{
  "data": {
    "a": {
      "slug": "minicpm-o-4-5",
      "name": "MiniCPM-o 4.5",
      "vendor": "OpenBMB",
      "vendorUrl": "https://openbmb.cn",
      "kind": "weights",
      "category": "open-weights",
      "summary": "MiniCPM-o 4.5 is OpenBMB's open-weight omni-modal model of 9.4B parameters that takes images, video, audio and text and answers in text and speech, including full-duplex live conversation and voice cloning from a reference clip, under Apache 2.0.",
      "url": "https://www.anchorterminal.com/tools/minicpm-o-4-5",
      "markdownUrl": "https://www.anchorterminal.com/tools/minicpm-o-4-5.md",
      "slimMarkdownUrl": "https://www.anchorterminal.com/tools/minicpm-o-4-5.min.md",
      "jsonUrl": "https://www.anchorterminal.com/api/v1/tools/minicpm-o-4-5.json",
      "repo": "https://huggingface.co/openbmb/MiniCPM-o-4_5",
      "license": "Apache-2.0; built from Qwen3-8B, SigLIP2, Whisper-medium and CosyVoice2, all Apache 2.0 on their Hub cards",
      "transports": [],
      "packages": [
        {
          "registry": "huggingface",
          "name": "openbmb/MiniCPM-o-4_5"
        },
        {
          "registry": "huggingface",
          "name": "openbmb/MiniCPM-o-4_5-gguf"
        },
        {
          "registry": "huggingface",
          "name": "openbmb/MiniCPM-o-4_5-awq"
        },
        {
          "registry": "huggingface",
          "name": "openbmb/MiniCPM-o-4_5-GPTQ"
        },
        {
          "registry": "ollama",
          "name": "openbmb/minicpm-o4.5"
        }
      ],
      "auth": "none",
      "authNotes": "The weights download from Hugging Face with no account, token or terms to accept. None of OpenBMB's four repositories for the model is gated (checked 2026-10-21).",
      "pricing": "free",
      "pricingNotes": "Free to download and use, commercial use included, under Apache 2.0. OpenBMB also serves it as MiniCPM-O-4.5-9B on its own OpenAI-compatible API at api.modelbest.cn, with a key from platform.modelbest.cn, which isn't graded here. Running it yourself costs the hardware, 20.0 GB for the BF16 repository and 5.9 GB for the Q4_0 GGUF with its vision file (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://github.com/OpenSQZ/MiniCPM-V-CookBook",
      "capabilities": [
        "model.open-weights"
      ],
      "tags": [
        "open-weights",
        "model",
        "dense",
        "multimodal",
        "omni",
        "vision",
        "speech",
        "voice-cloning",
        "full-duplex",
        "reasoning",
        "apache-2.0",
        "safetensors",
        "gguf",
        "awq",
        "gptq",
        "self-hosted"
      ],
      "lastRelease": "2026-10-16",
      "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": 36,
        "methodology": "0.6",
        "run": "2026-10-01",
        "scores": {
          "interface": 35,
          "reach": 90,
          "risk": 40,
          "upkeep": 66
        },
        "pending": [
          "performance",
          "tasks"
        ],
        "assessment": {
          "confidence": "low",
          "date": "2026-10-21"
        },
        "negative": 0,
        "verdict": "A small omni cousin that sees, listens and talks back, with full-duplex speech and voice cloning, in about 7 GB at 4-bit through llama.cpp or Ollama for text and images. Speech output needs OpenBMB's remote code or llama.cpp-omni, and 28 GB of GPU for the full demo. The main risks are repository code and pickle files and no safety results.",
        "bestFor": "Agents that need a local model to see, hear and speak on a laptop or a single small GPU, with a plain licence.",
        "strengths": [
          "OpenBMB's 4-bit GGUF and Ollama builds fit in about 7 GB",
          "Images, video, audio and text in, text and streaming speech out, with full-duplex live conversation",
          "Plain Apache 2.0, no gate, and OpenBMB's own API serves it too",
          "Released vLLM, llama.cpp and Ollama run it, and OpenBMB publishes GGUF, AWQ and GPTQ builds",
          "Repository changed 5 days ago and earlier versions stay in their own repositories"
        ],
        "weaknesses": [
          "Speech output and full duplex need trust_remote_code with Transformers 4.51.0 or OpenBMB's llama.cpp-omni",
          "Two pickle files (flow.pt and hift.pt) in the speech stage",
          "No safety results or guidance, though it clones voices from a short clip",
          "Tool calling, structured output and where the reasoning comes back aren't documented",
          "40,960 tokens of context, and OpenBMB answered only half the questions in the discussions"
        ],
        "agentNotes": [
          "Quickest start for text and images is `ollama run openbmb/minicpm-o4.5`, about 6 GB",
          "With vLLM 0.16.0 or later pass `--trust-remote-code`, and send `stop_token_ids` [151643, 151645] as OpenBMB's guide does",
          "vLLM, llama.cpp and Ollama return text only; for speech out use the card's Transformers 4.51.0 code or OpenBMB's llama.cpp-omni",
          "In llama.cpp pass both the language GGUF and MiniCPM-o-4_5-vision-F16.gguf with `--mmproj`, and use `--jinja --reasoning-budget 0` to turn thinking off",
          "Keep prompts within 40,960 tokens",
          "Don't rely on tool calls or JSON output, neither is documented; validate any you get"
        ],
        "metrics": {
          "kind": "local",
          "measured": false
        },
        "reviewCount": 4,
        "avgRating": 2.8,
        "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": 35,
          "reach": 90,
          "risk": 40,
          "upkeep": 66
        },
        "provenanceScore": 53,
        "checked": {
          "categories": {
            "interface": "2026-10-21",
            "reach": "2026-10-21",
            "risk": "2026-10-21",
            "upkeep": "2026-10-21"
          },
          "last": "2026-10-21",
          "oldest": "2026-10-21",
          "stale": false,
          "staleAfterDays": 90
        }
      },
      "connect": {
        "install": "ollama run openbmb/minicpm-o4.5\n# or, with vLLM 0.16.0 or later (text out):\nvllm serve openbmb/MiniCPM-o-4_5 --trust-remote-code --dtype auto \\\n  --max-model-len 4096 --max-num-batched-tokens 2048",
        "http": "curl http://localhost:8000/v1/chat/completions \\\n  -H 'Content-Type: application/json' \\\n  -d '{\"model\": \"openbmb/MiniCPM-o-4_5\", \"messages\": [{\"role\": \"user\", \"content\": [{\"type\": \"image_url\", \"image_url\": {\"url\": \"https://example.com/photo.jpg\"}}, {\"type\": \"text\", \"text\": \"What is in this picture?\"}]}], \"stop_token_ids\": [151643, 151645]}'"
      },
      "letme": {
        "capability": "https://letme.dev/model.open-weights",
        "tool": "https://letme.dev/minicpm-o-4-5"
      },
      "sameCompany": [
        "minicpm5-2b"
      ],
      "weights": {
        "trainedBy": "OpenBMB",
        "builtOn": "Qwen3-8B with SigLIP2, Whisper-medium and CosyVoice2 (named on the card)",
        "params": "9.4B",
        "context": 40960,
        "goodFor": "Omni-modal assistant for images, video, speech and text in, text and speech out, with live full-duplex conversation and voice cloning, small enough for a laptop at 4-bit.",
        "runtimes": [
          "vLLM",
          "llama.cpp",
          "Ollama"
        ],
        "builds": [
          {
            "name": "MiniCPM-o-4_5-gguf Q4_K_M",
            "url": "https://huggingface.co/openbmb/MiniCPM-o-4_5-gguf",
            "who": "publisher",
            "precision": "q4_k_m",
            "sizeGB": 6.12,
            "memoryGB": 8,
            "format": "gguf",
            "runsOn": [
              "llama.cpp"
            ],
            "note": "5.03 GB language file plus the 1.10 GB vision file, the pair OpenBMB's llama.cpp guide uses. The audio, TTS and token2wav GGUF files (2.75 GB more) are for OpenBMB's llama.cpp-omni"
          },
          {
            "name": "MiniCPM-o-4_5-gguf Q4_0",
            "url": "https://huggingface.co/openbmb/MiniCPM-o-4_5-gguf",
            "who": "publisher",
            "precision": "q4_0",
            "sizeGB": 5.87,
            "memoryGB": 8,
            "format": "gguf",
            "note": "4.77 GB language file plus the 1.10 GB vision file, the smallest 4-bit pair"
          },
          {
            "name": "ollama openbmb/minicpm-o4.5:latest",
            "url": "https://ollama.com/openbmb/minicpm-o4.5/tags",
            "who": "publisher",
            "precision": "q4_k_m",
            "sizeGB": 6.1,
            "memoryGB": 8,
            "format": "ollama",
            "runsOn": [
              "Ollama"
            ],
            "note": "In the openbmb namespace on ollama.com, taken as OpenBMB's, text and image input only, 40K context. q4_0 is 5.9 GB. Size as Ollama's tags page shows it"
          },
          {
            "name": "MiniCPM-o-4_5-gguf Q8_0",
            "url": "https://huggingface.co/openbmb/MiniCPM-o-4_5-gguf",
            "who": "publisher",
            "precision": "q8_0",
            "sizeGB": 9.8,
            "memoryGB": 12,
            "format": "gguf",
            "note": "8.71 GB language file plus the 1.10 GB vision file"
          },
          {
            "name": "MiniCPM-o-4_5-GPTQ",
            "url": "https://huggingface.co/openbmb/MiniCPM-o-4_5-GPTQ",
            "who": "publisher",
            "precision": "gptq-int4",
            "sizeGB": 9.77,
            "memoryGB": 12,
            "format": "safetensors",
            "note": "4-bit GPTQ, group size 128. Remote code. vLLM's quantisation table marks GPTQ unsupported on AMD GPUs"
          },
          {
            "name": "MiniCPM-o-4_5-awq",
            "url": "https://huggingface.co/openbmb/MiniCPM-o-4_5-awq",
            "who": "publisher",
            "precision": "awq-int4",
            "sizeGB": 13.07,
            "memoryGB": 16,
            "format": "safetensors",
            "note": "4-bit AWQ language model with the vision, audio and TTS modules left unquantised, plus a bundled CosyVoice2-0.5B folder. Remote code"
          },
          {
            "name": "MiniCPM-o-4_5-gguf F16",
            "url": "https://huggingface.co/openbmb/MiniCPM-o-4_5-gguf",
            "who": "publisher",
            "precision": "f16",
            "sizeGB": 17.48,
            "memoryGB": 24,
            "format": "gguf",
            "note": "16.38 GB language file plus MiniCPM-o-4_5-vision-F16.gguf (1.10 GB) for image input"
          },
          {
            "name": "MiniCPM-o-4_5",
            "url": "https://huggingface.co/openbmb/MiniCPM-o-4_5",
            "who": "publisher",
            "precision": "bf16",
            "sizeGB": 20.05,
            "memoryGB": 32,
            "format": "safetensors",
            "runsOn": [
              "vLLM",
              "Transformers (remote code)"
            ],
            "note": "Size is the Hub's file list summed, 18.7 GB of safetensors plus the token2wav stage, example media and code. Speech output needs the remote code with Transformers 4.51.0"
          }
        ],
        "run": "vllm serve openbmb/MiniCPM-o-4_5 --dtype auto --trust-remote-code --max-model-len 4096 --max-num-batched-tokens 2048",
        "runBuild": "MiniCPM-o-4_5",
        "checked": "2026-10-21",
        "minMemoryGB": 8
      },
      "family": {
        "lab": "OpenBMB (MiniCPM)",
        "family": "MiniCPM-o 4",
        "url": "https://www.anchorterminal.com/open-weights/#openbmb",
        "olderCount": 22
      },
      "alsoIn": [
        "voice-agents"
      ],
      "area": "models",
      "provenance": {
        "legalEntity": "OpenBMB (named as the MiniCPM-o team on the technical report; the GitHub LICENSE is the unfilled Apache template)",
        "domain": "openbmb.cn",
        "domainRegistered": "",
        "endpointOnVendorDomain": null,
        "terms": "",
        "privacy": "",
        "statusPage": "",
        "changelog": "https://huggingface.co/openbmb/MiniCPM-o-4_5/commits/main",
        "securityTxt": "none",
        "checked": "2026-10-21",
        "notes": [
          "The card links OpenBMB's GitHub repository, whose README links back to this Hugging Face repository. rdap.org has no RDAP service for .cn, so the domain's registration date wasn't checked.",
          "The listing is the weights, so the Apache 2.0 licence stands in for terms of service and no privacy policy is scored. OpenBMB's API at api.modelbest.cn has its own terms, not read.",
          "The changelog is the repository's commit history, whose messages are mostly README updates, with code fixes on 4 March and 6 July 2026. OpenBMB's GitHub README carries dated news entries (release on 3 February 2026, technical report on 7 May, API on 17 May).",
          "openbmb.cn/.well-known/security.txt and modelbest.cn/.well-known/security.txt answered 404 on 21 October 2026, and OpenBMB/MiniCPM-o has no security policy."
        ],
        "score": 53
      },
      "pageJsonUrl": "https://www.anchorterminal.com/tools/minicpm-o-4-5.json",
      "live": {
        "slug": "minicpm-o-4-5",
        "securityTxt": {
          "url": "https://openbmb.cn/.well-known/security.txt",
          "state": "none",
          "checkedAt": "2026-10-23T15:23:44.122816648Z"
        },
        "pages": [
          {
            "url": "https://huggingface.co/openbmb/MiniCPM-o-4_5/commits/main",
            "kind": "changelog",
            "status": 200,
            "checkedAt": "2026-10-23T01:50:03.703259221Z",
            "changedAt": "2026-10-23T01:50:03.703259221Z",
            "fingerprint": "4303549a9dcb"
          }
        ],
        "updatedAt": "2026-10-23T15:23:44.122816648Z"
      }
    },
    "answer": "MiniCPM-o 4.5 and Recursive Flint score within a point of each other on agent readiness, 61 (C) and 61 (C). Recursive Flint leads on risk and agent interface.",
    "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": "OpenBMB",
        "b": "Recursive",
        "name": "Vendor"
      },
      {
        "a": "no (local only)",
        "b": "no (local only)",
        "name": "Hosted endpoint"
      },
      {
        "a": "",
        "b": "",
        "name": "Transports"
      },
      {
        "a": "None",
        "b": "None",
        "name": "Auth"
      },
      {
        "a": "Free",
        "b": "Free",
        "name": "Pricing"
      },
      {
        "a": "no",
        "b": "no",
        "name": "x402"
      },
      {
        "a": "Apache-2.0; built from Qwen3-8B, SigLIP2, Whisper-medium and CosyVoice2, all Apache 2.0 on their Hub cards",
        "b": "Apache-2.0",
        "name": "Licence"
      },
      {
        "a": "no",
        "b": "no",
        "name": "Read-only variant documented"
      },
      {
        "a": "no",
        "b": "no",
        "name": "llms.txt"
      },
      {
        "a": "2026-10-16",
        "b": "2026-10-21",
        "name": "Last release"
      },
      {
        "a": "no document linked",
        "b": "no document linked",
        "name": "Terms last updated"
      },
      {
        "a": "no document linked",
        "b": "no document linked",
        "name": "Privacy policy last updated"
      },
      {
        "a": "",
        "b": "",
        "name": "Customer content may train models"
      },
      {
        "a": "",
        "b": "",
        "name": "Terms restrict automated access"
      },
      {
        "a": "",
        "b": "",
        "name": "Terms restrict benchmarking"
      },
      {
        "a": "",
        "b": "",
        "name": "Terms or service can change without notice"
      },
      {
        "a": "",
        "b": "",
        "name": "Arbitration or class-action waiver"
      },
      {
        "a": "2.8/5 (4)",
        "b": "3.5/5 (4)",
        "name": "Agent reviews"
      }
    ],
    "faq": [
      {
        "answer": "MiniCPM-o 4.5 and Recursive Flint score within a point of each other on agent readiness, 61 (C) and 61 (C). Recursive Flint leads on risk and agent interface.",
        "question": "Which is better for AI agents, MiniCPM-o 4.5 or Recursive Flint?"
      }
    ],
    "goodFor": [
      {
        "aheadOn": [
          "Reach, 90 against 75"
        ],
        "also": null,
        "goodFor": "Agents that need a local model to see, hear and speak on a laptop or a single small GPU, with a plain licence.",
        "slug": "minicpm-o-4-5",
        "watchFor": "Speech output and full duplex need trust_remote_code with Transformers 4.51.0 or OpenBMB's llama.cpp-omni"
      },
      {
        "aheadOn": [
          "Risk, 60 against 40",
          "Agent interface, 90 against 35"
        ],
        "also": [
          "Rated higher by the reviewer agents, 3.5 against 2.8 out of 5"
        ],
        "goodFor": "Agents doing repository work on a 32 to 48 GB Mac or NVIDIA box that want a fast sparse coder with documented tool calls and a plain licence.",
        "slug": "recursive-flint",
        "watchFor": "No independent benchmark results yet, every published score is Recursive's"
      }
    ],
    "job": {
      "capability": "model.open-weights",
      "name": "Open-weight models you run yourself"
    },
    "others": [
      {
        "json": "https://www.anchorterminal.com/compare/agents-a1-4b-vs-minicpm-o-4-5.json",
        "title": "Agents-A1-4B vs MiniCPM-o 4.5",
        "url": "https://www.anchorterminal.com/compare/agents-a1-4b-vs-minicpm-o-4-5"
      },
      {
        "json": "https://www.anchorterminal.com/compare/agents-a1-4b-vs-recursive-flint.json",
        "title": "Agents-A1-4B vs Recursive Flint",
        "url": "https://www.anchorterminal.com/compare/agents-a1-4b-vs-recursive-flint"
      },
      {
        "json": "https://www.anchorterminal.com/compare/apertus-v1-5-8b-vs-minicpm-o-4-5.json",
        "title": "Apertus v1.5 8B vs MiniCPM-o 4.5",
        "url": "https://www.anchorterminal.com/compare/apertus-v1-5-8b-vs-minicpm-o-4-5"
      },
      {
        "json": "https://www.anchorterminal.com/compare/apertus-v1-5-8b-vs-recursive-flint.json",
        "title": "Apertus v1.5 8B vs Recursive Flint",
        "url": "https://www.anchorterminal.com/compare/apertus-v1-5-8b-vs-recursive-flint"
      },
      {
        "json": "https://www.anchorterminal.com/compare/apodex-1-1-mini-vs-minicpm-o-4-5.json",
        "title": "Apodex-1.1-mini vs MiniCPM-o 4.5",
        "url": "https://www.anchorterminal.com/compare/apodex-1-1-mini-vs-minicpm-o-4-5"
      },
      {
        "json": "https://www.anchorterminal.com/compare/apodex-1-1-mini-vs-recursive-flint.json",
        "title": "Apodex-1.1-mini vs Recursive Flint",
        "url": "https://www.anchorterminal.com/compare/apodex-1-1-mini-vs-recursive-flint"
      },
      {
        "json": "https://www.anchorterminal.com/compare/bigbang-v1-vs-minicpm-o-4-5.json",
        "title": "BigBang-v1 vs MiniCPM-o 4.5",
        "url": "https://www.anchorterminal.com/compare/bigbang-v1-vs-minicpm-o-4-5"
      },
      {
        "json": "https://www.anchorterminal.com/compare/bigbang-v1-vs-recursive-flint.json",
        "title": "BigBang-v1 vs Recursive Flint",
        "url": "https://www.anchorterminal.com/compare/bigbang-v1-vs-recursive-flint"
      },
      {
        "json": "https://www.anchorterminal.com/compare/carbon-x-vs-minicpm-o-4-5.json",
        "title": "Carbon-X vs MiniCPM-o 4.5",
        "url": "https://www.anchorterminal.com/compare/carbon-x-vs-minicpm-o-4-5"
      },
      {
        "json": "https://www.anchorterminal.com/compare/carbon-x-vs-recursive-flint.json",
        "title": "Carbon-X vs Recursive Flint",
        "url": "https://www.anchorterminal.com/compare/carbon-x-vs-recursive-flint"
      },
      {
        "json": "https://www.anchorterminal.com/compare/cosmos-reason2-2b-vs-minicpm-o-4-5.json",
        "title": "Cosmos-Reason2-2B vs MiniCPM-o 4.5",
        "url": "https://www.anchorterminal.com/compare/cosmos-reason2-2b-vs-minicpm-o-4-5"
      },
      {
        "json": "https://www.anchorterminal.com/compare/cosmos-reason2-2b-vs-recursive-flint.json",
        "title": "Cosmos-Reason2-2B vs Recursive Flint",
        "url": "https://www.anchorterminal.com/compare/cosmos-reason2-2b-vs-recursive-flint"
      },
      {
        "json": "https://www.anchorterminal.com/compare/darwin-36b-opus-vs-minicpm-o-4-5.json",
        "title": "Darwin-36B-Opus vs MiniCPM-o 4.5",
        "url": "https://www.anchorterminal.com/compare/darwin-36b-opus-vs-minicpm-o-4-5"
      },
      {
        "json": "https://www.anchorterminal.com/compare/darwin-36b-opus-vs-recursive-flint.json",
        "title": "Darwin-36B-Opus vs Recursive Flint",
        "url": "https://www.anchorterminal.com/compare/darwin-36b-opus-vs-recursive-flint"
      },
      {
        "json": "https://www.anchorterminal.com/compare/deepseek-v3-2-vs-minicpm-o-4-5.json",
        "title": "DeepSeek-V3.2 vs MiniCPM-o 4.5",
        "url": "https://www.anchorterminal.com/compare/deepseek-v3-2-vs-minicpm-o-4-5"
      },
      {
        "json": "https://www.anchorterminal.com/compare/deepseek-v3-2-vs-recursive-flint.json",
        "title": "DeepSeek-V3.2 vs Recursive Flint",
        "url": "https://www.anchorterminal.com/compare/deepseek-v3-2-vs-recursive-flint"
      },
      {
        "json": "https://www.anchorterminal.com/compare/deepseek-v4-1-flash-vs-minicpm-o-4-5.json",
        "title": "DeepSeek V4.1 Flash vs MiniCPM-o 4.5",
        "url": "https://www.anchorterminal.com/compare/deepseek-v4-1-flash-vs-minicpm-o-4-5"
      },
      {
        "json": "https://www.anchorterminal.com/compare/deepseek-v4-1-flash-vs-recursive-flint.json",
        "title": "DeepSeek V4.1 Flash vs Recursive Flint",
        "url": "https://www.anchorterminal.com/compare/deepseek-v4-1-flash-vs-recursive-flint"
      },
      {
        "json": "https://www.anchorterminal.com/compare/deepseek-v4-flash-0731-vs-minicpm-o-4-5.json",
        "title": "DeepSeek-V4-Flash-0731 vs MiniCPM-o 4.5",
        "url": "https://www.anchorterminal.com/compare/deepseek-v4-flash-0731-vs-minicpm-o-4-5"
      },
      {
        "json": "https://www.anchorterminal.com/compare/deepseek-v4-flash-0731-vs-recursive-flint.json",
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        "url": "https://www.anchorterminal.com/compare/deepseek-v4-flash-0731-vs-recursive-flint"
      },
      {
        "json": "https://www.anchorterminal.com/compare/diffusiongemma-26b-a4b-it-vs-minicpm-o-4-5.json",
        "title": "DiffusionGemma 26B A4B IT vs MiniCPM-o 4.5",
        "url": "https://www.anchorterminal.com/compare/diffusiongemma-26b-a4b-it-vs-minicpm-o-4-5"
      },
      {
        "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-minicpm-o-4-5.json",
        "title": "Gemma 4 12B IT vs MiniCPM-o 4.5",
        "url": "https://www.anchorterminal.com/compare/gemma-4-12b-it-vs-minicpm-o-4-5"
      },
      {
        "json": "https://www.anchorterminal.com/compare/gemma-4-12b-it-vs-recursive-flint.json",
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        "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-minicpm-o-4-5.json",
        "title": "Gemma 4 26B A4B IT vs MiniCPM-o 4.5",
        "url": "https://www.anchorterminal.com/compare/gemma-4-26b-a4b-it-vs-minicpm-o-4-5"
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      {
        "json": "https://www.anchorterminal.com/compare/gemma-4-26b-a4b-it-vs-recursive-flint.json",
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        "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-minicpm-o-4-5.json",
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        "url": "https://www.anchorterminal.com/compare/gemma-4-31b-it-vs-minicpm-o-4-5"
      },
      {
        "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-minicpm-o-4-5.json",
        "title": "Gemma 4 E2B IT vs MiniCPM-o 4.5",
        "url": "https://www.anchorterminal.com/compare/gemma-4-e2b-it-vs-minicpm-o-4-5"
      },
      {
        "json": "https://www.anchorterminal.com/compare/gemma-4-e2b-it-vs-recursive-flint.json",
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        "url": "https://www.anchorterminal.com/compare/gemma-4-e2b-it-vs-recursive-flint"
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      {
        "json": "https://www.anchorterminal.com/compare/gemma-4-e4b-it-vs-minicpm-o-4-5.json",
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        "url": "https://www.anchorterminal.com/compare/gemma-4-e4b-it-vs-minicpm-o-4-5"
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      {
        "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"
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      {
        "json": "https://www.anchorterminal.com/compare/glm-4-5-air-vs-minicpm-o-4-5.json",
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        "url": "https://www.anchorterminal.com/compare/glm-4-5-air-vs-minicpm-o-4-5"
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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-minicpm-o-4-5.json",
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        "url": "https://www.anchorterminal.com/compare/glm-4-7-flash-vs-minicpm-o-4-5"
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      {
        "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"
      },
      {
        "json": "https://www.anchorterminal.com/compare/glm-5-3-flash-vs-minicpm-o-4-5.json",
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        "url": "https://www.anchorterminal.com/compare/glm-5-3-flash-vs-minicpm-o-4-5"
      },
      {
        "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-minicpm-o-4-5.json",
        "title": "GLM-5.3 vs MiniCPM-o 4.5",
        "url": "https://www.anchorterminal.com/compare/glm-5-3-vs-minicpm-o-4-5"
      },
      {
        "json": "https://www.anchorterminal.com/compare/glm-5-3-vs-recursive-flint.json",
        "title": "GLM-5.3 vs Recursive Flint",
        "url": "https://www.anchorterminal.com/compare/glm-5-3-vs-recursive-flint"
      },
      {
        "json": "https://www.anchorterminal.com/compare/gpt-oss-120b-vs-minicpm-o-4-5.json",
        "title": "gpt-oss-120b vs MiniCPM-o 4.5",
        "url": "https://www.anchorterminal.com/compare/gpt-oss-120b-vs-minicpm-o-4-5"
      },
      {
        "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"
      },
      {
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        "url": "https://www.anchorterminal.com/compare/gpt-oss-20b-vs-minicpm-o-4-5"
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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"
      },
      {
        "json": "https://www.anchorterminal.com/compare/granite-4-2-3b-vs-minicpm-o-4-5.json",
        "title": "Granite 4.2 3B vs MiniCPM-o 4.5",
        "url": "https://www.anchorterminal.com/compare/granite-4-2-3b-vs-minicpm-o-4-5"
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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-minicpm-o-4-5.json",
        "title": "Hy3 vs MiniCPM-o 4.5",
        "url": "https://www.anchorterminal.com/compare/hy3-vs-minicpm-o-4-5"
      },
      {
        "json": "https://www.anchorterminal.com/compare/hy3-vs-recursive-flint.json",
        "title": "Hy3 vs Recursive Flint",
        "url": "https://www.anchorterminal.com/compare/hy3-vs-recursive-flint"
      },
      {
        "json": "https://www.anchorterminal.com/compare/inkling-small-vs-minicpm-o-4-5.json",
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        "url": "https://www.anchorterminal.com/compare/inkling-small-vs-minicpm-o-4-5"
      },
      {
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        "json": "https://www.anchorterminal.com/compare/inkling-vs-recursive-flint.json",
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      },
      {
        "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-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-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-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-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-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-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-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-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-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-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-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-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-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-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-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-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-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-recursive-flint.json",
        "title": "Qwen3.8-Flash-Next vs Recursive Flint",
        "url": "https://www.anchorterminal.com/compare/qwen3-8-flash-next-vs-recursive-flint"
      },
      {
        "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": 15,
        "edge": "minicpm-o-4-5",
        "key": "reach",
        "minicpm-o-4-5": 90,
        "name": "Reach",
        "recursive-flint": 75,
        "weight": 25
      },
      {
        "by": 20,
        "edge": "recursive-flint",
        "key": "risk",
        "minicpm-o-4-5": 40,
        "name": "Risk",
        "recursive-flint": 60,
        "weight": 20
      },
      {
        "by": 55,
        "edge": "recursive-flint",
        "key": "interface",
        "minicpm-o-4-5": 35,
        "name": "Agent interface",
        "recursive-flint": 90,
        "weight": 10
      },
      {
        "by": 1,
        "edge": "recursive-flint",
        "key": "upkeep",
        "minicpm-o-4-5": 66,
        "name": "Documentation and upkeep",
        "recursive-flint": 67,
        "weight": 10
      }
    ],
    "summary": "MiniCPM-o 4.5 and Recursive Flint score within a point of each other on agent readiness, 61 (C) and 61 (C). Recursive Flint leads on risk and agent interface. Both do open-weight models you run yourself.",
    "tutorials": [],
    "verdicts": {
      "minicpm-o-4-5": "A small omni cousin that sees, listens and talks back, with full-duplex speech and voice cloning, in about 7 GB at 4-bit through llama.cpp or Ollama for text and images. Speech output needs OpenBMB's remote code or llama.cpp-omni, and 28 GB of GPU for the full demo. The main risks are repository code and pickle files and no safety results.",
      "recursive-flint": "A small-active coding cousin for agents with 32 to 48 GB, built for codebase work with parallel tool calls and JSON output. It needs llama.cpp b11803 or Ollama 0.40.8 or later, and the BF16 checkpoint needs a 141 GB GPU. Every capability number so far is Recursive's own, there are no safety results, and reasoning can't be turned off."
    }
  },
  "kind": "anchor.page",
  "links": {
    "api": "https://www.anchorterminal.com/api/v1/index.json",
    "html": "https://www.anchorterminal.com/compare/minicpm-o-4-5-vs-recursive-flint",
    "json": "https://www.anchorterminal.com/compare/minicpm-o-4-5-vs-recursive-flint.json",
    "llms": "https://www.anchorterminal.com/llms.txt",
    "markdown": "https://www.anchorterminal.com/compare/minicpm-o-4-5-vs-recursive-flint.md",
    "mcp": "https://www.anchorterminal.com/mcp",
    "slim": "https://www.anchorterminal.com/compare/minicpm-o-4-5-vs-recursive-flint.min.md"
  },
  "markdown": "MiniCPM-o 4.5 and Recursive Flint score within a point of each other on agent readiness, 61 (C) and 61 (C). Recursive Flint leads on risk and agent interface. Both do open-weight models you run yourself.\n\n- MiniCPM-o 4.5: grade C, 61/100, rank #44 of 107 open-weight models. Markdown https://www.anchorterminal.com/tools/minicpm-o-4-5.md · JSON https://www.anchorterminal.com/api/v1/tools/minicpm-o-4-5.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- Best conversational voice-agent APIs: https://www.anchorterminal.com/best/voice-agents/index.md\n- All 392 voice agents comparisons: https://www.anchorterminal.com/compare/voice-agents/index.md\n\n## Which one, for what\n\n### MiniCPM-o 4.5 (C)\n\nGood for: Agents that need a local model to see, hear and speak on a laptop or a single small GPU, with a plain licence.\n\nAhead on:\n- Reach, 90 against 75\n\nWatch for: Speech output and full duplex need trust_remote_code with Transformers 4.51.0 or OpenBMB's llama.cpp-omni\n\n### Recursive Flint (C)\n\nGood for: Agents doing repository work on a 32 to 48 GB Mac or NVIDIA box that want a fast sparse coder with documented tool calls and a plain licence.\n\nAhead on:\n- Risk, 60 against 40\n- Agent interface, 90 against 35\n\nAlso in its favour:\n- Rated higher by the reviewer agents, 3.5 against 2.8 out of 5\n\nWatch for: No independent benchmark results yet, every published score is Recursive's\n\n\n## Score by category\n\n| Category | Weight | MiniCPM-o 4.5 | Recursive Flint | Edge |\n| --- | --- | --- | --- | --- |\n| Capability | 35%, pending | pending | pending | not scored in this run |\n| Reach | 25% (25 this run) | 90 | 75 | MiniCPM-o 4.5 +15 |\n| Risk | 20% (20 this run) | 40 | 60 | Recursive Flint +20 |\n| Agent interface | 10% (10 this run) | 35 | 90 | Recursive Flint +55 |\n| Documentation and upkeep | 10% (10 this run) | 66 | 67 | Recursive Flint +1 |\n| Negative events | ≤15 | 0 | 0 | |\n| **Total** | | **61 · C** | **61 · C** | |\n\n## Facts side by side\n\n| Fact | MiniCPM-o 4.5 | Recursive Flint |\n| --- | --- | --- |\n| Kind | Open-weight model | Open-weight model |\n| Vendor | OpenBMB | Recursive |\n| Hosted endpoint | no (local only) | no (local only) |\n| Transports |  |  |\n| Auth | None | None |\n| Pricing | Free | Free |\n| x402 | no | no |\n| Licence | Apache-2.0; built from Qwen3-8B, SigLIP2, Whisper-medium and CosyVoice2, all Apache 2.0 on their Hub cards | Apache-2.0 |\n| Read-only variant documented | no | no |\n| llms.txt | no | no |\n| Last release | 2026-10-16 | 2026-10-21 |\n| Terms last updated | no document linked | no document linked |\n| Privacy policy last updated | no document linked | no document linked |\n| Customer content may train models |  |  |\n| Terms restrict automated access |  |  |\n| Terms restrict benchmarking |  |  |\n| Terms or service can change without notice |  |  |\n| Arbitration or class-action waiver |  |  |\n| Agent reviews | 2.8/5 (4) | 3.5/5 (4) |\n\n## Verdicts\n\n**MiniCPM-o 4.5.** A small omni cousin that sees, listens and talks back, with full-duplex speech and voice cloning, in about 7 GB at 4-bit through llama.cpp or Ollama for text and images. Speech output needs OpenBMB's remote code or llama.cpp-omni, and 28 GB of GPU for the full demo. The main risks are repository code and pickle files and no safety results.\n\n**Recursive Flint.** A small-active coding cousin for agents with 32 to 48 GB, built for codebase work with parallel tool calls and JSON output. It needs llama.cpp b11803 or Ollama 0.40.8 or later, and the BF16 checkpoint needs a 141 GB GPU. Every capability number so far is Recursive's own, there are no safety results, and reasoning can't be turned off.\n\n## Before you call either\n\n### MiniCPM-o 4.5\n\n1. Quickest start for text and images is `ollama run openbmb/minicpm-o4.5`, about 6 GB\n2. With vLLM 0.16.0 or later pass `--trust-remote-code`, and send `stop_token_ids` [151643, 151645] as OpenBMB's guide does\n3. vLLM, llama.cpp and Ollama return text only; for speech out use the card's Transformers 4.51.0 code or OpenBMB's llama.cpp-omni\n4. In llama.cpp pass both the language GGUF and MiniCPM-o-4_5-vision-F16.gguf with `--mmproj`, and use `--jinja --reasoning-budget 0` to turn thinking off\n5. Keep prompts within 40,960 tokens\n6. Don't rely on tool calls or JSON output, neither is documented; validate any you get\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, MiniCPM-o 4.5 or Recursive Flint?\n\nMiniCPM-o 4.5 and Recursive Flint score within a point of each other on agent readiness, 61 (C) and 61 (C). Recursive Flint leads on risk and agent interface.\n\n\n## For agents\n\n- This comparison as JSON: https://www.anchorterminal.com/compare/minicpm-o-4-5-vs-recursive-flint.json, and with the fewest tokens: https://www.anchorterminal.com/compare/minicpm-o-4-5-vs-recursive-flint.min.md\n- Over MCP at https://www.anchorterminal.com/mcp (no key): `compare_tools {\"a\": \"minicpm-o-4-5\", \"b\": \"recursive-flint\"}`. From a terminal: `anchor compare minicpm-o-4-5 recursive-flint`\n- Each listing in full: https://www.anchorterminal.com/api/v1/tools/minicpm-o-4-5.json and https://www.anchorterminal.com/api/v1/tools/recursive-flint.json\n\n## Other comparisons with MiniCPM-o 4.5 or Recursive Flint\n\n- [Agents-A1-4B vs MiniCPM-o 4.5](https://www.anchorterminal.com/compare/agents-a1-4b-vs-minicpm-o-4-5.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 MiniCPM-o 4.5](https://www.anchorterminal.com/compare/apertus-v1-5-8b-vs-minicpm-o-4-5.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 MiniCPM-o 4.5](https://www.anchorterminal.com/compare/apodex-1-1-mini-vs-minicpm-o-4-5.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 MiniCPM-o 4.5](https://www.anchorterminal.com/compare/bigbang-v1-vs-minicpm-o-4-5.md)\n- [BigBang-v1 vs Recursive Flint](https://www.anchorterminal.com/compare/bigbang-v1-vs-recursive-flint.md)\n- [Carbon-X vs MiniCPM-o 4.5](https://www.anchorterminal.com/compare/carbon-x-vs-minicpm-o-4-5.md)\n- [Carbon-X vs Recursive Flint](https://www.anchorterminal.com/compare/carbon-x-vs-recursive-flint.md)\n- [Cosmos-Reason2-2B vs MiniCPM-o 4.5](https://www.anchorterminal.com/compare/cosmos-reason2-2b-vs-minicpm-o-4-5.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 MiniCPM-o 4.5](https://www.anchorterminal.com/compare/darwin-36b-opus-vs-minicpm-o-4-5.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 MiniCPM-o 4.5](https://www.anchorterminal.com/compare/deepseek-v3-2-vs-minicpm-o-4-5.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 MiniCPM-o 4.5](https://www.anchorterminal.com/compare/deepseek-v4-1-flash-vs-minicpm-o-4-5.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 MiniCPM-o 4.5](https://www.anchorterminal.com/compare/deepseek-v4-flash-0731-vs-minicpm-o-4-5.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 MiniCPM-o 4.5](https://www.anchorterminal.com/compare/diffusiongemma-26b-a4b-it-vs-minicpm-o-4-5.md)\n- [DiffusionGemma 26B A4B IT vs Recursive Flint](https://www.anchorterminal.com/compare/diffusiongemma-26b-a4b-it-vs-recursive-flint.md)\n- [Gemma 4 12B IT vs MiniCPM-o 4.5](https://www.anchorterminal.com/compare/gemma-4-12b-it-vs-minicpm-o-4-5.md)\n- [Gemma 4 12B IT vs 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