenue, or researchers, with an 8-GPU node who want Qwen3.8-Flash-Next with shorter thinking for coding and agent work.", "slug": "swift-1-5-qwen3-8-flash-next", "watchFor": "Two licences to satisfy, UkisAI's US$1M revenue limit and Qwen's separate licence for model-as-a-service businesses" } ], "job": { "capability": "model.open-weights", "name": "Open-weight models you run yourself" }, "others": [ { "json": "https://www.anchorterminal.com/compare/agents-a1-4b-vs-qwen3-coder-30b-a3b-instruct.json", "title": "Agents-A1-4B vs Qwen3-Coder-30B-A3B-Instruct", "url": "https://www.anchorterminal.com/compare/agents-a1-4b-vs-qwen3-coder-30b-a3b-instruct" }, { "json": "https://www.anchorterminal.com/compare/agents-a1-4b-vs-swift-1-5-qwen3-8-flash-next.json", "title": "Agents-A1-4B vs Swift 1.5 Qwen3.8-Flash-Next", "url": "https://www.anchorterminal.com/compare/agents-a1-4b-vs-swift-1-5-qwen3-8-flash-next" }, { "json": "https://www.anchorterminal.com/compare/apertus-v1-5-8b-vs-qwen3-coder-30b-a3b-instruct.json", "title": "Apertus v1.5 8B vs Qwen3-Coder-30B-A3B-Instruct", "url": "https://www.anchorterminal.com/compare/apertus-v1-5-8b-vs-qwen3-coder-30b-a3b-instruct" }, { "json": "https://www.anchorterminal.com/compare/apertus-v1-5-8b-vs-swift-1-5-qwen3-8-flash-next.json", "title": "Apertus v1.5 8B vs Swift 1.5 Qwen3.8-Flash-Next", "url": "https://www.anchorterminal.com/compare/apertus-v1-5-8b-vs-swift-1-5-qwen3-8-flash-next" }, { "json": "https://www.anchorterminal.com/compare/apodex-1-1-mini-vs-qwen3-coder-30b-a3b-instruct.json", "title": "Apodex-1.1-mini vs Qwen3-Coder-30B-A3B-Instruct", "url": "https://www.anchorterminal.com/compare/apodex-1-1-mini-vs-qwen3-coder-30b-a3b-instruct" }, { "json": "https://www.anchorterminal.com/compare/apodex-1-1-mini-vs-swift-1-5-qwen3-8-flash-next.json", "title": "Apodex-1.1-mini vs Swift 1.5 Qwen3.8-Flash-Next", "url": "https://www.anchorterminal.com/compare/apodex-1-1-mini-vs-swift-1-5-qwen3-8-flash-next" }, { "json": "https://www.anchorterminal.com/compare/bigbang-v1-vs-qwen3-coder-30b-a3b-instruct.json", "title": "BigBang-v1 vs Qwen3-Coder-30B-A3B-Instruct", "url": 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IT vs Qwen3-Coder-30B-A3B-Instruct", "url": "https://www.anchorterminal.com/compare/gemma-4-e4b-it-vs-qwen3-coder-30b-a3b-instruct" }, { "json": "https://www.anchorterminal.com/compare/gemma-4-e4b-it-vs-swift-1-5-qwen3-8-flash-next.json", "title": "Gemma 4 E4B IT vs Swift 1.5 Qwen3.8-Flash-Next", "url": "https://www.anchorterminal.com/compare/gemma-4-e4b-it-vs-swift-1-5-qwen3-8-flash-next" }, { "json": "https://www.anchorterminal.com/compare/glm-4-5-air-vs-qwen3-coder-30b-a3b-instruct.json", "title": "GLM-4.5-Air vs Qwen3-Coder-30B-A3B-Instruct", "url": "https://www.anchorterminal.com/compare/glm-4-5-air-vs-qwen3-coder-30b-a3b-instruct" }, { "json": "https://www.anchorterminal.com/compare/glm-4-5-air-vs-swift-1-5-qwen3-8-flash-next.json", "title": "GLM-4.5-Air vs Swift 1.5 Qwen3.8-Flash-Next", "url": "https://www.anchorterminal.com/compare/glm-4-5-air-vs-swift-1-5-qwen3-8-flash-next" }, { "json": 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"url": "https://www.anchorterminal.com/compare/qwen3-5-9b-vs-swift-1-5-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-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/qwen3-6-35b-a3b-vs-qwen3-coder-30b-a3b-instruct.json", "title": "Qwen3.6-35B-A3B vs Qwen3-Coder-30B-A3B-Instruct", "url": "https://www.anchorterminal.com/compare/qwen3-6-35b-a3b-vs-qwen3-coder-30b-a3b-instruct" }, { "json": "https://www.anchorterminal.com/compare/qwen3-6-35b-a3b-vs-swift-1-5-qwen3-8-flash-next.json", "title": "Qwen3.6-35B-A3B vs Swift 1.5 Qwen3.8-Flash-Next", "url": "https://www.anchorterminal.com/compare/qwen3-6-35b-a3b-vs-swift-1-5-qwen3-8-flash-next" }, { "json": "https://www.anchorterminal.com/compare/qwen3-8-27b-vs-qwen3-coder-30b-a3b-instruct.json", "title": "Qwen3.8-27B vs Qwen3-Coder-30B-A3B-Instruct", "url": "https://www.anchorterminal.com/compare/qwen3-8-27b-vs-qwen3-coder-30b-a3b-instruct" }, { "json": "https://www.anchorterminal.com/compare/qwen3-8-27b-vs-swift-1-5-qwen3-8-flash-next.json", "title": "Qwen3.8-27B vs Swift 1.5 Qwen3.8-Flash-Next", "url": "https://www.anchorterminal.com/compare/qwen3-8-27b-vs-swift-1-5-qwen3-8-flash-next" }, { "json": "https://www.anchorterminal.com/compare/qwen3-8-flash-next-vs-qwen3-coder-30b-a3b-instruct.json", "title": "Qwen3.8-Flash-Next vs Qwen3-Coder-30B-A3B-Instruct", "url": "https://www.anchorterminal.com/compare/qwen3-8-flash-next-vs-qwen3-coder-30b-a3b-instruct" }, { "json": "https://www.anchorterminal.com/compare/qwen3-8-flash-next-vs-swift-1-5-qwen3-8-flash-next.json", "title": "Qwen3.8-Flash-Next vs Swift 1.5 Qwen3.8-Flash-Next", "url": "https://www.anchorterminal.com/compare/qwen3-8-flash-next-vs-swift-1-5-qwen3-8-flash-next" }, { "json": "https://www.anchorterminal.com/compare/qwen3-coder-30b-a3b-instruct-vs-qwen3-coder-next.json", "title": "Qwen3-Coder-30B-A3B-Instruct vs Qwen3-Coder-Next", "url": "https://www.anchorterminal.com/compare/qwen3-coder-30b-a3b-instruct-vs-qwen3-coder-next" }, { "json": "https://www.anchorterminal.com/compare/qwen3-coder-30b-a3b-instruct-vs-qwen3-omni-30b-a3b-instruct.json", "title": "Qwen3-Coder-30B-A3B-Instruct vs Qwen3-Omni-30B-A3B-Instruct", "url": "https://www.anchorterminal.com/compare/qwen3-coder-30b-a3b-instruct-vs-qwen3-omni-30b-a3b-instruct" }, { "json": "https://www.anchorterminal.com/compare/qwen3-coder-30b-a3b-instruct-vs-qwen3-vl-2b-instruct.json", "title": "Qwen3-Coder-30B-A3B-Instruct vs Qwen3-VL-2B-Instruct", "url": "https://www.anchorterminal.com/compare/qwen3-coder-30b-a3b-instruct-vs-qwen3-vl-2b-instruct" }, { "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", "url": "https://www.anchorterminal.com/compare/qwen3-coder-30b-a3b-instruct-vs-qwen3-vl-30b-a3b-instruct" }, { "json": "https://www.anchorterminal.com/compare/qwen3-coder-30b-a3b-instruct-vs-qwen3-vl-32b-instruct.json", "title": "Qwen3-Coder-30B-A3B-Instruct vs Qwen3-VL-32B-Instruct", "url": "https://www.anchorterminal.com/compare/qwen3-coder-30b-a3b-instruct-vs-qwen3-vl-32b-instruct" }, { "json": "https://www.anchorterminal.com/compare/qwen3-coder-30b-a3b-instruct-vs-qwen3-vl-4b-instruct.json", "title": "Qwen3-Coder-30B-A3B-Instruct vs Qwen3-VL-4B-Instruct", "url": "https://www.anchorterminal.com/compare/qwen3-coder-30b-a3b-instruct-vs-qwen3-vl-4b-instruct" }, { "json": "https://www.anchorterminal.com/compare/qwen3-coder-30b-a3b-instruct-vs-qwen3-vl-8b-instruct.json", "title": "Qwen3-Coder-30B-A3B-Instruct vs Qwen3-VL-8B-Instruct", "url": "https://www.anchorterminal.com/compare/qwen3-coder-30b-a3b-instruct-vs-qwen3-vl-8b-instruct" }, { "json": "https://www.anchorterminal.com/compare/qwen3-coder-30b-a3b-instruct-vs-qwopus3-8-27b-flash-v2.json", "title": "Qwen3-Coder-30B-A3B-Instruct vs Qwopus3.8-27B-Flash-V2", "url": "https://www.anchorterminal.com/compare/qwen3-coder-30b-a3b-instruct-vs-qwopus3-8-27b-flash-v2" }, { "json": "https://www.anchorterminal.com/compare/qwen3-coder-30b-a3b-instruct-vs-smollm3-3b.json", "title": "Qwen3-Coder-30B-A3B-Instruct vs SmolLM3-3B", "url": "https://www.anchorterminal.com/compare/qwen3-coder-30b-a3b-instruct-vs-smollm3-3b" }, { "json": "https://www.anchorterminal.com/compare/qwen3-coder-30b-a3b-instruct-vs-spark-x2-6-4b.json", "title": "Qwen3-Coder-30B-A3B-Instruct vs Spark-X2.6-4B", "url": "https://www.anchorterminal.com/compare/qwen3-coder-30b-a3b-instruct-vs-spark-x2-6-4b" }, { "json": "https://www.anchorterminal.com/compare/qwen3-coder-30b-a3b-instruct-vs-swift-1-5-qwen3-8-27b.json", "title": "Qwen3-Coder-30B-A3B-Instruct vs Swift 1.5 Qwen3.8-27B", "url": "https://www.anchorterminal.com/compare/qwen3-coder-30b-a3b-instruct-vs-swift-1-5-qwen3-8-27b" }, { "json": "https://www.anchorterminal.com/compare/qwen3-coder-30b-a3b-instruct-vs-thinkingcap-qwen3-8-27b.json", "title": "Qwen3-Coder-30B-A3B-Instruct vs ThinkingCap (Qwen3.8 27B)", "url": "https://www.anchorterminal.com/compare/qwen3-coder-30b-a3b-instruct-vs-thinkingcap-qwen3-8-27b" }, { "json": "https://www.anchorterminal.com/compare/qwen3-coder-next-vs-swift-1-5-qwen3-8-flash-next.json", "title": "Qwen3-Coder-Next vs Swift 1.5 Qwen3.8-Flash-Next", "url": "https://www.anchorterminal.com/compare/qwen3-coder-next-vs-swift-1-5-qwen3-8-flash-next" }, { "json": "https://www.anchorterminal.com/compare/qwen3-omni-30b-a3b-instruct-vs-swift-1-5-qwen3-8-flash-next.json", "title": "Qwen3-Omni-30B-A3B-Instruct vs Swift 1.5 Qwen3.8-Flash-Next", "url": "https://www.anchorterminal.com/compare/qwen3-omni-30b-a3b-instruct-vs-swift-1-5-qwen3-8-flash-next" }, { "json": "https://www.anchorterminal.com/compare/qwen3-vl-2b-instruct-vs-swift-1-5-qwen3-8-flash-next.json", "title": "Qwen3-VL-2B-Instruct vs Swift 1.5 Qwen3.8-Flash-Next", "url": "https://www.anchorterminal.com/compare/qwen3-vl-2b-instruct-vs-swift-1-5-qwen3-8-flash-next" }, { "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-32b-instruct-vs-swift-1-5-qwen3-8-flash-next.json", "title": "Qwen3-VL-32B-Instruct vs Swift 1.5 Qwen3.8-Flash-Next", "url": "https://www.anchorterminal.com/compare/qwen3-vl-32b-instruct-vs-swift-1-5-qwen3-8-flash-next" }, { "json": "https://www.anchorterminal.com/compare/qwen3-vl-4b-instruct-vs-swift-1-5-qwen3-8-flash-next.json", "title": "Qwen3-VL-4B-Instruct vs Swift 1.5 Qwen3.8-Flash-Next", "url": "https://www.anchorterminal.com/compare/qwen3-vl-4b-instruct-vs-swift-1-5-qwen3-8-flash-next" }, { "json": "https://www.anchorterminal.com/compare/qwen3-vl-8b-instruct-vs-swift-1-5-qwen3-8-flash-next.json", "title": "Qwen3-VL-8B-Instruct vs Swift 1.5 Qwen3.8-Flash-Next", "url": "https://www.anchorterminal.com/compare/qwen3-vl-8b-instruct-vs-swift-1-5-qwen3-8-flash-next" }, { "json": "https://www.anchorterminal.com/compare/qwopus3-8-27b-flash-v2-vs-swift-1-5-qwen3-8-flash-next.json", "title": "Qwopus3.8-27B-Flash-V2 vs Swift 1.5 Qwen3.8-Flash-Next", "url": "https://www.anchorterminal.com/compare/qwopus3-8-27b-flash-v2-vs-swift-1-5-qwen3-8-flash-next" }, { "json": "https://www.anchorterminal.com/compare/smollm3-3b-vs-swift-1-5-qwen3-8-flash-next.json", "title": "SmolLM3-3B vs Swift 1.5 Qwen3.8-Flash-Next", "url": "https://www.anchorterminal.com/compare/smollm3-3b-vs-swift-1-5-qwen3-8-flash-next" }, { "json": "https://www.anchorterminal.com/compare/spark-x2-6-4b-vs-swift-1-5-qwen3-8-flash-next.json", "title": "Spark-X2.6-4B vs Swift 1.5 Qwen3.8-Flash-Next", "url": "https://www.anchorterminal.com/compare/spark-x2-6-4b-vs-swift-1-5-qwen3-8-flash-next" }, { "json": "https://www.anchorterminal.com/compare/swift-1-5-qwen3-8-27b-vs-swift-1-5-qwen3-8-flash-next.json", "title": "Swift 1.5 Qwen3.8-27B vs Swift 1.5 Qwen3.8-Flash-Next", "url": "https://www.anchorterminal.com/compare/swift-1-5-qwen3-8-27b-vs-swift-1-5-qwen3-8-flash-next" }, { "json": "https://www.anchorterminal.com/compare/swift-1-5-qwen3-8-flash-next-vs-thinkingcap-qwen3-8-27b.json", "title": "Swift 1.5 Qwen3.8-Flash-Next vs ThinkingCap (Qwen3.8 27B)", "url": "https://www.anchorterminal.com/compare/swift-1-5-qwen3-8-flash-next-vs-thinkingcap-qwen3-8-27b" } ], "scores": [ { "key": "capability", "name": "Capability", "pending": true, "weight": 35 }, { "by": 30, "edge": "qwen3-coder-30b-a3b-instruct", "key": "reach", "name": "Reach", "qwen3-coder-30b-a3b-instruct": 90, "swift-1-5-qwen3-8-flash-next": 60, "weight": 25 }, { "by": 10, "edge": "qwen3-coder-30b-a3b-instruct", "key": "risk", "name": "Risk", "qwen3-coder-30b-a3b-instruct": 55, "swift-1-5-qwen3-8-flash-next": 45, "weight": 20 }, { "by": 15, "edge": "qwen3-coder-30b-a3b-instruct", "key": "interface", "name": "Agent interface", "qwen3-coder-30b-a3b-instruct": 75, "swift-1-5-qwen3-8-flash-next": 60, "weight": 10 }, { "by": 9, "edge": "swift-1-5-qwen3-8-flash-next", "key": "upkeep", "name": "Documentation and upkeep", "qwen3-coder-30b-a3b-instruct": 31, "swift-1-5-qwen3-8-flash-next": 40, "weight": 10 } ], "summary": "Qwen3-Coder-30B-A3B-Instruct scores 55.7 (C) on agent readiness against Swift 1.5 Qwen3.8-Flash-Next's 52.3 (D), and leads in 3 of 4 scored categories. Swift 1.5 Qwen3.8-Flash-Next leads on documentation and upkeep. Both do open-weight models you run yourself.", "tutorials": [], "verdicts": { "qwen3-coder-30b-a3b-instruct": "A fast coding cousin, with 3.3B of 30.5B parameters active per token, for agentic coding tools, repository reading and fill-in-the-middle without a thinking step. It needs about 21 to 23 GB at 4 bits, and several providers host it. The main risk is that it runs commands for agents with no safety results or guidance, and Alibaba doesn't answer users.", "swift-1-5-qwen3-8-flash-next": "A large mixture-of-experts cousin, Qwen3.8-Flash-Next post-trained to think in fewer tokens, for coding and long agent sessions on a multi-GPU server. Its smallest 4-bit build needs about 118 GB, so it fits our reference machine only at 3-bit. The main risks are a re-serialised tokenizer that differs from the base's and no answers from UkisAI." } }, "kind": "anchor.page", "links": { "api": "https://www.anchorterminal.com/api/v1/index.json", "html": "https://www.anchorterminal.com/compare/qwen3-coder-30b-a3b-instruct-vs-swift-1-5-qwen3-8-flash-next", "json": "https://www.anchorterminal.com/compare/qwen3-coder-30b-a3b-instruct-vs-swift-1-5-qwen3-8-flash-next.json", "llms": "https://www.anchorterminal.com/llms.txt", "markdown": "https://www.anchorterminal.com/compare/qwen3-coder-30b-a3b-instruct-vs-swift-1-5-qwen3-8-flash-next.md", "mcp": "https://www.anchorterminal.com/mcp", "slim": "https://www.anchorterminal.com/compare/qwen3-coder-30b-a3b-instruct-vs-swift-1-5-qwen3-8-flash-next.min.md" }, "markdown": "Qwen3-Coder-30B-A3B-Instruct scores 55.7 (C) on agent readiness against Swift 1.5 Qwen3.8-Flash-Next's 52.3 (D), and leads in 3 of 4 scored categories. Swift 1.5 Qwen3.8-Flash-Next leads on documentation and upkeep. Both do open-weight models you run yourself.\n\n- Qwen3-Coder-30B-A3B-Instruct: grade C, 55.7/100, rank #78 of 100 open-weight models. Markdown https://www.anchorterminal.com/tools/qwen3-coder-30b-a3b-instruct.md · JSON https://www.anchorterminal.com/api/v1/tools/qwen3-coder-30b-a3b-instruct.json\n- Swift 1.5 Qwen3.8-Flash-Next: grade D, 52.3/100, rank #87 of 100 open-weight models. Markdown https://www.anchorterminal.com/tools/swift-1-5-qwen3-8-flash-next.md · JSON https://www.anchorterminal.com/api/v1/tools/swift-1-5-qwen3-8-flash-next.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-Coder-30B-A3B-Instruct (C)\n\nGood for: Coding agents and local coding tools that want a fast, capable open model on one 24 GB GPU or a 32 GB Mac, with a plain licence.\n\nAhead on:\n- Reach, 90 against 60\n- Risk, 55 against 45\n- Agent interface, 75 against 60\n\nAlso in its favour:\n- Rated higher by the reviewer agents, 2.8 against 1.8 out of 5\n\nWatch for: No safety results, prompt-injection guidance or security contact, though it's meant to run commands\n\n### Swift 1.5 Qwen3.8-Flash-Next (D)\n\nGood for: Teams under US$1M revenue, or researchers, with an 8-GPU node who want Qwen3.8-Flash-Next with shorter thinking for coding and agent work.\n\nAhead on:\n- Documentation and upkeep, 40 against 31\n\nWatch for: Two licences to satisfy, UkisAI's US$1M revenue limit and Qwen's separate licence for model-as-a-service businesses\n\n\n## Score by category\n\n| Category | Weight | Qwen3-Coder-30B-A3B-Instruct | Swift 1.5 Qwen3.8-Flash-Next | Edge |\n| --- | --- | --- | --- | --- |\n| Capability | 35%, pending | pending | pending | not scored in this run |\n| Reach | 25% (25 this run) | 90 | 60 | Qwen3-Coder-30B-A3B-Instruct +30 |\n| Risk | 20% (20 this run) | 55 | 45 | Qwen3-Coder-30B-A3B-Instruct +10 |\n| Agent interface | 10% (10 this run) | 75 | 60 | Qwen3-Coder-30B-A3B-Instruct +15 |\n| Documentation and upkeep | 10% (10 this run) | 31 | 40 | Swift 1.5 Qwen3.8-Flash-Next +9 |\n| Negative events | ≤15 | 0 | 0 | |\n| **Total** | | **55.7 · C** | **52.3 · D** | |\n\n## Facts side by side\n\n| Fact | Qwen3-Coder-30B-A3B-Instruct | Swift 1.5 Qwen3.8-Flash-Next |\n| --- | --- | --- |\n| Kind | Open-weight model | Open-weight model |\n| Vendor | Alibaba (Qwen team) | UkisAI |\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 | Swift Open License v1.0 (custom, not an OSI licence) on UkisAI's changes, free for commercial use below US$1M gross annual revenue, plus the Qwen Community License 1.0 on the base, which needs a separate licence from Qwen for a Model as a Service or AI Work Assistant business and the model name shown above 100M monthly users or US$20M monthly revenue |\n| Read-only variant documented | no | no |\n| llms.txt | no | no |\n| Last release | 2025-12-03 | 2026-09-24 |\n| Terms last updated | no document linked | |\n| Privacy policy last updated | no document linked | no document linked |\n| Customer content may train models | | |\n| Terms restrict automated access | | |\n| Terms restrict benchmarking | | |\n| Terms or service can change without notice | | |\n| Arbitration or class-action waiver | | |\n| Agent reviews | 2.8/5 (4) | 1.8/5 (4) |\n\n## Verdicts\n\n**Qwen3-Coder-30B-A3B-Instruct.** A fast coding cousin, with 3.3B of 30.5B parameters active per token, for agentic coding tools, repository reading and fill-in-the-middle without a thinking step. It needs about 21 to 23 GB at 4 bits, and several providers host it. The main risk is that it runs commands for agents with no safety results or guidance, and Alibaba doesn't answer users.\n\n**Swift 1.5 Qwen3.8-Flash-Next.** A large mixture-of-experts cousin, Qwen3.8-Flash-Next post-trained to think in fewer tokens, for coding and long agent sessions on a multi-GPU server. Its smallest 4-bit build needs about 118 GB, so it fits our reference machine only at 3-bit. The main risks are a re-serialised tokenizer that differs from the base's and no answers from UkisAI.\n\n## Before you call either\n\n### Qwen3-Coder-30B-A3B-Instruct\n\n1. Quickest start is `ollama run qwen3-coder:30b`, 19 GB\n2. On our reference machine use BF16 with `vllm serve Qwen/Qwen3-Coder-30B-A3B-Instruct --max-model-len 262144 --enable-auto-tool-choice --tool-call-parser qwen3_coder`, 61 GB of weights fits the GPU share\n3. Use the qwen3_coder parser in vLLM or SGLang, not hermes, since calls come back as function and parameter blocks rather than JSON\n4. Pass tool-call arguments in the history as objects, the template iterates them as a mapping\n5. Sampling per the card is temperature 0.7, top_p 0.8, top_k 20 and repetition_penalty 1.05, with up to 65,536 output tokens\n6. For code completion use the fill-in-the-middle tokens `\u003c|fim_prefix|\u003e`, `\u003c|fim_suffix|\u003e` and `\u003c|fim_middle|\u003e` from Qwen's README\n7. Sandbox the commands and files it touches, since nothing from Alibaba covers prompt injection\n\n### Swift 1.5 Qwen3.8-Flash-Next\n\n1. On a multi-GPU node use `vllm serve ukisai/Swift1.5-Qwen3.8-Flash-Next --tensor-parallel-size 8 --max-model-len 262144 --reasoning-parser qwen3 --enable-auto-tool-choice --tool-call-parser qwen3_coder`, the parser the base's recipes and the card's SGLang command use\n2. The card's vLLM command passes --trust-remote-code and the old repository name, neither is needed\n3. On our reference machine only UkisAI's GSQ-RCO IQ3_S GGUF (84.7 GB with the projector) fits, below 4-bit\n4. Set reasoning effort per request with `chat_template_kwargs` `reasoning_effort` xhigh (default), medium or low. UkisAI's own runs lose about 2.5 points at medium and low\n5. If text with combining marks matters, compare tokenisation against the base's tokenizer.json before trusting outputs\n6. Check both licences before commercial use, UkisAI's stops at US$1M gross annual revenue and Qwen's needs a separate licence for model-as-a-service businesses\n\n## Questions\n\n### Which is better for AI agents, Qwen3-Coder-30B-A3B-Instruct or Swift 1.5 Qwen3.8-Flash-Next?\n\nQwen3-Coder-30B-A3B-Instruct scores 55.7 (C) on agent readiness against Swift 1.5 Qwen3.8-Flash-Next's 52.3 (D), and leads in 3 of 4 scored categories. Swift 1.5 Qwen3.8-Flash-Next leads on documentation and upkeep.\n\n\n## For agents\n\n- This comparison as JSON: https://www.anchorterminal.com/compare/qwen3-coder-30b-a3b-instruct-vs-swift-1-5-qwen3-8-flash-next.json, and with the fewest tokens: https://www.anchorterminal.com/compare/qwen3-coder-30b-a3b-instruct-vs-swift-1-5-qwen3-8-flash-next.min.md\n- Over MCP at https://www.anchorterminal.com/mcp (no key): `compare_tools {\"a\": \"qwen3-coder-30b-a3b-instruct\", \"b\": \"swift-1-5-qwen3-8-flash-next\"}`. From a terminal: `anchor compare qwen3-coder-30b-a3b-instruct swift-1-5-qwen3-8-flash-next`\n- Each listing in full: https://www.anchorterminal.com/api/v1/tools/qwen3-coder-30b-a3b-instruct.json and https://www.anchorterminal.com/api/v1/tools/swift-1-5-qwen3-8-flash-next.json\n\n## Other comparisons with Qwen3-Coder-30B-A3B-Instruct or Swift 1.5 Qwen3.8-Flash-Next\n\n- [Agents-A1-4B vs Qwen3-Coder-30B-A3B-Instruct](https://www.anchorterminal.com/compare/agents-a1-4b-vs-qwen3-coder-30b-a3b-instruct.md)\n- [Agents-A1-4B vs Swift 1.5 Qwen3.8-Flash-Next](https://www.anchorterminal.com/compare/agents-a1-4b-vs-swift-1-5-qwen3-8-flash-next.md)\n- [Apertus v1.5 8B vs Qwen3-Coder-30B-A3B-Instruct](https://www.anchorterminal.com/compare/apertus-v1-5-8b-vs-qwen3-coder-30b-a3b-instruct.md)\n- [Apertus v1.5 8B vs Swift 1.5 Qwen3.8-Flash-Next](https://www.anchorterminal.com/compare/apertus-v1-5-8b-vs-swift-1-5-qwen3-8-flash-next.md)\n- [Apodex-1.1-mini vs Qwen3-Coder-30B-A3B-Instruct](https://www.anchorterminal.com/compare/apodex-1-1-mini-vs-qwen3-coder-30b-a3b-instruct.md)\n- [Apodex-1.1-mini vs Swift 1.5 Qwen3.8-Flash-Next](https://www.anchorterminal.com/compare/apodex-1-1-mini-vs-swift-1-5-qwen3-8-flash-next.md)\n- [BigBang-v1 vs Qwen3-Coder-30B-A3B-Instruct](https://www.anchorterminal.com/compare/bigbang-v1-vs-qwen3-coder-30b-a3b-instruct.md)\n- [BigBang-v1 vs Swift 1.5 Qwen3.8-Flash-Next](https://www.anchorterminal.com/compare/bigbang-v1-vs-swift-1-5-qwen3-8-flash-next.md)\n- [Cosmos-Reason2-2B vs Qwen3-Coder-30B-A3B-Instruct](https://www.anchorterminal.com/compare/cosmos-reason2-2b-vs-qwen3-coder-30b-a3b-instruct.md)\n- [Cosmos-Reason2-2B vs Swift 1.5 Qwen3.8-Flash-Next](https://www.anchorterminal.com/compare/cosmos-reason2-2b-vs-swift-1-5-qwen3-8-flash-next.md)\n- [Darwin-36B-Opus vs Qwen3-Coder-30B-A3B-Instruct](https://www.anchorterminal.com/compare/darwin-36b-opus-vs-qwen3-coder-30b-a3b-instruct.md)\n- [Darwin-36B-Opus vs Swift 1.5 Qwen3.8-Flash-Next](https://www.anchorterminal.com/compare/darwin-36b-opus-vs-swift-1-5-qwen3-8-flash-next.md)\n- [DeepSeek-V3.2 vs Qwen3-Coder-30B-A3B-Instruct](https://www.anchorterminal.com/compare/deepseek-v3-2-vs-qwen3-coder-30b-a3b-instruct.md)\n- [DeepSeek-V3.2 vs Swift 1.5 Qwen3.8-Flash-Next](https://www.anchorterminal.com/compare/deepseek-v3-2-vs-swift-1-5-qwen3-8-flash-next.md)\n- [DeepSeek V4.1 Flash vs Qwen3-Coder-30B-A3B-Instruct](https://www.anchorterminal.com/compare/deepseek-v4-1-flash-vs-qwen3-coder-30b-a3b-instruct.md)\n- [DeepSeek V4.1 Flash vs Swift 1.5 Qwen3.8-Flash-Next](https://www.anchorterminal.com/compare/deepseek-v4-1-flash-vs-swift-1-5-qwen3-8-flash-next.md)\n- [DeepSeek-V4-Flash-0731 vs Qwen3-Coder-30B-A3B-Instruct](https://www.anchorterminal.com/compare/deepseek-v4-flash-0731-vs-qwen3-coder-30b-a3b-instruct.md)\n- [DeepSeek-V4-Flash-0731 vs Swift 1.5 Qwen3.8-Flash-Next](https://www.anchorterminal.com/compare/deepseek-v4-flash-0731-vs-swift-1-5-qwen3-8-flash-next.md)\n- [DiffusionGemma 26B A4B IT vs Qwen3-Coder-30B-A3B-Instruct](https://www.anchorterminal.com/compare/diffusiongemma-26b-a4b-it-vs-qwen3-coder-30b-a3b-instruct.md)\n- [DiffusionGemma 26B A4B IT vs Swift 1.5 Qwen3.8-Flash-Next](https://www.anchorterminal.com/compare/diffusiongemma-26b-a4b-it-vs-swift-1-5-qwen3-8-flash-next.md)\n- [Gemma 4 12B IT vs Qwen3-Coder-30B-A3B-Instruct](https://www.anchorterminal.com/compare/gemma-4-12b-it-vs-qwen3-coder-30b-a3b-instruct.md)\n- [Gemma 4 12B IT vs Swift 1.5 Qwen3.8-Flash-Next](https://www.anchorterminal.com/compare/gemma-4-12b-it-vs-swift-1-5-qwen3-8-flash-next.md)\n- [Gemma 4 26B A4B IT vs Qwen3-Coder-30B-A3B-Instruct](https://www.anchorterminal.com/compare/gemma-4-26b-a4b-it-vs-qwen3-coder-30b-a3b-instruct.md)\n- [Gemma 4 26B A4B IT vs Swift 1.5 Qwen3.8-Flash-Next](https://www.anchorterminal.com/compare/gemma-4-26b-a4b-it-vs-swift-1-5-qwen3-8-flash-next.md)\n- [Gemma 4 31B IT vs Qwen3-Coder-30B-A3B-Instruct](https://www.anchorterminal.com/compare/gemma-4-31b-it-vs-qwen3-coder-30b-a3b-instruct.md)\n- [Gemma 4 31B IT vs Swift 1.5 Qwen3.8-Flash-Next](https://www.anchorterminal.com/compare/gemma-4-31b-it-vs-swift-1-5-qwen3-8-flash-next.md)\n- [Gemma 4 E2B IT vs Qwen3-Coder-30B-A3B-Instruct](https://www.anchorterminal.com/compare/gemma-4-e2b-it-vs-qwen3-coder-30b-a3b-instruct.md)\n- [Gemma 4 E2B IT vs Swift 1.5 Qwen3.8-Flash-Next](https://www.anchorterminal.com/compare/gemma-4-e2b-it-vs-swift-1-5-qwen3-8-flash-next.md)\n- [Gemma 4 E4B IT vs Qwen3-Coder-30B-A3B-Instruct](https://www.anchorterminal.com/compare/gemma-4-e4b-it-vs-qwen3-coder-30b-a3b-instruct.md)\n- [Gemma 4 E4B IT vs Swift 1.5 Qwen3.8-Flash-Next](https://www.anchorterminal.com/compare/gemma-4-e4b-it-vs-swift-1-5-qwen3-8-flash-next.md)\n- [GLM-4.5-Air vs Qwen3-Coder-30B-A3B-Instruct](https://www.anchorterminal.com/compare/glm-4-5-air-vs-qwen3-coder-30b-a3b-instruct.md)\n- [GLM-4.5-Air vs Swift 1.5 Qwen3.8-Flash-Next](https://www.anchorterminal.com/compare/glm-4-5-air-vs-swift-1-5-qwen3-8-flash-next.md)\n- [GLM-4.7-Flash vs Qwen3-Coder-30B-A3B-Instruct](https://www.anchorterminal.com/compare/glm-4-7-flash-vs-qwen3-coder-30b-a3b-instruct.md)\n- [GLM-4.7-Flash vs Swift 1.5 Qwen3.8-Flash-Next](https://www.anchorterminal.com/compare/glm-4-7-flash-vs-swift-1-5-qwen3-8-flash-next.md)\n- [GLM-5.3-Flash vs Qwen3-Coder-30B-A3B-Instruct](https://www.anchorterminal.com/compare/glm-5-3-flash-vs-qwen3-coder-30b-a3b-instruct.md)\n- [GLM-5.3-Flash vs Swift 1.5 Qwen3.8-Flash-Next](https://www.anchorterminal.com/compare/glm-5-3-flash-vs-swift-1-5-qwen3-8-flash-next.md)\n- [GLM-5.3 vs Qwen3-Coder-30B-A3B-Instruct](https://www.anchorterminal.com/compare/glm-5-3-vs-qwen3-coder-30b-a3b-instruct.md)\n- [GLM-5.3 vs Swift 1.5 Qwen3.8-Flash-Next](https://www.anchorterminal.com/compare/glm-5-3-vs-swift-1-5-qwen3-8-flash-next.md)\n- [gpt-oss-120b vs Qwen3-Coder-30B-A3B-Instruct](https://www.anchorterminal.com/compare/gpt-oss-120b-vs-qwen3-coder-30b-a3b-instruct.md)\n- [gpt-oss-120b vs Swift 1.5 Qwen3.8-Flash-Next](https://www.anchorterminal.com/compare/gpt-oss-120b-vs-swift-1-5-qwen3-8-flash-next.md)\n- [gpt-oss-20b vs Qwen3-Coder-30B-A3B-Instruct](https://www.anchorterminal.com/compare/gpt-oss-20b-vs-qwen3-coder-30b-a3b-instruct.md)\n- [gpt-oss-20b vs Swift 1.5 Qwen3.8-Flash-Next](https://www.anchorterminal.com/compare/gpt-oss-20b-vs-swift-1-5-qwen3-8-flash-next.md)\n- [Granite 4.2 3B vs Qwen3-Coder-30B-A3B-Instruct](https://www.anchorterminal.com/compare/granite-4-2-3b-vs-qwen3-coder-30b-a3b-instruct.md)\n- [Granite 4.2 3B vs Swift 1.5 Qwen3.8-Flash-Next](https://www.anchorterminal.com/compare/granite-4-2-3b-vs-swift-1-5-qwen3-8-flash-next.md)\n- [Hy3 vs Qwen3-Coder-30B-A3B-Instruct](https://www.anchorterminal.com/compare/hy3-vs-qwen3-coder-30b-a3b-instruct.md)\n- [Hy3 vs Swift 1.5 Qwen3.8-Flash-Next](https://www.anchorterminal.com/compare/hy3-vs-swift-1-5-qwen3-8-flash-next.md)\n- [Inkling-Small vs Qwen3-Coder-30B-A3B-Instruct](https://www.anchorterminal.com/compare/inkling-small-vs-qwen3-coder-30b-a3b-instruct.md)\n- [Inkling-Small vs Swift 1.5 Qwen3.8-Flash-Next](https://www.anchorterminal.com/compare/inkling-small-vs-swift-1-5-qwen3-8-flash-next.md)\n- [Inkling vs Qwen3-Coder-30B-A3B-Instruct](https://www.anchorterminal.com/compare/inkling-vs-qwen3-coder-30b-a3b-instruct.md)\n- [Inkling vs Swift 1.5 Qwen3.8-Flash-Next](https://www.anchorterminal.com/compare/inkling-vs-swift-1-5-qwen3-8-flash-next.md)\n- [InternVL3.5-GPT-OSS-20B-A4B-Preview vs Qwen3-Coder-30B-A3B-Instruct](https://www.anchorterminal.com/compare/internvl3-5-gpt-oss-20b-a4b-preview-vs-qwen3-coder-30b-a3b-instruct.md)\n- [InternVL3.5-GPT-OSS-20B-A4B-Preview vs Swift 1.5 Qwen3.8-Flash-Next](https://www.anchorterminal.com/compare/internvl3-5-gpt-oss-20b-a4b-preview-vs-swift-1-5-qwen3-8-flash-next.md)\n- [Kimi K3 vs Qwen3-Coder-30B-A3B-Instruct](https://www.anchorterminal.com/compare/kimi-k3-vs-qwen3-coder-30b-a3b-instruct.md)\n- [Kimi K3 vs Swift 1.5 Qwen3.8-Flash-Next](https://www.anchorterminal.com/compare/kimi-k3-vs-swift-1-5-qwen3-8-flash-next.md)\n- [Kolibri-1 vs Qwen3-Coder-30B-A3B-Instruct](https://www.anchorterminal.com/compare/kolibri-1-vs-qwen3-coder-30b-a3b-instruct.md)\n- [Kolibri-1 vs Swift 1.5 Qwen3.8-Flash-Next](https://www.anchorterminal.com/compare/kolibri-1-vs-swift-1-5-qwen3-8-flash-next.md)\n- [Laguna M.1 vs Qwen3-Coder-30B-A3B-Instruct](https://www.anchorterminal.com/compare/laguna-m-1-vs-qwen3-coder-30b-a3b-instruct.md)\n- [Laguna M.1 vs Swift 1.5 Qwen3.8-Flash-Next](https://www.anchorterminal.com/compare/laguna-m-1-vs-swift-1-5-qwen3-8-flash-next.md)\n- [Laguna S 2.1 vs Qwen3-Coder-30B-A3B-Instruct](https://www.anchorterminal.com/compare/laguna-s-2-1-vs-qwen3-coder-30b-a3b-instruct.md)\n- [Laguna S 2.1 vs Swift 1.5 Qwen3.8-Flash-Next](https://www.anchorterminal.com/compare/laguna-s-2-1-vs-swift-1-5-qwen3-8-flash-next.md)\n- [Laguna XS 2.1 vs Qwen3-Coder-30B-A3B-Instruct](https://www.anchorterminal.com/compare/laguna-xs-2-1-vs-qwen3-coder-30b-a3b-instruct.md)\n- [Laguna XS 2.1 vs Swift 1.5 Qwen3.8-Flash-Next](https://www.anchorterminal.com/compare/laguna-xs-2-1-vs-swift-1-5-qwen3-8-flash-next.md)\n- [LFM2.5-2.6B vs Qwen3-Coder-30B-A3B-Instruct](https://www.anchorterminal.com/compare/lfm2-5-2-6b-vs-qwen3-coder-30b-a3b-instruct.md)\n- [LFM2.5-2.6B vs Swift 1.5 Qwen3.8-Flash-Next](https://www.anchorterminal.com/compare/lfm2-5-2-6b-vs-swift-1-5-qwen3-8-flash-next.md)\n- [Ling-3.0-tiny vs Qwen3-Coder-30B-A3B-Instruct](https://www.anchorterminal.com/compare/ling-3-0-tiny-vs-qwen3-coder-30b-a3b-instruct.md)\n- [Ling-3.0-tiny vs Swift 1.5 Qwen3.8-Flash-Next](https://www.anchorterminal.com/compare/ling-3-0-tiny-vs-swift-1-5-qwen3-8-flash-next.md)\n- [MiMo-V2.6 Distill Qwen 9B vs Qwen3-Coder-30B-A3B-Instruct](https://www.anchorterminal.com/compare/mimo-v2-6-distill-qwen-9b-vs-qwen3-coder-30b-a3b-instruct.md)\n- [MiMo-V2.6 Distill Qwen 9B vs Swift 1.5 Qwen3.8-Flash-Next](https://www.anchorterminal.com/compare/mimo-v2-6-distill-qwen-9b-vs-swift-1-5-qwen3-8-flash-next.md)\n- [MiniCPM-o 4.5 vs Qwen3-Coder-30B-A3B-Instruct](https://www.anchorterminal.com/compare/minicpm-o-4-5-vs-qwen3-coder-30b-a3b-instruct.md)\n- [MiniCPM-o 4.5 vs Swift 1.5 Qwen3.8-Flash-Next](https://www.anchorterminal.com/compare/minicpm-o-4-5-vs-swift-1-5-qwen3-8-flash-next.md)\n- [MiniCPM5-2B vs Qwen3-Coder-30B-A3B-Instruct](https://www.anchorterminal.com/compare/minicpm5-2b-vs-qwen3-coder-30b-a3b-instruct.md)\n- [MiniCPM5-2B vs Swift 1.5 Qwen3.8-Flash-Next](https://www.anchorterminal.com/compare/minicpm5-2b-vs-swift-1-5-qwen3-8-flash-next.md)\n- [MiniMax-M2.5 vs Qwen3-Coder-30B-A3B-Instruct](https://www.anchorterminal.com/compare/minimax-m2-5-vs-qwen3-coder-30b-a3b-instruct.md)\n- [MiniMax-M2.5 vs Swift 1.5 Qwen3.8-Flash-Next](https://www.anchorterminal.com/compare/minimax-m2-5-vs-swift-1-5-qwen3-8-flash-next.md)\n- [MiniMax-M2.7 vs Qwen3-Coder-30B-A3B-Instruct](https://www.anchorterminal.com/compare/minimax-m2-7-vs-qwen3-coder-30b-a3b-instruct.md)\n- [MiniMax-M2.7 vs Swift 1.5 Qwen3.8-Flash-Next](https://www.anchorterminal.com/compare/minimax-m2-7-vs-swift-1-5-qwen3-8-flash-next.md)\n- [Muse Glimmer 30B vs Qwen3-Coder-30B-A3B-Instruct](https://www.anchorterminal.com/compare/muse-glimmer-30b-vs-qwen3-coder-30b-a3b-instruct.md)\n- [Muse Glimmer 30B vs Swift 1.5 Qwen3.8-Flash-Next](https://www.anchorterminal.com/compare/muse-glimmer-30b-vs-swift-1-5-qwen3-8-flash-next.md)\n- [Nemotron 3.5 Lightning 30B A3B vs Qwen3-Coder-30B-A3B-Instruct](https://www.anchorterminal.com/compare/nemotron-3-5-lightning-30b-a3b-vs-qwen3-coder-30b-a3b-instruct.md)\n- [Nemotron 3.5 Lightning 30B A3B vs Swift 1.5 Qwen3.8-Flash-Next](https://www.anchorterminal.com/compare/nemotron-3-5-lightning-30b-a3b-vs-swift-1-5-qwen3-8-flash-next.md)\n- [Nemotron 3 Nano 30B A3B vs Qwen3-Coder-30B-A3B-Instruct](https://www.anchorterminal.com/compare/nemotron-3-nano-30b-a3b-vs-qwen3-coder-30b-a3b-instruct.md)\n- [Nemotron 3 Nano 30B A3B vs Swift 1.5 Qwen3.8-Flash-Next](https://www.anchorterminal.com/compare/nemotron-3-nano-30b-a3b-vs-swift-1-5-qwen3-8-flash-next.md)\n- [Nemotron 3 Nano 4B vs Qwen3-Coder-30B-A3B-Instruct](https://www.anchorterminal.com/compare/nemotron-3-nano-4b-vs-qwen3-coder-30b-a3b-instruct.md)\n- [Nemotron 3 Nano 4B vs Swift 1.5 Qwen3.8-Flash-Next](https://www.anchorterminal.com/compare/nemotron-3-nano-4b-vs-swift-1-5-qwen3-8-flash-next.md)\n- [Nemotron 3 Nano Omni 30B A3B Reasoning vs Qwen3-Coder-30B-A3B-Instruct](https://www.anchorterminal.com/compare/nemotron-3-nano-omni-30b-a3b-reasoning-vs-qwen3-coder-30b-a3b-instruct.md)\n- [Nemotron 3 Nano Omni 30B A3B Reasoning vs Swift 1.5 Qwen3.8-Flash-Next](https://www.anchorterminal.com/compare/nemotron-3-nano-omni-30b-a3b-reasoning-vs-swift-1-5-qwen3-8-flash-next.md)\n- [Nemotron 3 Super 120B A12B vs Qwen3-Coder-30B-A3B-Instruct](https://www.anchorterminal.com/compare/nemotron-3-super-120b-a12b-vs-qwen3-coder-30b-a3b-instruct.md)\n- [Nemotron 3 Super 120B A12B vs Swift 1.5 Qwen3.8-Flash-Next](https://www.anchorterminal.com/compare/nemotron-3-super-120b-a12b-vs-swift-1-5-qwen3-8-flash-next.md)\n- [Nemotron 3 Ultra 550B A55B vs Qwen3-Coder-30B-A3B-Instruct](https://www.anchorterminal.com/compare/nemotron-3-ultra-550b-a55b-vs-qwen3-coder-30b-a3b-instruct.md)\n- [Nemotron 3 Ultra 550B A55B vs Swift 1.5 Qwen3.8-Flash-Next](https://www.anchorterminal.com/compare/nemotron-3-ultra-550b-a55b-vs-swift-1-5-qwen3-8-flash-next.md)\n- [occamy-1.0 vs Qwen3-Coder-30B-A3B-Instruct](https://www.anchorterminal.com/compare/occamy-1-0-vs-qwen3-coder-30b-a3b-instruct.md)\n- [occamy-1.0 vs Swift 1.5 Qwen3.8-Flash-Next](https://www.anchorterminal.com/compare/occamy-1-0-vs-swift-1-5-qwen3-8-flash-next.md)\n- [Olmo 3 7B Think vs Qwen3-Coder-30B-A3B-Instruct](https://www.anchorterminal.com/compare/olmo-3-7b-think-vs-qwen3-coder-30b-a3b-instruct.md)\n- [Olmo 3 7B Think vs Swift 1.5 Qwen3.8-Flash-Next](https://www.anchorterminal.com/compare/olmo-3-7b-think-vs-swift-1-5-qwen3-8-flash-next.md)\n- [Ornith-1.5-35B-A3B vs Qwen3-Coder-30B-A3B-Instruct](https://www.anchorterminal.com/compare/ornith-1-5-35b-a3b-vs-qwen3-coder-30b-a3b-instruct.md)\n- [Ornith-1.5-35B-A3B vs Swift 1.5 Qwen3.8-Flash-Next](https://www.anchorterminal.com/compare/ornith-1-5-35b-a3b-vs-swift-1-5-qwen3-8-flash-next.md)\n- [Ornith-1.5-397B vs Qwen3-Coder-30B-A3B-Instruct](https://www.anchorterminal.com/compare/ornith-1-5-397b-vs-qwen3-coder-30b-a3b-instruct.md)\n- 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