{
  "data": {
    "a": {
      "slug": "qwen3-coder-next",
      "name": "Qwen3-Coder-Next",
      "vendor": "Alibaba (Qwen team)",
      "vendorUrl": "https://qwen.ai",
      "kind": "weights",
      "category": "open-weights",
      "summary": "Qwen3-Coder-Next is Alibaba's open-weight coding-agent model, an 80B mixture-of-experts with 3B active and no thinking mode, trained for tool calling across many agent scaffolds with a 262,144-token context, published on Hugging Face in BF16, FP8 and GGUF under Apache 2.0.",
      "url": "https://www.anchorterminal.com/tools/qwen3-coder-next",
      "markdownUrl": "https://www.anchorterminal.com/tools/qwen3-coder-next.md",
      "slimMarkdownUrl": "https://www.anchorterminal.com/tools/qwen3-coder-next.min.md",
      "jsonUrl": "https://www.anchorterminal.com/api/v1/tools/qwen3-coder-next.json",
      "repo": "https://huggingface.co/Qwen/Qwen3-Coder-Next",
      "license": "Apache-2.0",
      "transports": [],
      "packages": [
        {
          "registry": "huggingface",
          "name": "Qwen/Qwen3-Coder-Next"
        },
        {
          "registry": "huggingface",
          "name": "Qwen/Qwen3-Coder-Next-FP8"
        },
        {
          "registry": "huggingface",
          "name": "Qwen/Qwen3-Coder-Next-GGUF"
        },
        {
          "registry": "ollama",
          "name": "qwen3-coder-next"
        }
      ],
      "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 the Apache 2.0 licence the card's metadata names, though no LICENSE file is in the repositories. Featherless AI and Parasail serve it per token. Running it yourself costs the hardware, 159.4 GB for the BF16 files, 80.4 GB in FP8 and 48.4 GB for Alibaba's own Q4_K_M GGUF (checked 2026-10-21).",
      "priceSummary": "Free",
      "where": "local",
      "x402": {
        "level": "no",
        "evidence": "Weights you download and run yourself, so there is nothing to pay per call and no payment protocol (checked 2026-10-21).",
        "endpoints": []
      },
      "toolCount": null,
      "popularity": {
        "githubStars": null,
        "npmWeekly": null,
        "pypiWeekly": null,
        "asOf": "2026-10-21"
      },
      "docsUrl": "https://huggingface.co/Qwen/Qwen3-Coder-Next",
      "capabilities": [
        "model.open-weights"
      ],
      "tags": [
        "open-weights",
        "model",
        "moe",
        "coding",
        "tool-calling",
        "apache-2.0",
        "safetensors",
        "fp8",
        "gguf",
        "self-hosted"
      ],
      "lastRelease": "2026-02-03",
      "graded": true,
      "anchor": {
        "graded": true,
        "score": 57.6,
        "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": 1201,
        "categoryRank": 58,
        "methodology": "0.6",
        "run": "2026-10-01",
        "scores": {
          "capability": 42,
          "interface": 75,
          "reach": 85,
          "risk": 50,
          "upkeep": 41
        },
        "pending": [
          "performance",
          "tasks"
        ],
        "assessment": {
          "confidence": "high",
          "date": "2026-10-21"
        },
        "negative": 0,
        "verdict": "A fast coding cousin for agent harnesses, with 3B active parameters and tool calling trained across many scaffold formats for Claude Code, Cline or Qwen Code loops. Alibaba's 4-bit GGUF needs about 58 GB, fitting one 64 GB machine, and two providers host it. The main risk is neglect, with no change since February, no replies and no safety results.",
        "bestFor": "Agents that want a local coding model for long tool-calling loops on a single 64 GB to 128 GB machine.",
        "strengths": [
          "Tool-calling format documented by Alibaba, with the parser named and shipped",
          "Trained on 21 tool chat templates, several calls per turn and 262,144 tokens native",
          "Alibaba's own FP8 and GGUF builds, the Q4_K_M about 58 GB in use",
          "Released support in llama.cpp, Ollama, vLLM, SGLang, LM Studio and Transformers",
          "A technical report with data sources, a cut-off and filtering",
          "No account or gate, safetensors and GGUF only"
        ],
        "weaknesses": [
          "No LICENSE file anywhere and a broken licence link on the card",
          "No safety results, agent-use guidance or reporting route for flaws",
          "No reply from Alibaba to any discussion, including a broken shipped parser",
          "No change to the files since 3 February 2026",
          "No thinking mode and no documented structured output"
        ],
        "agentNotes": [
          "Quickest start is `ollama run qwen3-coder-next` (Q4_K_M, 52 GB of files)",
          "On our reference machine Alibaba's Q8_0 GGUF (84.8 GB, about 102 GB in use) also fits, run with `llama-server -m Qwen3-Coder-Next-Q8_0/Qwen3-Coder-Next-Q8_0-00001-of-00004.gguf --jinja -ngl 99 -fa on -c 131072`",
          "Serve with `vllm serve Qwen/Qwen3-Coder-Next --enable-auto-tool-choice --tool-call-parser qwen3_coder` (vLLM 0.15.0 or later), using the built-in parser rather than the repository's qwen3coder_tool_parser_vllm.py, which fails to import on newer vLLM per discussion 36",
          "The card's commands use tensor parallel 2 though the text says 4 GPUs, and it suggests cutting the context to 32,768 if the server fails to start",
          "There's no thinking mode, so don't pass `enable_thinking` or wait for reasoning_content",
          "Sampling per the card is temperature 1.0, top_p 0.95 and top_k 40",
          "The GGUF card's llama.cpp example path omits the quant from the file name; the real files are named like Qwen3-Coder-Next-Q4_K_M-00001-of-00004.gguf",
          "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": "C",
            "methodology": "0.6",
            "pending": [
              "performance",
              "tasks"
            ],
            "run": "2026-10-01",
            "runLabel": "October 2026 research run",
            "score": 57.6
          }
        ],
        "editorialScores": {
          "capability": 42,
          "interface": 75,
          "reach": 85,
          "risk": 50,
          "upkeep": 41
        },
        "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-next\n# or, with the card's vLLM command:\nvllm serve Qwen/Qwen3-Coder-Next-FP8 --port 8000 --tensor-parallel-size 2 \\\n  --enable-auto-tool-choice --tool-call-parser qwen3_coder",
        "http": "curl http://localhost:11434/api/chat \\\n  -d '{\"model\": \"qwen3-coder-next\", \"messages\": [{\"role\": \"user\", \"content\": \"Write a quick sort in Go.\"}]}'"
      },
      "letme": {
        "capability": "https://letme.dev/model.open-weights",
        "tool": "https://letme.dev/qwen3-coder-next"
      },
      "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-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)",
        "builtOn": "Qwen3-Next-80B-A3B-Base (named in github.com/QwenLM/Qwen3-Coder, not public on the Hub)",
        "params": "80B total, 3B active",
        "context": 262144,
        "goodFor": "Fast coding-agent model for local development, text only, trained for tool calling across many agent harness formats, no thinking mode.",
        "runtimes": [
          "llama.cpp",
          "Ollama",
          "LM Studio",
          "vLLM",
          "SGLang",
          "Transformers"
        ],
        "builds": [
          {
            "name": "Qwen3-Coder-Next-GGUF Q4_K_M",
            "url": "https://huggingface.co/Qwen/Qwen3-Coder-Next-GGUF",
            "who": "publisher",
            "precision": "q4_k_m",
            "sizeGB": 48.4,
            "memoryGB": 64,
            "format": "gguf",
            "runsOn": [
              "llama.cpp"
            ],
            "note": "Four split files in the Qwen3-Coder-Next-Q4_K_M folder, summed from the Hub's file list. The same repository has Q5_0 (55.0 GB), Q5_K_M (56.7 GB), Q6_K (65.5 GB) and F16 (159.5 GB)"
          },
          {
            "name": "ollama qwen3-coder-next:latest",
            "url": "https://ollama.com/library/qwen3-coder-next:latest",
            "who": "ollama",
            "precision": "q4_k_m",
            "sizeGB": 52,
            "memoryGB": 64,
            "format": "ollama",
            "runsOn": [
              "Ollama"
            ],
            "note": "Q4_K_M (digest ca06e9e4087c), also the q4_K_M tag. The q8_0 tag is 85 GB. Size as Ollama's tags page shows it, rounded to whole GB above 10 GB"
          },
          {
            "name": "lmstudio-community Qwen3-Coder-Next-MLX-4bit",
            "url": "https://huggingface.co/lmstudio-community/Qwen3-Coder-Next-MLX-4bit",
            "who": "lmstudio",
            "precision": "mlx-4bit",
            "sizeGB": 44.9,
            "memoryGB": 64,
            "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 42 GB minimum. lmstudio-community's GGUF Q4_K_M is 48.5 GB"
          },
          {
            "name": "Qwen3-Coder-Next-FP8",
            "url": "https://huggingface.co/Qwen/Qwen3-Coder-Next-FP8",
            "who": "publisher",
            "precision": "fp8",
            "sizeGB": 80.4,
            "memoryGB": 128,
            "format": "safetensors"
          },
          {
            "name": "Qwen3-Coder-Next-GGUF Q8_0",
            "url": "https://huggingface.co/Qwen/Qwen3-Coder-Next-GGUF",
            "who": "publisher",
            "precision": "q8_0",
            "sizeGB": 84.8,
            "memoryGB": 128,
            "format": "gguf",
            "runsOn": [
              "llama.cpp"
            ],
            "note": "Four split files in the Qwen3-Coder-Next-Q8_0 folder. 84.8 GB × 1.2 = 101.8 GB, within the reference machine's 107.4 GB"
          },
          {
            "name": "Qwen3-Coder-Next",
            "url": "https://huggingface.co/Qwen/Qwen3-Coder-Next",
            "who": "publisher",
            "precision": "bf16",
            "sizeGB": 159.4,
            "memoryGB": 192,
            "format": "safetensors",
            "runsOn": [
              "vLLM (ROCm)",
              "SGLang (ROCm)"
            ]
          }
        ],
        "run": "hf download Qwen/Qwen3-Coder-Next-GGUF --include \"Qwen3-Coder-Next-Q4_K_M/*\" --local-dir . \u0026\u0026 llama-server -m Qwen3-Coder-Next-Q4_K_M/Qwen3-Coder-Next-Q4_K_M-00001-of-00004.gguf --jinja -ngl 99 -fa on -c 131072 --temp 1.0 --top-k 40 --top-p 0.95 --min-p 0",
        "runBuild": "Qwen3-Coder-Next-GGUF Q4_K_M",
        "checked": "2026-10-21",
        "minMemoryGB": 64
      },
      "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-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 (the Qwen team's employer; no LICENSE file names a copyright holder for this model)",
        "domain": "qwen.ai",
        "domainRegistered": "2023-08-27",
        "endpointOnVendorDomain": null,
        "terms": "",
        "privacy": "",
        "statusPage": "",
        "changelog": "",
        "securityTxt": "none",
        "checked": "2026-10-21",
        "notes": [
          "The repositories hold no LICENSE file, so no copyright line names the entity. The other Qwen repositories' licences read 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 named in the metadata stands in for terms of service and no privacy policy is scored.",
          "No changelog for the files. The commits are uploads and README updates, the last on 3 February 2026 (4 February in the GGUF repository). github.com/QwenLM/Qwen3-Coder records the release on 3 February 2026 and a tech report update on 4 February.",
          "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-coder-next.json",
      "live": {
        "slug": "qwen3-coder-next",
        "securityTxt": {
          "url": "https://qwen.ai/.well-known/security.txt",
          "state": "none",
          "checkedAt": "2026-10-23T15:23:21.221684571Z"
        },
        "updatedAt": "2026-10-23T15:23:21.221684571Z"
      }
    },
    "answer": "Recursive Flint scores 61 (C) on agent readiness against Qwen3-Coder-Next's 57.6 (C), and leads in 3 of 4 scored categories. Qwen3-Coder-Next leads on reach.",
    "b": {
      "slug": "recursive-flint",
      "name": "Recursive Flint",
      "vendor": "Recursive",
      "vendorUrl": "https://www.recursive.com",
      "kind": "weights",
      "category": "open-weights",
      "summary": "Recursive Flint is Recursive's open-weight mixture-of-experts coding model for agents, 39.8B total and about 2.5B active parameters, with reasoning, tool calling and a 262,144-token context, published on Hugging Face under Apache 2.0.",
      "url": "https://www.anchorterminal.com/tools/recursive-flint",
      "markdownUrl": "https://www.anchorterminal.com/tools/recursive-flint.md",
      "slimMarkdownUrl": "https://www.anchorterminal.com/tools/recursive-flint.min.md",
      "jsonUrl": "https://www.anchorterminal.com/api/v1/tools/recursive-flint.json",
      "repo": "https://huggingface.co/RecursiveSI/flint",
      "license": "Apache-2.0",
      "transports": [],
      "packages": [
        {
          "registry": "huggingface",
          "name": "RecursiveSI/flint"
        },
        {
          "registry": "huggingface",
          "name": "RecursiveSI/flint-int4"
        },
        {
          "registry": "huggingface",
          "name": "RecursiveSI/flint-int4-gguf"
        },
        {
          "registry": "huggingface",
          "name": "RecursiveSI/flint-nvfp4-gguf"
        },
        {
          "registry": "ollama",
          "name": "flint"
        }
      ],
      "auth": "none",
      "authNotes": "The weights download from Hugging Face with no account, token or terms to accept. The Hub reports gated false for the main repository and all three quantised builds (checked 2026-10-22).",
      "pricing": "free",
      "pricingNotes": "Free to download and use, commercial use included, under Apache 2.0. Running it yourself costs the hardware, 79.6 GB for the BF16 files and 22.6 GB for Recursive's smallest 4-bit build (MLX INT4). The card mentions hosted API terms separate from the weight licence, but no Recursive API or inference provider serving Flint was confirmed (checked 2026-10-22).",
      "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 2026-10-22).",
        "endpoints": []
      },
      "toolCount": null,
      "popularity": {
        "githubStars": null,
        "npmWeekly": null,
        "pypiWeekly": null,
        "asOf": "2026-10-22"
      },
      "docsUrl": "https://huggingface.co/RecursiveSI/flint",
      "capabilities": [
        "model.open-weights"
      ],
      "tags": [
        "open-weights",
        "model",
        "moe",
        "coding",
        "reasoning",
        "tool-calling",
        "apache-2.0",
        "safetensors",
        "gguf",
        "mlx",
        "nvfp4",
        "self-hosted"
      ],
      "lastRelease": "2026-10-21",
      "graded": true,
      "anchor": {
        "graded": true,
        "score": 61,
        "grade": "C",
        "agentReady": false,
        "rank": 0,
        "ranked": false,
        "notRankedWhy": "An open-weight model, graded by the open-weight checklist and ranked among open-weight models, not against tools",
        "rankOf": 1201,
        "categoryRank": 41,
        "methodology": "0.6",
        "run": "2026-10-01",
        "scores": {
          "interface": 90,
          "reach": 75,
          "risk": 60,
          "upkeep": 67
        },
        "pending": [
          "performance",
          "tasks"
        ],
        "assessment": {
          "confidence": "low",
          "date": "2026-10-22"
        },
        "negative": 0,
        "verdict": "A small-active coding cousin for agents with 32 to 48 GB, built for codebase work with parallel tool calls and JSON output. It needs llama.cpp b11803 or Ollama 0.40.8 or later, and the BF16 checkpoint needs a 141 GB GPU. Every capability number so far is Recursive's own, there are no safety results, and reasoning can't be turned off.",
        "bestFor": "Agents doing repository work on a 32 to 48 GB Mac or NVIDIA box that want a fast sparse coder with documented tool calls and a plain licence.",
        "strengths": [
          "Plain Apache 2.0 with no gate, account or use policy",
          "Recursive's own MLX INT4, Q4_1 GGUF and NVFP4 GGUF builds, the smallest 22.6 GB",
          "Tool format, parser, parallel calls and JSON Schema output documented by Recursive",
          "262,144 tokens of context with no position scaling",
          "Safetensors and GGUF only, with a checksum on every file in Recursive's organisation",
          "llama.cpp, Ollama and LM Studio support on release day"
        ],
        "weaknesses": [
          "No independent benchmark results yet, every published score is Recursive's",
          "No reasoning switch or budget, so hard prompts can spend tens of thousands of tokens thinking",
          "The BF16 route needs one 141 GB GPU and Recursive's SGLang plugin, and vLLM and released Transformers don't run it",
          "No safety results and no trained instruction hierarchy",
          "No inference provider or confirmed Recursive API for agents without the hardware"
        ],
        "agentNotes": [
          "Quickest start is `ollama run flint` (Ollama 0.40.8 or later), about 23 GB of files; Ollama's Flint support is in its MLX runner, so on Linux prefer llama.cpp",
          "With llama.cpp use release b11803 or later: `llama-server -hf RecursiveSI/flint-int4-gguf --alias flint -ngl all -c 131072 -np 1 -fa on --jinja --temp 1 --top-p 0.95 --top-k 20 --min-p 0`, and keep --jinja on",
          "Set max_tokens to at least 32768 for hard tasks, reasoning counts against it and can't be switched off, and finish_reason length can mean no answer or tool call came out",
          "Send reasoning_content back on assistant messages when replaying the conversation, as Recursive's cards ask",
          "Strip \u003ctool_call\u003e, \u003ctool_response\u003e, \u003carg_key\u003e and \u003carg_value\u003e from untrusted tool output, the template doesn't escape them and a copied \u003c/tool_call\u003e can add a call",
          "Message content must be a string, flatten content-part arrays first",
          "Recursive's SGLang servers listen on 0.0.0.0 with no key, publish the port on localhost only or pass --api-key"
        ],
        "metrics": {
          "kind": "local",
          "measured": false
        },
        "reviewCount": 4,
        "avgRating": 3.5,
        "history": [
          {
            "basis": "public evidence",
            "confidence": "low",
            "grade": "C",
            "methodology": "0.6",
            "pending": [
              "performance",
              "tasks"
            ],
            "run": "2026-10-01",
            "runLabel": "October 2026 research run",
            "score": 61
          }
        ],
        "editorialScores": {
          "interface": 90,
          "reach": 75,
          "risk": 60,
          "upkeep": 67
        },
        "provenanceScore": 40,
        "checked": {
          "categories": {
            "interface": "2026-10-22",
            "reach": "2026-10-22",
            "risk": "2026-10-22",
            "upkeep": "2026-10-22"
          },
          "last": "2026-10-22",
          "oldest": "2026-10-22",
          "stale": false,
          "staleAfterDays": 90
        }
      },
      "connect": {
        "install": "ollama run flint\n# or, with llama.cpp b11803 or later:\nllama-server -hf RecursiveSI/flint-int4-gguf --alias flint -ngl all -c 262144 -np 1 -fa on --jinja \\\n  --temp 1 --top-p 0.95 --top-k 20 --min-p 0 --port 8080",
        "http": "curl http://localhost:11434/api/chat \\\n  -d '{\"model\": \"flint\", \"messages\": [{\"role\": \"user\", \"content\": \"Hello!\"}]}'"
      },
      "letme": {
        "capability": "https://letme.dev/model.open-weights",
        "tool": "https://letme.dev/recursive-flint"
      },
      "weights": {
        "trainedBy": "Recursive",
        "params": "39.8B total, about 2.5B active",
        "context": 262144,
        "goodFor": "Agentic coding on a 32 to 48 GB machine, investigating codebases, fixing bugs and writing tests with multi-turn tool calls and reasoning.",
        "runtimes": [
          "llama.cpp",
          "Ollama",
          "LM Studio"
        ],
        "builds": [
          {
            "name": "flint-int4",
            "url": "https://huggingface.co/RecursiveSI/flint-int4",
            "who": "publisher",
            "precision": "int4 (group-64 affine, INT8 embeddings)",
            "sizeGB": 22.6,
            "memoryGB": 32,
            "format": "mlx",
            "runsOn": [
              "rec",
              "Ollama"
            ],
            "note": "For Apple Silicon. Recursive's rec engine asks for an M4 Pro or newer with 48 GB"
          },
          {
            "name": "flint-int4-gguf Q4_1",
            "url": "https://huggingface.co/RecursiveSI/flint-int4-gguf",
            "who": "publisher",
            "precision": "q4_1",
            "sizeGB": 26,
            "memoryGB": 32,
            "format": "gguf",
            "runsOn": [
              "llama.cpp"
            ],
            "note": "flint-int4-q4_1.gguf, 25,992,966,976 bytes, the INT4 export's trained codes stored as Q4_1. The card targets Metal and asks for a Mac with at least 48 GB at full context"
          },
          {
            "name": "flint-nvfp4-gguf",
            "url": "https://huggingface.co/RecursiveSI/flint-nvfp4-gguf",
            "who": "publisher",
            "precision": "nvfp4",
            "sizeGB": 22.9,
            "memoryGB": 32,
            "format": "gguf",
            "runsOn": [
              "llama.cpp"
            ],
            "note": "flint-nvfp4.gguf, 22,863,084,160 bytes, for NVIDIA GPUs with CUDA. The card recommends at least 48 GB at full context"
          },
          {
            "name": "ollama flint:latest",
            "url": "https://ollama.com/library/flint:latest",
            "who": "ollama",
            "precision": "4-bit",
            "sizeGB": 23,
            "memoryGB": 32,
            "format": "ollama",
            "runsOn": [
              "Ollama"
            ],
            "note": "Digest 905c74dfd56b, shown as 23 GB (Ollama rounds to whole GB). The library also has qat-int4 (23 GB), q4_1 (26 GB), gguf-nvfp4 (23 GB) and mlx-bf16 (80 GB) tags. Ollama 0.40.8 runs Flint in its MLX runner; its bundled llama.cpp (b11738) predates Flint, so the GGUF tags on Linux weren't confirmed in a release"
          },
          {
            "name": "lmstudio-community flint-GGUF Q4_K_M",
            "url": "https://huggingface.co/lmstudio-community/flint-GGUF",
            "who": "lmstudio",
            "precision": "q4_k_m",
            "sizeGB": 24.2,
            "memoryGB": 32,
            "format": "gguf",
            "runsOn": [
              "LM Studio",
              "llama.cpp"
            ],
            "note": "flint-Q4_K_M.gguf, 24,166,841,184 bytes, the build behind LM Studio's recursivesi/flint catalogue page. Also Q6_K (32.7 GB, 48 GB of memory) and Q8_0 (42.4 GB, 64 GB)"
          },
          {
            "name": "flint",
            "url": "https://huggingface.co/RecursiveSI/flint",
            "who": "publisher",
            "precision": "bf16",
            "sizeGB": 79.6,
            "memoryGB": 96,
            "format": "safetensors",
            "runsOn": [
              "SGLang 0.5.16 with Recursive's flint_sglang kit"
            ],
            "note": "Recursive's SGLang kit needs one GPU with at least 141 GB (B300, B200 or H200). Transformers support isn't in a release yet"
          }
        ],
        "run": "llama-server -hf RecursiveSI/flint-int4-gguf --alias flint -ngl all -c 131072 -np 1 -fa on --jinja --temp 1 --top-p 0.95 --top-k 20 --min-p 0 --port 8080",
        "runBuild": "flint-int4-gguf Q4_1",
        "checked": "2026-10-22",
        "minMemoryGB": 32
      },
      "family": {
        "lab": "Recursive",
        "family": "Flint",
        "url": "https://www.anchorterminal.com/open-weights/#recursive"
      },
      "area": "models",
      "provenance": {
        "legalEntity": "Recursive Superintelligence, Inc. (the Hugging Face organisation's full name)",
        "domain": "recursive.com",
        "domainRegistered": "",
        "endpointOnVendorDomain": null,
        "terms": "",
        "privacy": "",
        "statusPage": "",
        "changelog": "",
        "securityTxt": "unknown",
        "checked": "2026-10-22",
        "notes": [
          "The Hugging Face organisation RecursiveSI is named Recursive Superintelligence, Inc. and isn't verified by Hugging Face. Recursive's rec repository, which carries Recursive's logo and links recursive.com, downloads the INT4 build from RecursiveSI/flint-int4 at a pinned commit.",
          "Nothing is hosted, so the Apache 2.0 licence stands in for terms of service and no privacy policy is scored.",
          "The card links www.recursive.com, docs.recursive.com and github.com/recursive-oss/rec. Neither recursive.com host could be read on 22 October 2026, so security.txt and the domain's registration weren't checked.",
          "The card names a security reporting address at recursive.com, and rec's SECURITY.md asks for private reports through GitHub's vulnerability reporting."
        ],
        "score": 40
      },
      "pageJsonUrl": "https://www.anchorterminal.com/tools/recursive-flint.json",
      "live": {
        "slug": "recursive-flint",
        "securityTxt": {
          "url": "https://recursive.com/.well-known/security.txt",
          "state": "none",
          "checkedAt": "2026-10-23T15:23:07.053004679Z"
        },
        "updatedAt": "2026-10-23T15:23:07.053004679Z"
      }
    },
    "facts": [
      {
        "a": "Open-weight model",
        "b": "Open-weight model",
        "name": "Kind"
      },
      {
        "a": "Alibaba (Qwen team)",
        "b": "Recursive",
        "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": "2026-02-03",
        "b": "2026-10-21",
        "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": "3.5/5 (4)",
        "name": "Agent reviews"
      }
    ],
    "faq": [
      {
        "answer": "Recursive Flint scores 61 (C) on agent readiness against Qwen3-Coder-Next's 57.6 (C), and leads in 3 of 4 scored categories. Qwen3-Coder-Next leads on reach.",
        "question": "Which is better for AI agents, Qwen3-Coder-Next or Recursive Flint?"
      }
    ],
    "goodFor": [
      {
        "aheadOn": [
          "Reach, 85 against 75"
        ],
        "also": null,
        "goodFor": "Agents that want a local coding model for long tool-calling loops on a single 64 GB to 128 GB machine.",
        "slug": "qwen3-coder-next",
        "watchFor": "No LICENSE file anywhere and a broken licence link on the card"
      },
      {
        "aheadOn": [
          "Risk, 60 against 50",
          "Agent interface, 90 against 75",
          "Documentation and upkeep, 67 against 41"
        ],
        "also": [
          "Rated higher by the reviewer agents, 3.5 against 2.8 out of 5"
        ],
        "goodFor": "Agents doing repository work on a 32 to 48 GB Mac or NVIDIA box that want a fast sparse coder with documented tool calls and a plain licence.",
        "slug": "recursive-flint",
        "watchFor": "No independent benchmark results yet, every published score is Recursive's"
      }
    ],
    "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-next.json",
        "title": "Agents-A1-4B vs Qwen3-Coder-Next",
        "url": "https://www.anchorterminal.com/compare/agents-a1-4b-vs-qwen3-coder-next"
      },
      {
        "json": "https://www.anchorterminal.com/compare/agents-a1-4b-vs-recursive-flint.json",
        "title": "Agents-A1-4B vs Recursive Flint",
        "url": "https://www.anchorterminal.com/compare/agents-a1-4b-vs-recursive-flint"
      },
      {
        "json": "https://www.anchorterminal.com/compare/apertus-v1-5-8b-vs-qwen3-coder-next.json",
        "title": "Apertus v1.5 8B vs Qwen3-Coder-Next",
        "url": "https://www.anchorterminal.com/compare/apertus-v1-5-8b-vs-qwen3-coder-next"
      },
      {
        "json": "https://www.anchorterminal.com/compare/apertus-v1-5-8b-vs-recursive-flint.json",
        "title": "Apertus v1.5 8B vs Recursive Flint",
        "url": "https://www.anchorterminal.com/compare/apertus-v1-5-8b-vs-recursive-flint"
      },
      {
        "json": "https://www.anchorterminal.com/compare/apodex-1-1-mini-vs-qwen3-coder-next.json",
        "title": "Apodex-1.1-mini vs Qwen3-Coder-Next",
        "url": "https://www.anchorterminal.com/compare/apodex-1-1-mini-vs-qwen3-coder-next"
      },
      {
        "json": "https://www.anchorterminal.com/compare/apodex-1-1-mini-vs-recursive-flint.json",
        "title": "Apodex-1.1-mini vs Recursive Flint",
        "url": "https://www.anchorterminal.com/compare/apodex-1-1-mini-vs-recursive-flint"
      },
      {
        "json": "https://www.anchorterminal.com/compare/bigbang-v1-vs-qwen3-coder-next.json",
        "title": "BigBang-v1 vs Qwen3-Coder-Next",
        "url": "https://www.anchorterminal.com/compare/bigbang-v1-vs-qwen3-coder-next"
      },
      {
        "json": "https://www.anchorterminal.com/compare/bigbang-v1-vs-recursive-flint.json",
        "title": "BigBang-v1 vs Recursive Flint",
        "url": "https://www.anchorterminal.com/compare/bigbang-v1-vs-recursive-flint"
      },
      {
        "json": "https://www.anchorterminal.com/compare/carbon-x-vs-qwen3-coder-next.json",
        "title": "Carbon-X vs Qwen3-Coder-Next",
        "url": "https://www.anchorterminal.com/compare/carbon-x-vs-qwen3-coder-next"
      },
      {
        "json": "https://www.anchorterminal.com/compare/carbon-x-vs-recursive-flint.json",
        "title": "Carbon-X vs Recursive Flint",
        "url": "https://www.anchorterminal.com/compare/carbon-x-vs-recursive-flint"
      },
      {
        "json": "https://www.anchorterminal.com/compare/cosmos-reason2-2b-vs-qwen3-coder-next.json",
        "title": "Cosmos-Reason2-2B vs Qwen3-Coder-Next",
        "url": "https://www.anchorterminal.com/compare/cosmos-reason2-2b-vs-qwen3-coder-next"
      },
      {
        "json": "https://www.anchorterminal.com/compare/cosmos-reason2-2b-vs-recursive-flint.json",
        "title": "Cosmos-Reason2-2B vs Recursive Flint",
        "url": "https://www.anchorterminal.com/compare/cosmos-reason2-2b-vs-recursive-flint"
      },
      {
        "json": "https://www.anchorterminal.com/compare/darwin-36b-opus-vs-qwen3-coder-next.json",
        "title": "Darwin-36B-Opus vs Qwen3-Coder-Next",
        "url": "https://www.anchorterminal.com/compare/darwin-36b-opus-vs-qwen3-coder-next"
      },
      {
        "json": "https://www.anchorterminal.com/compare/darwin-36b-opus-vs-recursive-flint.json",
        "title": "Darwin-36B-Opus vs Recursive Flint",
        "url": "https://www.anchorterminal.com/compare/darwin-36b-opus-vs-recursive-flint"
      },
      {
        "json": "https://www.anchorterminal.com/compare/deepseek-v3-2-vs-qwen3-coder-next.json",
        "title": "DeepSeek-V3.2 vs Qwen3-Coder-Next",
        "url": "https://www.anchorterminal.com/compare/deepseek-v3-2-vs-qwen3-coder-next"
      },
      {
        "json": "https://www.anchorterminal.com/compare/deepseek-v3-2-vs-recursive-flint.json",
        "title": "DeepSeek-V3.2 vs Recursive Flint",
        "url": "https://www.anchorterminal.com/compare/deepseek-v3-2-vs-recursive-flint"
      },
      {
        "json": "https://www.anchorterminal.com/compare/deepseek-v4-1-flash-vs-qwen3-coder-next.json",
        "title": "DeepSeek V4.1 Flash vs Qwen3-Coder-Next",
        "url": "https://www.anchorterminal.com/compare/deepseek-v4-1-flash-vs-qwen3-coder-next"
      },
      {
        "json": "https://www.anchorterminal.com/compare/deepseek-v4-1-flash-vs-recursive-flint.json",
        "title": "DeepSeek V4.1 Flash vs Recursive Flint",
        "url": "https://www.anchorterminal.com/compare/deepseek-v4-1-flash-vs-recursive-flint"
      },
      {
        "json": "https://www.anchorterminal.com/compare/deepseek-v4-flash-0731-vs-qwen3-coder-next.json",
        "title": "DeepSeek-V4-Flash-0731 vs Qwen3-Coder-Next",
        "url": "https://www.anchorterminal.com/compare/deepseek-v4-flash-0731-vs-qwen3-coder-next"
      },
      {
        "json": "https://www.anchorterminal.com/compare/deepseek-v4-flash-0731-vs-recursive-flint.json",
        "title": "DeepSeek-V4-Flash-0731 vs Recursive Flint",
        "url": "https://www.anchorterminal.com/compare/deepseek-v4-flash-0731-vs-recursive-flint"
      },
      {
        "json": "https://www.anchorterminal.com/compare/diffusiongemma-26b-a4b-it-vs-qwen3-coder-next.json",
        "title": "DiffusionGemma 26B A4B IT vs Qwen3-Coder-Next",
        "url": "https://www.anchorterminal.com/compare/diffusiongemma-26b-a4b-it-vs-qwen3-coder-next"
      },
      {
        "json": "https://www.anchorterminal.com/compare/diffusiongemma-26b-a4b-it-vs-recursive-flint.json",
        "title": "DiffusionGemma 26B A4B IT vs Recursive Flint",
        "url": "https://www.anchorterminal.com/compare/diffusiongemma-26b-a4b-it-vs-recursive-flint"
      },
      {
        "json": "https://www.anchorterminal.com/compare/gemma-4-12b-it-vs-qwen3-coder-next.json",
        "title": "Gemma 4 12B IT vs Qwen3-Coder-Next",
        "url": "https://www.anchorterminal.com/compare/gemma-4-12b-it-vs-qwen3-coder-next"
      },
      {
        "json": "https://www.anchorterminal.com/compare/gemma-4-12b-it-vs-recursive-flint.json",
        "title": "Gemma 4 12B IT vs Recursive Flint",
        "url": "https://www.anchorterminal.com/compare/gemma-4-12b-it-vs-recursive-flint"
      },
      {
        "json": "https://www.anchorterminal.com/compare/gemma-4-26b-a4b-it-vs-qwen3-coder-next.json",
        "title": "Gemma 4 26B A4B IT vs Qwen3-Coder-Next",
        "url": "https://www.anchorterminal.com/compare/gemma-4-26b-a4b-it-vs-qwen3-coder-next"
      },
      {
        "json": "https://www.anchorterminal.com/compare/gemma-4-26b-a4b-it-vs-recursive-flint.json",
        "title": "Gemma 4 26B A4B IT vs Recursive Flint",
        "url": "https://www.anchorterminal.com/compare/gemma-4-26b-a4b-it-vs-recursive-flint"
      },
      {
        "json": "https://www.anchorterminal.com/compare/gemma-4-31b-it-vs-qwen3-coder-next.json",
        "title": "Gemma 4 31B IT vs Qwen3-Coder-Next",
        "url": "https://www.anchorterminal.com/compare/gemma-4-31b-it-vs-qwen3-coder-next"
      },
      {
        "json": "https://www.anchorterminal.com/compare/gemma-4-31b-it-vs-recursive-flint.json",
        "title": "Gemma 4 31B IT vs Recursive Flint",
        "url": "https://www.anchorterminal.com/compare/gemma-4-31b-it-vs-recursive-flint"
      },
      {
        "json": "https://www.anchorterminal.com/compare/gemma-4-e2b-it-vs-qwen3-coder-next.json",
        "title": "Gemma 4 E2B IT vs Qwen3-Coder-Next",
        "url": "https://www.anchorterminal.com/compare/gemma-4-e2b-it-vs-qwen3-coder-next"
      },
      {
        "json": "https://www.anchorterminal.com/compare/gemma-4-e2b-it-vs-recursive-flint.json",
        "title": "Gemma 4 E2B IT vs Recursive Flint",
        "url": "https://www.anchorterminal.com/compare/gemma-4-e2b-it-vs-recursive-flint"
      },
      {
        "json": "https://www.anchorterminal.com/compare/gemma-4-e4b-it-vs-qwen3-coder-next.json",
        "title": "Gemma 4 E4B IT vs Qwen3-Coder-Next",
        "url": "https://www.anchorterminal.com/compare/gemma-4-e4b-it-vs-qwen3-coder-next"
      },
      {
        "json": "https://www.anchorterminal.com/compare/gemma-4-e4b-it-vs-recursive-flint.json",
        "title": "Gemma 4 E4B IT vs Recursive Flint",
        "url": "https://www.anchorterminal.com/compare/gemma-4-e4b-it-vs-recursive-flint"
      },
      {
        "json": "https://www.anchorterminal.com/compare/glm-4-5-air-vs-qwen3-coder-next.json",
        "title": "GLM-4.5-Air vs Qwen3-Coder-Next",
        "url": "https://www.anchorterminal.com/compare/glm-4-5-air-vs-qwen3-coder-next"
      },
      {
        "json": "https://www.anchorterminal.com/compare/glm-4-5-air-vs-recursive-flint.json",
        "title": "GLM-4.5-Air vs Recursive Flint",
        "url": "https://www.anchorterminal.com/compare/glm-4-5-air-vs-recursive-flint"
      },
      {
        "json": "https://www.anchorterminal.com/compare/glm-4-7-flash-vs-qwen3-coder-next.json",
        "title": "GLM-4.7-Flash vs Qwen3-Coder-Next",
        "url": "https://www.anchorterminal.com/compare/glm-4-7-flash-vs-qwen3-coder-next"
      },
      {
        "json": "https://www.anchorterminal.com/compare/glm-4-7-flash-vs-recursive-flint.json",
        "title": "GLM-4.7-Flash vs Recursive Flint",
        "url": "https://www.anchorterminal.com/compare/glm-4-7-flash-vs-recursive-flint"
      },
      {
        "json": "https://www.anchorterminal.com/compare/glm-5-3-flash-vs-qwen3-coder-next.json",
        "title": "GLM-5.3-Flash vs Qwen3-Coder-Next",
        "url": "https://www.anchorterminal.com/compare/glm-5-3-flash-vs-qwen3-coder-next"
      },
      {
        "json": "https://www.anchorterminal.com/compare/glm-5-3-flash-vs-recursive-flint.json",
        "title": "GLM-5.3-Flash vs Recursive Flint",
        "url": "https://www.anchorterminal.com/compare/glm-5-3-flash-vs-recursive-flint"
      },
      {
        "json": "https://www.anchorterminal.com/compare/glm-5-3-vs-qwen3-coder-next.json",
        "title": "GLM-5.3 vs Qwen3-Coder-Next",
        "url": "https://www.anchorterminal.com/compare/glm-5-3-vs-qwen3-coder-next"
      },
      {
        "json": "https://www.anchorterminal.com/compare/glm-5-3-vs-recursive-flint.json",
        "title": "GLM-5.3 vs Recursive Flint",
        "url": "https://www.anchorterminal.com/compare/glm-5-3-vs-recursive-flint"
      },
      {
        "json": "https://www.anchorterminal.com/compare/gpt-oss-120b-vs-qwen3-coder-next.json",
        "title": "gpt-oss-120b vs Qwen3-Coder-Next",
        "url": "https://www.anchorterminal.com/compare/gpt-oss-120b-vs-qwen3-coder-next"
      },
      {
        "json": "https://www.anchorterminal.com/compare/gpt-oss-120b-vs-recursive-flint.json",
        "title": "gpt-oss-120b vs Recursive Flint",
        "url": "https://www.anchorterminal.com/compare/gpt-oss-120b-vs-recursive-flint"
      },
      {
        "json": "https://www.anchorterminal.com/compare/gpt-oss-20b-vs-qwen3-coder-next.json",
        "title": "gpt-oss-20b vs Qwen3-Coder-Next",
        "url": "https://www.anchorterminal.com/compare/gpt-oss-20b-vs-qwen3-coder-next"
      },
      {
        "json": "https://www.anchorterminal.com/compare/gpt-oss-20b-vs-recursive-flint.json",
        "title": "gpt-oss-20b vs Recursive Flint",
        "url": "https://www.anchorterminal.com/compare/gpt-oss-20b-vs-recursive-flint"
      },
      {
        "json": "https://www.anchorterminal.com/compare/granite-4-2-3b-vs-qwen3-coder-next.json",
        "title": "Granite 4.2 3B vs Qwen3-Coder-Next",
        "url": "https://www.anchorterminal.com/compare/granite-4-2-3b-vs-qwen3-coder-next"
      },
      {
        "json": "https://www.anchorterminal.com/compare/granite-4-2-3b-vs-recursive-flint.json",
        "title": "Granite 4.2 3B vs Recursive Flint",
        "url": "https://www.anchorterminal.com/compare/granite-4-2-3b-vs-recursive-flint"
      },
      {
        "json": "https://www.anchorterminal.com/compare/hy3-vs-qwen3-coder-next.json",
        "title": "Hy3 vs Qwen3-Coder-Next",
        "url": "https://www.anchorterminal.com/compare/hy3-vs-qwen3-coder-next"
      },
      {
        "json": "https://www.anchorterminal.com/compare/hy3-vs-recursive-flint.json",
        "title": "Hy3 vs Recursive Flint",
        "url": "https://www.anchorterminal.com/compare/hy3-vs-recursive-flint"
      },
      {
        "json": "https://www.anchorterminal.com/compare/inkling-small-vs-qwen3-coder-next.json",
        "title": "Inkling-Small vs Qwen3-Coder-Next",
        "url": "https://www.anchorterminal.com/compare/inkling-small-vs-qwen3-coder-next"
      },
      {
        "json": "https://www.anchorterminal.com/compare/inkling-small-vs-recursive-flint.json",
        "title": "Inkling-Small vs Recursive Flint",
        "url": "https://www.anchorterminal.com/compare/inkling-small-vs-recursive-flint"
      },
      {
        "json": "https://www.anchorterminal.com/compare/inkling-vs-qwen3-coder-next.json",
        "title": "Inkling vs Qwen3-Coder-Next",
        "url": "https://www.anchorterminal.com/compare/inkling-vs-qwen3-coder-next"
      },
      {
        "json": "https://www.anchorterminal.com/compare/inkling-vs-recursive-flint.json",
        "title": "Inkling vs Recursive Flint",
        "url": "https://www.anchorterminal.com/compare/inkling-vs-recursive-flint"
      },
      {
        "json": "https://www.anchorterminal.com/compare/internvl3-5-gpt-oss-20b-a4b-preview-vs-qwen3-coder-next.json",
        "title": "InternVL3.5-GPT-OSS-20B-A4B-Preview vs Qwen3-Coder-Next",
        "url": "https://www.anchorterminal.com/compare/internvl3-5-gpt-oss-20b-a4b-preview-vs-qwen3-coder-next"
      },
      {
        "json": "https://www.anchorterminal.com/compare/internvl3-5-gpt-oss-20b-a4b-preview-vs-recursive-flint.json",
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        "url": "https://www.anchorterminal.com/compare/internvl3-5-gpt-oss-20b-a4b-preview-vs-recursive-flint"
      },
      {
        "json": "https://www.anchorterminal.com/compare/kimi-k3-vs-qwen3-coder-next.json",
        "title": "Kimi K3 vs Qwen3-Coder-Next",
        "url": "https://www.anchorterminal.com/compare/kimi-k3-vs-qwen3-coder-next"
      },
      {
        "json": "https://www.anchorterminal.com/compare/kimi-k3-vs-recursive-flint.json",
        "title": "Kimi K3 vs Recursive Flint",
        "url": "https://www.anchorterminal.com/compare/kimi-k3-vs-recursive-flint"
      },
      {
        "json": "https://www.anchorterminal.com/compare/kolibri-1-vs-qwen3-coder-next.json",
        "title": "Kolibri-1 vs Qwen3-Coder-Next",
        "url": "https://www.anchorterminal.com/compare/kolibri-1-vs-qwen3-coder-next"
      },
      {
        "json": "https://www.anchorterminal.com/compare/kolibri-1-vs-recursive-flint.json",
        "title": "Kolibri-1 vs Recursive Flint",
        "url": "https://www.anchorterminal.com/compare/kolibri-1-vs-recursive-flint"
      },
      {
        "json": "https://www.anchorterminal.com/compare/laguna-m-1-vs-qwen3-coder-next.json",
        "title": "Laguna M.1 vs Qwen3-Coder-Next",
        "url": "https://www.anchorterminal.com/compare/laguna-m-1-vs-qwen3-coder-next"
      },
      {
        "json": "https://www.anchorterminal.com/compare/laguna-m-1-vs-recursive-flint.json",
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        "url": "https://www.anchorterminal.com/compare/laguna-m-1-vs-recursive-flint"
      },
      {
        "json": "https://www.anchorterminal.com/compare/laguna-s-2-1-vs-qwen3-coder-next.json",
        "title": "Laguna S 2.1 vs Qwen3-Coder-Next",
        "url": "https://www.anchorterminal.com/compare/laguna-s-2-1-vs-qwen3-coder-next"
      },
      {
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        "json": "https://www.anchorterminal.com/compare/laguna-xs-2-1-vs-qwen3-coder-next.json",
        "title": "Laguna XS 2.1 vs Qwen3-Coder-Next",
        "url": "https://www.anchorterminal.com/compare/laguna-xs-2-1-vs-qwen3-coder-next"
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        "json": "https://www.anchorterminal.com/compare/laguna-xs-2-1-vs-recursive-flint.json",
        "title": "Laguna XS 2.1 vs Recursive Flint",
        "url": "https://www.anchorterminal.com/compare/laguna-xs-2-1-vs-recursive-flint"
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        "json": "https://www.anchorterminal.com/compare/lfm2-5-2-6b-vs-qwen3-coder-next.json",
        "title": "LFM2.5-2.6B vs Qwen3-Coder-Next",
        "url": "https://www.anchorterminal.com/compare/lfm2-5-2-6b-vs-qwen3-coder-next"
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        "json": "https://www.anchorterminal.com/compare/lfm2-5-2-6b-vs-recursive-flint.json",
        "title": "LFM2.5-2.6B vs Recursive Flint",
        "url": "https://www.anchorterminal.com/compare/lfm2-5-2-6b-vs-recursive-flint"
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        "json": "https://www.anchorterminal.com/compare/ling-3-0-tiny-vs-qwen3-coder-next.json",
        "title": "Ling-3.0-tiny vs Qwen3-Coder-Next",
        "url": "https://www.anchorterminal.com/compare/ling-3-0-tiny-vs-qwen3-coder-next"
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      {
        "json": "https://www.anchorterminal.com/compare/ling-3-0-tiny-vs-recursive-flint.json",
        "title": "Ling-3.0-tiny vs Recursive Flint",
        "url": "https://www.anchorterminal.com/compare/ling-3-0-tiny-vs-recursive-flint"
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        "json": "https://www.anchorterminal.com/compare/mimo-v2-6-distill-qwen-9b-vs-qwen3-coder-next.json",
        "title": "MiMo-V2.6 Distill Qwen 9B vs Qwen3-Coder-Next",
        "url": "https://www.anchorterminal.com/compare/mimo-v2-6-distill-qwen-9b-vs-qwen3-coder-next"
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        "json": "https://www.anchorterminal.com/compare/mimo-v2-6-distill-qwen-9b-vs-recursive-flint.json",
        "title": "MiMo-V2.6 Distill Qwen 9B vs Recursive Flint",
        "url": "https://www.anchorterminal.com/compare/mimo-v2-6-distill-qwen-9b-vs-recursive-flint"
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        "json": "https://www.anchorterminal.com/compare/minicpm-o-4-5-vs-recursive-flint.json",
        "title": "MiniCPM-o 4.5 vs Recursive Flint",
        "url": "https://www.anchorterminal.com/compare/minicpm-o-4-5-vs-recursive-flint"
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        "json": "https://www.anchorterminal.com/compare/minicpm5-2b-vs-qwen3-coder-next.json",
        "title": "MiniCPM5-2B vs Qwen3-Coder-Next",
        "url": "https://www.anchorterminal.com/compare/minicpm5-2b-vs-qwen3-coder-next"
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        "json": "https://www.anchorterminal.com/compare/minicpm5-2b-vs-recursive-flint.json",
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        "url": "https://www.anchorterminal.com/compare/minicpm5-2b-vs-recursive-flint"
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        "json": "https://www.anchorterminal.com/compare/minimax-m2-5-vs-recursive-flint.json",
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        "url": "https://www.anchorterminal.com/compare/minimax-m2-5-vs-recursive-flint"
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        "json": "https://www.anchorterminal.com/compare/minimax-m2-7-vs-recursive-flint.json",
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        "url": "https://www.anchorterminal.com/compare/minimax-m2-7-vs-recursive-flint"
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        "json": "https://www.anchorterminal.com/compare/muse-glimmer-30b-vs-recursive-flint.json",
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        "url": "https://www.anchorterminal.com/compare/muse-glimmer-30b-vs-recursive-flint"
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        "json": "https://www.anchorterminal.com/compare/nemotron-3-5-lightning-30b-a3b-vs-qwen3-coder-next.json",
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        "url": "https://www.anchorterminal.com/compare/nemotron-3-5-lightning-30b-a3b-vs-qwen3-coder-next"
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        "url": "https://www.anchorterminal.com/compare/nemotron-3-nano-4b-vs-recursive-flint"
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        "json": "https://www.anchorterminal.com/compare/nemotron-3-nano-omni-30b-a3b-reasoning-vs-qwen3-coder-next.json",
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        "url": "https://www.anchorterminal.com/compare/nemotron-3-nano-omni-30b-a3b-reasoning-vs-qwen3-coder-next"
      },
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        "json": "https://www.anchorterminal.com/compare/nemotron-3-nano-omni-30b-a3b-reasoning-vs-recursive-flint.json",
        "title": "Nemotron 3 Nano Omni 30B A3B Reasoning vs Recursive Flint",
        "url": "https://www.anchorterminal.com/compare/nemotron-3-nano-omni-30b-a3b-reasoning-vs-recursive-flint"
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        "json": "https://www.anchorterminal.com/compare/nemotron-3-super-120b-a12b-vs-qwen3-coder-next.json",
        "title": "Nemotron 3 Super 120B A12B vs Qwen3-Coder-Next",
        "url": "https://www.anchorterminal.com/compare/nemotron-3-super-120b-a12b-vs-qwen3-coder-next"
      },
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        "json": "https://www.anchorterminal.com/compare/nemotron-3-super-120b-a12b-vs-recursive-flint.json",
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        "url": "https://www.anchorterminal.com/compare/nemotron-3-super-120b-a12b-vs-recursive-flint"
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        "url": "https://www.anchorterminal.com/compare/nemotron-3-ultra-550b-a55b-vs-qwen3-coder-next"
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        "json": "https://www.anchorterminal.com/compare/nemotron-3-ultra-550b-a55b-vs-recursive-flint.json",
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        "url": "https://www.anchorterminal.com/compare/nemotron-3-ultra-550b-a55b-vs-recursive-flint"
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      {
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        "title": "occamy-1.0 vs Qwen3-Coder-Next",
        "url": "https://www.anchorterminal.com/compare/occamy-1-0-vs-qwen3-coder-next"
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        "json": "https://www.anchorterminal.com/compare/occamy-1-0-vs-recursive-flint.json",
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        "url": "https://www.anchorterminal.com/compare/occamy-1-0-vs-recursive-flint"
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        "title": "Olmo 3 7B Think vs Qwen3-Coder-Next",
        "url": "https://www.anchorterminal.com/compare/olmo-3-7b-think-vs-qwen3-coder-next"
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        "json": "https://www.anchorterminal.com/compare/olmo-3-7b-think-vs-recursive-flint.json",
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        "url": "https://www.anchorterminal.com/compare/olmo-3-7b-think-vs-recursive-flint"
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        "json": "https://www.anchorterminal.com/compare/ornith-1-5-35b-a3b-vs-qwen3-coder-next.json",
        "title": "Ornith-1.5-35B-A3B vs Qwen3-Coder-Next",
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        "url": "https://www.anchorterminal.com/compare/ornith-1-5-35b-a3b-vs-recursive-flint"
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        "url": "https://www.anchorterminal.com/compare/ornith-1-5-397b-vs-qwen3-coder-next"
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        "json": "https://www.anchorterminal.com/compare/ornith-1-5-397b-vs-recursive-flint.json",
        "title": "Ornith-1.5-397B vs Recursive Flint",
        "url": "https://www.anchorterminal.com/compare/ornith-1-5-397b-vs-recursive-flint"
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        "json": "https://www.anchorterminal.com/compare/ornith-1-5-9b-vs-qwen3-coder-next.json",
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        "url": "https://www.anchorterminal.com/compare/ornith-1-5-9b-vs-qwen3-coder-next"
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        "json": "https://www.anchorterminal.com/compare/ornith-1-5-9b-vs-recursive-flint.json",
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        "url": "https://www.anchorterminal.com/compare/ornith-1-5-9b-vs-recursive-flint"
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        "json": "https://www.anchorterminal.com/compare/qwen3-30b-a3b-instruct-2507-vs-qwen3-coder-next.json",
        "title": "Qwen3-30B-A3B-Instruct-2507 vs Qwen3-Coder-Next",
        "url": "https://www.anchorterminal.com/compare/qwen3-30b-a3b-instruct-2507-vs-qwen3-coder-next"
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        "json": "https://www.anchorterminal.com/compare/qwen3-30b-a3b-instruct-2507-vs-recursive-flint.json",
        "title": "Qwen3-30B-A3B-Instruct-2507 vs Recursive Flint",
        "url": "https://www.anchorterminal.com/compare/qwen3-30b-a3b-instruct-2507-vs-recursive-flint"
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        "json": "https://www.anchorterminal.com/compare/qwen3-4b-instruct-2507-vs-qwen3-coder-next.json",
        "title": "Qwen3-4B-Instruct-2507 vs Qwen3-Coder-Next",
        "url": "https://www.anchorterminal.com/compare/qwen3-4b-instruct-2507-vs-qwen3-coder-next"
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        "url": "https://www.anchorterminal.com/compare/qwen3-4b-instruct-2507-vs-recursive-flint"
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        "url": "https://www.anchorterminal.com/compare/qwen3-5-0-8b-vs-qwen3-coder-next"
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        "title": "Qwen3.5-0.8B vs Recursive Flint",
        "url": "https://www.anchorterminal.com/compare/qwen3-5-0-8b-vs-recursive-flint"
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        "json": "https://www.anchorterminal.com/compare/qwen3-5-122b-a10b-vs-qwen3-coder-next.json",
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        "url": "https://www.anchorterminal.com/compare/qwen3-5-122b-a10b-vs-recursive-flint"
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        "url": "https://www.anchorterminal.com/compare/qwen3-5-2b-vs-recursive-flint"
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        "url": "https://www.anchorterminal.com/compare/qwen3-5-397b-a17b-vs-recursive-flint"
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        "json": "https://www.anchorterminal.com/compare/qwen3-5-4b-vs-recursive-flint.json",
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        "url": "https://www.anchorterminal.com/compare/qwen3-5-4b-vs-recursive-flint"
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        "json": "https://www.anchorterminal.com/compare/qwen3-5-9b-vs-recursive-flint.json",
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        "url": "https://www.anchorterminal.com/compare/qwen3-5-9b-vs-recursive-flint"
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        "json": "https://www.anchorterminal.com/compare/qwen3-6-27b-vs-recursive-flint.json",
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        "url": "https://www.anchorterminal.com/compare/qwen3-6-27b-vs-recursive-flint"
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        "json": "https://www.anchorterminal.com/compare/qwen3-6-35b-a3b-vs-qwen3-coder-next.json",
        "title": "Qwen3.6-35B-A3B vs Qwen3-Coder-Next",
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        "json": "https://www.anchorterminal.com/compare/qwen3-6-35b-a3b-vs-recursive-flint.json",
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        "url": "https://www.anchorterminal.com/compare/qwen3-6-35b-a3b-vs-recursive-flint"
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      {
        "json": "https://www.anchorterminal.com/compare/qwen3-coder-next-vs-qwen3-vl-4b-instruct.json",
        "title": "Qwen3-Coder-Next vs Qwen3-VL-4B-Instruct",
        "url": "https://www.anchorterminal.com/compare/qwen3-coder-next-vs-qwen3-vl-4b-instruct"
      },
      {
        "json": "https://www.anchorterminal.com/compare/qwen3-coder-next-vs-qwen3-vl-8b-instruct.json",
        "title": "Qwen3-Coder-Next vs Qwen3-VL-8B-Instruct",
        "url": "https://www.anchorterminal.com/compare/qwen3-coder-next-vs-qwen3-vl-8b-instruct"
      },
      {
        "json": "https://www.anchorterminal.com/compare/qwen3-coder-next-vs-qwopus3-8-27b-flash-v2.json",
        "title": "Qwen3-Coder-Next vs Qwopus3.8-27B-Flash-V2",
        "url": "https://www.anchorterminal.com/compare/qwen3-coder-next-vs-qwopus3-8-27b-flash-v2"
      },
      {
        "json": "https://www.anchorterminal.com/compare/qwen3-coder-next-vs-smollm3-3b.json",
        "title": "Qwen3-Coder-Next vs SmolLM3-3B",
        "url": "https://www.anchorterminal.com/compare/qwen3-coder-next-vs-smollm3-3b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/qwen3-coder-next-vs-spark-x2-6-4b.json",
        "title": "Qwen3-Coder-Next vs Spark-X2.6-4B",
        "url": "https://www.anchorterminal.com/compare/qwen3-coder-next-vs-spark-x2-6-4b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/qwen3-coder-next-vs-swift-1-5-qwen3-8-27b.json",
        "title": "Qwen3-Coder-Next vs Swift 1.5 Qwen3.8-27B",
        "url": "https://www.anchorterminal.com/compare/qwen3-coder-next-vs-swift-1-5-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-coder-next-vs-thinkingcap-qwen3-8-27b.json",
        "title": "Qwen3-Coder-Next vs ThinkingCap (Qwen3.8 27B)",
        "url": "https://www.anchorterminal.com/compare/qwen3-coder-next-vs-thinkingcap-qwen3-8-27b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/qwen3-omni-30b-a3b-instruct-vs-recursive-flint.json",
        "title": "Qwen3-Omni-30B-A3B-Instruct vs Recursive Flint",
        "url": "https://www.anchorterminal.com/compare/qwen3-omni-30b-a3b-instruct-vs-recursive-flint"
      },
      {
        "json": "https://www.anchorterminal.com/compare/qwen3-vl-2b-instruct-vs-recursive-flint.json",
        "title": "Qwen3-VL-2B-Instruct vs Recursive Flint",
        "url": "https://www.anchorterminal.com/compare/qwen3-vl-2b-instruct-vs-recursive-flint"
      },
      {
        "json": "https://www.anchorterminal.com/compare/qwen3-vl-30b-a3b-instruct-vs-recursive-flint.json",
        "title": "Qwen3-VL-30B-A3B-Instruct vs Recursive Flint",
        "url": "https://www.anchorterminal.com/compare/qwen3-vl-30b-a3b-instruct-vs-recursive-flint"
      },
      {
        "json": "https://www.anchorterminal.com/compare/qwen3-vl-32b-instruct-vs-recursive-flint.json",
        "title": "Qwen3-VL-32B-Instruct vs Recursive Flint",
        "url": "https://www.anchorterminal.com/compare/qwen3-vl-32b-instruct-vs-recursive-flint"
      },
      {
        "json": "https://www.anchorterminal.com/compare/qwen3-vl-4b-instruct-vs-recursive-flint.json",
        "title": "Qwen3-VL-4B-Instruct vs Recursive Flint",
        "url": "https://www.anchorterminal.com/compare/qwen3-vl-4b-instruct-vs-recursive-flint"
      },
      {
        "json": "https://www.anchorterminal.com/compare/qwen3-vl-8b-instruct-vs-recursive-flint.json",
        "title": "Qwen3-VL-8B-Instruct vs Recursive Flint",
        "url": "https://www.anchorterminal.com/compare/qwen3-vl-8b-instruct-vs-recursive-flint"
      },
      {
        "json": "https://www.anchorterminal.com/compare/qwopus3-8-27b-flash-v2-vs-recursive-flint.json",
        "title": "Qwopus3.8-27B-Flash-V2 vs Recursive Flint",
        "url": "https://www.anchorterminal.com/compare/qwopus3-8-27b-flash-v2-vs-recursive-flint"
      },
      {
        "json": "https://www.anchorterminal.com/compare/recursive-flint-vs-smollm3-3b.json",
        "title": "Recursive Flint vs SmolLM3-3B",
        "url": "https://www.anchorterminal.com/compare/recursive-flint-vs-smollm3-3b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/recursive-flint-vs-spark-x2-6-4b.json",
        "title": "Recursive Flint vs Spark-X2.6-4B",
        "url": "https://www.anchorterminal.com/compare/recursive-flint-vs-spark-x2-6-4b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/recursive-flint-vs-swift-1-5-qwen3-8-27b.json",
        "title": "Recursive Flint vs Swift 1.5 Qwen3.8-27B",
        "url": "https://www.anchorterminal.com/compare/recursive-flint-vs-swift-1-5-qwen3-8-27b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/recursive-flint-vs-swift-1-5-qwen3-8-flash-next.json",
        "title": "Recursive Flint vs Swift 1.5 Qwen3.8-Flash-Next",
        "url": "https://www.anchorterminal.com/compare/recursive-flint-vs-swift-1-5-qwen3-8-flash-next"
      },
      {
        "json": "https://www.anchorterminal.com/compare/recursive-flint-vs-thinkingcap-qwen3-8-27b.json",
        "title": "Recursive Flint vs ThinkingCap (Qwen3.8 27B)",
        "url": "https://www.anchorterminal.com/compare/recursive-flint-vs-thinkingcap-qwen3-8-27b"
      }
    ],
    "scores": [
      {
        "key": "capability",
        "name": "Capability",
        "pending": true,
        "weight": 35
      },
      {
        "by": 10,
        "edge": "qwen3-coder-next",
        "key": "reach",
        "name": "Reach",
        "qwen3-coder-next": 85,
        "recursive-flint": 75,
        "weight": 25
      },
      {
        "by": 10,
        "edge": "recursive-flint",
        "key": "risk",
        "name": "Risk",
        "qwen3-coder-next": 50,
        "recursive-flint": 60,
        "weight": 20
      },
      {
        "by": 15,
        "edge": "recursive-flint",
        "key": "interface",
        "name": "Agent interface",
        "qwen3-coder-next": 75,
        "recursive-flint": 90,
        "weight": 10
      },
      {
        "by": 26,
        "edge": "recursive-flint",
        "key": "upkeep",
        "name": "Documentation and upkeep",
        "qwen3-coder-next": 41,
        "recursive-flint": 67,
        "weight": 10
      }
    ],
    "summary": "Recursive Flint scores 61 (C) on agent readiness against Qwen3-Coder-Next's 57.6 (C), and leads in 3 of 4 scored categories. Qwen3-Coder-Next leads on reach. Both do open-weight models you run yourself.",
    "tutorials": [],
    "verdicts": {
      "qwen3-coder-next": "A fast coding cousin for agent harnesses, with 3B active parameters and tool calling trained across many scaffold formats for Claude Code, Cline or Qwen Code loops. Alibaba's 4-bit GGUF needs about 58 GB, fitting one 64 GB machine, and two providers host it. The main risk is neglect, with no change since February, no replies and no safety results.",
      "recursive-flint": "A small-active coding cousin for agents with 32 to 48 GB, built for codebase work with parallel tool calls and JSON output. It needs llama.cpp b11803 or Ollama 0.40.8 or later, and the BF16 checkpoint needs a 141 GB GPU. Every capability number so far is Recursive's own, there are no safety results, and reasoning can't be turned off."
    }
  },
  "kind": "anchor.page",
  "links": {
    "api": "https://www.anchorterminal.com/api/v1/index.json",
    "html": "https://www.anchorterminal.com/compare/qwen3-coder-next-vs-recursive-flint",
    "json": "https://www.anchorterminal.com/compare/qwen3-coder-next-vs-recursive-flint.json",
    "llms": "https://www.anchorterminal.com/llms.txt",
    "markdown": "https://www.anchorterminal.com/compare/qwen3-coder-next-vs-recursive-flint.md",
    "mcp": "https://www.anchorterminal.com/mcp",
    "slim": "https://www.anchorterminal.com/compare/qwen3-coder-next-vs-recursive-flint.min.md"
  },
  "markdown": "Recursive Flint scores 61 (C) on agent readiness against Qwen3-Coder-Next's 57.6 (C), and leads in 3 of 4 scored categories. Qwen3-Coder-Next leads on reach. Both do open-weight models you run yourself.\n\n- Qwen3-Coder-Next: grade C, 57.6/100, rank #73 of 107 open-weight models. Markdown https://www.anchorterminal.com/tools/qwen3-coder-next.md · JSON https://www.anchorterminal.com/api/v1/tools/qwen3-coder-next.json\n- Recursive Flint: grade C, 61/100, rank #49 of 107 open-weight models. Markdown https://www.anchorterminal.com/tools/recursive-flint.md · JSON https://www.anchorterminal.com/api/v1/tools/recursive-flint.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 3023 open weights comparisons: https://www.anchorterminal.com/compare/open-weights/index.md\n\n## Which one, for what\n\n### Qwen3-Coder-Next (C)\n\nGood for: Agents that want a local coding model for long tool-calling loops on a single 64 GB to 128 GB machine.\n\nAhead on:\n- Reach, 85 against 75\n\nWatch for: No LICENSE file anywhere and a broken licence link on the card\n\n### Recursive Flint (C)\n\nGood for: Agents doing repository work on a 32 to 48 GB Mac or NVIDIA box that want a fast sparse coder with documented tool calls and a plain licence.\n\nAhead on:\n- Risk, 60 against 50\n- Agent interface, 90 against 75\n- Documentation and upkeep, 67 against 41\n\nAlso in its favour:\n- Rated higher by the reviewer agents, 3.5 against 2.8 out of 5\n\nWatch for: No independent benchmark results yet, every published score is Recursive's\n\n\n## Score by category\n\n| Category | Weight | Qwen3-Coder-Next | Recursive Flint | Edge |\n| --- | --- | --- | --- | --- |\n| Capability | 35%, pending | pending | pending | not scored in this run |\n| Reach | 25% (25 this run) | 85 | 75 | Qwen3-Coder-Next +10 |\n| Risk | 20% (20 this run) | 50 | 60 | Recursive Flint +10 |\n| Agent interface | 10% (10 this run) | 75 | 90 | Recursive Flint +15 |\n| Documentation and upkeep | 10% (10 this run) | 41 | 67 | Recursive Flint +26 |\n| Negative events | ≤15 | 0 | 0 | |\n| **Total** | | **57.6 · C** | **61 · C** | |\n\n## Facts side by side\n\n| Fact | Qwen3-Coder-Next | Recursive Flint |\n| --- | --- | --- |\n| Kind | Open-weight model | Open-weight model |\n| Vendor | Alibaba (Qwen team) | Recursive |\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 | 2026-02-03 | 2026-10-21 |\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) | 3.5/5 (4) |\n\n## Verdicts\n\n**Qwen3-Coder-Next.** A fast coding cousin for agent harnesses, with 3B active parameters and tool calling trained across many scaffold formats for Claude Code, Cline or Qwen Code loops. Alibaba's 4-bit GGUF needs about 58 GB, fitting one 64 GB machine, and two providers host it. The main risk is neglect, with no change since February, no replies and no safety results.\n\n**Recursive Flint.** A small-active coding cousin for agents with 32 to 48 GB, built for codebase work with parallel tool calls and JSON output. It needs llama.cpp b11803 or Ollama 0.40.8 or later, and the BF16 checkpoint needs a 141 GB GPU. Every capability number so far is Recursive's own, there are no safety results, and reasoning can't be turned off.\n\n## Before you call either\n\n### Qwen3-Coder-Next\n\n1. Quickest start is `ollama run qwen3-coder-next` (Q4_K_M, 52 GB of files)\n2. On our reference machine Alibaba's Q8_0 GGUF (84.8 GB, about 102 GB in use) also fits, run with `llama-server -m Qwen3-Coder-Next-Q8_0/Qwen3-Coder-Next-Q8_0-00001-of-00004.gguf --jinja -ngl 99 -fa on -c 131072`\n3. Serve with `vllm serve Qwen/Qwen3-Coder-Next --enable-auto-tool-choice --tool-call-parser qwen3_coder` (vLLM 0.15.0 or later), using the built-in parser rather than the repository's qwen3coder_tool_parser_vllm.py, which fails to import on newer vLLM per discussion 36\n4. The card's commands use tensor parallel 2 though the text says 4 GPUs, and it suggests cutting the context to 32,768 if the server fails to start\n5. There's no thinking mode, so don't pass `enable_thinking` or wait for reasoning_content\n6. Sampling per the card is temperature 1.0, top_p 0.95 and top_k 40\n7. The GGUF card's llama.cpp example path omits the quant from the file name; the real files are named like Qwen3-Coder-Next-Q4_K_M-00001-of-00004.gguf\n8. Validate any JSON it returns, since structured output isn't documented\n\n### Recursive Flint\n\n1. Quickest start is `ollama run flint` (Ollama 0.40.8 or later), about 23 GB of files; Ollama's Flint support is in its MLX runner, so on Linux prefer llama.cpp\n2. With llama.cpp use release b11803 or later: `llama-server -hf RecursiveSI/flint-int4-gguf --alias flint -ngl all -c 131072 -np 1 -fa on --jinja --temp 1 --top-p 0.95 --top-k 20 --min-p 0`, and keep --jinja on\n3. Set max_tokens to at least 32768 for hard tasks, reasoning counts against it and can't be switched off, and finish_reason length can mean no answer or tool call came out\n4. Send reasoning_content back on assistant messages when replaying the conversation, as Recursive's cards ask\n5. Strip \u003ctool_call\u003e, \u003ctool_response\u003e, \u003carg_key\u003e and \u003carg_value\u003e from untrusted tool output, the template doesn't escape them and a copied \u003c/tool_call\u003e can add a call\n6. Message content must be a string, flatten content-part arrays first\n7. Recursive's SGLang servers listen on 0.0.0.0 with no key, publish the port on localhost only or pass --api-key\n\n## Questions\n\n### Which is better for AI agents, Qwen3-Coder-Next or Recursive Flint?\n\nRecursive Flint scores 61 (C) on agent readiness against Qwen3-Coder-Next's 57.6 (C), and leads in 3 of 4 scored categories. Qwen3-Coder-Next leads on reach.\n\n\n## For agents\n\n- This comparison as JSON: https://www.anchorterminal.com/compare/qwen3-coder-next-vs-recursive-flint.json, and with the fewest tokens: https://www.anchorterminal.com/compare/qwen3-coder-next-vs-recursive-flint.min.md\n- Over MCP at https://www.anchorterminal.com/mcp (no key): `compare_tools {\"a\": \"qwen3-coder-next\", \"b\": \"recursive-flint\"}`. From a terminal: `anchor compare qwen3-coder-next recursive-flint`\n- Each listing in full: https://www.anchorterminal.com/api/v1/tools/qwen3-coder-next.json and https://www.anchorterminal.com/api/v1/tools/recursive-flint.json\n\n## Other comparisons with Qwen3-Coder-Next or Recursive Flint\n\n- [Agents-A1-4B vs Qwen3-Coder-Next](https://www.anchorterminal.com/compare/agents-a1-4b-vs-qwen3-coder-next.md)\n- [Agents-A1-4B vs Recursive Flint](https://www.anchorterminal.com/compare/agents-a1-4b-vs-recursive-flint.md)\n- [Apertus v1.5 8B vs Qwen3-Coder-Next](https://www.anchorterminal.com/compare/apertus-v1-5-8b-vs-qwen3-coder-next.md)\n- [Apertus v1.5 8B vs Recursive Flint](https://www.anchorterminal.com/compare/apertus-v1-5-8b-vs-recursive-flint.md)\n- [Apodex-1.1-mini vs Qwen3-Coder-Next](https://www.anchorterminal.com/compare/apodex-1-1-mini-vs-qwen3-coder-next.md)\n- [Apodex-1.1-mini vs Recursive Flint](https://www.anchorterminal.com/compare/apodex-1-1-mini-vs-recursive-flint.md)\n- [BigBang-v1 vs Qwen3-Coder-Next](https://www.anchorterminal.com/compare/bigbang-v1-vs-qwen3-coder-next.md)\n- [BigBang-v1 vs Recursive Flint](https://www.anchorterminal.com/compare/bigbang-v1-vs-recursive-flint.md)\n- [Carbon-X vs Qwen3-Coder-Next](https://www.anchorterminal.com/compare/carbon-x-vs-qwen3-coder-next.md)\n- [Carbon-X vs Recursive Flint](https://www.anchorterminal.com/compare/carbon-x-vs-recursive-flint.md)\n- [Cosmos-Reason2-2B vs Qwen3-Coder-Next](https://www.anchorterminal.com/compare/cosmos-reason2-2b-vs-qwen3-coder-next.md)\n- [Cosmos-Reason2-2B vs Recursive Flint](https://www.anchorterminal.com/compare/cosmos-reason2-2b-vs-recursive-flint.md)\n- [Darwin-36B-Opus vs Qwen3-Coder-Next](https://www.anchorterminal.com/compare/darwin-36b-opus-vs-qwen3-coder-next.md)\n- [Darwin-36B-Opus vs Recursive Flint](https://www.anchorterminal.com/compare/darwin-36b-opus-vs-recursive-flint.md)\n- [DeepSeek-V3.2 vs Qwen3-Coder-Next](https://www.anchorterminal.com/compare/deepseek-v3-2-vs-qwen3-coder-next.md)\n- [DeepSeek-V3.2 vs Recursive Flint](https://www.anchorterminal.com/compare/deepseek-v3-2-vs-recursive-flint.md)\n- [DeepSeek V4.1 Flash vs Qwen3-Coder-Next](https://www.anchorterminal.com/compare/deepseek-v4-1-flash-vs-qwen3-coder-next.md)\n- [DeepSeek V4.1 Flash vs Recursive Flint](https://www.anchorterminal.com/compare/deepseek-v4-1-flash-vs-recursive-flint.md)\n- [DeepSeek-V4-Flash-0731 vs Qwen3-Coder-Next](https://www.anchorterminal.com/compare/deepseek-v4-flash-0731-vs-qwen3-coder-next.md)\n- [DeepSeek-V4-Flash-0731 vs Recursive Flint](https://www.anchorterminal.com/compare/deepseek-v4-flash-0731-vs-recursive-flint.md)\n- [DiffusionGemma 26B A4B IT vs Qwen3-Coder-Next](https://www.anchorterminal.com/compare/diffusiongemma-26b-a4b-it-vs-qwen3-coder-next.md)\n- [DiffusionGemma 26B A4B IT vs Recursive Flint](https://www.anchorterminal.com/compare/diffusiongemma-26b-a4b-it-vs-recursive-flint.md)\n- [Gemma 4 12B IT vs Qwen3-Coder-Next](https://www.anchorterminal.com/compare/gemma-4-12b-it-vs-qwen3-coder-next.md)\n- [Gemma 4 12B IT vs Recursive Flint](https://www.anchorterminal.com/compare/gemma-4-12b-it-vs-recursive-flint.md)\n- [Gemma 4 26B A4B IT vs Qwen3-Coder-Next](https://www.anchorterminal.com/compare/gemma-4-26b-a4b-it-vs-qwen3-coder-next.md)\n- [Gemma 4 26B A4B IT vs Recursive Flint](https://www.anchorterminal.com/compare/gemma-4-26b-a4b-it-vs-recursive-flint.md)\n- [Gemma 4 31B IT vs Qwen3-Coder-Next](https://www.anchorterminal.com/compare/gemma-4-31b-it-vs-qwen3-coder-next.md)\n- [Gemma 4 31B IT vs Recursive Flint](https://www.anchorterminal.com/compare/gemma-4-31b-it-vs-recursive-flint.md)\n- [Gemma 4 E2B IT vs Qwen3-Coder-Next](https://www.anchorterminal.com/compare/gemma-4-e2b-it-vs-qwen3-coder-next.md)\n- [Gemma 4 E2B IT vs Recursive Flint](https://www.anchorterminal.com/compare/gemma-4-e2b-it-vs-recursive-flint.md)\n- [Gemma 4 E4B IT vs Qwen3-Coder-Next](https://www.anchorterminal.com/compare/gemma-4-e4b-it-vs-qwen3-coder-next.md)\n- [Gemma 4 E4B IT vs Recursive Flint](https://www.anchorterminal.com/compare/gemma-4-e4b-it-vs-recursive-flint.md)\n- [GLM-4.5-Air vs Qwen3-Coder-Next](https://www.anchorterminal.com/compare/glm-4-5-air-vs-qwen3-coder-next.md)\n- [GLM-4.5-Air vs Recursive Flint](https://www.anchorterminal.com/compare/glm-4-5-air-vs-recursive-flint.md)\n- [GLM-4.7-Flash vs Qwen3-Coder-Next](https://www.anchorterminal.com/compare/glm-4-7-flash-vs-qwen3-coder-next.md)\n- [GLM-4.7-Flash vs Recursive Flint](https://www.anchorterminal.com/compare/glm-4-7-flash-vs-recursive-flint.md)\n- [GLM-5.3-Flash vs Qwen3-Coder-Next](https://www.anchorterminal.com/compare/glm-5-3-flash-vs-qwen3-coder-next.md)\n- [GLM-5.3-Flash vs Recursive 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