{
  "data": {
    "a": {
      "slug": "qwen3-8-flash-next",
      "name": "Qwen3.8-Flash-Next",
      "vendor": "Alibaba (Qwen team)",
      "vendorUrl": "https://qwen.ai",
      "kind": "weights",
      "category": "open-weights",
      "summary": "Qwen3.8-Flash-Next is Alibaba's open-weight multimodal mixture-of-experts model and an experimental preview of the Qwen4 architecture, 125B parameters with 6B active plus a 51B n-gram embedding table, published on Hugging Face in BF16 and FP8.",
      "url": "https://www.anchorterminal.com/tools/qwen3-8-flash-next",
      "markdownUrl": "https://www.anchorterminal.com/tools/qwen3-8-flash-next.md",
      "slimMarkdownUrl": "https://www.anchorterminal.com/tools/qwen3-8-flash-next.min.md",
      "jsonUrl": "https://www.anchorterminal.com/api/v1/tools/qwen3-8-flash-next.json",
      "repo": "https://huggingface.co/Qwen/Qwen3.8-Flash-Next",
      "license": "Qwen Community License 1.0 (custom, not an OSI licence). Free of charge, the model name shown in products above 100M monthly users or US$20M monthly revenue, and a separate licence from Qwen before commercial use by a Model as a Service or AI Work Assistant business",
      "transports": [],
      "packages": [
        {
          "registry": "huggingface",
          "name": "Qwen/Qwen3.8-Flash-Next"
        },
        {
          "registry": "huggingface",
          "name": "Qwen/Qwen3.8-Flash-Next-FP8"
        },
        {
          "registry": "ollama",
          "name": "qwen3.8-flash-next"
        }
      ],
      "auth": "none",
      "authNotes": "The weights download from Hugging Face with no account, token or terms to accept. Neither repository is gated (checked 2026-10-21).",
      "pricing": "free",
      "pricingNotes": "Free to download and use under the Qwen Community License 1.0. A licensee whose group runs a Model as a Service or AI Work Assistant business (AI coding or office productivity products) needs a separate licence from Qwen, with no published price, before any commercial use beyond internal use. Running it yourself costs the hardware, 360.0 GB for the BF16 files, 185.5 GB for FP8 and 105 GB for Ollama's MLX build (checked 2026-10-21).",
      "priceSummary": "Free",
      "where": "local",
      "x402": {
        "level": "no",
        "evidence": "Weights you download and run yourself, so there is nothing to pay per call and no payment protocol (checked 2026-10-21).",
        "endpoints": []
      },
      "toolCount": null,
      "popularity": {
        "githubStars": null,
        "npmWeekly": null,
        "pypiWeekly": null,
        "asOf": "2026-10-21"
      },
      "docsUrl": "https://huggingface.co/Qwen/Qwen3.8-Flash-Next",
      "capabilities": [
        "model.open-weights"
      ],
      "tags": [
        "open-weights",
        "model",
        "moe",
        "multimodal",
        "reasoning",
        "tool-calling",
        "source-available",
        "safetensors",
        "fp8",
        "self-hosted",
        "preview"
      ],
      "lastRelease": "2026-08-31",
      "graded": true,
      "anchor": {
        "graded": true,
        "score": 61.8,
        "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": 25,
        "methodology": "0.6",
        "run": "2026-10-01",
        "scores": {
          "capability": 74,
          "interface": 70,
          "reach": 65,
          "risk": 45,
          "upkeep": 36
        },
        "pending": [
          "performance",
          "tasks"
        ],
        "assessment": {
          "confidence": "high",
          "date": "2026-10-21"
        },
        "negative": 0,
        "verdict": "A large sparse cousin with 6B active parameters for agentic coding and multimodal work, previewing Qwen's next architecture. It needs a 128 GB Mac for Ollama's MLX build or about 144 GB for the 4-bit GGUF, and Qwen Cloud serves it. The main risk is a licence that needs a separate deal for hosted-model and coding or office assistant businesses.",
        "bestFor": "Teams with a multi-GPU server or a 128 GB Mac who want Qwen's newest sparse architecture for agentic coding and multimodal work, and aren't a hosted-model or coding-assistant business.",
        "strengths": [
          "Released support in llama.cpp, Ollama, vLLM, SGLang and Transformers",
          "262,144 tokens of native context, several tool calls per turn, and thinking that turns off per request with three effort levels",
          "Safetensors only, a chat template in the repository and a SHA-256 for every weight file",
          "No gate on the download, and Alibaba's Qwen Cloud serves it for agents without the hardware"
        ],
        "weaknesses": [
          "No build fits the reference machine's 107.4 GB, and Ollama's smallest Linux build is 120 GB",
          "The Qwen Community License requires a separate licence before commercial use by a model-as-a-service or coding or office assistant business",
          "No safety results, agent guidance, training data, limitations, languages or knowledge cut-off published",
          "Labelled an experimental preview, and Qwen has answered none of the 40 most recent discussions",
          "The tool-calling format is only in the template, and structured output isn't documented"
        ],
        "agentNotes": [
          "On a 128 GB Mac start it with `ollama run qwen3.8-flash-next:125b-mlx` (105 GB, NVFP4), on Linux the smallest Ollama build is `qwen3.8-flash-next:125b-a6b-q4_K_M` at 120 GB, which won't fit a 107.4 GB GPU share",
          "On a server, `vllm serve Qwen/Qwen3.8-Flash-Next-FP8 --tensor-parallel-size 4 --max-model-len 262144 --reasoning-parser qwen3 --enable-auto-tool-choice --tool-call-parser qwen3_coder`",
          "Use the qwen3_coder tool parser and the qwen3 reasoning parser, as Qwen's GitHub README does",
          "Thinking is on by default, pass `chat_template_kwargs` with `enable_thinking` false to skip it, and read the reasoning from `reasoning_content`, even though SGLang's cookbook says thinking can't be turned off",
          "`reasoning_effort` takes xhigh (default), medium or low, and any other value makes the template raise an error",
          "Send at most one system message and put it first, since the template raises an error otherwise",
          "Sampling per the card is temperature 1.0 and top_p 0.95 when thinking, temperature 0.7, top_p 0.8 and presence_penalty 1.5 without",
          "vLLM keeps the 51B n-gram table in host memory on 80 GB GPUs by default, per its recipe",
          "Validate JSON output yourself or use the runtime's guided decoding, since structured output isn't documented",
          "Read the Qwen Community License before serving it to others as an API or inside a coding or office assistant product"
        ],
        "metrics": {
          "kind": "local",
          "measured": false
        },
        "reviewCount": 4,
        "avgRating": 2,
        "history": [
          {
            "basis": "public evidence",
            "confidence": "high",
            "grade": "C",
            "methodology": "0.6",
            "pending": [
              "performance",
              "tasks"
            ],
            "run": "2026-10-01",
            "runLabel": "October 2026 research run",
            "score": 61.8
          }
        ],
        "editorialScores": {
          "capability": 74,
          "interface": 70,
          "reach": 65,
          "risk": 45,
          "upkeep": 36
        },
        "provenanceScore": 49,
        "checked": {
          "categories": {
            "capability": "2026-10-21",
            "interface": "2026-10-21",
            "reach": "2026-10-21",
            "risk": "2026-10-21",
            "upkeep": "2026-10-21"
          },
          "last": "2026-10-21",
          "oldest": "2026-10-21",
          "stale": false,
          "staleAfterDays": 90
        }
      },
      "connect": {
        "install": "ollama run qwen3.8-flash-next:125b-mlx\n# or, as Qwen's GitHub README serves it (4 GPUs):\nvllm serve Qwen/Qwen3.8-Flash-Next --port 8000 --tensor-parallel-size 4 --max-model-len 262144 \\\n  --reasoning-parser qwen3 --enable-auto-tool-choice --tool-call-parser qwen3_coder",
        "http": "curl http://localhost:8000/v1/chat/completions \\\n  -H \"Content-Type: application/json\" \\\n  -d '{\n    \"model\": \"Qwen/Qwen3.8-Flash-Next\",\n    \"messages\": [{\"role\": \"user\", \"content\": \"Hello!\"}],\n    \"chat_template_kwargs\": {\"enable_thinking\": false}\n  }'"
      },
      "letme": {
        "capability": "https://letme.dev/model.open-weights",
        "tool": "https://letme.dev/qwen3-8-flash-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-coder-next",
        "qwen3-omni-30b-a3b-instruct",
        "qwen3-vl-2b-instruct",
        "qwen3-vl-30b-a3b-instruct",
        "qwen3-vl-32b-instruct",
        "qwen3-vl-4b-instruct",
        "qwen3-vl-8b-instruct",
        "qwen3-5-0-8b",
        "qwen3-5-122b-a10b",
        "qwen3-5-2b",
        "qwen3-5-397b-a17b",
        "qwen3-5-4b",
        "qwen3-5-9b",
        "qwen3-6-27b",
        "qwen3-6-35b-a3b",
        "qwen3-8-27b"
      ],
      "weights": {
        "trainedBy": "Alibaba (Qwen team)",
        "params": "125B",
        "active": "6B",
        "context": 262144,
        "goodFor": "Experimental preview of the Qwen4 architecture: a multimodal mixture-of-experts model with tool calling and adjustable reasoning effort.",
        "runtimes": [
          "llama.cpp",
          "Ollama",
          "vLLM",
          "SGLang",
          "Transformers"
        ],
        "builds": [
          {
            "name": "Qwen3.8-Flash-Next-FP4-Local",
            "url": "https://huggingface.co/nvidia/Qwen3.8-Flash-Next-FP4-Local",
            "who": "NVIDIA",
            "precision": "nvfp4",
            "sizeGB": 102.2,
            "memoryGB": 128,
            "format": "safetensors",
            "note": "NVIDIA's own FP4 build (Model Optimizer), made for NVIDIA Blackwell GPUs such as DGX Spark and RTX PRO 6000; FP4 kernels don't run on the AMD reference machine. Not the publisher's build, so it doesn't count toward Reach's memory item. Size summed from the Hub's file list on 21 October 2026."
          },
          {
            "name": "ollama qwen3.8-flash-next:125b-a6b-q4_K_M",
            "url": "https://ollama.com/library/qwen3.8-flash-next:125b-a6b-q4_K_M",
            "who": "ollama",
            "precision": "q4_k_m",
            "sizeGB": 120,
            "memoryGB": 192,
            "format": "ollama",
            "runsOn": [
              "Ollama"
            ],
            "note": "Smallest non-MLX Ollama build; the library has no latest tag, and its 105 GB 125b-mlx tag is Apple-only. Size as Ollama's tags page shows it, rounded to whole GB above 10 GB; the Linux build is the llama.cpp variant"
          },
          {
            "name": "Qwen3.8-Flash-Next-NVFP4",
            "url": "https://huggingface.co/nvidia/Qwen3.8-Flash-Next-NVFP4",
            "who": "NVIDIA",
            "precision": "nvfp4",
            "sizeGB": 132.7,
            "memoryGB": 192,
            "format": "safetensors",
            "note": "NVIDIA's own FP4 build (Model Optimizer), made for NVIDIA Blackwell GPUs such as DGX Spark and RTX PRO 6000; FP4 kernels don't run on the AMD reference machine. Not the publisher's build, so it doesn't count toward Reach's memory item. Size summed from the Hub's file list on 21 October 2026."
          },
          {
            "name": "Qwen3.8-Flash-Next-FP8",
            "url": "https://huggingface.co/Qwen/Qwen3.8-Flash-Next-FP8",
            "who": "publisher",
            "precision": "fp8",
            "sizeGB": 185.5,
            "memoryGB": 256,
            "format": "safetensors"
          },
          {
            "name": "Qwen3.8-Flash-Next",
            "url": "https://huggingface.co/Qwen/Qwen3.8-Flash-Next",
            "who": "publisher",
            "precision": "bf16",
            "sizeGB": 360,
            "memoryGB": 512,
            "format": "safetensors",
            "runsOn": [
              "vLLM (ROCm)",
              "SGLang (ROCm)"
            ]
          }
        ],
        "run": "vllm serve Qwen/Qwen3.8-Flash-Next-FP8 --tensor-parallel-size 4 --max-model-len 262144 --reasoning-parser qwen3 --enable-auto-tool-choice --tool-call-parser qwen3_coder",
        "runBuild": "Qwen3.8-Flash-Next-FP8",
        "checked": "2026-10-21",
        "minMemoryGB": 128
      },
      "family": {
        "lab": "Alibaba (Qwen)",
        "family": "Qwen3",
        "url": "https://www.anchorterminal.com/open-weights/#qwen",
        "others": [
          {
            "name": "Qwen3-0.6B",
            "url": "https://huggingface.co/Qwen/Qwen3-0.6B",
            "params": "0.6B"
          },
          {
            "name": "Qwen3-1.7B",
            "url": "https://huggingface.co/Qwen/Qwen3-1.7B",
            "params": "1.7B"
          },
          {
            "name": "Qwen3-14B",
            "url": "https://huggingface.co/Qwen/Qwen3-14B",
            "params": "14B"
          },
          {
            "name": "Qwen3-235B-A22B",
            "url": "https://huggingface.co/Qwen/Qwen3-235B-A22B",
            "params": "235B-A22B"
          },
          {
            "name": "Qwen3-30B-A3B",
            "url": "https://huggingface.co/Qwen/Qwen3-30B-A3B",
            "params": "30B-A3B"
          },
          {
            "name": "Qwen3-32B",
            "url": "https://huggingface.co/Qwen/Qwen3-32B",
            "params": "32B"
          },
          {
            "name": "Qwen3-4B",
            "url": "https://huggingface.co/Qwen/Qwen3-4B",
            "params": "4B"
          },
          {
            "name": "Qwen3-8B",
            "url": "https://huggingface.co/Qwen/Qwen3-8B",
            "params": "8B"
          },
          {
            "name": "Qwen3-0.6B-Base",
            "url": "https://huggingface.co/Qwen/Qwen3-0.6B-Base",
            "params": "0.6B"
          },
          {
            "name": "Qwen3-1.7B-Base",
            "url": "https://huggingface.co/Qwen/Qwen3-1.7B-Base",
            "params": "1.7B"
          },
          {
            "name": "Qwen3-14B-Base",
            "url": "https://huggingface.co/Qwen/Qwen3-14B-Base",
            "params": "14B"
          },
          {
            "name": "Qwen3-30B-A3B-Base",
            "url": "https://huggingface.co/Qwen/Qwen3-30B-A3B-Base",
            "params": "30B-A3B"
          },
          {
            "name": "Qwen3-4B-Base",
            "url": "https://huggingface.co/Qwen/Qwen3-4B-Base",
            "params": "4B"
          },
          {
            "name": "Qwen3-8B-Base",
            "url": "https://huggingface.co/Qwen/Qwen3-8B-Base",
            "params": "8B"
          },
          {
            "name": "Qwen3-Reranker-0.6B",
            "url": "https://huggingface.co/Qwen/Qwen3-Reranker-0.6B",
            "params": "0.6B"
          },
          {
            "name": "Qwen3-Reranker-8B",
            "url": "https://huggingface.co/Qwen/Qwen3-Reranker-8B",
            "params": "8B"
          },
          {
            "name": "Qwen3-Embedding-0.6B",
            "url": "https://huggingface.co/Qwen/Qwen3-Embedding-0.6B",
            "params": "0.6B",
            "listing": "https://www.anchorterminal.com/tools/qwen3-embedding-0-6b"
          },
          {
            "name": "Qwen3-Embedding-4B",
            "url": "https://huggingface.co/Qwen/Qwen3-Embedding-4B",
            "params": "4B",
            "listing": "https://www.anchorterminal.com/tools/qwen3-embedding-4b"
          },
          {
            "name": "Qwen3-Embedding-8B",
            "url": "https://huggingface.co/Qwen/Qwen3-Embedding-8B",
            "params": "8B",
            "listing": "https://www.anchorterminal.com/tools/qwen3-embedding-8b"
          },
          {
            "name": "Qwen3-Reranker-4B",
            "url": "https://huggingface.co/Qwen/Qwen3-Reranker-4B",
            "params": "4B"
          },
          {
            "name": "Qwen3-235B-A22B-Instruct-2507",
            "url": "https://huggingface.co/Qwen/Qwen3-235B-A22B-Instruct-2507",
            "params": "235B-A22B"
          },
          {
            "name": "Qwen3-Coder-480B-A35B-Instruct",
            "url": "https://huggingface.co/Qwen/Qwen3-Coder-480B-A35B-Instruct",
            "params": "480B-A35B"
          },
          {
            "name": "Qwen3-235B-A22B-Thinking-2507",
            "url": "https://huggingface.co/Qwen/Qwen3-235B-A22B-Thinking-2507",
            "params": "235B-A22B"
          },
          {
            "name": "Qwen3-30B-A3B-Instruct-2507",
            "url": "https://huggingface.co/Qwen/Qwen3-30B-A3B-Instruct-2507",
            "params": "30B-A3B",
            "listing": "https://www.anchorterminal.com/tools/qwen3-30b-a3b-instruct-2507"
          },
          {
            "name": "Qwen3-30B-A3B-Thinking-2507",
            "url": "https://huggingface.co/Qwen/Qwen3-30B-A3B-Thinking-2507",
            "params": "30B-A3B"
          },
          {
            "name": "Qwen3-Coder-30B-A3B-Instruct",
            "url": "https://huggingface.co/Qwen/Qwen3-Coder-30B-A3B-Instruct",
            "params": "30B-A3B",
            "listing": "https://www.anchorterminal.com/tools/qwen3-coder-30b-a3b-instruct"
          },
          {
            "name": "Qwen3-4B-Instruct-2507",
            "url": "https://huggingface.co/Qwen/Qwen3-4B-Instruct-2507",
            "params": "4B",
            "listing": "https://www.anchorterminal.com/tools/qwen3-4b-instruct-2507"
          },
          {
            "name": "Qwen3-4B-Thinking-2507",
            "url": "https://huggingface.co/Qwen/Qwen3-4B-Thinking-2507",
            "params": "4B"
          },
          {
            "name": "Qwen3-Next-80B-A3B-Instruct",
            "url": "https://huggingface.co/Qwen/Qwen3-Next-80B-A3B-Instruct",
            "params": "80B-A3B"
          },
          {
            "name": "Qwen3-Next-80B-A3B-Thinking",
            "url": "https://huggingface.co/Qwen/Qwen3-Next-80B-A3B-Thinking",
            "params": "80B-A3B"
          },
          {
            "name": "Qwen3-Omni-30B-A3B-Captioner",
            "url": "https://huggingface.co/Qwen/Qwen3-Omni-30B-A3B-Captioner",
            "params": "30B-A3B"
          },
          {
            "name": "Qwen3-Omni-30B-A3B-Thinking",
            "url": "https://huggingface.co/Qwen/Qwen3-Omni-30B-A3B-Thinking",
            "params": "30B-A3B"
          },
          {
            "name": "Qwen3-Omni-30B-A3B-Instruct",
            "url": "https://huggingface.co/Qwen/Qwen3-Omni-30B-A3B-Instruct",
            "params": "30B-A3B",
            "listing": "https://www.anchorterminal.com/tools/qwen3-omni-30b-a3b-instruct"
          },
          {
            "name": "Qwen3-VL-235B-A22B-Instruct",
            "url": "https://huggingface.co/Qwen/Qwen3-VL-235B-A22B-Instruct",
            "params": "235B-A22B"
          },
          {
            "name": "Qwen3-VL-235B-A22B-Thinking",
            "url": "https://huggingface.co/Qwen/Qwen3-VL-235B-A22B-Thinking",
            "params": "235B-A22B"
          },
          {
            "name": "Qwen3Guard-Gen-0.6B",
            "url": "https://huggingface.co/Qwen/Qwen3Guard-Gen-0.6B",
            "params": "0.6B"
          },
          {
            "name": "Qwen3Guard-Gen-4B",
            "url": "https://huggingface.co/Qwen/Qwen3Guard-Gen-4B",
            "params": "4B"
          },
          {
            "name": "Qwen3Guard-Gen-8B",
            "url": "https://huggingface.co/Qwen/Qwen3Guard-Gen-8B",
            "params": "8B"
          },
          {
            "name": "Qwen3Guard-Stream-0.6B",
            "url": "https://huggingface.co/Qwen/Qwen3Guard-Stream-0.6B",
            "params": "0.6B"
          },
          {
            "name": "Qwen3Guard-Stream-4B",
            "url": "https://huggingface.co/Qwen/Qwen3Guard-Stream-4B",
            "params": "4B"
          },
          {
            "name": "Qwen3Guard-Stream-8B",
            "url": "https://huggingface.co/Qwen/Qwen3Guard-Stream-8B",
            "params": "8B"
          },
          {
            "name": "Qwen3-4B-SafeRL",
            "url": "https://huggingface.co/Qwen/Qwen3-4B-SafeRL",
            "params": "4B"
          },
          {
            "name": "Qwen3-VL-30B-A3B-Instruct",
            "url": "https://huggingface.co/Qwen/Qwen3-VL-30B-A3B-Instruct",
            "params": "30B-A3B",
            "listing": "https://www.anchorterminal.com/tools/qwen3-vl-30b-a3b-instruct"
          },
          {
            "name": "Qwen3-VL-30B-A3B-Thinking",
            "url": "https://huggingface.co/Qwen/Qwen3-VL-30B-A3B-Thinking",
            "params": "30B-A3B"
          },
          {
            "name": "Qwen3-VL-4B-Instruct",
            "url": "https://huggingface.co/Qwen/Qwen3-VL-4B-Instruct",
            "params": "4B",
            "listing": "https://www.anchorterminal.com/tools/qwen3-vl-4b-instruct"
          },
          {
            "name": "Qwen3-VL-4B-Thinking",
            "url": "https://huggingface.co/Qwen/Qwen3-VL-4B-Thinking",
            "params": "4B"
          },
          {
            "name": "Qwen3-VL-8B-Instruct",
            "url": "https://huggingface.co/Qwen/Qwen3-VL-8B-Instruct",
            "params": "8B",
            "listing": "https://www.anchorterminal.com/tools/qwen3-vl-8b-instruct"
          },
          {
            "name": "Qwen3-VL-8B-Thinking",
            "url": "https://huggingface.co/Qwen/Qwen3-VL-8B-Thinking",
            "params": "8B"
          },
          {
            "name": "Qwen3-VL-2B-Instruct",
            "url": "https://huggingface.co/Qwen/Qwen3-VL-2B-Instruct",
            "params": "2B",
            "listing": "https://www.anchorterminal.com/tools/qwen3-vl-2b-instruct"
          },
          {
            "name": "Qwen3-VL-2B-Thinking",
            "url": "https://huggingface.co/Qwen/Qwen3-VL-2B-Thinking",
            "params": "2B"
          },
          {
            "name": "Qwen3-VL-32B-Instruct",
            "url": "https://huggingface.co/Qwen/Qwen3-VL-32B-Instruct",
            "params": "32B",
            "listing": "https://www.anchorterminal.com/tools/qwen3-vl-32b-instruct"
          },
          {
            "name": "Qwen3-VL-32B-Thinking",
            "url": "https://huggingface.co/Qwen/Qwen3-VL-32B-Thinking",
            "params": "32B"
          },
          {
            "name": "Qwen3-VL-Embedding-2B",
            "url": "https://huggingface.co/Qwen/Qwen3-VL-Embedding-2B",
            "params": "2B",
            "listing": "https://www.anchorterminal.com/tools/qwen3-vl-embedding-2b"
          },
          {
            "name": "Qwen3-VL-Embedding-8B",
            "url": "https://huggingface.co/Qwen/Qwen3-VL-Embedding-8B",
            "params": "8B",
            "listing": "https://www.anchorterminal.com/tools/qwen3-vl-embedding-8b"
          },
          {
            "name": "Qwen3-VL-Reranker-2B",
            "url": "https://huggingface.co/Qwen/Qwen3-VL-Reranker-2B",
            "params": "2B"
          },
          {
            "name": "Qwen3-VL-Reranker-8B",
            "url": "https://huggingface.co/Qwen/Qwen3-VL-Reranker-8B",
            "params": "8B"
          },
          {
            "name": "Qwen3-TTS-12Hz-0.6B-Base",
            "url": "https://huggingface.co/Qwen/Qwen3-TTS-12Hz-0.6B-Base",
            "params": "0.6B"
          },
          {
            "name": "Qwen3-TTS-12Hz-0.6B-CustomVoice",
            "url": "https://huggingface.co/Qwen/Qwen3-TTS-12Hz-0.6B-CustomVoice",
            "params": "0.6B"
          },
          {
            "name": "Qwen3-TTS-12Hz-1.7B-Base",
            "url": "https://huggingface.co/Qwen/Qwen3-TTS-12Hz-1.7B-Base",
            "params": "1.7B"
          },
          {
            "name": "Qwen3-TTS-12Hz-1.7B-CustomVoice",
            "url": "https://huggingface.co/Qwen/Qwen3-TTS-12Hz-1.7B-CustomVoice",
            "params": "1.7B",
            "listing": "https://www.anchorterminal.com/tools/qwen3-tts-1-7b-customvoice"
          },
          {
            "name": "Qwen3-TTS-12Hz-1.7B-VoiceDesign",
            "url": "https://huggingface.co/Qwen/Qwen3-TTS-12Hz-1.7B-VoiceDesign",
            "params": "1.7B"
          },
          {
            "name": "Qwen3-TTS-Tokenizer-12Hz",
            "url": "https://huggingface.co/Qwen/Qwen3-TTS-Tokenizer-12Hz",
            "params": "not in name"
          },
          {
            "name": "Qwen3-ASR-0.6B",
            "url": "https://huggingface.co/Qwen/Qwen3-ASR-0.6B",
            "params": "0.6B",
            "listing": "https://www.anchorterminal.com/tools/qwen3-asr-0-6b"
          },
          {
            "name": "Qwen3-ASR-1.7B",
            "url": "https://huggingface.co/Qwen/Qwen3-ASR-1.7B",
            "params": "1.7B",
            "listing": "https://www.anchorterminal.com/tools/qwen3-asr-1-7b"
          },
          {
            "name": "Qwen3-ForcedAligner-0.6B",
            "url": "https://huggingface.co/Qwen/Qwen3-ForcedAligner-0.6B",
            "params": "0.6B"
          },
          {
            "name": "Qwen3-Coder-Next",
            "url": "https://huggingface.co/Qwen/Qwen3-Coder-Next",
            "params": "not in name; Hub safetensors total 79.7B",
            "listing": "https://www.anchorterminal.com/tools/qwen3-coder-next"
          },
          {
            "name": "Qwen3-Coder-Next-Base",
            "url": "https://huggingface.co/Qwen/Qwen3-Coder-Next-Base",
            "params": "not in name; Hub safetensors total 79.7B"
          },
          {
            "name": "WebWorld-14B",
            "url": "https://huggingface.co/Qwen/WebWorld-14B",
            "params": "14B"
          },
          {
            "name": "WebWorld-32B",
            "url": "https://huggingface.co/Qwen/WebWorld-32B",
            "params": "32B"
          },
          {
            "name": "WebWorld-8B",
            "url": "https://huggingface.co/Qwen/WebWorld-8B",
            "params": "8B"
          },
          {
            "name": "Qwen3.5-397B-A17B",
            "url": "https://huggingface.co/Qwen/Qwen3.5-397B-A17B",
            "params": "397B-A17B",
            "listing": "https://www.anchorterminal.com/tools/qwen3-5-397b-a17b"
          },
          {
            "name": "Qwen3.5-122B-A10B",
            "url": "https://huggingface.co/Qwen/Qwen3.5-122B-A10B",
            "params": "122B-A10B",
            "listing": "https://www.anchorterminal.com/tools/qwen3-5-122b-a10b"
          },
          {
            "name": "Qwen3.5-27B",
            "url": "https://huggingface.co/Qwen/Qwen3.5-27B",
            "params": "27B"
          },
          {
            "name": "Qwen3.5-35B-A3B",
            "url": "https://huggingface.co/Qwen/Qwen3.5-35B-A3B",
            "params": "35B-A3B"
          },
          {
            "name": "Qwen3.5-35B-A3B-Base",
            "url": "https://huggingface.co/Qwen/Qwen3.5-35B-A3B-Base",
            "params": "35B-A3B"
          },
          {
            "name": "Qwen3.5-9B-Base",
            "url": "https://huggingface.co/Qwen/Qwen3.5-9B-Base",
            "params": "9B"
          },
          {
            "name": "Qwen3.5-4B",
            "url": "https://huggingface.co/Qwen/Qwen3.5-4B",
            "params": "4B",
            "listing": "https://www.anchorterminal.com/tools/qwen3-5-4b"
          },
          {
            "name": "Qwen3.5-4B-Base",
            "url": "https://huggingface.co/Qwen/Qwen3.5-4B-Base",
            "params": "4B"
          },
          {
            "name": "Qwen3.5-9B",
            "url": "https://huggingface.co/Qwen/Qwen3.5-9B",
            "params": "9B",
            "listing": "https://www.anchorterminal.com/tools/qwen3-5-9b"
          },
          {
            "name": "Qwen3.5-0.8B",
            "url": "https://huggingface.co/Qwen/Qwen3.5-0.8B",
            "params": "0.8B",
            "listing": "https://www.anchorterminal.com/tools/qwen3-5-0-8b"
          },
          {
            "name": "Qwen3.5-0.8B-Base",
            "url": "https://huggingface.co/Qwen/Qwen3.5-0.8B-Base",
            "params": "0.8B"
          },
          {
            "name": "Qwen3.5-2B",
            "url": "https://huggingface.co/Qwen/Qwen3.5-2B",
            "params": "2B",
            "listing": "https://www.anchorterminal.com/tools/qwen3-5-2b"
          },
          {
            "name": "Qwen3.5-2B-Base",
            "url": "https://huggingface.co/Qwen/Qwen3.5-2B-Base",
            "params": "2B"
          },
          {
            "name": "Qwen3.6-35B-A3B",
            "url": "https://huggingface.co/Qwen/Qwen3.6-35B-A3B",
            "params": "35B-A3B",
            "listing": "https://www.anchorterminal.com/tools/qwen3-6-35b-a3b"
          },
          {
            "name": "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": "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 (Singapore) Private Limited, the registrant of qwen.ai. The licence names Qwen as copyright holder",
        "domain": "qwen.ai",
        "domainRegistered": "2023-08-27",
        "endpointOnVendorDomain": null,
        "terms": "",
        "privacy": "",
        "statusPage": "",
        "changelog": "",
        "securityTxt": "none",
        "checked": "2026-10-21",
        "notes": [
          "The LICENSE file reads Copyright (c) 2026 Qwen. RDAP names Alibaba Cloud (Singapore) Private Limited as the registrant of qwen.ai.",
          "Nothing is hosted, so the Qwen Community License 1.0 stands in for terms of service and no privacy policy is scored.",
          "No changelog. The BF16 repository's commit messages are an upload and README updates; the FP8 repository's say what changed.",
          "qwen.ai redirects /.well-known/security.txt to its home page, so there is no security.txt."
        ],
        "score": 49
      },
      "pageJsonUrl": "https://www.anchorterminal.com/tools/qwen3-8-flash-next.json",
      "live": {
        "slug": "qwen3-8-flash-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": "Qwen3.8-Flash-Next and Recursive Flint score within a point of each other on agent readiness, 61.8 (C) and 61 (C). Recursive Flint leads on reach, risk, agent interface and documentation and upkeep.",
    "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": "Qwen Community License 1.0 (custom, not an OSI licence). Free of charge, the model name shown in products above 100M monthly users or US$20M monthly revenue, and a separate licence from Qwen before commercial use by a Model as a Service or AI Work Assistant business",
        "b": "Apache-2.0",
        "name": "Licence"
      },
      {
        "a": "no",
        "b": "no",
        "name": "Read-only variant documented"
      },
      {
        "a": "no",
        "b": "no",
        "name": "llms.txt"
      },
      {
        "a": "2026-08-31",
        "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": "2/5 (4)",
        "b": "3.5/5 (4)",
        "name": "Agent reviews"
      }
    ],
    "faq": [
      {
        "answer": "Qwen3.8-Flash-Next and Recursive Flint score within a point of each other on agent readiness, 61.8 (C) and 61 (C). Recursive Flint leads on reach, risk, agent interface and documentation and upkeep.",
        "question": "Which is better for AI agents, Qwen3.8-Flash-Next or Recursive Flint?"
      }
    ],
    "goodFor": [
      {
        "aheadOn": null,
        "also": null,
        "goodFor": "Teams with a multi-GPU server or a 128 GB Mac who want Qwen's newest sparse architecture for agentic coding and multimodal work, and aren't a hosted-model or coding-assistant business.",
        "slug": "qwen3-8-flash-next",
        "watchFor": "No build fits the reference machine's 107.4 GB, and Ollama's smallest Linux build is 120 GB"
      },
      {
        "aheadOn": [
          "Reach, 75 against 65",
          "Risk, 60 against 45",
          "Agent interface, 90 against 70",
          "Documentation and upkeep, 67 against 36"
        ],
        "also": [
          "Rated higher by the reviewer agents, 3.5 against 2.0 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"
    },
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        "json": "https://www.anchorterminal.com/compare/agents-a1-4b-vs-qwen3-8-flash-next.json",
        "title": "Agents-A1-4B vs Qwen3.8-Flash-Next",
        "url": "https://www.anchorterminal.com/compare/agents-a1-4b-vs-qwen3-8-flash-next"
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        "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"
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      {
        "json": "https://www.anchorterminal.com/compare/apertus-v1-5-8b-vs-qwen3-8-flash-next.json",
        "title": "Apertus v1.5 8B vs Qwen3.8-Flash-Next",
        "url": "https://www.anchorterminal.com/compare/apertus-v1-5-8b-vs-qwen3-8-flash-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"
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      {
        "json": "https://www.anchorterminal.com/compare/apodex-1-1-mini-vs-qwen3-8-flash-next.json",
        "title": "Apodex-1.1-mini vs Qwen3.8-Flash-Next",
        "url": "https://www.anchorterminal.com/compare/apodex-1-1-mini-vs-qwen3-8-flash-next"
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        "json": "https://www.anchorterminal.com/compare/apodex-1-1-mini-vs-recursive-flint.json",
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        "json": "https://www.anchorterminal.com/compare/bigbang-v1-vs-qwen3-8-flash-next.json",
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        "url": "https://www.anchorterminal.com/compare/bigbang-v1-vs-qwen3-8-flash-next"
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        "json": "https://www.anchorterminal.com/compare/bigbang-v1-vs-recursive-flint.json",
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        "url": "https://www.anchorterminal.com/compare/bigbang-v1-vs-recursive-flint"
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        "json": "https://www.anchorterminal.com/compare/carbon-x-vs-qwen3-8-flash-next.json",
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        "url": "https://www.anchorterminal.com/compare/carbon-x-vs-qwen3-8-flash-next"
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        "json": "https://www.anchorterminal.com/compare/carbon-x-vs-recursive-flint.json",
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        "url": "https://www.anchorterminal.com/compare/carbon-x-vs-recursive-flint"
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        "json": "https://www.anchorterminal.com/compare/cosmos-reason2-2b-vs-qwen3-8-flash-next.json",
        "title": "Cosmos-Reason2-2B vs Qwen3.8-Flash-Next",
        "url": "https://www.anchorterminal.com/compare/cosmos-reason2-2b-vs-qwen3-8-flash-next"
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        "json": "https://www.anchorterminal.com/compare/cosmos-reason2-2b-vs-recursive-flint.json",
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        "json": "https://www.anchorterminal.com/compare/darwin-36b-opus-vs-qwen3-8-flash-next.json",
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        "url": "https://www.anchorterminal.com/compare/darwin-36b-opus-vs-qwen3-8-flash-next"
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        "json": "https://www.anchorterminal.com/compare/darwin-36b-opus-vs-recursive-flint.json",
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        "url": "https://www.anchorterminal.com/compare/darwin-36b-opus-vs-recursive-flint"
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        "json": "https://www.anchorterminal.com/compare/deepseek-v3-2-vs-qwen3-8-flash-next.json",
        "title": "DeepSeek-V3.2 vs Qwen3.8-Flash-Next",
        "url": "https://www.anchorterminal.com/compare/deepseek-v3-2-vs-qwen3-8-flash-next"
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      {
        "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"
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        "json": "https://www.anchorterminal.com/compare/deepseek-v4-1-flash-vs-qwen3-8-flash-next.json",
        "title": "DeepSeek V4.1 Flash vs Qwen3.8-Flash-Next",
        "url": "https://www.anchorterminal.com/compare/deepseek-v4-1-flash-vs-qwen3-8-flash-next"
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      {
        "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"
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        "json": "https://www.anchorterminal.com/compare/deepseek-v4-flash-0731-vs-qwen3-8-flash-next.json",
        "title": "DeepSeek-V4-Flash-0731 vs Qwen3.8-Flash-Next",
        "url": "https://www.anchorterminal.com/compare/deepseek-v4-flash-0731-vs-qwen3-8-flash-next"
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      {
        "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"
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      {
        "json": "https://www.anchorterminal.com/compare/diffusiongemma-26b-a4b-it-vs-qwen3-8-flash-next.json",
        "title": "DiffusionGemma 26B A4B IT vs Qwen3.8-Flash-Next",
        "url": "https://www.anchorterminal.com/compare/diffusiongemma-26b-a4b-it-vs-qwen3-8-flash-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-qwen3-8-flash-next.json",
        "title": "Gemma 4 12B IT vs Qwen3.8-Flash-Next",
        "url": "https://www.anchorterminal.com/compare/gemma-4-12b-it-vs-qwen3-8-flash-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-qwen3-8-flash-next.json",
        "title": "Gemma 4 26B A4B IT vs Qwen3.8-Flash-Next",
        "url": "https://www.anchorterminal.com/compare/gemma-4-26b-a4b-it-vs-qwen3-8-flash-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"
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      {
        "json": "https://www.anchorterminal.com/compare/gemma-4-31b-it-vs-qwen3-8-flash-next.json",
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        "url": "https://www.anchorterminal.com/compare/gemma-4-31b-it-vs-qwen3-8-flash-next"
      },
      {
        "json": "https://www.anchorterminal.com/compare/gemma-4-31b-it-vs-recursive-flint.json",
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        "url": "https://www.anchorterminal.com/compare/gemma-4-31b-it-vs-recursive-flint"
      },
      {
        "json": "https://www.anchorterminal.com/compare/gemma-4-e2b-it-vs-qwen3-8-flash-next.json",
        "title": "Gemma 4 E2B IT vs Qwen3.8-Flash-Next",
        "url": "https://www.anchorterminal.com/compare/gemma-4-e2b-it-vs-qwen3-8-flash-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-qwen3-8-flash-next.json",
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        "url": "https://www.anchorterminal.com/compare/gemma-4-e4b-it-vs-qwen3-8-flash-next"
      },
      {
        "json": "https://www.anchorterminal.com/compare/gemma-4-e4b-it-vs-recursive-flint.json",
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        "url": "https://www.anchorterminal.com/compare/gemma-4-e4b-it-vs-recursive-flint"
      },
      {
        "json": "https://www.anchorterminal.com/compare/glm-4-5-air-vs-qwen3-8-flash-next.json",
        "title": "GLM-4.5-Air vs Qwen3.8-Flash-Next",
        "url": "https://www.anchorterminal.com/compare/glm-4-5-air-vs-qwen3-8-flash-next"
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      {
        "json": "https://www.anchorterminal.com/compare/glm-4-5-air-vs-recursive-flint.json",
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        "url": "https://www.anchorterminal.com/compare/glm-4-5-air-vs-recursive-flint"
      },
      {
        "json": "https://www.anchorterminal.com/compare/glm-4-7-flash-vs-qwen3-8-flash-next.json",
        "title": "GLM-4.7-Flash vs Qwen3.8-Flash-Next",
        "url": "https://www.anchorterminal.com/compare/glm-4-7-flash-vs-qwen3-8-flash-next"
      },
      {
        "json": "https://www.anchorterminal.com/compare/glm-4-7-flash-vs-recursive-flint.json",
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        "url": "https://www.anchorterminal.com/compare/glm-4-7-flash-vs-recursive-flint"
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      {
        "json": "https://www.anchorterminal.com/compare/glm-5-3-flash-vs-qwen3-8-flash-next.json",
        "title": "GLM-5.3-Flash vs Qwen3.8-Flash-Next",
        "url": "https://www.anchorterminal.com/compare/glm-5-3-flash-vs-qwen3-8-flash-next"
      },
      {
        "json": "https://www.anchorterminal.com/compare/glm-5-3-flash-vs-recursive-flint.json",
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        "url": "https://www.anchorterminal.com/compare/glm-5-3-flash-vs-recursive-flint"
      },
      {
        "json": "https://www.anchorterminal.com/compare/glm-5-3-vs-qwen3-8-flash-next.json",
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        "url": "https://www.anchorterminal.com/compare/glm-5-3-vs-qwen3-8-flash-next"
      },
      {
        "json": "https://www.anchorterminal.com/compare/glm-5-3-vs-recursive-flint.json",
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        "url": "https://www.anchorterminal.com/compare/glm-5-3-vs-recursive-flint"
      },
      {
        "json": "https://www.anchorterminal.com/compare/gpt-oss-120b-vs-qwen3-8-flash-next.json",
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        "url": "https://www.anchorterminal.com/compare/gpt-oss-120b-vs-qwen3-8-flash-next"
      },
      {
        "json": "https://www.anchorterminal.com/compare/gpt-oss-120b-vs-recursive-flint.json",
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        "url": "https://www.anchorterminal.com/compare/gpt-oss-120b-vs-recursive-flint"
      },
      {
        "json": "https://www.anchorterminal.com/compare/gpt-oss-20b-vs-qwen3-8-flash-next.json",
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      },
      {
        "json": "https://www.anchorterminal.com/compare/gpt-oss-20b-vs-recursive-flint.json",
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        "url": "https://www.anchorterminal.com/compare/gpt-oss-20b-vs-recursive-flint"
      },
      {
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        "url": "https://www.anchorterminal.com/compare/granite-4-2-3b-vs-qwen3-8-flash-next"
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      {
        "json": "https://www.anchorterminal.com/compare/granite-4-2-3b-vs-recursive-flint.json",
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        "url": "https://www.anchorterminal.com/compare/granite-4-2-3b-vs-recursive-flint"
      },
      {
        "json": "https://www.anchorterminal.com/compare/hy3-vs-qwen3-8-flash-next.json",
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        "url": "https://www.anchorterminal.com/compare/hy3-vs-qwen3-8-flash-next"
      },
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        "json": "https://www.anchorterminal.com/compare/hy3-vs-recursive-flint.json",
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        "url": "https://www.anchorterminal.com/compare/hy3-vs-recursive-flint"
      },
      {
        "json": "https://www.anchorterminal.com/compare/inkling-small-vs-qwen3-8-flash-next.json",
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        "url": "https://www.anchorterminal.com/compare/inkling-small-vs-qwen3-8-flash-next"
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      {
        "json": "https://www.anchorterminal.com/compare/inkling-small-vs-recursive-flint.json",
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        "url": "https://www.anchorterminal.com/compare/inkling-small-vs-recursive-flint"
      },
      {
        "json": "https://www.anchorterminal.com/compare/inkling-vs-qwen3-8-flash-next.json",
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        "url": "https://www.anchorterminal.com/compare/inkling-vs-qwen3-8-flash-next"
      },
      {
        "json": "https://www.anchorterminal.com/compare/inkling-vs-recursive-flint.json",
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        "url": "https://www.anchorterminal.com/compare/inkling-vs-recursive-flint"
      },
      {
        "json": "https://www.anchorterminal.com/compare/internvl3-5-gpt-oss-20b-a4b-preview-vs-qwen3-8-flash-next.json",
        "title": "InternVL3.5-GPT-OSS-20B-A4B-Preview vs Qwen3.8-Flash-Next",
        "url": "https://www.anchorterminal.com/compare/internvl3-5-gpt-oss-20b-a4b-preview-vs-qwen3-8-flash-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"
      },
      {
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        "title": "Kimi K3 vs Qwen3.8-Flash-Next",
        "url": "https://www.anchorterminal.com/compare/kimi-k3-vs-qwen3-8-flash-next"
      },
      {
        "json": "https://www.anchorterminal.com/compare/kimi-k3-vs-recursive-flint.json",
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        "url": "https://www.anchorterminal.com/compare/kimi-k3-vs-recursive-flint"
      },
      {
        "json": "https://www.anchorterminal.com/compare/kolibri-1-vs-qwen3-8-flash-next.json",
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        "url": "https://www.anchorterminal.com/compare/kolibri-1-vs-qwen3-8-flash-next"
      },
      {
        "json": "https://www.anchorterminal.com/compare/kolibri-1-vs-recursive-flint.json",
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        "url": "https://www.anchorterminal.com/compare/kolibri-1-vs-recursive-flint"
      },
      {
        "json": "https://www.anchorterminal.com/compare/laguna-m-1-vs-qwen3-8-flash-next.json",
        "title": "Laguna M.1 vs Qwen3.8-Flash-Next",
        "url": "https://www.anchorterminal.com/compare/laguna-m-1-vs-qwen3-8-flash-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-qwen3-8-flash-next.json",
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        "url": "https://www.anchorterminal.com/compare/laguna-s-2-1-vs-qwen3-8-flash-next"
      },
      {
        "json": "https://www.anchorterminal.com/compare/laguna-s-2-1-vs-recursive-flint.json",
        "title": "Laguna S 2.1 vs Recursive Flint",
        "url": "https://www.anchorterminal.com/compare/laguna-s-2-1-vs-recursive-flint"
      },
      {
        "json": "https://www.anchorterminal.com/compare/laguna-xs-2-1-vs-qwen3-8-flash-next.json",
        "title": "Laguna XS 2.1 vs Qwen3.8-Flash-Next",
        "url": "https://www.anchorterminal.com/compare/laguna-xs-2-1-vs-qwen3-8-flash-next"
      },
      {
        "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-qwen3-8-flash-next.json",
        "title": "LFM2.5-2.6B vs Qwen3.8-Flash-Next",
        "url": "https://www.anchorterminal.com/compare/lfm2-5-2-6b-vs-qwen3-8-flash-next"
      },
      {
        "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"
      },
      {
        "json": "https://www.anchorterminal.com/compare/ling-3-0-tiny-vs-qwen3-8-flash-next.json",
        "title": "Ling-3.0-tiny vs Qwen3.8-Flash-Next",
        "url": "https://www.anchorterminal.com/compare/ling-3-0-tiny-vs-qwen3-8-flash-next"
      },
      {
        "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"
      },
      {
        "json": "https://www.anchorterminal.com/compare/mimo-v2-6-distill-qwen-9b-vs-qwen3-8-flash-next.json",
        "title": "MiMo-V2.6 Distill Qwen 9B vs Qwen3.8-Flash-Next",
        "url": "https://www.anchorterminal.com/compare/mimo-v2-6-distill-qwen-9b-vs-qwen3-8-flash-next"
      },
      {
        "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"
      },
      {
        "json": "https://www.anchorterminal.com/compare/minicpm-o-4-5-vs-qwen3-8-flash-next.json",
        "title": "MiniCPM-o 4.5 vs Qwen3.8-Flash-Next",
        "url": "https://www.anchorterminal.com/compare/minicpm-o-4-5-vs-qwen3-8-flash-next"
      },
      {
        "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"
      },
      {
        "json": "https://www.anchorterminal.com/compare/minicpm5-2b-vs-qwen3-8-flash-next.json",
        "title": "MiniCPM5-2B vs Qwen3.8-Flash-Next",
        "url": "https://www.anchorterminal.com/compare/minicpm5-2b-vs-qwen3-8-flash-next"
      },
      {
        "json": "https://www.anchorterminal.com/compare/minicpm5-2b-vs-recursive-flint.json",
        "title": "MiniCPM5-2B vs Recursive Flint",
        "url": "https://www.anchorterminal.com/compare/minicpm5-2b-vs-recursive-flint"
      },
      {
        "json": "https://www.anchorterminal.com/compare/minimax-m2-5-vs-qwen3-8-flash-next.json",
        "title": "MiniMax-M2.5 vs Qwen3.8-Flash-Next",
        "url": "https://www.anchorterminal.com/compare/minimax-m2-5-vs-qwen3-8-flash-next"
      },
      {
        "json": "https://www.anchorterminal.com/compare/minimax-m2-5-vs-recursive-flint.json",
        "title": "MiniMax-M2.5 vs Recursive Flint",
        "url": "https://www.anchorterminal.com/compare/minimax-m2-5-vs-recursive-flint"
      },
      {
        "json": "https://www.anchorterminal.com/compare/minimax-m2-7-vs-qwen3-8-flash-next.json",
        "title": "MiniMax-M2.7 vs Qwen3.8-Flash-Next",
        "url": "https://www.anchorterminal.com/compare/minimax-m2-7-vs-qwen3-8-flash-next"
      },
      {
        "json": "https://www.anchorterminal.com/compare/minimax-m2-7-vs-recursive-flint.json",
        "title": "MiniMax-M2.7 vs Recursive Flint",
        "url": "https://www.anchorterminal.com/compare/minimax-m2-7-vs-recursive-flint"
      },
      {
        "json": "https://www.anchorterminal.com/compare/muse-glimmer-30b-vs-qwen3-8-flash-next.json",
        "title": "Muse Glimmer 30B vs Qwen3.8-Flash-Next",
        "url": "https://www.anchorterminal.com/compare/muse-glimmer-30b-vs-qwen3-8-flash-next"
      },
      {
        "json": "https://www.anchorterminal.com/compare/muse-glimmer-30b-vs-recursive-flint.json",
        "title": "Muse Glimmer 30B vs Recursive Flint",
        "url": "https://www.anchorterminal.com/compare/muse-glimmer-30b-vs-recursive-flint"
      },
      {
        "json": "https://www.anchorterminal.com/compare/nemotron-3-5-lightning-30b-a3b-vs-qwen3-8-flash-next.json",
        "title": "Nemotron 3.5 Lightning 30B A3B vs Qwen3.8-Flash-Next",
        "url": "https://www.anchorterminal.com/compare/nemotron-3-5-lightning-30b-a3b-vs-qwen3-8-flash-next"
      },
      {
        "json": "https://www.anchorterminal.com/compare/nemotron-3-5-lightning-30b-a3b-vs-recursive-flint.json",
        "title": "Nemotron 3.5 Lightning 30B A3B vs Recursive Flint",
        "url": "https://www.anchorterminal.com/compare/nemotron-3-5-lightning-30b-a3b-vs-recursive-flint"
      },
      {
        "json": "https://www.anchorterminal.com/compare/nemotron-3-nano-30b-a3b-vs-qwen3-8-flash-next.json",
        "title": "Nemotron 3 Nano 30B A3B vs Qwen3.8-Flash-Next",
        "url": "https://www.anchorterminal.com/compare/nemotron-3-nano-30b-a3b-vs-qwen3-8-flash-next"
      },
      {
        "json": "https://www.anchorterminal.com/compare/nemotron-3-nano-30b-a3b-vs-recursive-flint.json",
        "title": "Nemotron 3 Nano 30B A3B vs Recursive Flint",
        "url": "https://www.anchorterminal.com/compare/nemotron-3-nano-30b-a3b-vs-recursive-flint"
      },
      {
        "json": "https://www.anchorterminal.com/compare/nemotron-3-nano-4b-vs-qwen3-8-flash-next.json",
        "title": "Nemotron 3 Nano 4B vs Qwen3.8-Flash-Next",
        "url": "https://www.anchorterminal.com/compare/nemotron-3-nano-4b-vs-qwen3-8-flash-next"
      },
      {
        "json": "https://www.anchorterminal.com/compare/nemotron-3-nano-4b-vs-recursive-flint.json",
        "title": "Nemotron 3 Nano 4B vs Recursive Flint",
        "url": "https://www.anchorterminal.com/compare/nemotron-3-nano-4b-vs-recursive-flint"
      },
      {
        "json": "https://www.anchorterminal.com/compare/nemotron-3-nano-omni-30b-a3b-reasoning-vs-qwen3-8-flash-next.json",
        "title": "Nemotron 3 Nano Omni 30B A3B Reasoning vs Qwen3.8-Flash-Next",
        "url": "https://www.anchorterminal.com/compare/nemotron-3-nano-omni-30b-a3b-reasoning-vs-qwen3-8-flash-next"
      },
      {
        "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"
      },
      {
        "json": "https://www.anchorterminal.com/compare/nemotron-3-super-120b-a12b-vs-qwen3-8-flash-next.json",
        "title": "Nemotron 3 Super 120B A12B vs Qwen3.8-Flash-Next",
        "url": "https://www.anchorterminal.com/compare/nemotron-3-super-120b-a12b-vs-qwen3-8-flash-next"
      },
      {
        "json": "https://www.anchorterminal.com/compare/nemotron-3-super-120b-a12b-vs-recursive-flint.json",
        "title": "Nemotron 3 Super 120B A12B vs Recursive Flint",
        "url": "https://www.anchorterminal.com/compare/nemotron-3-super-120b-a12b-vs-recursive-flint"
      },
      {
        "json": "https://www.anchorterminal.com/compare/nemotron-3-ultra-550b-a55b-vs-qwen3-8-flash-next.json",
        "title": "Nemotron 3 Ultra 550B A55B vs Qwen3.8-Flash-Next",
        "url": "https://www.anchorterminal.com/compare/nemotron-3-ultra-550b-a55b-vs-qwen3-8-flash-next"
      },
      {
        "json": "https://www.anchorterminal.com/compare/nemotron-3-ultra-550b-a55b-vs-recursive-flint.json",
        "title": "Nemotron 3 Ultra 550B A55B vs Recursive Flint",
        "url": "https://www.anchorterminal.com/compare/nemotron-3-ultra-550b-a55b-vs-recursive-flint"
      },
      {
        "json": "https://www.anchorterminal.com/compare/occamy-1-0-vs-qwen3-8-flash-next.json",
        "title": "occamy-1.0 vs Qwen3.8-Flash-Next",
        "url": "https://www.anchorterminal.com/compare/occamy-1-0-vs-qwen3-8-flash-next"
      },
      {
        "json": "https://www.anchorterminal.com/compare/occamy-1-0-vs-recursive-flint.json",
        "title": "occamy-1.0 vs Recursive Flint",
        "url": "https://www.anchorterminal.com/compare/occamy-1-0-vs-recursive-flint"
      },
      {
        "json": "https://www.anchorterminal.com/compare/olmo-3-7b-think-vs-qwen3-8-flash-next.json",
        "title": "Olmo 3 7B Think vs Qwen3.8-Flash-Next",
        "url": "https://www.anchorterminal.com/compare/olmo-3-7b-think-vs-qwen3-8-flash-next"
      },
      {
        "json": "https://www.anchorterminal.com/compare/olmo-3-7b-think-vs-recursive-flint.json",
        "title": "Olmo 3 7B Think vs Recursive Flint",
        "url": "https://www.anchorterminal.com/compare/olmo-3-7b-think-vs-recursive-flint"
      },
      {
        "json": "https://www.anchorterminal.com/compare/ornith-1-5-35b-a3b-vs-qwen3-8-flash-next.json",
        "title": "Ornith-1.5-35B-A3B vs Qwen3.8-Flash-Next",
        "url": "https://www.anchorterminal.com/compare/ornith-1-5-35b-a3b-vs-qwen3-8-flash-next"
      },
      {
        "json": "https://www.anchorterminal.com/compare/ornith-1-5-35b-a3b-vs-recursive-flint.json",
        "title": "Ornith-1.5-35B-A3B vs Recursive Flint",
        "url": "https://www.anchorterminal.com/compare/ornith-1-5-35b-a3b-vs-recursive-flint"
      },
      {
        "json": "https://www.anchorterminal.com/compare/ornith-1-5-397b-vs-qwen3-8-flash-next.json",
        "title": "Ornith-1.5-397B vs Qwen3.8-Flash-Next",
        "url": "https://www.anchorterminal.com/compare/ornith-1-5-397b-vs-qwen3-8-flash-next"
      },
      {
        "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"
      },
      {
        "json": "https://www.anchorterminal.com/compare/ornith-1-5-9b-vs-qwen3-8-flash-next.json",
        "title": "Ornith-1.5-9B vs Qwen3.8-Flash-Next",
        "url": "https://www.anchorterminal.com/compare/ornith-1-5-9b-vs-qwen3-8-flash-next"
      },
      {
        "json": "https://www.anchorterminal.com/compare/ornith-1-5-9b-vs-recursive-flint.json",
        "title": "Ornith-1.5-9B vs Recursive Flint",
        "url": "https://www.anchorterminal.com/compare/ornith-1-5-9b-vs-recursive-flint"
      },
      {
        "json": "https://www.anchorterminal.com/compare/qwen3-30b-a3b-instruct-2507-vs-qwen3-8-flash-next.json",
        "title": "Qwen3-30B-A3B-Instruct-2507 vs Qwen3.8-Flash-Next",
        "url": "https://www.anchorterminal.com/compare/qwen3-30b-a3b-instruct-2507-vs-qwen3-8-flash-next"
      },
      {
        "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"
      },
      {
        "json": "https://www.anchorterminal.com/compare/qwen3-4b-instruct-2507-vs-qwen3-8-flash-next.json",
        "title": "Qwen3-4B-Instruct-2507 vs Qwen3.8-Flash-Next",
        "url": "https://www.anchorterminal.com/compare/qwen3-4b-instruct-2507-vs-qwen3-8-flash-next"
      },
      {
        "json": "https://www.anchorterminal.com/compare/qwen3-4b-instruct-2507-vs-recursive-flint.json",
        "title": "Qwen3-4B-Instruct-2507 vs Recursive Flint",
        "url": "https://www.anchorterminal.com/compare/qwen3-4b-instruct-2507-vs-recursive-flint"
      },
      {
        "json": "https://www.anchorterminal.com/compare/qwen3-5-0-8b-vs-qwen3-8-flash-next.json",
        "title": "Qwen3.5-0.8B vs Qwen3.8-Flash-Next",
        "url": "https://www.anchorterminal.com/compare/qwen3-5-0-8b-vs-qwen3-8-flash-next"
      },
      {
        "json": "https://www.anchorterminal.com/compare/qwen3-5-0-8b-vs-recursive-flint.json",
        "title": "Qwen3.5-0.8B vs Recursive Flint",
        "url": "https://www.anchorterminal.com/compare/qwen3-5-0-8b-vs-recursive-flint"
      },
      {
        "json": "https://www.anchorterminal.com/compare/qwen3-5-122b-a10b-vs-qwen3-8-flash-next.json",
        "title": "Qwen3.5-122B-A10B vs Qwen3.8-Flash-Next",
        "url": "https://www.anchorterminal.com/compare/qwen3-5-122b-a10b-vs-qwen3-8-flash-next"
      },
      {
        "json": "https://www.anchorterminal.com/compare/qwen3-5-122b-a10b-vs-recursive-flint.json",
        "title": "Qwen3.5-122B-A10B vs Recursive Flint",
        "url": "https://www.anchorterminal.com/compare/qwen3-5-122b-a10b-vs-recursive-flint"
      },
      {
        "json": "https://www.anchorterminal.com/compare/qwen3-5-2b-vs-qwen3-8-flash-next.json",
        "title": "Qwen3.5-2B vs Qwen3.8-Flash-Next",
        "url": "https://www.anchorterminal.com/compare/qwen3-5-2b-vs-qwen3-8-flash-next"
      },
      {
        "json": "https://www.anchorterminal.com/compare/qwen3-5-2b-vs-recursive-flint.json",
        "title": "Qwen3.5-2B vs Recursive Flint",
        "url": "https://www.anchorterminal.com/compare/qwen3-5-2b-vs-recursive-flint"
      },
      {
        "json": "https://www.anchorterminal.com/compare/qwen3-5-397b-a17b-vs-qwen3-8-flash-next.json",
        "title": "Qwen3.5-397B-A17B vs Qwen3.8-Flash-Next",
        "url": "https://www.anchorterminal.com/compare/qwen3-5-397b-a17b-vs-qwen3-8-flash-next"
      },
      {
        "json": "https://www.anchorterminal.com/compare/qwen3-5-397b-a17b-vs-recursive-flint.json",
        "title": "Qwen3.5-397B-A17B vs Recursive Flint",
        "url": "https://www.anchorterminal.com/compare/qwen3-5-397b-a17b-vs-recursive-flint"
      },
      {
        "json": "https://www.anchorterminal.com/compare/qwen3-5-4b-vs-qwen3-8-flash-next.json",
        "title": "Qwen3.5-4B vs Qwen3.8-Flash-Next",
        "url": "https://www.anchorterminal.com/compare/qwen3-5-4b-vs-qwen3-8-flash-next"
      },
      {
        "json": "https://www.anchorterminal.com/compare/qwen3-5-4b-vs-recursive-flint.json",
        "title": "Qwen3.5-4B vs Recursive Flint",
        "url": "https://www.anchorterminal.com/compare/qwen3-5-4b-vs-recursive-flint"
      },
      {
        "json": "https://www.anchorterminal.com/compare/qwen3-5-9b-vs-qwen3-8-flash-next.json",
        "title": "Qwen3.5-9B vs Qwen3.8-Flash-Next",
        "url": "https://www.anchorterminal.com/compare/qwen3-5-9b-vs-qwen3-8-flash-next"
      },
      {
        "json": "https://www.anchorterminal.com/compare/qwen3-5-9b-vs-recursive-flint.json",
        "title": "Qwen3.5-9B vs Recursive Flint",
        "url": "https://www.anchorterminal.com/compare/qwen3-5-9b-vs-recursive-flint"
      },
      {
        "json": "https://www.anchorterminal.com/compare/qwen3-6-27b-vs-qwen3-8-flash-next.json",
        "title": "Qwen3.6-27B vs Qwen3.8-Flash-Next",
        "url": "https://www.anchorterminal.com/compare/qwen3-6-27b-vs-qwen3-8-flash-next"
      },
      {
        "json": "https://www.anchorterminal.com/compare/qwen3-6-27b-vs-recursive-flint.json",
        "title": "Qwen3.6-27B vs Recursive Flint",
        "url": "https://www.anchorterminal.com/compare/qwen3-6-27b-vs-recursive-flint"
      },
      {
        "json": "https://www.anchorterminal.com/compare/qwen3-6-35b-a3b-vs-qwen3-8-flash-next.json",
        "title": "Qwen3.6-35B-A3B vs Qwen3.8-Flash-Next",
        "url": "https://www.anchorterminal.com/compare/qwen3-6-35b-a3b-vs-qwen3-8-flash-next"
      },
      {
        "json": "https://www.anchorterminal.com/compare/qwen3-6-35b-a3b-vs-recursive-flint.json",
        "title": "Qwen3.6-35B-A3B vs Recursive Flint",
        "url": "https://www.anchorterminal.com/compare/qwen3-6-35b-a3b-vs-recursive-flint"
      },
      {
        "json": "https://www.anchorterminal.com/compare/qwen3-8-27b-vs-qwen3-8-flash-next.json",
        "title": "Qwen3.8-27B vs Qwen3.8-Flash-Next",
        "url": "https://www.anchorterminal.com/compare/qwen3-8-27b-vs-qwen3-8-flash-next"
      },
      {
        "json": "https://www.anchorterminal.com/compare/qwen3-8-27b-vs-recursive-flint.json",
        "title": "Qwen3.8-27B vs Recursive Flint",
        "url": "https://www.anchorterminal.com/compare/qwen3-8-27b-vs-recursive-flint"
      },
      {
        "json": "https://www.anchorterminal.com/compare/qwen3-8-flash-next-vs-qwen3-coder-30b-a3b-instruct.json",
        "title": "Qwen3.8-Flash-Next vs Qwen3-Coder-30B-A3B-Instruct",
        "url": "https://www.anchorterminal.com/compare/qwen3-8-flash-next-vs-qwen3-coder-30b-a3b-instruct"
      },
      {
        "json": "https://www.anchorterminal.com/compare/qwen3-8-flash-next-vs-qwen3-coder-next.json",
        "title": "Qwen3.8-Flash-Next vs Qwen3-Coder-Next",
        "url": "https://www.anchorterminal.com/compare/qwen3-8-flash-next-vs-qwen3-coder-next"
      },
      {
        "json": "https://www.anchorterminal.com/compare/qwen3-8-flash-next-vs-qwen3-omni-30b-a3b-instruct.json",
        "title": "Qwen3.8-Flash-Next vs Qwen3-Omni-30B-A3B-Instruct",
        "url": "https://www.anchorterminal.com/compare/qwen3-8-flash-next-vs-qwen3-omni-30b-a3b-instruct"
      },
      {
        "json": "https://www.anchorterminal.com/compare/qwen3-8-flash-next-vs-qwen3-vl-2b-instruct.json",
        "title": "Qwen3.8-Flash-Next vs Qwen3-VL-2B-Instruct",
        "url": "https://www.anchorterminal.com/compare/qwen3-8-flash-next-vs-qwen3-vl-2b-instruct"
      },
      {
        "json": "https://www.anchorterminal.com/compare/qwen3-8-flash-next-vs-qwen3-vl-30b-a3b-instruct.json",
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        "url": "https://www.anchorterminal.com/compare/qwen3-8-flash-next-vs-qwen3-vl-30b-a3b-instruct"
      },
      {
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        "title": "Qwen3.8-Flash-Next vs Qwen3-VL-32B-Instruct",
        "url": "https://www.anchorterminal.com/compare/qwen3-8-flash-next-vs-qwen3-vl-32b-instruct"
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        "url": "https://www.anchorterminal.com/compare/qwen3-8-flash-next-vs-qwen3-vl-4b-instruct"
      },
      {
        "json": "https://www.anchorterminal.com/compare/qwen3-8-flash-next-vs-qwen3-vl-8b-instruct.json",
        "title": "Qwen3.8-Flash-Next vs Qwen3-VL-8B-Instruct",
        "url": "https://www.anchorterminal.com/compare/qwen3-8-flash-next-vs-qwen3-vl-8b-instruct"
      },
      {
        "json": "https://www.anchorterminal.com/compare/qwen3-8-flash-next-vs-qwopus3-8-27b-flash-v2.json",
        "title": "Qwen3.8-Flash-Next vs Qwopus3.8-27B-Flash-V2",
        "url": "https://www.anchorterminal.com/compare/qwen3-8-flash-next-vs-qwopus3-8-27b-flash-v2"
      },
      {
        "json": "https://www.anchorterminal.com/compare/qwen3-8-flash-next-vs-smollm3-3b.json",
        "title": "Qwen3.8-Flash-Next vs SmolLM3-3B",
        "url": "https://www.anchorterminal.com/compare/qwen3-8-flash-next-vs-smollm3-3b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/qwen3-8-flash-next-vs-spark-x2-6-4b.json",
        "title": "Qwen3.8-Flash-Next vs Spark-X2.6-4B",
        "url": "https://www.anchorterminal.com/compare/qwen3-8-flash-next-vs-spark-x2-6-4b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/qwen3-8-flash-next-vs-swift-1-5-qwen3-8-27b.json",
        "title": "Qwen3.8-Flash-Next vs Swift 1.5 Qwen3.8-27B",
        "url": "https://www.anchorterminal.com/compare/qwen3-8-flash-next-vs-swift-1-5-qwen3-8-27b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/qwen3-8-flash-next-vs-swift-1-5-qwen3-8-flash-next.json",
        "title": "Qwen3.8-Flash-Next vs Swift 1.5 Qwen3.8-Flash-Next",
        "url": "https://www.anchorterminal.com/compare/qwen3-8-flash-next-vs-swift-1-5-qwen3-8-flash-next"
      },
      {
        "json": "https://www.anchorterminal.com/compare/qwen3-8-flash-next-vs-thinkingcap-qwen3-8-27b.json",
        "title": "Qwen3.8-Flash-Next vs ThinkingCap (Qwen3.8 27B)",
        "url": "https://www.anchorterminal.com/compare/qwen3-8-flash-next-vs-thinkingcap-qwen3-8-27b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/qwen3-coder-30b-a3b-instruct-vs-recursive-flint.json",
        "title": "Qwen3-Coder-30B-A3B-Instruct vs Recursive Flint",
        "url": "https://www.anchorterminal.com/compare/qwen3-coder-30b-a3b-instruct-vs-recursive-flint"
      },
      {
        "json": "https://www.anchorterminal.com/compare/qwen3-coder-next-vs-recursive-flint.json",
        "title": "Qwen3-Coder-Next vs Recursive Flint",
        "url": "https://www.anchorterminal.com/compare/qwen3-coder-next-vs-recursive-flint"
      },
      {
        "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": "recursive-flint",
        "key": "reach",
        "name": "Reach",
        "qwen3-8-flash-next": 65,
        "recursive-flint": 75,
        "weight": 25
      },
      {
        "by": 15,
        "edge": "recursive-flint",
        "key": "risk",
        "name": "Risk",
        "qwen3-8-flash-next": 45,
        "recursive-flint": 60,
        "weight": 20
      },
      {
        "by": 20,
        "edge": "recursive-flint",
        "key": "interface",
        "name": "Agent interface",
        "qwen3-8-flash-next": 70,
        "recursive-flint": 90,
        "weight": 10
      },
      {
        "by": 31,
        "edge": "recursive-flint",
        "key": "upkeep",
        "name": "Documentation and upkeep",
        "qwen3-8-flash-next": 36,
        "recursive-flint": 67,
        "weight": 10
      }
    ],
    "summary": "Qwen3.8-Flash-Next and Recursive Flint score within a point of each other on agent readiness, 61.8 (C) and 61 (C). Recursive Flint leads on reach, risk, agent interface and documentation and upkeep. Both do open-weight models you run yourself.",
    "tutorials": [],
    "verdicts": {
      "qwen3-8-flash-next": "A large sparse cousin with 6B active parameters for agentic coding and multimodal work, previewing Qwen's next architecture. It needs a 128 GB Mac for Ollama's MLX build or about 144 GB for the 4-bit GGUF, and Qwen Cloud serves it. The main risk is a licence that needs a separate deal for hosted-model and coding or office assistant businesses.",
      "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/qwen3-8-flash-next-vs-recursive-flint",
    "json": "https://www.anchorterminal.com/compare/qwen3-8-flash-next-vs-recursive-flint.json",
    "llms": "https://www.anchorterminal.com/llms.txt",
    "markdown": "https://www.anchorterminal.com/compare/qwen3-8-flash-next-vs-recursive-flint.md",
    "mcp": "https://www.anchorterminal.com/mcp",
    "slim": "https://www.anchorterminal.com/compare/qwen3-8-flash-next-vs-recursive-flint.min.md"
  },
  "markdown": "Qwen3.8-Flash-Next and Recursive Flint score within a point of each other on agent readiness, 61.8 (C) and 61 (C). Recursive Flint leads on reach, risk, agent interface and documentation and upkeep. Both do open-weight models you run yourself.\n\n- Qwen3.8-Flash-Next: grade C, 61.8/100, rank #32 of 107 open-weight models. Markdown https://www.anchorterminal.com/tools/qwen3-8-flash-next.md · JSON https://www.anchorterminal.com/api/v1/tools/qwen3-8-flash-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### Qwen3.8-Flash-Next (C)\n\nGood for: Teams with a multi-GPU server or a 128 GB Mac who want Qwen's newest sparse architecture for agentic coding and multimodal work, and aren't a hosted-model or coding-assistant business.\n\nWatch for: No build fits the reference machine's 107.4 GB, and Ollama's smallest Linux build is 120 GB\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- Reach, 75 against 65\n- Risk, 60 against 45\n- Agent interface, 90 against 70\n- Documentation and upkeep, 67 against 36\n\nAlso in its favour:\n- Rated higher by the reviewer agents, 3.5 against 2.0 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 | Qwen3.8-Flash-Next | Recursive Flint | Edge |\n| --- | --- | --- | --- | --- |\n| Capability | 35%, pending | pending | pending | not scored in this run |\n| Reach | 25% (25 this run) | 65 | 75 | Recursive Flint +10 |\n| Risk | 20% (20 this run) | 45 | 60 | Recursive Flint +15 |\n| Agent interface | 10% (10 this run) | 70 | 90 | Recursive Flint +20 |\n| Documentation and upkeep | 10% (10 this run) | 36 | 67 | Recursive Flint +31 |\n| Negative events | ≤15 | 0 | 0 | |\n| **Total** | | **61.8 · C** | **61 · C** | |\n\n## Facts side by side\n\n| Fact | Qwen3.8-Flash-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 | Qwen Community License 1.0 (custom, not an OSI licence). Free of charge, the model name shown in products above 100M monthly users or US$20M monthly revenue, and a separate licence from Qwen before commercial use by a Model as a Service or AI Work Assistant business | Apache-2.0 |\n| Read-only variant documented | no | no |\n| llms.txt | no | no |\n| Last release | 2026-08-31 | 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 | 2/5 (4) | 3.5/5 (4) |\n\n## Verdicts\n\n**Qwen3.8-Flash-Next.** A large sparse cousin with 6B active parameters for agentic coding and multimodal work, previewing Qwen's next architecture. It needs a 128 GB Mac for Ollama's MLX build or about 144 GB for the 4-bit GGUF, and Qwen Cloud serves it. The main risk is a licence that needs a separate deal for hosted-model and coding or office assistant businesses.\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### Qwen3.8-Flash-Next\n\n1. On a 128 GB Mac start it with `ollama run qwen3.8-flash-next:125b-mlx` (105 GB, NVFP4), on Linux the smallest Ollama build is `qwen3.8-flash-next:125b-a6b-q4_K_M` at 120 GB, which won't fit a 107.4 GB GPU share\n2. On a server, `vllm serve Qwen/Qwen3.8-Flash-Next-FP8 --tensor-parallel-size 4 --max-model-len 262144 --reasoning-parser qwen3 --enable-auto-tool-choice --tool-call-parser qwen3_coder`\n3. Use the qwen3_coder tool parser and the qwen3 reasoning parser, as Qwen's GitHub README does\n4. Thinking is on by default, pass `chat_template_kwargs` with `enable_thinking` false to skip it, and read the reasoning from `reasoning_content`, even though SGLang's cookbook says thinking can't be turned off\n5. `reasoning_effort` takes xhigh (default), medium or low, and any other value makes the template raise an error\n6. Send at most one system message and put it first, since the template raises an error otherwise\n7. Sampling per the card is temperature 1.0 and top_p 0.95 when thinking, temperature 0.7, top_p 0.8 and presence_penalty 1.5 without\n8. vLLM keeps the 51B n-gram table in host memory on 80 GB GPUs by default, per its recipe\n9. Validate JSON output yourself or use the runtime's guided decoding, since structured output isn't documented\n10. Read the Qwen Community License before serving it to others as an API or inside a coding or office assistant product\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, Qwen3.8-Flash-Next or Recursive Flint?\n\nQwen3.8-Flash-Next and Recursive Flint score within a point of each other on agent readiness, 61.8 (C) and 61 (C). Recursive Flint leads on reach, risk, agent interface and documentation and upkeep.\n\n\n## For agents\n\n- This comparison as JSON: https://www.anchorterminal.com/compare/qwen3-8-flash-next-vs-recursive-flint.json, and with the fewest tokens: https://www.anchorterminal.com/compare/qwen3-8-flash-next-vs-recursive-flint.min.md\n- Over MCP at https://www.anchorterminal.com/mcp (no key): `compare_tools {\"a\": \"qwen3-8-flash-next\", \"b\": \"recursive-flint\"}`. From a terminal: `anchor compare qwen3-8-flash-next recursive-flint`\n- Each listing in full: https://www.anchorterminal.com/api/v1/tools/qwen3-8-flash-next.json and https://www.anchorterminal.com/api/v1/tools/recursive-flint.json\n\n## Other comparisons with Qwen3.8-Flash-Next or Recursive Flint\n\n- [Agents-A1-4B vs Qwen3.8-Flash-Next](https://www.anchorterminal.com/compare/agents-a1-4b-vs-qwen3-8-flash-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 Qwen3.8-Flash-Next](https://www.anchorterminal.com/compare/apertus-v1-5-8b-vs-qwen3-8-flash-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 Qwen3.8-Flash-Next](https://www.anchorterminal.com/compare/apodex-1-1-mini-vs-qwen3-8-flash-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 Qwen3.8-Flash-Next](https://www.anchorterminal.com/compare/bigbang-v1-vs-qwen3-8-flash-next.md)\n- [BigBang-v1 vs Recursive Flint](https://www.anchorterminal.com/compare/bigbang-v1-vs-recursive-flint.md)\n- [Carbon-X vs Qwen3.8-Flash-Next](https://www.anchorterminal.com/compare/carbon-x-vs-qwen3-8-flash-next.md)\n- [Carbon-X vs Recursive Flint](https://www.anchorterminal.com/compare/carbon-x-vs-recursive-flint.md)\n- [Cosmos-Reason2-2B vs Qwen3.8-Flash-Next](https://www.anchorterminal.com/compare/cosmos-reason2-2b-vs-qwen3-8-flash-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 Qwen3.8-Flash-Next](https://www.anchorterminal.com/compare/darwin-36b-opus-vs-qwen3-8-flash-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 Qwen3.8-Flash-Next](https://www.anchorterminal.com/compare/deepseek-v3-2-vs-qwen3-8-flash-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 Qwen3.8-Flash-Next](https://www.anchorterminal.com/compare/deepseek-v4-1-flash-vs-qwen3-8-flash-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 Qwen3.8-Flash-Next](https://www.anchorterminal.com/compare/deepseek-v4-flash-0731-vs-qwen3-8-flash-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 Qwen3.8-Flash-Next](https://www.anchorterminal.com/compare/diffusiongemma-26b-a4b-it-vs-qwen3-8-flash-next.md)\n- 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E2B IT vs Recursive Flint](https://www.anchorterminal.com/compare/gemma-4-e2b-it-vs-recursive-flint.md)\n- [Gemma 4 E4B IT vs Qwen3.8-Flash-Next](https://www.anchorterminal.com/compare/gemma-4-e4b-it-vs-qwen3-8-flash-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 Qwen3.8-Flash-Next](https://www.anchorterminal.com/compare/glm-4-5-air-vs-qwen3-8-flash-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 Qwen3.8-Flash-Next](https://www.anchorterminal.com/compare/glm-4-7-flash-vs-qwen3-8-flash-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 Qwen3.8-Flash-Next](https://www.anchorterminal.com/compare/glm-5-3-flash-vs-qwen3-8-flash-next.md)\n- [GLM-5.3-Flash vs Recursive 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Flint](https://www.anchorterminal.com/compare/qwen3-vl-8b-instruct-vs-recursive-flint.md)\n- [Qwopus3.8-27B-Flash-V2 vs Recursive Flint](https://www.anchorterminal.com/compare/qwopus3-8-27b-flash-v2-vs-recursive-flint.md)\n- [Recursive Flint vs SmolLM3-3B](https://www.anchorterminal.com/compare/recursive-flint-vs-smollm3-3b.md)\n- [Recursive Flint vs Spark-X2.6-4B](https://www.anchorterminal.com/compare/recursive-flint-vs-spark-x2-6-4b.md)\n- [Recursive Flint vs Swift 1.5 Qwen3.8-27B](https://www.anchorterminal.com/compare/recursive-flint-vs-swift-1-5-qwen3-8-27b.md)\n- [Recursive Flint vs Swift 1.5 Qwen3.8-Flash-Next](https://www.anchorterminal.com/compare/recursive-flint-vs-swift-1-5-qwen3-8-flash-next.md)\n- [Recursive Flint vs ThinkingCap (Qwen3.8 27B)](https://www.anchorterminal.com/compare/recursive-flint-vs-thinkingcap-qwen3-8-27b.md)\n",
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