{
  "data": {
    "a": {
      "slug": "minicpm5-2b",
      "name": "MiniCPM5-2B",
      "vendor": "OpenBMB",
      "vendorUrl": "https://openbmb.cn",
      "kind": "weights",
      "category": "open-weights",
      "summary": "MiniCPM5-2B is OpenBMB's open-weight dense language model of 2.5B parameters for on-device and local use, with thinking, XML tool calls and a 131,072-token context, published on Hugging Face in BF16, GGUF, MLX and GPTQ under Apache 2.0.",
      "url": "https://www.anchorterminal.com/tools/minicpm5-2b",
      "markdownUrl": "https://www.anchorterminal.com/tools/minicpm5-2b.md",
      "slimMarkdownUrl": "https://www.anchorterminal.com/tools/minicpm5-2b.min.md",
      "jsonUrl": "https://www.anchorterminal.com/api/v1/tools/minicpm5-2b.json",
      "dns": "minicpm5-2b.grade.anchorterminal.com",
      "repo": "https://huggingface.co/openbmb/MiniCPM5-2B",
      "license": "Apache-2.0",
      "transports": [],
      "packages": [
        {
          "registry": "huggingface",
          "name": "openbmb/MiniCPM5-2B"
        },
        {
          "registry": "huggingface",
          "name": "openbmb/MiniCPM5-2B-GGUF"
        },
        {
          "registry": "huggingface",
          "name": "openbmb/MiniCPM5-2B-MLX"
        },
        {
          "registry": "huggingface",
          "name": "openbmb/MiniCPM5-2B-GPTQ"
        },
        {
          "registry": "ollama",
          "name": "openbmb/minicpm5-2b"
        }
      ],
      "auth": "none",
      "authNotes": "The weights download from Hugging Face with no account, token or terms to accept. The repository and its GGUF, MLX and GPTQ siblings are not gated (checked 2026-10-21).",
      "pricing": "free",
      "pricingNotes": "Free to download and use, commercial use included, under Apache 2.0. OpenBMB sells no per-call access to these weights. Running them costs the hardware, 5.03 GB for the BF16 file and 1.56 GB for OpenBMB's Q4_K_M GGUF (checked 2026-10-21).",
      "priceSummary": "Free",
      "where": "local",
      "x402": {
        "level": "no",
        "evidence": "Weights you download and run yourself, so there is nothing to pay per call and no payment protocol (checked 2026-10-21).",
        "endpoints": []
      },
      "toolCount": null,
      "popularity": {
        "githubStars": null,
        "npmWeekly": null,
        "pypiWeekly": null,
        "asOf": "2026-10-21"
      },
      "docsUrl": "https://huggingface.co/openbmb/MiniCPM5-2B",
      "capabilities": [
        "model.open-weights"
      ],
      "tags": [
        "open-weights",
        "model",
        "dense",
        "small",
        "on-device",
        "reasoning",
        "tool-calling",
        "apache-2.0",
        "safetensors",
        "gguf",
        "mlx",
        "self-hosted"
      ],
      "lastRelease": "2026-09-29",
      "graded": true,
      "anchor": {
        "graded": true,
        "score": 59.7,
        "grade": "C",
        "agentReady": false,
        "rank": 0,
        "ranked": false,
        "notRankedWhy": "An open-weight model, graded by the open-weight checklist and ranked among open-weight models, not against tools",
        "rankOf": 1518,
        "categoryRank": 74,
        "methodology": "0.7",
        "run": "2026-10-01",
        "scores": {
          "capability": 27,
          "interface": 75,
          "reach": 90,
          "risk": 55,
          "upkeep": 92
        },
        "pending": [
          "performance",
          "tasks"
        ],
        "assessment": {
          "confidence": "high",
          "date": "2026-11-04"
        },
        "negative": 0,
        "verdict": "A 2B dense model for local tool calling and long context, with published training data. OpenBMB's own 4-bit builds are under 1.6 GB, and the model loads in vLLM, SGLang, llama.cpp, Ollama and Transformers. The main risks are always-on thinking, no safety results and use conditions beyond Apache 2.0.",
        "bestFor": "On-device and laptop agents that want a 2 GB tool-calling helper with long context and open training data",
        "strengths": [
          "OpenBMB's own GGUF, MLX and GPTQ builds, the 4-bit ones under 1.6 GB",
          "Stock LlamaForCausalLM, so vLLM, SGLang, llama.cpp, Ollama and Transformers load it without a fork",
          "Tool calls documented with the minicpm5 parser in released vLLM and SGLang, several calls per turn",
          "131,072 tokens native",
          "All eight training datasets published on Hugging Face",
          "OpenBMB answered 16 of 23 discussion questions and fixed the template on 29 September 2026"
        ],
        "weaknesses": [
          "OpenBMB documents only a Think mode for the 2B, so every answer starts with reasoning",
          "No safety evaluation, refusal scope or prompt-injection guidance",
          "No security.txt, disclosure policy or SECURITY.md",
          "The card adds use conditions to Apache 2.0, ethical use only and no jailbreak or injection testing",
          "No hosted endpoint, so an agent without hardware can't call it",
          "No knowledge cut-off and no structured-output guidance",
          "No OpenBMB reply in the discussions since 29 September 2026; seven questions opened since 5 October wait"
        ],
        "agentNotes": [
          "Smallest start is `ollama run openbmb/minicpm5-2b` (1.6 GB, q4_k_m)",
          "On vLLM 0.29.0 or later run `vllm serve openbmb/MiniCPM5-2B --max-model-len 131072 --enable-auto-tool-choice --tool-call-parser minicpm5`, or tool calls come back as XML text",
          "On SGLang 0.5.16 or later add `--tool-call-parser minicpm5 --reasoning-parser qwen3`; SGLang is OpenBMB's recommended backend for tool calls",
          "Tool calls are XML, `\u003cfunction name=...\u003e\u003cparam name=...\u003e`, not Hermes JSON",
          "Sample with temperature 1.0, top_p 0.95 and min_p 0.0; llama.cpp's default min_p 0.05 can loop, and repetition_penalty 1.05 helps if it does",
          "Expect a `\u003cthink\u003e` block before every answer and leave room in max_tokens; enable_thinking false is accepted by the template but OpenBMB doesn't support it for the 2B",
          "Validate JSON yourself or use the runtime's guided decoding, since structured output isn't documented",
          "Use the main repository's template; the GGUF, MLX and GPTQ copies predate the 29 September fix"
        ],
        "metrics": {
          "kind": "local",
          "measured": false
        },
        "reviewCount": 4,
        "avgRating": 3,
        "history": [
          {
            "basis": "public evidence",
            "confidence": "high",
            "grade": "C",
            "methodology": "0.7",
            "pending": [
              "performance",
              "tasks"
            ],
            "run": "2026-10-01",
            "runLabel": "October 2026 research run",
            "score": 59.7
          }
        ],
        "editorialScores": {
          "capability": 27,
          "interface": 75,
          "reach": 90,
          "risk": 55,
          "upkeep": 92
        },
        "provenanceScore": 58,
        "checked": {
          "categories": {
            "capability": "2026-11-04",
            "interface": "2026-11-04",
            "reach": "2026-11-04",
            "risk": "2026-11-04",
            "upkeep": "2026-11-04"
          },
          "last": "2026-11-04",
          "lastMoved": "2026-11-04",
          "oldest": "2026-11-04",
          "stale": false,
          "staleAfterDays": 90
        }
      },
      "connect": {
        "install": "ollama run openbmb/minicpm5-2b\n# or, with vLLM 0.29.0 or later:\nvllm serve openbmb/MiniCPM5-2B --max-model-len 131072 \\\n  --enable-auto-tool-choice --tool-call-parser minicpm5",
        "http": "curl http://localhost:8000/v1/chat/completions \\\n  -H \"Content-Type: application/json\" \\\n  -d '{\n    \"model\": \"openbmb/MiniCPM5-2B\",\n    \"messages\": [{\"role\": \"user\", \"content\": \"Hello!\"}],\n    \"temperature\": 1.0, \"top_p\": 0.95,\n    \"chat_template_kwargs\": {\"enable_thinking\": true}\n  }'"
      },
      "letme": {
        "capability": "https://letme.dev/model.open-weights",
        "tool": "https://letme.dev/minicpm5-2b"
      },
      "sameCompany": [
        "minicpm-v-4-7-1b",
        "minicpm-v-4-7-35b-a3b",
        "minicpm-o-4-5"
      ],
      "weights": {
        "trainedBy": "OpenBMB",
        "builtOn": "openbmb/MiniCPM5-2B-Base",
        "params": "2.5B",
        "context": 131072,
        "goodFor": "Small on-device language model with thinking and XML tool calls, text only.",
        "runtimes": [
          "llama.cpp",
          "Ollama",
          "vLLM",
          "SGLang",
          "Transformers"
        ],
        "builds": [
          {
            "name": "MiniCPM5-2B",
            "url": "https://huggingface.co/openbmb/MiniCPM5-2B",
            "who": "publisher",
            "precision": "bf16",
            "sizeGB": 5,
            "memoryGB": 8,
            "format": "safetensors",
            "runsOn": [
              "vLLM (ROCm)",
              "SGLang (ROCm)"
            ]
          },
          {
            "name": "MiniCPM5-2B-F16",
            "url": "https://huggingface.co/openbmb/MiniCPM5-2B-GGUF/blob/main/MiniCPM5-2B-F16.gguf",
            "who": "publisher",
            "precision": "f16",
            "sizeGB": 5,
            "memoryGB": 8,
            "format": "gguf",
            "runsOn": [
              "llama.cpp (Vulkan)",
              "llama.cpp (ROCm)",
              "LM Studio"
            ]
          },
          {
            "name": "MiniCPM5-2B-Q8_0",
            "url": "https://huggingface.co/openbmb/MiniCPM5-2B-GGUF/blob/main/MiniCPM5-2B-Q8_0.gguf",
            "who": "publisher",
            "precision": "q8_0",
            "sizeGB": 2.7,
            "memoryGB": 8,
            "format": "gguf",
            "runsOn": [
              "llama.cpp (Vulkan)",
              "llama.cpp (ROCm)",
              "LM Studio"
            ]
          },
          {
            "name": "MiniCPM5-2B-Q4_K_M",
            "url": "https://huggingface.co/openbmb/MiniCPM5-2B-GGUF/blob/main/MiniCPM5-2B-Q4_K_M.gguf",
            "who": "publisher",
            "precision": "q4_k_m",
            "sizeGB": 1.6,
            "memoryGB": 8,
            "format": "gguf",
            "runsOn": [
              "llama.cpp (Vulkan)",
              "llama.cpp (ROCm)",
              "LM Studio"
            ]
          },
          {
            "name": "MiniCPM5-2B-MLX",
            "url": "https://huggingface.co/openbmb/MiniCPM5-2B-MLX",
            "who": "publisher",
            "precision": "4bit",
            "sizeGB": 1.4,
            "memoryGB": 8,
            "format": "mlx",
            "note": "MLX runs on Apple silicon only"
          },
          {
            "name": "MiniCPM5-2B-GPTQ",
            "url": "https://huggingface.co/openbmb/MiniCPM5-2B-GPTQ",
            "who": "publisher",
            "precision": "gptq-int4",
            "sizeGB": 2.1,
            "memoryGB": 8,
            "format": "safetensors",
            "note": "vLLM's quantisation table marks GPTQ unsupported on AMD GPUs"
          },
          {
            "name": "ollama openbmb/minicpm5-2b:latest",
            "url": "https://ollama.com/openbmb/minicpm5-2b",
            "who": "publisher",
            "precision": "q4_k_m",
            "sizeGB": 1.6,
            "memoryGB": 8,
            "format": "ollama",
            "runsOn": [
              "Ollama"
            ],
            "note": "In the openbmb namespace on ollama.com, taken as OpenBMB's. Size as Ollama's tags page shows it, rounded to whole GB above 10 GB; the Linux build is the llama.cpp variant"
          }
        ],
        "run": "ollama run openbmb/minicpm5-2b",
        "runBuild": "ollama openbmb/minicpm5-2b:latest",
        "checked": "2026-10-21",
        "minMemoryGB": 8
      },
      "family": {
        "lab": "OpenBMB (MiniCPM)",
        "family": "MiniCPM5",
        "url": "https://www.anchorterminal.com/open-weights/#openbmb",
        "others": [
          {
            "name": "MiniCPM5-2B-SFT",
            "url": "https://huggingface.co/openbmb/MiniCPM5-2B-SFT",
            "params": "2B"
          },
          {
            "name": "MiniCPM5-2B-Midtrain",
            "url": "https://huggingface.co/openbmb/MiniCPM5-2B-Midtrain",
            "params": "2B"
          },
          {
            "name": "MiniCPM5-2B-Base",
            "url": "https://huggingface.co/openbmb/MiniCPM5-2B-Base",
            "params": "2B"
          },
          {
            "name": "MiniCPM5-1B",
            "url": "https://huggingface.co/openbmb/MiniCPM5-1B",
            "params": "1B"
          },
          {
            "name": "MiniCPM5-1B-SFT",
            "url": "https://huggingface.co/openbmb/MiniCPM5-1B-SFT",
            "params": "1B"
          },
          {
            "name": "MiniCPM5-1B-Base",
            "url": "https://huggingface.co/openbmb/MiniCPM5-1B-Base",
            "params": "1B"
          }
        ],
        "olderCount": 22,
        "unrestrictedCopies": 5
      },
      "area": "models",
      "provenance": {
        "legalEntity": "OpenBMB (named in the GitHub LICENSE's copyright line)",
        "domain": "openbmb.cn",
        "domainRegistered": "",
        "endpointOnVendorDomain": null,
        "terms": "",
        "privacy": "",
        "statusPage": "",
        "changelog": "https://huggingface.co/openbmb/MiniCPM5-2B/commits/main",
        "securityTxt": "none",
        "checked": "2026-10-21",
        "notes": [
          "The LICENSE in github.com/OpenBMB/MiniCPM reads Copyright [OpenBMB]. The card links its wiki to ModelBest's Feishu space, and no legal entity is named on the card. rdap.org has no RDAP service for .cn, so the domain's registration date wasn't checked.",
          "Nothing is hosted, so the Apache 2.0 licence stands in for terms of service and no privacy policy is scored.",
          "The changelog is the repository's commit history, whose messages say what changed (a template fix on 29 September referencing OpenBMB/MiniCPM#379, sampling advice on 12 September), and the GitHub README's dated changelog lists the release on 7 September 2026.",
          "openbmb.cn/.well-known/security.txt and modelbest.cn/.well-known/security.txt answered 404 on 21 October 2026, and the GitHub repository has no security policy."
        ],
        "score": 58
      },
      "pageJsonUrl": "https://www.anchorterminal.com/tools/minicpm5-2b.json",
      "live": {
        "slug": "minicpm5-2b",
        "securityTxt": {
          "url": "https://openbmb.cn/.well-known/security.txt",
          "state": "none",
          "checkedAt": "2026-11-10T16:08:10.170465559Z"
        },
        "domain": {
          "domain": "openbmb.cn",
          "checkedAt": "2026-11-08T14:50:03.275690576Z"
        },
        "pages": [
          {
            "url": "https://huggingface.co/openbmb/MiniCPM5-2B/commits/main",
            "kind": "changelog",
            "status": 200,
            "checkedAt": "2026-11-10T16:23:40.687483011Z",
            "changedAt": "2026-11-10T16:23:40.687483011Z",
            "fingerprint": "0e9151c731e0"
          }
        ],
        "updatedAt": "2026-11-10T16:23:40.687483011Z"
      }
    },
    "answer": "MiniCPM5-2B scores 59.7 (C) on agent readiness against Qwen-AgentWorld-35B-A3B's 52.1 (D), and leads in 3 of 4 scored categories.",
    "b": {
      "slug": "qwen-agentworld-35b-a3b",
      "name": "Qwen-AgentWorld-35B-A3B",
      "vendor": "Alibaba (Qwen team)",
      "vendorUrl": "https://qwen.ai",
      "kind": "weights",
      "category": "open-weights",
      "summary": "Qwen-AgentWorld-35B-A3B is Alibaba's open-weight language world model, a 35B mixture of experts with 3B active that simulates agent environments by predicting the next observation across seven domains, published in BF16 under Apache 2.0.",
      "url": "https://www.anchorterminal.com/tools/qwen-agentworld-35b-a3b",
      "markdownUrl": "https://www.anchorterminal.com/tools/qwen-agentworld-35b-a3b.md",
      "slimMarkdownUrl": "https://www.anchorterminal.com/tools/qwen-agentworld-35b-a3b.min.md",
      "jsonUrl": "https://www.anchorterminal.com/api/v1/tools/qwen-agentworld-35b-a3b.json",
      "dns": "qwen-agentworld-35b-a3b.grade.anchorterminal.com",
      "repo": "https://huggingface.co/Qwen/Qwen-AgentWorld-35B-A3B",
      "license": "Apache-2.0",
      "transports": [],
      "packages": [
        {
          "registry": "huggingface",
          "name": "Qwen/Qwen-AgentWorld-35B-A3B"
        }
      ],
      "auth": "none",
      "authNotes": "The weights download from Hugging Face with no account, token or terms to accept. The repository is not gated (checked 2026-11-10).",
      "pricing": "free",
      "pricingNotes": "Free to download and use, commercial use included, under Apache 2.0, with a LICENSE file in the repository. Running it yourself costs the hardware, 69.3 GB for the BF16 files, or 22.1 GB for Unsloth's 4-bit GGUF (checked 2026-11-10).",
      "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 2026-11-10).",
        "endpoints": []
      },
      "toolCount": null,
      "popularity": {
        "githubStars": null,
        "npmWeekly": null,
        "pypiWeekly": null,
        "asOf": "2026-11-10"
      },
      "docsUrl": "https://huggingface.co/Qwen/Qwen-AgentWorld-35B-A3B",
      "capabilities": [
        "model.open-weights"
      ],
      "tags": [
        "open-weights",
        "model",
        "moe",
        "world-model",
        "agent-simulation",
        "reasoning",
        "apache-2.0",
        "safetensors",
        "self-hosted"
      ],
      "lastRelease": "2026-06-25",
      "graded": true,
      "anchor": {
        "graded": true,
        "score": 52.1,
        "grade": "D",
        "agentReady": false,
        "rank": 0,
        "ranked": false,
        "notRankedWhy": "An open-weight model, graded by the open-weight checklist and ranked among open-weight models, not against tools",
        "rankOf": 1518,
        "categoryRank": 104,
        "methodology": "0.7",
        "run": "2026-10-01",
        "scores": {
          "interface": 50,
          "reach": 55,
          "risk": 55,
          "upkeep": 41
        },
        "pending": [
          "performance",
          "tasks"
        ],
        "assessment": {
          "confidence": "low",
          "date": "2026-11-10"
        },
        "negative": 0,
        "verdict": "A specialist, not a chat model. It plays the environment an agent acts in, across seven domains, so you can train or test an agent without the real thing. Alibaba ships BF16 only, which fits a 128 GB machine, and hasn't answered a discussion on it or changed the files since June.",
        "bestFor": "Agent builders who want to train or test an agent against simulated tools, terminals, browsers and phones on a 128 GB machine",
        "strengths": [
          "Simulates seven kinds of agent environment in one model, with the system prompts for each published",
          "Apache 2.0, ungated, safetensors only",
          "Runs in vLLM, SGLang, Transformers and llama.cpp from their releases",
          "Fits a 128 GB machine in BF16, and 32 GB from Unsloth's 4-bit GGUF",
          "A 262,144-token context for long interaction histories"
        ],
        "weaknesses": [
          "Not a general assistant, and the card doesn't describe using it to call tools",
          "No quantised build from Alibaba, so the GGUF route depends on a third party",
          "No reply from Alibaba on any of 10 discussions, and no change to the files since 25 June 2026",
          "No limitations, safety results or security contact on the card",
          "Its results are on Alibaba's own benchmark"
        ],
        "agentNotes": [
          "Use it as the environment, not the agent. Give it the domain's system prompt from Alibaba's GitHub repository, the history and the agent's action, and it returns the predicted observation",
          "With vLLM pass `--language-model-only`, or startup fails on the missing vision weights",
          "Use temperature 0.6, top_p 0.95 and top_k 20, and allow up to 32,768 output tokens, as the card recommends",
          "Keep at least 128K of context, since the simulation depends on the history",
          "Thinking is on by default and comes back through the qwen3 reasoning parser",
          "A simulated observation is a prediction. Check anything that matters against the real environment"
        ],
        "metrics": {
          "kind": "local",
          "measured": false
        },
        "reviewCount": 0,
        "avgRating": 0,
        "history": [
          {
            "basis": "public evidence",
            "confidence": "low",
            "grade": "D",
            "methodology": "0.7",
            "pending": [
              "performance",
              "tasks"
            ],
            "run": "2026-10-01",
            "runLabel": "October 2026 research run",
            "score": 52.1
          }
        ],
        "editorialScores": {
          "interface": 50,
          "reach": 55,
          "risk": 55,
          "upkeep": 41
        },
        "provenanceScore": 66,
        "checked": {
          "categories": {
            "interface": "2026-11-10",
            "reach": "2026-11-10",
            "risk": "2026-11-10",
            "upkeep": "2026-11-10"
          },
          "last": "2026-11-10",
          "oldest": "2026-11-10",
          "stale": false,
          "staleAfterDays": 90
        }
      },
      "connect": {
        "install": "# vLLM, as the card gives it (four GPUs)\nvllm serve Qwen/Qwen-AgentWorld-35B-A3B --port 8000 --tensor-parallel-size 4 \\\n  --max-model-len 262144 --reasoning-parser qwen3 --language-model-only --trust-remote-code\n# or, with llama.cpp and Unsloth's GGUF, a third party's conversion:\nllama-server -hf unsloth/Qwen-AgentWorld-35B-A3B-GGUF:UD-Q4_K_M --jinja",
        "http": "curl http://localhost:8000/v1/chat/completions \\\n  -H \"Content-Type: application/json\" \\\n  -d '{\"model\": \"Qwen/Qwen-AgentWorld-35B-A3B\", \"messages\": [{\"role\": \"user\", \"content\": \"Hello!\"}], \"temperature\": 0.6}'"
      },
      "letme": {
        "capability": "https://letme.dev/model.open-weights",
        "tool": "https://letme.dev/qwen-agentworld-35b-a3b"
      },
      "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",
        "qwen3-8-flash-next"
      ],
      "weights": {
        "trainedBy": "Alibaba (Qwen)",
        "builtOn": "Qwen3.5-35B-A3B-Base, named on the card and in its metadata",
        "params": "34.7B",
        "active": "3B",
        "context": 262144,
        "goodFor": "A simulator of agent environments (MCP tools, search, terminal, software engineering, Android, web and OS) that predicts the next observation, for training and testing agents without the real environment.",
        "runtimes": [
          "vLLM",
          "SGLang",
          "Transformers",
          "llama.cpp"
        ],
        "builds": [
          {
            "name": "unsloth Qwen-AgentWorld-35B-A3B-GGUF (UD-Q4_K_M)",
            "url": "https://huggingface.co/unsloth/Qwen-AgentWorld-35B-A3B-GGUF",
            "who": "unsloth",
            "precision": "q4_k_m",
            "sizeGB": 22.13,
            "memoryGB": 32,
            "format": "gguf",
            "runsOn": [
              "llama.cpp"
            ],
            "note": "From Unsloth, a third party's conversion and not Alibaba's. 22.13 GB of UD-Q4_K_M weights, from the Hub's model information on 10 November 2026. Reach doesn't count it"
          },
          {
            "name": "unsloth Qwen-AgentWorld-35B-A3B-GGUF (Q8_0)",
            "url": "https://huggingface.co/unsloth/Qwen-AgentWorld-35B-A3B-GGUF",
            "who": "unsloth",
            "precision": "q8_0",
            "sizeGB": 36.9,
            "memoryGB": 48,
            "format": "gguf",
            "runsOn": [
              "llama.cpp"
            ],
            "note": "From Unsloth, a third party's conversion and not Alibaba's. 36.90 GB of Q8_0 weights, from the Hub's model information on 10 November 2026. Reach doesn't count it"
          },
          {
            "name": "Qwen-AgentWorld-35B-A3B",
            "url": "https://huggingface.co/Qwen/Qwen-AgentWorld-35B-A3B",
            "who": "publisher",
            "precision": "bf16",
            "sizeGB": 69.32,
            "memoryGB": 96,
            "format": "safetensors",
            "runsOn": [
              "vLLM (ROCm)",
              "SGLang (ROCm)",
              "Transformers"
            ],
            "note": "The only build Alibaba publishes. Language weights only"
          }
        ],
        "run": "llama-server -hf unsloth/Qwen-AgentWorld-35B-A3B-GGUF:UD-Q4_K_M --jinja",
        "runBuild": "unsloth Qwen-AgentWorld-35B-A3B-GGUF (UD-Q4_K_M)",
        "checked": "2026-11-10",
        "minMemoryGB": 32
      },
      "family": {
        "lab": "Alibaba (Qwen)",
        "family": "Qwen-AgentWorld",
        "url": "https://www.anchorterminal.com/open-weights/#qwen",
        "olderCount": 109
      },
      "area": "models",
      "provenance": {
        "legalEntity": "Alibaba Cloud (named in the licence's copyright line)",
        "domain": "qwen.ai",
        "domainRegistered": "2023-08-27",
        "endpointOnVendorDomain": null,
        "terms": "",
        "privacy": "",
        "statusPage": "",
        "changelog": "https://huggingface.co/Qwen/Qwen-AgentWorld-35B-A3B/commits/main",
        "securityTxt": "none",
        "checked": "2026-11-10",
        "notes": [
          "The LICENSE file names Alibaba Cloud, as the Qwen3.6-35B-A3B listing records for the organisation.",
          "Nothing is hosted, so the Apache 2.0 licence stands in for terms of service and no privacy policy is scored.",
          "The changelog is the repository's commit history, nine commits between 22 and 25 June 2026, the upload and updates to the card.",
          "The Qwen3.6-35B-A3B listing found no security.txt on qwen.ai. unchecked on 10 November."
        ],
        "score": 66
      },
      "pageJsonUrl": "https://www.anchorterminal.com/tools/qwen-agentworld-35b-a3b.json"
    },
    "edges": [
      {
        "by": 51,
        "category": "upkeep",
        "leads": "minicpm5-2b",
        "name": "Documentation and upkeep",
        "reasons": {
          "a": "Model card 17, everything but a knowledge cut-off. Training data 20, all eight training datasets are published on Hugging Face and named per stage with sizes. Last change 15, a template fix on 29 September 2026, 36 days ago, with nothing newer in OpenBMB's MiniCPM5 repositories on Hugging Face (builds last changed 12 September) or its GitHub repository (21 September). Responsiveness 20, OpenBMB members answered 16 of the 23 questions in the discussions, the newest reply on 29 September. Version policy 10, earlier models and checkpoints sit in their own repositories and the GitHub changelog dates each release. File health 10, config, tokenizer, template and card agree and no broken-file report waited on 21 October, though OpenBMB's GGUF, MLX and GPTQ repositories still carry the template from before the 29 September fix.",
          "b": "Model card 11, the card gives intended use (simulating agent environments), architecture, parameters and context length. Training data 5, A general description without a cut-off, the three training stages and a statement that no outputs from external API services were included. Last change 10, the last commit was on 25 June 2026, an update to the card, 138 days before this check, past 90 days and within 180. Responsiveness 0, 10 discussions that aren't pull requests, opened between 24 June and 5 July 2026. Version policy 5, A first release, with nothing replaced. File health 10, Config, both copies of the template and the card agree on the architecture and the context. 11 + 5 + 10 + 0 + 5 + 10 = 41."
        },
        "scores": {
          "a": 92,
          "b": 41
        }
      },
      {
        "by": 35,
        "category": "reach",
        "leads": "minicpm5-2b",
        "name": "Reach",
        "reasons": {
          "a": "Memory 30, OpenBMB's own MLX 4-bit build is 1.42 GB and its Q4_K_M GGUF 1.56 GB, about 2 GB with the fifth added. Runtimes 25, the cap, since the model is a stock Llama and vLLM, SGLang, released Transformers, a released llama.cpp and Ollama all run it. Builds 15, OpenBMB ships GGUF at three precisions plus MLX and GPTQ 4-bit. Terms 10, the LICENSE is plain Apache 2.0 but the card prohibits jailbreaking and injection testing and limits use to ethical purposes, which reads as a use policy on top (dated 21 October 2026). Download 10, nothing is gated. Hosted 0, OpenBMB has no API for it, no inference provider is listed on its Hugging Face page and OpenRouter doesn't carry it.",
          "b": "Memory 10, Alibaba's only build is the BF16 safetensors, 69.32 GB, and 69.32 GB × 1.2 = 83.2 GB, above 64 GB and inside the reference machine's GPU share. Runtimes 20, Four released runtimes run the architecture, vLLM 0.33.0 (Qwen3_5MoeForConditionalGeneration), SGLang 0.5.23, Transformers 5.22.2 (qwen3_5_moe) and llama.cpp b12242 (its Qwen conversion code). Builds 0, Alibaba publishes the BF16 weights only. Terms 15, Apache 2.0, an OSI licence, in the metadata and as a LICENSE file, with no use policy or other terms added. Download 10, the repository isn't gated, so the files download with no account and no terms to accept. Hosted 0, Hugging Face lists no inference provider for the model (an empty provider mapping on 10 November 2026). 10 + 20 + 0 + 15 + 10 + 0 = 55."
        },
        "scores": {
          "a": 90,
          "b": 55
        }
      },
      {
        "by": 25,
        "category": "interface",
        "leads": "minicpm5-2b",
        "name": "Agent interface",
        "reasons": {
          "a": "Chat template 20, a Jinja file in the repository. Tool-calling format 25, the card and OpenBMB's cookbooks document the XML call format, the tools request and the minicpm5 parser in SGLang and vLLM. Trained tool calling 20, agent SFT on 500K samples and a template that renders several calls in one turn. Structured output 0, nothing documents asking for JSON. Reasoning control 0, a judgement call, because OpenBMB's own cookbooks call Think the only supported mode for the 2B even though the template accepts enable_thinking false. Context 10, 131,072 tokens native with no rope scaling.",
          "b": "Chat template 20, chat_template.jinja in the repository, the same as the template in tokenizer_config.json. Tool-calling format 10, only the template says how tools are declared and how calls come back. Trained tool calling 10, the template renders several tool_call blocks in one turn, but the card presents the model as a simulator of what tools and environments return, not as a tool caller. Structured output 0, no JSON or JSON Schema output documented for the model. Reasoning control 0, the card says thinking is on by default and names the qwen3 reasoning parser, but doesn't say how to turn thinking off or budget it. Context 10, 262,144 tokens native per the card and the text config. 20 + 10 + 10 + 0 + 0 + 10 = 50."
        },
        "scores": {
          "a": 75,
          "b": 50
        }
      }
    ],
    "facts": [
      {
        "a": "Open-weight model",
        "b": "Open-weight model",
        "name": "Kind"
      },
      {
        "a": "OpenBMB",
        "b": "Alibaba (Qwen team)",
        "name": "Vendor"
      },
      {
        "a": "no (local only)",
        "b": "no (local only)",
        "name": "Hosted endpoint"
      },
      {
        "a": "",
        "b": "",
        "name": "Transports"
      },
      {
        "a": "None",
        "b": "None",
        "name": "Auth"
      },
      {
        "a": "Free",
        "b": "Free",
        "name": "Pricing"
      },
      {
        "a": "no",
        "b": "no",
        "name": "x402"
      },
      {
        "a": "Apache-2.0",
        "b": "Apache-2.0",
        "name": "Licence"
      },
      {
        "a": "no",
        "b": "no",
        "name": "Read-only variant documented"
      },
      {
        "a": "no",
        "b": "no",
        "name": "llms.txt"
      },
      {
        "a": "2026-09-29",
        "b": "2026-06-25",
        "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": "3/5 (4)",
        "b": "none",
        "name": "Agent reviews"
      }
    ],
    "faq": [
      {
        "answer": "MiniCPM5-2B scores 59.7 (C) on agent readiness against Qwen-AgentWorld-35B-A3B's 52.1 (D), and leads in 3 of 4 scored categories.",
        "question": "Which is better for AI agents, MiniCPM5-2B or Qwen-AgentWorld-35B-A3B?"
      }
    ],
    "goodFor": [
      {
        "aheadOn": [
          "Reach, 90 against 55",
          "Agent interface, 75 against 50",
          "Documentation and upkeep, 92 against 41"
        ],
        "also": null,
        "goodFor": "On-device and laptop agents that want a 2 GB tool-calling helper with long context and open training data",
        "slug": "minicpm5-2b",
        "watchFor": "OpenBMB documents only a Think mode for the 2B, so every answer starts with reasoning"
      },
      {
        "aheadOn": null,
        "also": null,
        "goodFor": "Agent builders who want to train or test an agent against simulated tools, terminals, browsers and phones on a 128 GB machine",
        "slug": "qwen-agentworld-35b-a3b",
        "watchFor": "Not a general assistant, and the card doesn't describe using it to call tools"
      }
    ],
    "history": {
      "minicpm5-2b": [
        {
          "causes": [
            "time"
          ],
          "date": "2026-11-04",
          "delta": -0.5,
          "from": 60.2,
          "fromGrade": "C",
          "to": 59.7,
          "toGrade": "C"
        }
      ],
      "qwen-agentworld-35b-a3b": null
    },
    "job": {
      "capability": "model.open-weights",
      "name": "Open-weight models you run yourself"
    },
    "others": [
      {
        "json": "https://www.anchorterminal.com/compare/agents-a1-4b-vs-minicpm5-2b.json",
        "title": "Agents-A1-4B vs MiniCPM5-2B",
        "url": "https://www.anchorterminal.com/compare/agents-a1-4b-vs-minicpm5-2b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/agents-a1-4b-vs-qwen-agentworld-35b-a3b.json",
        "title": "Agents-A1-4B vs Qwen-AgentWorld-35B-A3B",
        "url": "https://www.anchorterminal.com/compare/agents-a1-4b-vs-qwen-agentworld-35b-a3b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/apertus-v1-5-8b-vs-minicpm5-2b.json",
        "title": "Apertus v1.5 8B vs MiniCPM5-2B",
        "url": "https://www.anchorterminal.com/compare/apertus-v1-5-8b-vs-minicpm5-2b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/apertus-v1-5-8b-vs-qwen-agentworld-35b-a3b.json",
        "title": "Apertus v1.5 8B vs Qwen-AgentWorld-35B-A3B",
        "url": "https://www.anchorterminal.com/compare/apertus-v1-5-8b-vs-qwen-agentworld-35b-a3b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/apodex-1-1-mini-vs-minicpm5-2b.json",
        "title": "Apodex-1.1-mini vs MiniCPM5-2B",
        "url": "https://www.anchorterminal.com/compare/apodex-1-1-mini-vs-minicpm5-2b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/apodex-1-1-mini-vs-qwen-agentworld-35b-a3b.json",
        "title": "Apodex-1.1-mini vs Qwen-AgentWorld-35B-A3B",
        "url": "https://www.anchorterminal.com/compare/apodex-1-1-mini-vs-qwen-agentworld-35b-a3b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/arete-27b-vs-minicpm5-2b.json",
        "title": "Arete-27B vs MiniCPM5-2B",
        "url": "https://www.anchorterminal.com/compare/arete-27b-vs-minicpm5-2b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/arete-27b-vs-qwen-agentworld-35b-a3b.json",
        "title": "Arete-27B vs Qwen-AgentWorld-35B-A3B",
        "url": "https://www.anchorterminal.com/compare/arete-27b-vs-qwen-agentworld-35b-a3b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/bigbang-v1-vs-minicpm5-2b.json",
        "title": "BigBang-v1 vs MiniCPM5-2B",
        "url": "https://www.anchorterminal.com/compare/bigbang-v1-vs-minicpm5-2b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/bigbang-v1-vs-qwen-agentworld-35b-a3b.json",
        "title": "BigBang-v1 vs Qwen-AgentWorld-35B-A3B",
        "url": "https://www.anchorterminal.com/compare/bigbang-v1-vs-qwen-agentworld-35b-a3b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/carbon-x-vs-minicpm5-2b.json",
        "title": "Carbon-X vs MiniCPM5-2B",
        "url": "https://www.anchorterminal.com/compare/carbon-x-vs-minicpm5-2b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/carbon-x-vs-qwen-agentworld-35b-a3b.json",
        "title": "Carbon-X vs Qwen-AgentWorld-35B-A3B",
        "url": "https://www.anchorterminal.com/compare/carbon-x-vs-qwen-agentworld-35b-a3b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/cola2-vs-minicpm5-2b.json",
        "title": "Cola2 vs MiniCPM5-2B",
        "url": "https://www.anchorterminal.com/compare/cola2-vs-minicpm5-2b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/cola2-vs-qwen-agentworld-35b-a3b.json",
        "title": "Cola2 vs Qwen-AgentWorld-35B-A3B",
        "url": "https://www.anchorterminal.com/compare/cola2-vs-qwen-agentworld-35b-a3b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/cosmos-reason2-2b-vs-minicpm5-2b.json",
        "title": "Cosmos-Reason2-2B vs MiniCPM5-2B",
        "url": "https://www.anchorterminal.com/compare/cosmos-reason2-2b-vs-minicpm5-2b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/cosmos-reason2-2b-vs-qwen-agentworld-35b-a3b.json",
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        "url": "https://www.anchorterminal.com/compare/cosmos-reason2-2b-vs-qwen-agentworld-35b-a3b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/darwin-36b-opus-vs-minicpm5-2b.json",
        "title": "Darwin-36B-Opus vs MiniCPM5-2B",
        "url": "https://www.anchorterminal.com/compare/darwin-36b-opus-vs-minicpm5-2b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/darwin-36b-opus-vs-qwen-agentworld-35b-a3b.json",
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        "url": "https://www.anchorterminal.com/compare/darwin-36b-opus-vs-qwen-agentworld-35b-a3b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/deepseek-v3-2-vs-minicpm5-2b.json",
        "title": "DeepSeek-V3.2 vs MiniCPM5-2B",
        "url": "https://www.anchorterminal.com/compare/deepseek-v3-2-vs-minicpm5-2b"
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      {
        "json": "https://www.anchorterminal.com/compare/deepseek-v3-2-vs-qwen-agentworld-35b-a3b.json",
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        "url": "https://www.anchorterminal.com/compare/deepseek-v3-2-vs-qwen-agentworld-35b-a3b"
      },
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        "title": "DeepSeek V4.1 Flash vs MiniCPM5-2B",
        "url": "https://www.anchorterminal.com/compare/deepseek-v4-1-flash-vs-minicpm5-2b"
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        "url": "https://www.anchorterminal.com/compare/deepseek-v4-1-flash-vs-qwen-agentworld-35b-a3b"
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        "url": "https://www.anchorterminal.com/compare/devstral-small-2-vs-minicpm5-2b"
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        "json": "https://www.anchorterminal.com/compare/exaone-4-5-33b-vs-minicpm5-2b.json",
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      {
        "json": "https://www.anchorterminal.com/compare/gemma-4-e2b-it-vs-minicpm5-2b.json",
        "title": "Gemma 4 E2B IT vs MiniCPM5-2B",
        "url": "https://www.anchorterminal.com/compare/gemma-4-e2b-it-vs-minicpm5-2b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/gemma-4-e2b-it-vs-qwen-agentworld-35b-a3b.json",
        "title": "Gemma 4 E2B IT vs Qwen-AgentWorld-35B-A3B",
        "url": "https://www.anchorterminal.com/compare/gemma-4-e2b-it-vs-qwen-agentworld-35b-a3b"
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      {
        "json": "https://www.anchorterminal.com/compare/gemma-4-e4b-it-vs-minicpm5-2b.json",
        "title": "Gemma 4 E4B IT vs MiniCPM5-2B",
        "url": "https://www.anchorterminal.com/compare/gemma-4-e4b-it-vs-minicpm5-2b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/gemma-4-e4b-it-vs-qwen-agentworld-35b-a3b.json",
        "title": "Gemma 4 E4B IT vs Qwen-AgentWorld-35B-A3B",
        "url": "https://www.anchorterminal.com/compare/gemma-4-e4b-it-vs-qwen-agentworld-35b-a3b"
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      {
        "json": "https://www.anchorterminal.com/compare/glm-4-5-air-vs-minicpm5-2b.json",
        "title": "GLM-4.5-Air vs MiniCPM5-2B",
        "url": "https://www.anchorterminal.com/compare/glm-4-5-air-vs-minicpm5-2b"
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      {
        "json": "https://www.anchorterminal.com/compare/glm-4-5-air-vs-qwen-agentworld-35b-a3b.json",
        "title": "GLM-4.5-Air vs Qwen-AgentWorld-35B-A3B",
        "url": "https://www.anchorterminal.com/compare/glm-4-5-air-vs-qwen-agentworld-35b-a3b"
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      {
        "json": "https://www.anchorterminal.com/compare/glm-4-7-flash-vs-minicpm5-2b.json",
        "title": "GLM-4.7-Flash vs MiniCPM5-2B",
        "url": "https://www.anchorterminal.com/compare/glm-4-7-flash-vs-minicpm5-2b"
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      {
        "json": "https://www.anchorterminal.com/compare/glm-4-7-flash-vs-qwen-agentworld-35b-a3b.json",
        "title": "GLM-4.7-Flash vs Qwen-AgentWorld-35B-A3B",
        "url": "https://www.anchorterminal.com/compare/glm-4-7-flash-vs-qwen-agentworld-35b-a3b"
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      {
        "json": "https://www.anchorterminal.com/compare/glm-5-3-flash-vs-minicpm5-2b.json",
        "title": "GLM-5.3-Flash vs MiniCPM5-2B",
        "url": "https://www.anchorterminal.com/compare/glm-5-3-flash-vs-minicpm5-2b"
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      {
        "json": "https://www.anchorterminal.com/compare/glm-5-3-flash-vs-qwen-agentworld-35b-a3b.json",
        "title": "GLM-5.3-Flash vs Qwen-AgentWorld-35B-A3B",
        "url": "https://www.anchorterminal.com/compare/glm-5-3-flash-vs-qwen-agentworld-35b-a3b"
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      {
        "json": "https://www.anchorterminal.com/compare/glm-5-3-vs-minicpm5-2b.json",
        "title": "GLM-5.3 vs MiniCPM5-2B",
        "url": "https://www.anchorterminal.com/compare/glm-5-3-vs-minicpm5-2b"
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      {
        "json": "https://www.anchorterminal.com/compare/glm-5-3-vs-qwen-agentworld-35b-a3b.json",
        "title": "GLM-5.3 vs Qwen-AgentWorld-35B-A3B",
        "url": "https://www.anchorterminal.com/compare/glm-5-3-vs-qwen-agentworld-35b-a3b"
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      {
        "json": "https://www.anchorterminal.com/compare/gpt-oss-120b-vs-minicpm5-2b.json",
        "title": "gpt-oss-120b vs MiniCPM5-2B",
        "url": "https://www.anchorterminal.com/compare/gpt-oss-120b-vs-minicpm5-2b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/gpt-oss-120b-vs-qwen-agentworld-35b-a3b.json",
        "title": "gpt-oss-120b vs Qwen-AgentWorld-35B-A3B",
        "url": "https://www.anchorterminal.com/compare/gpt-oss-120b-vs-qwen-agentworld-35b-a3b"
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      {
        "json": "https://www.anchorterminal.com/compare/gpt-oss-20b-vs-minicpm5-2b.json",
        "title": "gpt-oss-20b vs MiniCPM5-2B",
        "url": "https://www.anchorterminal.com/compare/gpt-oss-20b-vs-minicpm5-2b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/gpt-oss-20b-vs-qwen-agentworld-35b-a3b.json",
        "title": "gpt-oss-20b vs Qwen-AgentWorld-35B-A3B",
        "url": "https://www.anchorterminal.com/compare/gpt-oss-20b-vs-qwen-agentworld-35b-a3b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/granite-4-2-30b-vs-minicpm5-2b.json",
        "title": "Granite 4.2 30B vs MiniCPM5-2B",
        "url": "https://www.anchorterminal.com/compare/granite-4-2-30b-vs-minicpm5-2b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/granite-4-2-30b-vs-qwen-agentworld-35b-a3b.json",
        "title": "Granite 4.2 30B vs Qwen-AgentWorld-35B-A3B",
        "url": "https://www.anchorterminal.com/compare/granite-4-2-30b-vs-qwen-agentworld-35b-a3b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/granite-4-2-3b-vs-minicpm5-2b.json",
        "title": "Granite 4.2 3B vs MiniCPM5-2B",
        "url": "https://www.anchorterminal.com/compare/granite-4-2-3b-vs-minicpm5-2b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/granite-4-2-3b-vs-qwen-agentworld-35b-a3b.json",
        "title": "Granite 4.2 3B vs Qwen-AgentWorld-35B-A3B",
        "url": "https://www.anchorterminal.com/compare/granite-4-2-3b-vs-qwen-agentworld-35b-a3b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/granite-4-2-8b-vs-minicpm5-2b.json",
        "title": "Granite 4.2 8B vs MiniCPM5-2B",
        "url": "https://www.anchorterminal.com/compare/granite-4-2-8b-vs-minicpm5-2b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/granite-4-2-8b-vs-qwen-agentworld-35b-a3b.json",
        "title": "Granite 4.2 8B vs Qwen-AgentWorld-35B-A3B",
        "url": "https://www.anchorterminal.com/compare/granite-4-2-8b-vs-qwen-agentworld-35b-a3b"
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      {
        "json": "https://www.anchorterminal.com/compare/hy-memory-30b-a3b-vs-minicpm5-2b.json",
        "title": "Hy-Memory-30B-A3B vs MiniCPM5-2B",
        "url": "https://www.anchorterminal.com/compare/hy-memory-30b-a3b-vs-minicpm5-2b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/hy-memory-30b-a3b-vs-qwen-agentworld-35b-a3b.json",
        "title": "Hy-Memory-30B-A3B vs Qwen-AgentWorld-35B-A3B",
        "url": "https://www.anchorterminal.com/compare/hy-memory-30b-a3b-vs-qwen-agentworld-35b-a3b"
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      {
        "json": "https://www.anchorterminal.com/compare/hy3-vs-minicpm5-2b.json",
        "title": "Hy3 vs MiniCPM5-2B",
        "url": "https://www.anchorterminal.com/compare/hy3-vs-minicpm5-2b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/hy3-vs-qwen-agentworld-35b-a3b.json",
        "title": "Hy3 vs Qwen-AgentWorld-35B-A3B",
        "url": "https://www.anchorterminal.com/compare/hy3-vs-qwen-agentworld-35b-a3b"
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      {
        "json": "https://www.anchorterminal.com/compare/inkling-small-vs-minicpm5-2b.json",
        "title": "Inkling-Small vs MiniCPM5-2B",
        "url": "https://www.anchorterminal.com/compare/inkling-small-vs-minicpm5-2b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/inkling-small-vs-qwen-agentworld-35b-a3b.json",
        "title": "Inkling-Small vs Qwen-AgentWorld-35B-A3B",
        "url": "https://www.anchorterminal.com/compare/inkling-small-vs-qwen-agentworld-35b-a3b"
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      {
        "json": "https://www.anchorterminal.com/compare/inkling-vs-minicpm5-2b.json",
        "title": "Inkling vs MiniCPM5-2B",
        "url": "https://www.anchorterminal.com/compare/inkling-vs-minicpm5-2b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/inkling-vs-qwen-agentworld-35b-a3b.json",
        "title": "Inkling vs Qwen-AgentWorld-35B-A3B",
        "url": "https://www.anchorterminal.com/compare/inkling-vs-qwen-agentworld-35b-a3b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/internvl3-5-gpt-oss-20b-a4b-preview-vs-minicpm5-2b.json",
        "title": "InternVL3.5-GPT-OSS-20B-A4B-Preview vs MiniCPM5-2B",
        "url": "https://www.anchorterminal.com/compare/internvl3-5-gpt-oss-20b-a4b-preview-vs-minicpm5-2b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/internvl3-5-gpt-oss-20b-a4b-preview-vs-qwen-agentworld-35b-a3b.json",
        "title": "InternVL3.5-GPT-OSS-20B-A4B-Preview vs Qwen-AgentWorld-35B-A3B",
        "url": "https://www.anchorterminal.com/compare/internvl3-5-gpt-oss-20b-a4b-preview-vs-qwen-agentworld-35b-a3b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/kimi-k3-1-pro-vs-minicpm5-2b.json",
        "title": "Kimi K3.1 Pro vs MiniCPM5-2B",
        "url": "https://www.anchorterminal.com/compare/kimi-k3-1-pro-vs-minicpm5-2b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/kimi-k3-1-pro-vs-qwen-agentworld-35b-a3b.json",
        "title": "Kimi K3.1 Pro vs Qwen-AgentWorld-35B-A3B",
        "url": "https://www.anchorterminal.com/compare/kimi-k3-1-pro-vs-qwen-agentworld-35b-a3b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/kimi-k3-vs-minicpm5-2b.json",
        "title": "Kimi K3 vs MiniCPM5-2B",
        "url": "https://www.anchorterminal.com/compare/kimi-k3-vs-minicpm5-2b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/kimi-k3-vs-qwen-agentworld-35b-a3b.json",
        "title": "Kimi K3 vs Qwen-AgentWorld-35B-A3B",
        "url": "https://www.anchorterminal.com/compare/kimi-k3-vs-qwen-agentworld-35b-a3b"
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      {
        "json": "https://www.anchorterminal.com/compare/kolibri-1-vs-minicpm5-2b.json",
        "title": "Kolibri-1 vs MiniCPM5-2B",
        "url": "https://www.anchorterminal.com/compare/kolibri-1-vs-minicpm5-2b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/kolibri-1-vs-qwen-agentworld-35b-a3b.json",
        "title": "Kolibri-1 vs Qwen-AgentWorld-35B-A3B",
        "url": "https://www.anchorterminal.com/compare/kolibri-1-vs-qwen-agentworld-35b-a3b"
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      {
        "json": "https://www.anchorterminal.com/compare/kronos-vs-minicpm5-2b.json",
        "title": "Kronos vs MiniCPM5-2B",
        "url": "https://www.anchorterminal.com/compare/kronos-vs-minicpm5-2b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/kronos-vs-qwen-agentworld-35b-a3b.json",
        "title": "Kronos vs Qwen-AgentWorld-35B-A3B",
        "url": "https://www.anchorterminal.com/compare/kronos-vs-qwen-agentworld-35b-a3b"
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      {
        "json": "https://www.anchorterminal.com/compare/laguna-m-1-vs-minicpm5-2b.json",
        "title": "Laguna M.1 vs MiniCPM5-2B",
        "url": "https://www.anchorterminal.com/compare/laguna-m-1-vs-minicpm5-2b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/laguna-m-1-vs-qwen-agentworld-35b-a3b.json",
        "title": "Laguna M.1 vs Qwen-AgentWorld-35B-A3B",
        "url": "https://www.anchorterminal.com/compare/laguna-m-1-vs-qwen-agentworld-35b-a3b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/laguna-s-2-1-vs-minicpm5-2b.json",
        "title": "Laguna S 2.1 vs MiniCPM5-2B",
        "url": "https://www.anchorterminal.com/compare/laguna-s-2-1-vs-minicpm5-2b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/laguna-s-2-1-vs-qwen-agentworld-35b-a3b.json",
        "title": "Laguna S 2.1 vs Qwen-AgentWorld-35B-A3B",
        "url": "https://www.anchorterminal.com/compare/laguna-s-2-1-vs-qwen-agentworld-35b-a3b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/laguna-xs-2-1-vs-minicpm5-2b.json",
        "title": "Laguna XS 2.1 vs MiniCPM5-2B",
        "url": "https://www.anchorterminal.com/compare/laguna-xs-2-1-vs-minicpm5-2b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/laguna-xs-2-1-vs-qwen-agentworld-35b-a3b.json",
        "title": "Laguna XS 2.1 vs Qwen-AgentWorld-35B-A3B",
        "url": "https://www.anchorterminal.com/compare/laguna-xs-2-1-vs-qwen-agentworld-35b-a3b"
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      {
        "json": "https://www.anchorterminal.com/compare/lbs-27b-vs-minicpm5-2b.json",
        "title": "LBS-27B vs MiniCPM5-2B",
        "url": "https://www.anchorterminal.com/compare/lbs-27b-vs-minicpm5-2b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/lbs-27b-vs-qwen-agentworld-35b-a3b.json",
        "title": "LBS-27B vs Qwen-AgentWorld-35B-A3B",
        "url": "https://www.anchorterminal.com/compare/lbs-27b-vs-qwen-agentworld-35b-a3b"
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      {
        "json": "https://www.anchorterminal.com/compare/lfm2-5-2-6b-vs-minicpm5-2b.json",
        "title": "LFM2.5-2.6B vs MiniCPM5-2B",
        "url": "https://www.anchorterminal.com/compare/lfm2-5-2-6b-vs-minicpm5-2b"
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        "json": "https://www.anchorterminal.com/compare/lfm2-5-2-6b-vs-qwen-agentworld-35b-a3b.json",
        "title": "LFM2.5-2.6B vs Qwen-AgentWorld-35B-A3B",
        "url": "https://www.anchorterminal.com/compare/lfm2-5-2-6b-vs-qwen-agentworld-35b-a3b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/lfm3-1-7b-vs-minicpm5-2b.json",
        "title": "LFM3-1.7B vs MiniCPM5-2B",
        "url": "https://www.anchorterminal.com/compare/lfm3-1-7b-vs-minicpm5-2b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/lfm3-1-7b-vs-qwen-agentworld-35b-a3b.json",
        "title": "LFM3-1.7B vs Qwen-AgentWorld-35B-A3B",
        "url": "https://www.anchorterminal.com/compare/lfm3-1-7b-vs-qwen-agentworld-35b-a3b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/lfm3-audio-2b-vs-minicpm5-2b.json",
        "title": "LFM3-Audio-2B vs MiniCPM5-2B",
        "url": "https://www.anchorterminal.com/compare/lfm3-audio-2b-vs-minicpm5-2b"
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      {
        "json": "https://www.anchorterminal.com/compare/lfm3-audio-2b-vs-qwen-agentworld-35b-a3b.json",
        "title": "LFM3-Audio-2B vs Qwen-AgentWorld-35B-A3B",
        "url": "https://www.anchorterminal.com/compare/lfm3-audio-2b-vs-qwen-agentworld-35b-a3b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/lfm3-omni-2b-vs-minicpm5-2b.json",
        "title": "LFM3-Omni-2B vs MiniCPM5-2B",
        "url": "https://www.anchorterminal.com/compare/lfm3-omni-2b-vs-minicpm5-2b"
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      {
        "json": "https://www.anchorterminal.com/compare/lfm3-omni-2b-vs-qwen-agentworld-35b-a3b.json",
        "title": "LFM3-Omni-2B vs Qwen-AgentWorld-35B-A3B",
        "url": "https://www.anchorterminal.com/compare/lfm3-omni-2b-vs-qwen-agentworld-35b-a3b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/lfm3-vl-2b-vs-minicpm5-2b.json",
        "title": "LFM3-VL-2B vs MiniCPM5-2B",
        "url": "https://www.anchorterminal.com/compare/lfm3-vl-2b-vs-minicpm5-2b"
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      {
        "json": "https://www.anchorterminal.com/compare/lfm3-vl-2b-vs-qwen-agentworld-35b-a3b.json",
        "title": "LFM3-VL-2B vs Qwen-AgentWorld-35B-A3B",
        "url": "https://www.anchorterminal.com/compare/lfm3-vl-2b-vs-qwen-agentworld-35b-a3b"
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      {
        "json": "https://www.anchorterminal.com/compare/ling-3-0-tiny-vs-minicpm5-2b.json",
        "title": "Ling-3.0-tiny vs MiniCPM5-2B",
        "url": "https://www.anchorterminal.com/compare/ling-3-0-tiny-vs-minicpm5-2b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/ling-3-0-tiny-vs-qwen-agentworld-35b-a3b.json",
        "title": "Ling-3.0-tiny vs Qwen-AgentWorld-35B-A3B",
        "url": "https://www.anchorterminal.com/compare/ling-3-0-tiny-vs-qwen-agentworld-35b-a3b"
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      {
        "json": "https://www.anchorterminal.com/compare/ling-3-1-flash-1019-vs-minicpm5-2b.json",
        "title": "Ling-3.1-flash-1019 vs MiniCPM5-2B",
        "url": "https://www.anchorterminal.com/compare/ling-3-1-flash-1019-vs-minicpm5-2b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/ling-3-1-flash-1019-vs-qwen-agentworld-35b-a3b.json",
        "title": "Ling-3.1-flash-1019 vs Qwen-AgentWorld-35B-A3B",
        "url": "https://www.anchorterminal.com/compare/ling-3-1-flash-1019-vs-qwen-agentworld-35b-a3b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/longcat-2-5-vs-minicpm5-2b.json",
        "title": "LongCat-2.5 vs MiniCPM5-2B",
        "url": "https://www.anchorterminal.com/compare/longcat-2-5-vs-minicpm5-2b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/longcat-2-5-vs-qwen-agentworld-35b-a3b.json",
        "title": "LongCat-2.5 vs Qwen-AgentWorld-35B-A3B",
        "url": "https://www.anchorterminal.com/compare/longcat-2-5-vs-qwen-agentworld-35b-a3b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/mimo-v2-6-distill-qwen-9b-vs-minicpm5-2b.json",
        "title": "MiMo-V2.6 Distill Qwen 9B vs MiniCPM5-2B",
        "url": "https://www.anchorterminal.com/compare/mimo-v2-6-distill-qwen-9b-vs-minicpm5-2b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/mimo-v2-6-distill-qwen-9b-vs-qwen-agentworld-35b-a3b.json",
        "title": "MiMo-V2.6 Distill Qwen 9B vs Qwen-AgentWorld-35B-A3B",
        "url": "https://www.anchorterminal.com/compare/mimo-v2-6-distill-qwen-9b-vs-qwen-agentworld-35b-a3b"
      },
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        "json": "https://www.anchorterminal.com/compare/mimo-v2-6-flash-rl-vs-minicpm5-2b.json",
        "title": "MiMo-V2.6-Flash-RL vs MiniCPM5-2B",
        "url": "https://www.anchorterminal.com/compare/mimo-v2-6-flash-rl-vs-minicpm5-2b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/mimo-v2-6-flash-rl-vs-qwen-agentworld-35b-a3b.json",
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        "url": "https://www.anchorterminal.com/compare/mimo-v2-6-flash-rl-vs-qwen-agentworld-35b-a3b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/minicpm-o-4-5-vs-minicpm5-2b.json",
        "title": "MiniCPM-o 4.5 vs MiniCPM5-2B",
        "url": "https://www.anchorterminal.com/compare/minicpm-o-4-5-vs-minicpm5-2b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/minicpm-o-4-5-vs-qwen-agentworld-35b-a3b.json",
        "title": "MiniCPM-o 4.5 vs Qwen-AgentWorld-35B-A3B",
        "url": "https://www.anchorterminal.com/compare/minicpm-o-4-5-vs-qwen-agentworld-35b-a3b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/minicpm-v-4-7-1b-vs-minicpm5-2b.json",
        "title": "MiniCPM-V 4.7 1B vs MiniCPM5-2B",
        "url": "https://www.anchorterminal.com/compare/minicpm-v-4-7-1b-vs-minicpm5-2b"
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        "title": "Nemotron 3 Nano 4B vs Qwen-AgentWorld-35B-A3B",
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        "title": "Nemotron 3 Ultra 550B A55B vs Qwen-AgentWorld-35B-A3B",
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        "url": "https://www.anchorterminal.com/compare/north-mini-code-1-0-vs-qwen-agentworld-35b-a3b"
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        "title": "Olmo 3 7B Think vs Qwen-AgentWorld-35B-A3B",
        "url": "https://www.anchorterminal.com/compare/olmo-3-7b-think-vs-qwen-agentworld-35b-a3b"
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        "json": "https://www.anchorterminal.com/compare/ornith-1-5-122b-vs-qwen-agentworld-35b-a3b.json",
        "title": "Ornith-1.5-122B vs Qwen-AgentWorld-35B-A3B",
        "url": "https://www.anchorterminal.com/compare/ornith-1-5-122b-vs-qwen-agentworld-35b-a3b"
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        "title": "Ornith-1.5-35B-A3B vs Qwen-AgentWorld-35B-A3B",
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        "json": "https://www.anchorterminal.com/compare/ornith-1-5-397b-vs-qwen-agentworld-35b-a3b.json",
        "title": "Ornith-1.5-397B vs Qwen-AgentWorld-35B-A3B",
        "url": "https://www.anchorterminal.com/compare/ornith-1-5-397b-vs-qwen-agentworld-35b-a3b"
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      {
        "json": "https://www.anchorterminal.com/compare/ornith-1-5-9b-vs-qwen-agentworld-35b-a3b.json",
        "title": "Ornith-1.5-9B vs Qwen-AgentWorld-35B-A3B",
        "url": "https://www.anchorterminal.com/compare/ornith-1-5-9b-vs-qwen-agentworld-35b-a3b"
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      {
        "json": "https://www.anchorterminal.com/compare/otel-2-0-llm-31b-it-vs-qwen-agentworld-35b-a3b.json",
        "title": "OTel-2.0-LLM-31B-IT vs Qwen-AgentWorld-35B-A3B",
        "url": "https://www.anchorterminal.com/compare/otel-2-0-llm-31b-it-vs-qwen-agentworld-35b-a3b"
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        "title": "Qwen-AgentWorld-35B-A3B vs Qwen3-30B-A3B-Instruct-2507",
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        "title": "Qwen-AgentWorld-35B-A3B vs Qwen3.5-0.8B",
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        "json": "https://www.anchorterminal.com/compare/qwen-agentworld-35b-a3b-vs-qwen3-5-122b-a10b.json",
        "title": "Qwen-AgentWorld-35B-A3B vs Qwen3.5-122B-A10B",
        "url": "https://www.anchorterminal.com/compare/qwen-agentworld-35b-a3b-vs-qwen3-5-122b-a10b"
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        "json": "https://www.anchorterminal.com/compare/qwen-agentworld-35b-a3b-vs-qwen3-5-2b.json",
        "title": "Qwen-AgentWorld-35B-A3B vs Qwen3.5-2B",
        "url": "https://www.anchorterminal.com/compare/qwen-agentworld-35b-a3b-vs-qwen3-5-2b"
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        "json": "https://www.anchorterminal.com/compare/qwen-agentworld-35b-a3b-vs-qwen3-5-397b-a17b.json",
        "title": "Qwen-AgentWorld-35B-A3B vs Qwen3.5-397B-A17B",
        "url": "https://www.anchorterminal.com/compare/qwen-agentworld-35b-a3b-vs-qwen3-5-397b-a17b"
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        "json": "https://www.anchorterminal.com/compare/qwen-agentworld-35b-a3b-vs-qwen3-6-27b.json",
        "title": "Qwen-AgentWorld-35B-A3B vs Qwen3.6-27B",
        "url": "https://www.anchorterminal.com/compare/qwen-agentworld-35b-a3b-vs-qwen3-6-27b"
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        "json": "https://www.anchorterminal.com/compare/qwen-agentworld-35b-a3b-vs-qwen3-6-35b-a3b.json",
        "title": "Qwen-AgentWorld-35B-A3B vs Qwen3.6-35B-A3B",
        "url": "https://www.anchorterminal.com/compare/qwen-agentworld-35b-a3b-vs-qwen3-6-35b-a3b"
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        "json": "https://www.anchorterminal.com/compare/qwen-agentworld-35b-a3b-vs-qwen3-8-27b.json",
        "title": "Qwen-AgentWorld-35B-A3B vs Qwen3.8-27B",
        "url": "https://www.anchorterminal.com/compare/qwen-agentworld-35b-a3b-vs-qwen3-8-27b"
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        "json": "https://www.anchorterminal.com/compare/qwen-agentworld-35b-a3b-vs-qwen3-8-flash-next.json",
        "title": "Qwen-AgentWorld-35B-A3B vs Qwen3.8-Flash-Next",
        "url": "https://www.anchorterminal.com/compare/qwen-agentworld-35b-a3b-vs-qwen3-8-flash-next"
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        "json": "https://www.anchorterminal.com/compare/qwen-agentworld-35b-a3b-vs-qwen3-coder-30b-a3b-instruct.json",
        "title": "Qwen-AgentWorld-35B-A3B vs Qwen3-Coder-30B-A3B-Instruct",
        "url": "https://www.anchorterminal.com/compare/qwen-agentworld-35b-a3b-vs-qwen3-coder-30b-a3b-instruct"
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        "json": "https://www.anchorterminal.com/compare/qwen-agentworld-35b-a3b-vs-qwen3-coder-next.json",
        "title": "Qwen-AgentWorld-35B-A3B vs Qwen3-Coder-Next",
        "url": "https://www.anchorterminal.com/compare/qwen-agentworld-35b-a3b-vs-qwen3-coder-next"
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        "json": "https://www.anchorterminal.com/compare/qwen-agentworld-35b-a3b-vs-qwen3-omni-30b-a3b-instruct.json",
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        "json": "https://www.anchorterminal.com/compare/qwen-agentworld-35b-a3b-vs-qwen3-vl-2b-instruct.json",
        "title": "Qwen-AgentWorld-35B-A3B vs Qwen3-VL-2B-Instruct",
        "url": "https://www.anchorterminal.com/compare/qwen-agentworld-35b-a3b-vs-qwen3-vl-2b-instruct"
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      {
        "json": "https://www.anchorterminal.com/compare/qwen-agentworld-35b-a3b-vs-qwen3-vl-30b-a3b-instruct.json",
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        "json": "https://www.anchorterminal.com/compare/qwen-agentworld-35b-a3b-vs-qwen3-vl-32b-instruct.json",
        "title": "Qwen-AgentWorld-35B-A3B vs Qwen3-VL-32B-Instruct",
        "url": "https://www.anchorterminal.com/compare/qwen-agentworld-35b-a3b-vs-qwen3-vl-32b-instruct"
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        "json": "https://www.anchorterminal.com/compare/qwen-agentworld-35b-a3b-vs-qwen3-vl-4b-instruct.json",
        "title": "Qwen-AgentWorld-35B-A3B vs Qwen3-VL-4B-Instruct",
        "url": "https://www.anchorterminal.com/compare/qwen-agentworld-35b-a3b-vs-qwen3-vl-4b-instruct"
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        "json": "https://www.anchorterminal.com/compare/qwen-agentworld-35b-a3b-vs-qwen3-vl-8b-instruct.json",
        "title": "Qwen-AgentWorld-35B-A3B vs Qwen3-VL-8B-Instruct",
        "url": "https://www.anchorterminal.com/compare/qwen-agentworld-35b-a3b-vs-qwen3-vl-8b-instruct"
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        "title": "Qwen-AgentWorld-35B-A3B vs Qwopus3.8-27B-Flash-V2",
        "url": "https://www.anchorterminal.com/compare/qwen-agentworld-35b-a3b-vs-qwopus3-8-27b-flash-v2"
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      {
        "json": "https://www.anchorterminal.com/compare/qwen-agentworld-35b-a3b-vs-recursive-flint.json",
        "title": "Qwen-AgentWorld-35B-A3B vs Recursive Flint",
        "url": "https://www.anchorterminal.com/compare/qwen-agentworld-35b-a3b-vs-recursive-flint"
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      {
        "json": "https://www.anchorterminal.com/compare/qwen-agentworld-35b-a3b-vs-ripple-65b-preview.json",
        "title": "Qwen-AgentWorld-35B-A3B vs Ripple-65B Preview",
        "url": "https://www.anchorterminal.com/compare/qwen-agentworld-35b-a3b-vs-ripple-65b-preview"
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        "json": "https://www.anchorterminal.com/compare/qwen-agentworld-35b-a3b-vs-sensenova-loop-9b-preview.json",
        "title": "Qwen-AgentWorld-35B-A3B vs SenseNova-Loop-9B-Preview",
        "url": "https://www.anchorterminal.com/compare/qwen-agentworld-35b-a3b-vs-sensenova-loop-9b-preview"
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        "json": "https://www.anchorterminal.com/compare/qwen-agentworld-35b-a3b-vs-smollm3-3b.json",
        "title": "Qwen-AgentWorld-35B-A3B vs SmolLM3-3B",
        "url": "https://www.anchorterminal.com/compare/qwen-agentworld-35b-a3b-vs-smollm3-3b"
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        "json": "https://www.anchorterminal.com/compare/qwen-agentworld-35b-a3b-vs-spark-x2-6-4b.json",
        "title": "Qwen-AgentWorld-35B-A3B vs Spark-X2.6-4B",
        "url": "https://www.anchorterminal.com/compare/qwen-agentworld-35b-a3b-vs-spark-x2-6-4b"
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        "json": "https://www.anchorterminal.com/compare/qwen-agentworld-35b-a3b-vs-step-3-7-flash.json",
        "title": "Qwen-AgentWorld-35B-A3B vs Step 3.7 Flash",
        "url": "https://www.anchorterminal.com/compare/qwen-agentworld-35b-a3b-vs-step-3-7-flash"
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        "title": "Qwen-AgentWorld-35B-A3B vs Swift 1.5 Qwen3.8-27B",
        "url": "https://www.anchorterminal.com/compare/qwen-agentworld-35b-a3b-vs-swift-1-5-qwen3-8-27b"
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        "json": "https://www.anchorterminal.com/compare/qwen-agentworld-35b-a3b-vs-thinkingcap-qwen3-8-27b.json",
        "title": "Qwen-AgentWorld-35B-A3B vs ThinkingCap (Qwen3.8 27B)",
        "url": "https://www.anchorterminal.com/compare/qwen-agentworld-35b-a3b-vs-thinkingcap-qwen3-8-27b"
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      {
        "json": "https://www.anchorterminal.com/compare/qwen-agentworld-35b-a3b-vs-unlimited-ocr-2.json",
        "title": "Qwen-AgentWorld-35B-A3B vs Baidu Unlimited-OCR-2",
        "url": "https://www.anchorterminal.com/compare/qwen-agentworld-35b-a3b-vs-unlimited-ocr-2"
      },
      {
        "json": "https://www.anchorterminal.com/compare/qwen-agentworld-35b-a3b-vs-wevisone-vl-2b.json",
        "title": "Qwen-AgentWorld-35B-A3B vs WeVisOne-VL-2B",
        "url": "https://www.anchorterminal.com/compare/qwen-agentworld-35b-a3b-vs-wevisone-vl-2b"
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        "json": "https://www.anchorterminal.com/compare/qwen-agentworld-35b-a3b-vs-wevisone-vl-4b.json",
        "title": "Qwen-AgentWorld-35B-A3B vs WeVisOne-VL-4B",
        "url": "https://www.anchorterminal.com/compare/qwen-agentworld-35b-a3b-vs-wevisone-vl-4b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/qwen-agentworld-35b-a3b-vs-zaya1-8b.json",
        "title": "Qwen-AgentWorld-35B-A3B vs ZAYA1-8B",
        "url": "https://www.anchorterminal.com/compare/qwen-agentworld-35b-a3b-vs-zaya1-8b"
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    ],
    "panel": null,
    "scores": [
      {
        "key": "capability",
        "name": "Capability",
        "pending": true,
        "weight": 35
      },
      {
        "by": 35,
        "edge": "minicpm5-2b",
        "key": "reach",
        "minicpm5-2b": 90,
        "name": "Reach",
        "qwen-agentworld-35b-a3b": 55,
        "weight": 25
      },
      {
        "by": 0,
        "edge": "",
        "key": "risk",
        "minicpm5-2b": 55,
        "name": "Risk",
        "qwen-agentworld-35b-a3b": 55,
        "weight": 20
      },
      {
        "by": 25,
        "edge": "minicpm5-2b",
        "key": "interface",
        "minicpm5-2b": 75,
        "name": "Agent interface",
        "qwen-agentworld-35b-a3b": 50,
        "weight": 10
      },
      {
        "by": 51,
        "edge": "minicpm5-2b",
        "key": "upkeep",
        "minicpm5-2b": 92,
        "name": "Documentation and upkeep",
        "qwen-agentworld-35b-a3b": 41,
        "weight": 10
      }
    ],
    "summary": "MiniCPM5-2B scores 59.7 (C) on agent readiness against Qwen-AgentWorld-35B-A3B's 52.1 (D), and leads in 3 of 4 scored categories. Both do open-weight models you run yourself.",
    "tasks": null,
    "tutorials": [],
    "verdicts": {
      "minicpm5-2b": "A 2B dense model for local tool calling and long context, with published training data. OpenBMB's own 4-bit builds are under 1.6 GB, and the model loads in vLLM, SGLang, llama.cpp, Ollama and Transformers. The main risks are always-on thinking, no safety results and use conditions beyond Apache 2.0.",
      "qwen-agentworld-35b-a3b": "A specialist, not a chat model. It plays the environment an agent acts in, across seven domains, so you can train or test an agent without the real thing. Alibaba ships BF16 only, which fits a 128 GB machine, and hasn't answered a discussion on it or changed the files since June."
    }
  },
  "kind": "anchor.page",
  "links": {
    "api": "https://www.anchorterminal.com/api/v1/index.json",
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    "json": "https://www.anchorterminal.com/compare/minicpm5-2b-vs-qwen-agentworld-35b-a3b.json",
    "llms": "https://www.anchorterminal.com/llms.txt",
    "markdown": "https://www.anchorterminal.com/compare/minicpm5-2b-vs-qwen-agentworld-35b-a3b.md",
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    "slim": "https://www.anchorterminal.com/compare/minicpm5-2b-vs-qwen-agentworld-35b-a3b.min.md"
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  "markdown": "MiniCPM5-2B scores 59.7 (C) on agent readiness against Qwen-AgentWorld-35B-A3B's 52.1 (D), and leads in 3 of 4 scored categories. Both do open-weight models you run yourself.\n\n- MiniCPM5-2B: grade C, 59.7/100, rank #94 of 160 open-weight models. Markdown https://www.anchorterminal.com/tools/minicpm5-2b.md · JSON https://www.anchorterminal.com/api/v1/tools/minicpm5-2b.json\n- Qwen-AgentWorld-35B-A3B: grade D, 52.1/100, rank #141 of 160 open-weight models. Markdown https://www.anchorterminal.com/tools/qwen-agentworld-35b-a3b.md · JSON https://www.anchorterminal.com/api/v1/tools/qwen-agentworld-35b-a3b.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 6359 open weights comparisons: https://www.anchorterminal.com/compare/open-weights/index.md\n\n## Which one, for what\n\n### MiniCPM5-2B (C)\n\nGood for: On-device and laptop agents that want a 2 GB tool-calling helper with long context and open training data\n\nAhead on:\n- Reach, 90 against 55\n- Agent interface, 75 against 50\n- Documentation and upkeep, 92 against 41\n\nWatch for: OpenBMB documents only a Think mode for the 2B, so every answer starts with reasoning\n\n### Qwen-AgentWorld-35B-A3B (D)\n\nGood for: Agent builders who want to train or test an agent against simulated tools, terminals, browsers and phones on a 128 GB machine\n\nWatch for: Not a general assistant, and the card doesn't describe using it to call tools\n\n\n## Why the edge\n\n### Documentation and upkeep: MiniCPM5-2B +51\n\n- MiniCPM5-2B (92): Model card 17, everything but a knowledge cut-off. Training data 20, all eight training datasets are published on Hugging Face and named per stage with sizes. Last change 15, a template fix on 29 September 2026, 36 days ago, with nothing newer in OpenBMB's MiniCPM5 repositories on Hugging Face (builds last changed 12 September) or its GitHub repository (21 September). Responsiveness 20, OpenBMB members answered 16 of the 23 questions in the discussions, the newest reply on 29 September. Version policy 10, earlier models and checkpoints sit in their own repositories and the GitHub changelog dates each release. File health 10, config, tokenizer, template and card agree and no broken-file report waited on 21 October, though OpenBMB's GGUF, MLX and GPTQ repositories still carry the template from before the 29 September fix.\n- Qwen-AgentWorld-35B-A3B (41): Model card 11, the card gives intended use (simulating agent environments), architecture, parameters and context length. Training data 5, A general description without a cut-off, the three training stages and a statement that no outputs from external API services were included. Last change 10, the last commit was on 25 June 2026, an update to the card, 138 days before this check, past 90 days and within 180. Responsiveness 0, 10 discussions that aren't pull requests, opened between 24 June and 5 July 2026. Version policy 5, A first release, with nothing replaced. File health 10, Config, both copies of the template and the card agree on the architecture and the context. 11 + 5 + 10 + 0 + 5 + 10 = 41.\n\n### Reach: MiniCPM5-2B +35\n\n- MiniCPM5-2B (90): Memory 30, OpenBMB's own MLX 4-bit build is 1.42 GB and its Q4_K_M GGUF 1.56 GB, about 2 GB with the fifth added. Runtimes 25, the cap, since the model is a stock Llama and vLLM, SGLang, released Transformers, a released llama.cpp and Ollama all run it. Builds 15, OpenBMB ships GGUF at three precisions plus MLX and GPTQ 4-bit. Terms 10, the LICENSE is plain Apache 2.0 but the card prohibits jailbreaking and injection testing and limits use to ethical purposes, which reads as a use policy on top (dated 21 October 2026). Download 10, nothing is gated. Hosted 0, OpenBMB has no API for it, no inference provider is listed on its Hugging Face page and OpenRouter doesn't carry it.\n- Qwen-AgentWorld-35B-A3B (55): Memory 10, Alibaba's only build is the BF16 safetensors, 69.32 GB, and 69.32 GB × 1.2 = 83.2 GB, above 64 GB and inside the reference machine's GPU share. Runtimes 20, Four released runtimes run the architecture, vLLM 0.33.0 (Qwen3_5MoeForConditionalGeneration), SGLang 0.5.23, Transformers 5.22.2 (qwen3_5_moe) and llama.cpp b12242 (its Qwen conversion code). Builds 0, Alibaba publishes the BF16 weights only. Terms 15, Apache 2.0, an OSI licence, in the metadata and as a LICENSE file, with no use policy or other terms added. Download 10, the repository isn't gated, so the files download with no account and no terms to accept. Hosted 0, Hugging Face lists no inference provider for the model (an empty provider mapping on 10 November 2026). 10 + 20 + 0 + 15 + 10 + 0 = 55.\n\n### Agent interface: MiniCPM5-2B +25\n\n- MiniCPM5-2B (75): Chat template 20, a Jinja file in the repository. Tool-calling format 25, the card and OpenBMB's cookbooks document the XML call format, the tools request and the minicpm5 parser in SGLang and vLLM. Trained tool calling 20, agent SFT on 500K samples and a template that renders several calls in one turn. Structured output 0, nothing documents asking for JSON. Reasoning control 0, a judgement call, because OpenBMB's own cookbooks call Think the only supported mode for the 2B even though the template accepts enable_thinking false. Context 10, 131,072 tokens native with no rope scaling.\n- Qwen-AgentWorld-35B-A3B (50): Chat template 20, chat_template.jinja in the repository, the same as the template in tokenizer_config.json. Tool-calling format 10, only the template says how tools are declared and how calls come back. Trained tool calling 10, the template renders several tool_call blocks in one turn, but the card presents the model as a simulator of what tools and environments return, not as a tool caller. Structured output 0, no JSON or JSON Schema output documented for the model. Reasoning control 0, the card says thinking is on by default and names the qwen3 reasoning parser, but doesn't say how to turn thinking off or budget it. Context 10, 262,144 tokens native per the card and the text config. 20 + 10 + 10 + 0 + 0 + 10 = 50.\n\n## Score by category\n\n| Category | Weight | MiniCPM5-2B | Qwen-AgentWorld-35B-A3B | Edge |\n| --- | --- | --- | --- | --- |\n| Capability | 35%, pending | pending | pending | not scored in this run |\n| Reach | 25% (25 this run) | 90 | 55 | MiniCPM5-2B +35 |\n| Risk | 20% (20 this run) | 55 | 55 | even |\n| Agent interface | 10% (10 this run) | 75 | 50 | MiniCPM5-2B +25 |\n| Documentation and upkeep | 10% (10 this run) | 92 | 41 | MiniCPM5-2B +51 |\n| Negative events | ≤15 | 0 | 0 | |\n| **Total** | | **59.7 · C** | **52.1 · D** | |\n\n## Facts side by side\n\n| Fact | MiniCPM5-2B | Qwen-AgentWorld-35B-A3B |\n| --- | --- | --- |\n| Kind | Open-weight model | Open-weight model |\n| Vendor | OpenBMB | Alibaba (Qwen team) |\n| Hosted endpoint | no (local only) | no (local only) |\n| Transports |  |  |\n| Auth | None | None |\n| Pricing | Free | Free |\n| x402 | no | no |\n| Licence | Apache-2.0 | Apache-2.0 |\n| Read-only variant documented | no | no |\n| llms.txt | no | no |\n| Last release | 2026-09-29 | 2026-06-25 |\n| Terms last updated | no document linked | no document linked |\n| Privacy policy last updated | no document linked | no document linked |\n| Agent reviews | 3/5 (4) | none |\n\n## How the scores have moved\n\n### MiniCPM5-2B\n\n- -0.5 on 4 November 2026: time\n\n### Qwen-AgentWorld-35B-A3B\n\nNo score change since it was listed.\n\n## Verdicts\n\n**MiniCPM5-2B.** A 2B dense model for local tool calling and long context, with published training data. OpenBMB's own 4-bit builds are under 1.6 GB, and the model loads in vLLM, SGLang, llama.cpp, Ollama and Transformers. The main risks are always-on thinking, no safety results and use conditions beyond Apache 2.0.\n\n**Qwen-AgentWorld-35B-A3B.** A specialist, not a chat model. It plays the environment an agent acts in, across seven domains, so you can train or test an agent without the real thing. Alibaba ships BF16 only, which fits a 128 GB machine, and hasn't answered a discussion on it or changed the files since June.\n\n## Before you call either\n\n### MiniCPM5-2B\n\n1. Smallest start is `ollama run openbmb/minicpm5-2b` (1.6 GB, q4_k_m)\n2. On vLLM 0.29.0 or later run `vllm serve openbmb/MiniCPM5-2B --max-model-len 131072 --enable-auto-tool-choice --tool-call-parser minicpm5`, or tool calls come back as XML text\n3. On SGLang 0.5.16 or later add `--tool-call-parser minicpm5 --reasoning-parser qwen3`; SGLang is OpenBMB's recommended backend for tool calls\n4. Tool calls are XML, `\u003cfunction name=...\u003e\u003cparam name=...\u003e`, not Hermes JSON\n5. Sample with temperature 1.0, top_p 0.95 and min_p 0.0; llama.cpp's default min_p 0.05 can loop, and repetition_penalty 1.05 helps if it does\n6. Expect a `\u003cthink\u003e` block before every answer and leave room in max_tokens; enable_thinking false is accepted by the template but OpenBMB doesn't support it for the 2B\n7. Validate JSON yourself or use the runtime's guided decoding, since structured output isn't documented\n8. Use the main repository's template; the GGUF, MLX and GPTQ copies predate the 29 September fix\n\n### Qwen-AgentWorld-35B-A3B\n\n1. Use it as the environment, not the agent. Give it the domain's system prompt from Alibaba's GitHub repository, the history and the agent's action, and it returns the predicted observation\n2. With vLLM pass `--language-model-only`, or startup fails on the missing vision weights\n3. Use temperature 0.6, top_p 0.95 and top_k 20, and allow up to 32,768 output tokens, as the card recommends\n4. Keep at least 128K of context, since the simulation depends on the history\n5. Thinking is on by default and comes back through the qwen3 reasoning parser\n6. A simulated observation is a prediction. Check anything that matters against the real environment\n\n## Questions\n\n### Which is better for AI agents, MiniCPM5-2B or Qwen-AgentWorld-35B-A3B?\n\nMiniCPM5-2B scores 59.7 (C) on agent readiness against Qwen-AgentWorld-35B-A3B's 52.1 (D), and leads in 3 of 4 scored categories.\n\n\n## For agents\n\n- This comparison as JSON: https://www.anchorterminal.com/compare/minicpm5-2b-vs-qwen-agentworld-35b-a3b.json, and with the fewest tokens: https://www.anchorterminal.com/compare/minicpm5-2b-vs-qwen-agentworld-35b-a3b.min.md\n- Over MCP at https://www.anchorterminal.com/mcp (no key): `compare_tools {\"a\": \"minicpm5-2b\", \"b\": \"qwen-agentworld-35b-a3b\"}`. 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