{
  "data": {
    "a": {
      "slug": "lbs-27b",
      "name": "LBS-27B",
      "vendor": "inclusionAI (Ant Group)",
      "vendorUrl": "https://www.inclusion-ai.org",
      "kind": "weights",
      "category": "open-weights",
      "summary": "LBS-27B is an open-weight vision-language model from inclusionAI's UI-Venus line, fine-tuned from Qwen3.8-27B to find what to click on a screenshot by zooming into regions over several turns, and applied to visual questions on large images.",
      "url": "https://www.anchorterminal.com/tools/lbs-27b",
      "markdownUrl": "https://www.anchorterminal.com/tools/lbs-27b.md",
      "slimMarkdownUrl": "https://www.anchorterminal.com/tools/lbs-27b.min.md",
      "jsonUrl": "https://www.anchorterminal.com/api/v1/tools/lbs-27b.json",
      "repo": "https://huggingface.co/inclusionAI/LBS-27B",
      "license": "Apache-2.0 (the card's metadata and licence section; the LICENSE file sits in the GitHub repository inclusionAI/UI-Venus on its LBS branch, not in the Hugging Face repository)",
      "transports": [],
      "packages": [
        {
          "registry": "huggingface",
          "name": "inclusionAI/LBS-27B"
        }
      ],
      "auth": "none",
      "authNotes": "The weights download from Hugging Face with no account, token or terms to accept. The Hub reports gated false for inclusionAI/LBS-27B (checked 2026-10-27).",
      "pricing": "free",
      "pricingNotes": "Free to download and use, commercial use included, under Apache 2.0 as the card states for the weights and the code. Running it costs the hardware, 54.73 GB of BF16 files and no quantised build from the publisher. No hosted API or inference provider serves it (checked 2026-10-27).",
      "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 2026-10-27).",
        "endpoints": []
      },
      "toolCount": null,
      "popularity": {
        "githubStars": null,
        "npmWeekly": null,
        "pypiWeekly": null,
        "asOf": "2026-10-27"
      },
      "docsUrl": "https://github.com/inclusionAI/UI-Venus/tree/LBS",
      "capabilities": [
        "model.open-weights"
      ],
      "tags": [
        "open-weights",
        "model",
        "dense",
        "qwen",
        "vision",
        "gui-grounding",
        "computer-use",
        "reasoning",
        "safetensors",
        "self-hosted",
        "new"
      ],
      "lastRelease": "2026-10-26",
      "graded": true,
      "anchor": {
        "graded": true,
        "score": 53.9,
        "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": 1217,
        "categoryRank": 73,
        "methodology": "0.6",
        "run": "2026-10-01",
        "scores": {
          "interface": 70,
          "reach": 55,
          "risk": 50,
          "upkeep": 43
        },
        "pending": [
          "performance",
          "tasks"
        ],
        "assessment": {
          "confidence": "low",
          "date": "2026-10-27"
        },
        "negative": 0,
        "verdict": "A 27B Qwen3.8 fine-tune for GUI grounding that zooms into screenshots over a few turns before naming a point, and inclusionAI says it also helps with fine detail in large images. It needs about 96 GB at BF16 and a client that runs its crop actions. Every result so far is inclusionAI's own, with no safety results or injection guidance.",
        "bestFor": "Agents with about 96 GB of GPU memory that need to find click targets on dense professional screenshots, or read fine detail in large images, and can run a small crop loop and wait for independent results.",
        "strengths": [
          "Qwen3.8-27B's stock architecture with no repository code, so released vLLM, SGLang, Transformers and llama.cpp load it",
          "Apache 2.0 for the weights and the base, ungated, safetensors only",
          "A simple, documented plain-text crop protocol with a point answer on a 0 to 1000 scale, and the training recipe and evaluation kit published",
          "Up to two crops per turn, learned in GRPO, and 262,144 tokens of context from the base",
          "inclusionAI publishes per-item scores and selected trajectories for its own benchmark runs"
        ],
        "weaknesses": [
          "No independent benchmark result yet; ScreenSpot-Pro, OS-World-G, PerceptionBench and HR-Bench numbers are inclusionAI's own runs",
          "BF16 only, about 66 GB to load, and no Ollama, LM Studio or quantised build",
          "The crop loop and system prompt come from the publisher's Python, not a runtime parser or a template",
          "No safety evaluation, prompt-injection guidance, training data sources or knowledge cut-off",
          "No hosted API or inference provider serves it"
        ],
        "agentNotes": [
          "Serve with `vllm serve inclusionAI/LBS-27B --tensor-parallel-size 4 --max-model-len 65536`, which is what the card's wrapper script runs; keep the context at 32,768 or more for multi-turn images",
          "Build the system prompt with `build_system_prompt` from the LBS branch's `zoomin_grounding_protocol.py`, send the screenshot after `image_path: \u003cname\u003e`, and don't pass `tools`; the model answers in plain text",
          "Parse `\u003caction\u003ecrop_image(image_path=..., x1=..., y1=..., x2=..., y2=...)\u003c/action\u003e`, cut the crop yourself and return it with its mapping to the original image; allow at most two crops per turn and three per episode",
          "Read the final answer as `[x.xx,y.yy]` on a 0 to 1000 scale of the original image, and use your own executor to click",
          "Pass `reasoning_effort` as `xhigh`, `medium` or `low` only, since the template raises an error for `high`, and don't count on `thinking_budget`, which the template ignores",
          "Don't turn on MTP speculative decoding; the MTP weights aren't in the repository though config.json names one MTP layer"
        ],
        "metrics": {
          "kind": "local",
          "measured": false
        },
        "reviewCount": 0,
        "avgRating": 0,
        "history": [
          {
            "basis": "public evidence",
            "confidence": "low",
            "grade": "D",
            "methodology": "0.6",
            "pending": [
              "performance",
              "tasks"
            ],
            "run": "2026-10-01",
            "runLabel": "October 2026 research run",
            "score": 53.9
          }
        ],
        "editorialScores": {
          "interface": 70,
          "reach": 55,
          "risk": 50,
          "upkeep": 43
        },
        "provenanceScore": 57,
        "checked": {
          "categories": {
            "interface": "2026-10-27",
            "reach": "2026-10-27",
            "risk": "2026-10-27",
            "upkeep": "2026-10-27"
          },
          "last": "2026-10-27",
          "oldest": "2026-10-27",
          "stale": false,
          "staleAfterDays": 90
        }
      },
      "connect": {
        "install": "# The card's route clones the LBS branch and wraps vllm serve (four GPUs in its example)\ngit clone --branch LBS --single-branch https://github.com/inclusionAI/UI-Venus.git\ncd UI-Venus/evaluation\nbash scripts/serve_vllm.sh start inclusionAI/LBS-27B --name lbs --tp 4 --dp 1 --daemon\n# the same server without the wrapper (the script's defaults are a 65,536-token context and 64 sequences)\nvllm serve inclusionAI/LBS-27B --served-model-name lbs --tensor-parallel-size 4 --max-model-len 65536",
        "http": "curl http://localhost:8000/v1/chat/completions -H 'Content-Type: application/json' \\\n  -d '{\"model\": \"lbs\", \"max_tokens\": 2560,\n       \"messages\": [{\"role\": \"system\", \"content\": \"\u003ctask, image size, crop_image spec and answer format, as build_system_prompt in the LBS branch writes them\u003e\"},\n                    {\"role\": \"user\", \"content\": [{\"type\": \"text\", \"text\": \"image_path: screenshot.png\"},\n                                                {\"type\": \"image_url\", \"image_url\": {\"url\": \"data:image/png;base64,...\"}}]}],\n       \"chat_template_kwargs\": {\"reasoning_effort\": \"xhigh\"}}'"
      },
      "letme": {
        "capability": "https://letme.dev/model.open-weights",
        "tool": "https://letme.dev/lbs-27b"
      },
      "sameCompany": [
        "ming-3-0-asr-tiny",
        "ming-3-0-audio-flash",
        "ming-3-0-audio-tiny",
        "ming-3-0-tts-tiny",
        "ling-3-0-tiny"
      ],
      "weights": {
        "trainedBy": "inclusionAI (Ant Group), with Wuhan University of Technology, CASIA and Zhejiang University",
        "builtOn": "Qwen/Qwen3.8-27B (fine-tune, named in the card's text, not in its base_model metadata; Apache 2.0, copyright Alibaba Cloud)",
        "params": "27B",
        "context": 262144,
        "goodFor": "A cousin that finds the point to click on a screenshot, and answers questions about fine detail in large images, by zooming in over a few turns, on a machine with about 96 GB of memory and a client that runs the crops, if inclusionAI's own results hold up.",
        "runtimes": [
          "vLLM",
          "SGLang",
          "Transformers",
          "llama.cpp"
        ],
        "builds": [
          {
            "name": "LBS-27B (BF16)",
            "url": "https://huggingface.co/inclusionAI/LBS-27B",
            "who": "publisher",
            "precision": "bf16",
            "sizeGB": 54.73,
            "memoryGB": 96,
            "format": "safetensors",
            "runsOn": [
              "vLLM",
              "SGLang",
              "Transformers"
            ],
            "note": "Whole repository, 54.73 GB, almost all of it 12 BF16 shards. 54.73 GB × 1.2 = 65.7 GB, just over 64 GB. The only build; no Ollama, LM Studio or ggml-org build and no copy by anyone else on 27 October 2026"
          }
        ],
        "run": "vllm serve inclusionAI/LBS-27B --served-model-name lbs --tensor-parallel-size 4 --max-model-len 65536",
        "runBuild": "LBS-27B (BF16)",
        "checked": "2026-10-27",
        "minMemoryGB": 96
      },
      "family": {
        "lab": "inclusionAI (Ant Group)",
        "family": "UI-Venus",
        "url": "https://www.anchorterminal.com/open-weights/#inclusionai",
        "others": [
          {
            "name": "UI-Venus-2-9B",
            "url": "https://huggingface.co/inclusionAI/UI-Venus-2-9B",
            "params": "9B"
          },
          {
            "name": "UI-Venus-1.5-30B-A3B",
            "url": "https://huggingface.co/inclusionAI/UI-Venus-1.5-30B-A3B",
            "params": "30B total, 3B active"
          },
          {
            "name": "UI-Venus-1.5-8B",
            "url": "https://huggingface.co/inclusionAI/UI-Venus-1.5-8B",
            "params": "8B"
          },
          {
            "name": "UI-Venus-1.5-2B",
            "url": "https://huggingface.co/inclusionAI/UI-Venus-1.5-2B",
            "params": "2B"
          }
        ],
        "olderCount": 54
      },
      "area": "models",
      "provenance": {
        "legalEntity": "inclusionAI, Ant Group (named in the site footer of inclusion-ai.org); the work is credited to authors from Wuhan University of Technology, CASIA, Zhejiang University and Ant Group",
        "domain": "inclusion-ai.org",
        "domainRegistered": "2025-04-03",
        "endpointOnVendorDomain": null,
        "terms": "",
        "privacy": "",
        "statusPage": "",
        "changelog": "https://huggingface.co/inclusionAI/LBS-27B/commits/main",
        "securityTxt": "none",
        "checked": "2026-10-27",
        "notes": [
          "inclusion-ai.org links to huggingface.co/inclusionAI and github.com/inclusionAI (read 2026-10-27). The Hub doesn't verify the organisation, which the calibration of 21 October credits as the publisher's own. The domain registration date is carried from the Ming-3.0 listings' check of 21 October 2026.",
          "The model card links github.com/inclusionAI/UI-Venus on its LBS branch, where the LICENSE, the NOTICE, the training recipe and the evaluation kit sit. The NOTICE reads Copyright 2026 the LBS contributors.",
          "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 Hugging Face commit history, two commits on 26 October 2026 (initial commit and one upload).",
          "inclusion-ai.org/.well-known/security.txt reset the connection on 27 October 2026 and answered 404 on 21 October. The LBS branch has no SECURITY.md. Ant Group runs a company-wide security response centre, AntSRC (https://security.alipay.com/, answering on 27 October 2026); nothing on the card or the branch links it."
        ],
        "score": 57
      },
      "pageJsonUrl": "https://www.anchorterminal.com/tools/lbs-27b.json",
      "live": {
        "slug": "lbs-27b",
        "securityTxt": {
          "url": "https://inclusion-ai.org/.well-known/security.txt",
          "state": "unknown",
          "checkedAt": "2026-10-27T15:31:25.810013407Z"
        },
        "updatedAt": "2026-10-27T15:31:25.810013407Z"
      }
    },
    "answer": "MiniCPM5-2B scores 60.2 (C) on agent readiness against LBS-27B's 53.9 (D), and leads in every scored category.",
    "b": {
      "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",
      "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": 60.2,
        "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": 1217,
        "categoryRank": 52,
        "methodology": "0.6",
        "run": "2026-10-01",
        "scores": {
          "capability": 27,
          "interface": 75,
          "reach": 90,
          "risk": 55,
          "upkeep": 97
        },
        "pending": [
          "performance",
          "tasks"
        ],
        "assessment": {
          "confidence": "high",
          "date": "2026-10-21"
        },
        "negative": 0,
        "verdict": "A tiny dense cousin for local tool calling and long context, with published training data and an active publisher. OpenBMB's own 4-bit builds need about 2 GB, so it runs on a laptop or phone in vLLM, SGLang, llama.cpp, Ollama or 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 18 discussions and fixed the template on 29 September"
        ],
        "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"
        ],
        "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": "0.6",
            "pending": [
              "performance",
              "tasks"
            ],
            "run": "2026-10-01",
            "runLabel": "October 2026 research run",
            "score": 60.2
          }
        ],
        "editorialScores": {
          "capability": 27,
          "interface": 75,
          "reach": 90,
          "risk": 55,
          "upkeep": 97
        },
        "provenanceScore": 53,
        "checked": {
          "categories": {
            "capability": "2026-10-21",
            "interface": "2026-10-21",
            "reach": "2026-10-21",
            "risk": "2026-10-21",
            "upkeep": "2026-10-21"
          },
          "last": "2026-10-21",
          "oldest": "2026-10-21",
          "stale": false,
          "staleAfterDays": 90
        }
      },
      "connect": {
        "install": "ollama run 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-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": 53
      },
      "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": "2026-10-27T15:32:10.557854231Z"
        },
        "domain": {
          "domain": "openbmb.cn",
          "checkedAt": "2026-10-25T13:52:42.572890011Z"
        },
        "pages": [
          {
            "url": "https://huggingface.co/openbmb/MiniCPM5-2B/commits/main",
            "kind": "changelog",
            "status": 200,
            "checkedAt": "2026-10-27T03:49:07.647191018Z",
            "changedAt": "2026-10-27T03:49:07.647191018Z",
            "fingerprint": "5bb61429ff1f"
          }
        ],
        "updatedAt": "2026-10-27T15:32:10.557854231Z"
      }
    },
    "facts": [
      {
        "a": "Open-weight model",
        "b": "Open-weight model",
        "name": "Kind"
      },
      {
        "a": "inclusionAI (Ant Group)",
        "b": "OpenBMB",
        "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 (the card's metadata and licence section; the LICENSE file sits in the GitHub repository inclusionAI/UI-Venus on its LBS branch, not in the Hugging Face repository)",
        "b": "Apache-2.0",
        "name": "Licence"
      },
      {
        "a": "no",
        "b": "no",
        "name": "Read-only variant documented"
      },
      {
        "a": "no",
        "b": "no",
        "name": "llms.txt"
      },
      {
        "a": "2026-10-26",
        "b": "2026-09-29",
        "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": "none",
        "b": "3/5 (4)",
        "name": "Agent reviews"
      }
    ],
    "faq": [
      {
        "answer": "MiniCPM5-2B scores 60.2 (C) on agent readiness against LBS-27B's 53.9 (D), and leads in every scored category.",
        "question": "Which is better for AI agents, LBS-27B or MiniCPM5-2B?"
      }
    ],
    "goodFor": [
      {
        "aheadOn": null,
        "also": null,
        "goodFor": "Agents with about 96 GB of GPU memory that need to find click targets on dense professional screenshots, or read fine detail in large images, and can run a small crop loop and wait for independent results.",
        "slug": "lbs-27b",
        "watchFor": "No independent benchmark result yet; ScreenSpot-Pro, OS-World-G, PerceptionBench and HR-Bench numbers are inclusionAI's own runs"
      },
      {
        "aheadOn": [
          "Reach, 90 against 55",
          "Risk, 55 against 50",
          "Agent interface, 75 against 70",
          "Documentation and upkeep, 97 against 43"
        ],
        "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"
      }
    ],
    "job": {
      "capability": "model.open-weights",
      "name": "Open-weight models you run yourself"
    },
    "others": [
      {
        "json": "https://www.anchorterminal.com/compare/agents-a1-4b-vs-lbs-27b.json",
        "title": "Agents-A1-4B vs LBS-27B",
        "url": "https://www.anchorterminal.com/compare/agents-a1-4b-vs-lbs-27b"
      },
      {
        "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/apertus-v1-5-8b-vs-lbs-27b.json",
        "title": "Apertus v1.5 8B vs LBS-27B",
        "url": "https://www.anchorterminal.com/compare/apertus-v1-5-8b-vs-lbs-27b"
      },
      {
        "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/apodex-1-1-mini-vs-lbs-27b.json",
        "title": "Apodex-1.1-mini vs LBS-27B",
        "url": "https://www.anchorterminal.com/compare/apodex-1-1-mini-vs-lbs-27b"
      },
      {
        "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/bigbang-v1-vs-lbs-27b.json",
        "title": "BigBang-v1 vs LBS-27B",
        "url": "https://www.anchorterminal.com/compare/bigbang-v1-vs-lbs-27b"
      },
      {
        "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/carbon-x-vs-lbs-27b.json",
        "title": "Carbon-X vs LBS-27B",
        "url": "https://www.anchorterminal.com/compare/carbon-x-vs-lbs-27b"
      },
      {
        "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/cosmos-reason2-2b-vs-lbs-27b.json",
        "title": "Cosmos-Reason2-2B vs LBS-27B",
        "url": "https://www.anchorterminal.com/compare/cosmos-reason2-2b-vs-lbs-27b"
      },
      {
        "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/darwin-36b-opus-vs-lbs-27b.json",
        "title": "Darwin-36B-Opus vs LBS-27B",
        "url": "https://www.anchorterminal.com/compare/darwin-36b-opus-vs-lbs-27b"
      },
      {
        "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/deepseek-v3-2-vs-lbs-27b.json",
        "title": "DeepSeek-V3.2 vs LBS-27B",
        "url": "https://www.anchorterminal.com/compare/deepseek-v3-2-vs-lbs-27b"
      },
      {
        "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"
      },
      {
        "json": "https://www.anchorterminal.com/compare/deepseek-v4-1-flash-vs-lbs-27b.json",
        "title": "DeepSeek V4.1 Flash vs LBS-27B",
        "url": "https://www.anchorterminal.com/compare/deepseek-v4-1-flash-vs-lbs-27b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/deepseek-v4-1-flash-vs-minicpm5-2b.json",
        "title": "DeepSeek V4.1 Flash vs MiniCPM5-2B",
        "url": "https://www.anchorterminal.com/compare/deepseek-v4-1-flash-vs-minicpm5-2b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/deepseek-v4-flash-0731-vs-lbs-27b.json",
        "title": "DeepSeek-V4-Flash-0731 vs LBS-27B",
        "url": "https://www.anchorterminal.com/compare/deepseek-v4-flash-0731-vs-lbs-27b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/deepseek-v4-flash-0731-vs-minicpm5-2b.json",
        "title": "DeepSeek-V4-Flash-0731 vs MiniCPM5-2B",
        "url": "https://www.anchorterminal.com/compare/deepseek-v4-flash-0731-vs-minicpm5-2b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/diffusiongemma-26b-a4b-it-vs-lbs-27b.json",
        "title": "DiffusionGemma 26B A4B IT vs LBS-27B",
        "url": "https://www.anchorterminal.com/compare/diffusiongemma-26b-a4b-it-vs-lbs-27b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/diffusiongemma-26b-a4b-it-vs-minicpm5-2b.json",
        "title": "DiffusionGemma 26B A4B IT vs MiniCPM5-2B",
        "url": "https://www.anchorterminal.com/compare/diffusiongemma-26b-a4b-it-vs-minicpm5-2b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/gemma-4-12b-it-vs-lbs-27b.json",
        "title": "Gemma 4 12B IT vs LBS-27B",
        "url": "https://www.anchorterminal.com/compare/gemma-4-12b-it-vs-lbs-27b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/gemma-4-12b-it-vs-minicpm5-2b.json",
        "title": "Gemma 4 12B IT vs MiniCPM5-2B",
        "url": "https://www.anchorterminal.com/compare/gemma-4-12b-it-vs-minicpm5-2b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/gemma-4-26b-a4b-it-vs-lbs-27b.json",
        "title": "Gemma 4 26B A4B IT vs LBS-27B",
        "url": "https://www.anchorterminal.com/compare/gemma-4-26b-a4b-it-vs-lbs-27b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/gemma-4-26b-a4b-it-vs-minicpm5-2b.json",
        "title": "Gemma 4 26B A4B IT vs MiniCPM5-2B",
        "url": "https://www.anchorterminal.com/compare/gemma-4-26b-a4b-it-vs-minicpm5-2b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/gemma-4-31b-it-vs-lbs-27b.json",
        "title": "Gemma 4 31B IT vs LBS-27B",
        "url": "https://www.anchorterminal.com/compare/gemma-4-31b-it-vs-lbs-27b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/gemma-4-31b-it-vs-minicpm5-2b.json",
        "title": "Gemma 4 31B IT vs MiniCPM5-2B",
        "url": "https://www.anchorterminal.com/compare/gemma-4-31b-it-vs-minicpm5-2b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/gemma-4-e2b-it-vs-lbs-27b.json",
        "title": "Gemma 4 E2B IT vs LBS-27B",
        "url": "https://www.anchorterminal.com/compare/gemma-4-e2b-it-vs-lbs-27b"
      },
      {
        "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-e4b-it-vs-lbs-27b.json",
        "title": "Gemma 4 E4B IT vs LBS-27B",
        "url": "https://www.anchorterminal.com/compare/gemma-4-e4b-it-vs-lbs-27b"
      },
      {
        "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/glm-4-5-air-vs-lbs-27b.json",
        "title": "GLM-4.5-Air vs LBS-27B",
        "url": "https://www.anchorterminal.com/compare/glm-4-5-air-vs-lbs-27b"
      },
      {
        "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"
      },
      {
        "json": "https://www.anchorterminal.com/compare/glm-4-7-flash-vs-lbs-27b.json",
        "title": "GLM-4.7-Flash vs LBS-27B",
        "url": "https://www.anchorterminal.com/compare/glm-4-7-flash-vs-lbs-27b"
      },
      {
        "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"
      },
      {
        "json": "https://www.anchorterminal.com/compare/glm-5-3-flash-vs-lbs-27b.json",
        "title": "GLM-5.3-Flash vs LBS-27B",
        "url": "https://www.anchorterminal.com/compare/glm-5-3-flash-vs-lbs-27b"
      },
      {
        "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"
      },
      {
        "json": "https://www.anchorterminal.com/compare/glm-5-3-vs-lbs-27b.json",
        "title": "GLM-5.3 vs LBS-27B",
        "url": "https://www.anchorterminal.com/compare/glm-5-3-vs-lbs-27b"
      },
      {
        "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"
      },
      {
        "json": "https://www.anchorterminal.com/compare/gpt-oss-120b-vs-lbs-27b.json",
        "title": "gpt-oss-120b vs LBS-27B",
        "url": "https://www.anchorterminal.com/compare/gpt-oss-120b-vs-lbs-27b"
      },
      {
        "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-20b-vs-lbs-27b.json",
        "title": "gpt-oss-20b vs LBS-27B",
        "url": "https://www.anchorterminal.com/compare/gpt-oss-20b-vs-lbs-27b"
      },
      {
        "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/granite-4-2-3b-vs-lbs-27b.json",
        "title": "Granite 4.2 3B vs LBS-27B",
        "url": "https://www.anchorterminal.com/compare/granite-4-2-3b-vs-lbs-27b"
      },
      {
        "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/hy3-vs-lbs-27b.json",
        "title": "Hy3 vs LBS-27B",
        "url": "https://www.anchorterminal.com/compare/hy3-vs-lbs-27b"
      },
      {
        "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/inkling-small-vs-lbs-27b.json",
        "title": "Inkling-Small vs LBS-27B",
        "url": "https://www.anchorterminal.com/compare/inkling-small-vs-lbs-27b"
      },
      {
        "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-vs-lbs-27b.json",
        "title": "Inkling vs LBS-27B",
        "url": "https://www.anchorterminal.com/compare/inkling-vs-lbs-27b"
      },
      {
        "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"
      },
      {
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        "json": "https://www.anchorterminal.com/compare/laguna-m-1-vs-lbs-27b.json",
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        "json": "https://www.anchorterminal.com/compare/laguna-s-2-1-vs-minicpm5-2b.json",
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        "json": "https://www.anchorterminal.com/compare/lbs-27b-vs-ling-3-0-tiny.json",
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        "json": "https://www.anchorterminal.com/compare/lbs-27b-vs-minimax-m2-7.json",
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      },
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        "json": "https://www.anchorterminal.com/compare/minicpm5-2b-vs-nemotron-3-nano-30b-a3b.json",
        "title": "MiniCPM5-2B vs Nemotron 3 Nano 30B A3B",
        "url": "https://www.anchorterminal.com/compare/minicpm5-2b-vs-nemotron-3-nano-30b-a3b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/minicpm5-2b-vs-nemotron-3-nano-4b.json",
        "title": "MiniCPM5-2B vs Nemotron 3 Nano 4B",
        "url": "https://www.anchorterminal.com/compare/minicpm5-2b-vs-nemotron-3-nano-4b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/minicpm5-2b-vs-nemotron-3-nano-omni-30b-a3b-reasoning.json",
        "title": "MiniCPM5-2B vs Nemotron 3 Nano Omni 30B A3B Reasoning",
        "url": "https://www.anchorterminal.com/compare/minicpm5-2b-vs-nemotron-3-nano-omni-30b-a3b-reasoning"
      },
      {
        "json": "https://www.anchorterminal.com/compare/minicpm5-2b-vs-nemotron-3-super-120b-a12b.json",
        "title": "MiniCPM5-2B vs Nemotron 3 Super 120B A12B",
        "url": "https://www.anchorterminal.com/compare/minicpm5-2b-vs-nemotron-3-super-120b-a12b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/minicpm5-2b-vs-nemotron-3-ultra-550b-a55b.json",
        "title": "MiniCPM5-2B vs Nemotron 3 Ultra 550B A55B",
        "url": "https://www.anchorterminal.com/compare/minicpm5-2b-vs-nemotron-3-ultra-550b-a55b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/minicpm5-2b-vs-occamy-1-0.json",
        "title": "MiniCPM5-2B vs occamy-1.0",
        "url": "https://www.anchorterminal.com/compare/minicpm5-2b-vs-occamy-1-0"
      },
      {
        "json": "https://www.anchorterminal.com/compare/minicpm5-2b-vs-olmo-3-7b-think.json",
        "title": "MiniCPM5-2B vs Olmo 3 7B Think",
        "url": "https://www.anchorterminal.com/compare/minicpm5-2b-vs-olmo-3-7b-think"
      },
      {
        "json": "https://www.anchorterminal.com/compare/minicpm5-2b-vs-ornith-1-5-35b-a3b.json",
        "title": "MiniCPM5-2B vs Ornith-1.5-35B-A3B",
        "url": "https://www.anchorterminal.com/compare/minicpm5-2b-vs-ornith-1-5-35b-a3b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/minicpm5-2b-vs-ornith-1-5-397b.json",
        "title": "MiniCPM5-2B vs Ornith-1.5-397B",
        "url": "https://www.anchorterminal.com/compare/minicpm5-2b-vs-ornith-1-5-397b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/minicpm5-2b-vs-ornith-1-5-9b.json",
        "title": "MiniCPM5-2B vs Ornith-1.5-9B",
        "url": "https://www.anchorterminal.com/compare/minicpm5-2b-vs-ornith-1-5-9b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/minicpm5-2b-vs-qwen3-30b-a3b-instruct-2507.json",
        "title": "MiniCPM5-2B vs Qwen3-30B-A3B-Instruct-2507",
        "url": "https://www.anchorterminal.com/compare/minicpm5-2b-vs-qwen3-30b-a3b-instruct-2507"
      },
      {
        "json": "https://www.anchorterminal.com/compare/minicpm5-2b-vs-qwen3-4b-instruct-2507.json",
        "title": "MiniCPM5-2B vs Qwen3-4B-Instruct-2507",
        "url": "https://www.anchorterminal.com/compare/minicpm5-2b-vs-qwen3-4b-instruct-2507"
      },
      {
        "json": "https://www.anchorterminal.com/compare/minicpm5-2b-vs-qwen3-5-0-8b.json",
        "title": "MiniCPM5-2B vs Qwen3.5-0.8B",
        "url": "https://www.anchorterminal.com/compare/minicpm5-2b-vs-qwen3-5-0-8b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/minicpm5-2b-vs-qwen3-5-122b-a10b.json",
        "title": "MiniCPM5-2B vs Qwen3.5-122B-A10B",
        "url": "https://www.anchorterminal.com/compare/minicpm5-2b-vs-qwen3-5-122b-a10b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/minicpm5-2b-vs-qwen3-5-2b.json",
        "title": "MiniCPM5-2B vs Qwen3.5-2B",
        "url": "https://www.anchorterminal.com/compare/minicpm5-2b-vs-qwen3-5-2b"
      },
      {
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        "title": "MiniCPM5-2B vs Qwen3.5-397B-A17B",
        "url": "https://www.anchorterminal.com/compare/minicpm5-2b-vs-qwen3-5-397b-a17b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/minicpm5-2b-vs-qwen3-5-4b.json",
        "title": "MiniCPM5-2B vs Qwen3.5-4B",
        "url": "https://www.anchorterminal.com/compare/minicpm5-2b-vs-qwen3-5-4b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/minicpm5-2b-vs-qwen3-5-9b.json",
        "title": "MiniCPM5-2B vs Qwen3.5-9B",
        "url": "https://www.anchorterminal.com/compare/minicpm5-2b-vs-qwen3-5-9b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/minicpm5-2b-vs-qwen3-6-27b.json",
        "title": "MiniCPM5-2B vs Qwen3.6-27B",
        "url": "https://www.anchorterminal.com/compare/minicpm5-2b-vs-qwen3-6-27b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/minicpm5-2b-vs-qwen3-6-35b-a3b.json",
        "title": "MiniCPM5-2B vs Qwen3.6-35B-A3B",
        "url": "https://www.anchorterminal.com/compare/minicpm5-2b-vs-qwen3-6-35b-a3b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/minicpm5-2b-vs-qwen3-8-27b.json",
        "title": "MiniCPM5-2B vs Qwen3.8-27B",
        "url": "https://www.anchorterminal.com/compare/minicpm5-2b-vs-qwen3-8-27b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/minicpm5-2b-vs-qwen3-8-flash-next.json",
        "title": "MiniCPM5-2B vs Qwen3.8-Flash-Next",
        "url": "https://www.anchorterminal.com/compare/minicpm5-2b-vs-qwen3-8-flash-next"
      },
      {
        "json": "https://www.anchorterminal.com/compare/minicpm5-2b-vs-qwen3-coder-30b-a3b-instruct.json",
        "title": "MiniCPM5-2B vs Qwen3-Coder-30B-A3B-Instruct",
        "url": "https://www.anchorterminal.com/compare/minicpm5-2b-vs-qwen3-coder-30b-a3b-instruct"
      },
      {
        "json": "https://www.anchorterminal.com/compare/minicpm5-2b-vs-qwen3-coder-next.json",
        "title": "MiniCPM5-2B vs Qwen3-Coder-Next",
        "url": "https://www.anchorterminal.com/compare/minicpm5-2b-vs-qwen3-coder-next"
      },
      {
        "json": "https://www.anchorterminal.com/compare/minicpm5-2b-vs-qwen3-omni-30b-a3b-instruct.json",
        "title": "MiniCPM5-2B vs Qwen3-Omni-30B-A3B-Instruct",
        "url": "https://www.anchorterminal.com/compare/minicpm5-2b-vs-qwen3-omni-30b-a3b-instruct"
      },
      {
        "json": "https://www.anchorterminal.com/compare/minicpm5-2b-vs-qwen3-vl-2b-instruct.json",
        "title": "MiniCPM5-2B vs Qwen3-VL-2B-Instruct",
        "url": "https://www.anchorterminal.com/compare/minicpm5-2b-vs-qwen3-vl-2b-instruct"
      },
      {
        "json": "https://www.anchorterminal.com/compare/minicpm5-2b-vs-qwen3-vl-30b-a3b-instruct.json",
        "title": "MiniCPM5-2B vs Qwen3-VL-30B-A3B-Instruct",
        "url": "https://www.anchorterminal.com/compare/minicpm5-2b-vs-qwen3-vl-30b-a3b-instruct"
      },
      {
        "json": "https://www.anchorterminal.com/compare/minicpm5-2b-vs-qwen3-vl-32b-instruct.json",
        "title": "MiniCPM5-2B vs Qwen3-VL-32B-Instruct",
        "url": "https://www.anchorterminal.com/compare/minicpm5-2b-vs-qwen3-vl-32b-instruct"
      },
      {
        "json": "https://www.anchorterminal.com/compare/minicpm5-2b-vs-qwen3-vl-4b-instruct.json",
        "title": "MiniCPM5-2B vs Qwen3-VL-4B-Instruct",
        "url": "https://www.anchorterminal.com/compare/minicpm5-2b-vs-qwen3-vl-4b-instruct"
      },
      {
        "json": "https://www.anchorterminal.com/compare/minicpm5-2b-vs-qwen3-vl-8b-instruct.json",
        "title": "MiniCPM5-2B vs Qwen3-VL-8B-Instruct",
        "url": "https://www.anchorterminal.com/compare/minicpm5-2b-vs-qwen3-vl-8b-instruct"
      },
      {
        "json": "https://www.anchorterminal.com/compare/minicpm5-2b-vs-qwopus3-8-27b-flash-v2.json",
        "title": "MiniCPM5-2B vs Qwopus3.8-27B-Flash-V2",
        "url": "https://www.anchorterminal.com/compare/minicpm5-2b-vs-qwopus3-8-27b-flash-v2"
      },
      {
        "json": "https://www.anchorterminal.com/compare/minicpm5-2b-vs-recursive-flint.json",
        "title": "MiniCPM5-2B vs Recursive Flint",
        "url": "https://www.anchorterminal.com/compare/minicpm5-2b-vs-recursive-flint"
      },
      {
        "json": "https://www.anchorterminal.com/compare/minicpm5-2b-vs-smollm3-3b.json",
        "title": "MiniCPM5-2B vs SmolLM3-3B",
        "url": "https://www.anchorterminal.com/compare/minicpm5-2b-vs-smollm3-3b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/minicpm5-2b-vs-spark-x2-6-4b.json",
        "title": "MiniCPM5-2B vs Spark-X2.6-4B",
        "url": "https://www.anchorterminal.com/compare/minicpm5-2b-vs-spark-x2-6-4b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/minicpm5-2b-vs-swift-1-5-qwen3-8-27b.json",
        "title": "MiniCPM5-2B vs Swift 1.5 Qwen3.8-27B",
        "url": "https://www.anchorterminal.com/compare/minicpm5-2b-vs-swift-1-5-qwen3-8-27b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/minicpm5-2b-vs-swift-1-5-qwen3-8-flash-next.json",
        "title": "MiniCPM5-2B vs Swift 1.5 Qwen3.8-Flash-Next",
        "url": "https://www.anchorterminal.com/compare/minicpm5-2b-vs-swift-1-5-qwen3-8-flash-next"
      },
      {
        "json": "https://www.anchorterminal.com/compare/minicpm5-2b-vs-thinkingcap-qwen3-8-27b.json",
        "title": "MiniCPM5-2B vs ThinkingCap (Qwen3.8 27B)",
        "url": "https://www.anchorterminal.com/compare/minicpm5-2b-vs-thinkingcap-qwen3-8-27b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/minicpm5-2b-vs-unlimited-ocr-2.json",
        "title": "MiniCPM5-2B vs Baidu Unlimited-OCR-2",
        "url": "https://www.anchorterminal.com/compare/minicpm5-2b-vs-unlimited-ocr-2"
      }
    ],
    "scores": [
      {
        "key": "capability",
        "name": "Capability",
        "pending": true,
        "weight": 35
      },
      {
        "by": 35,
        "edge": "minicpm5-2b",
        "key": "reach",
        "lbs-27b": 55,
        "minicpm5-2b": 90,
        "name": "Reach",
        "weight": 25
      },
      {
        "by": 5,
        "edge": "minicpm5-2b",
        "key": "risk",
        "lbs-27b": 50,
        "minicpm5-2b": 55,
        "name": "Risk",
        "weight": 20
      },
      {
        "by": 5,
        "edge": "minicpm5-2b",
        "key": "interface",
        "lbs-27b": 70,
        "minicpm5-2b": 75,
        "name": "Agent interface",
        "weight": 10
      },
      {
        "by": 54,
        "edge": "minicpm5-2b",
        "key": "upkeep",
        "lbs-27b": 43,
        "minicpm5-2b": 97,
        "name": "Documentation and upkeep",
        "weight": 10
      }
    ],
    "summary": "MiniCPM5-2B scores 60.2 (C) on agent readiness against LBS-27B's 53.9 (D), and leads in every scored category. Both do open-weight models you run yourself.",
    "tutorials": [],
    "verdicts": {
      "lbs-27b": "A 27B Qwen3.8 fine-tune for GUI grounding that zooms into screenshots over a few turns before naming a point, and inclusionAI says it also helps with fine detail in large images. It needs about 96 GB at BF16 and a client that runs its crop actions. Every result so far is inclusionAI's own, with no safety results or injection guidance.",
      "minicpm5-2b": "A tiny dense cousin for local tool calling and long context, with published training data and an active publisher. OpenBMB's own 4-bit builds need about 2 GB, so it runs on a laptop or phone in vLLM, SGLang, llama.cpp, Ollama or Transformers. The main risks are always-on thinking, no safety results and use conditions beyond Apache 2.0."
    }
  },
  "kind": "anchor.page",
  "links": {
    "api": "https://www.anchorterminal.com/api/v1/index.json",
    "html": "https://www.anchorterminal.com/compare/lbs-27b-vs-minicpm5-2b",
    "json": "https://www.anchorterminal.com/compare/lbs-27b-vs-minicpm5-2b.json",
    "llms": "https://www.anchorterminal.com/llms.txt",
    "markdown": "https://www.anchorterminal.com/compare/lbs-27b-vs-minicpm5-2b.md",
    "mcp": "https://www.anchorterminal.com/mcp",
    "slim": "https://www.anchorterminal.com/compare/lbs-27b-vs-minicpm5-2b.min.md"
  },
  "markdown": "MiniCPM5-2B scores 60.2 (C) on agent readiness against LBS-27B's 53.9 (D), and leads in every scored category. Both do open-weight models you run yourself.\n\n- LBS-27B: grade D, 53.9/100, rank #91 of 113 open-weight models. Markdown https://www.anchorterminal.com/tools/lbs-27b.md · JSON https://www.anchorterminal.com/api/v1/tools/lbs-27b.json\n- MiniCPM5-2B: grade C, 60.2/100, rank #61 of 113 open-weight models. Markdown https://www.anchorterminal.com/tools/minicpm5-2b.md · JSON https://www.anchorterminal.com/api/v1/tools/minicpm5-2b.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 3504 open weights comparisons: https://www.anchorterminal.com/compare/open-weights/index.md\n\n## Which one, for what\n\n### LBS-27B (D)\n\nGood for: Agents with about 96 GB of GPU memory that need to find click targets on dense professional screenshots, or read fine detail in large images, and can run a small crop loop and wait for independent results.\n\nWatch for: No independent benchmark result yet; ScreenSpot-Pro, OS-World-G, PerceptionBench and HR-Bench numbers are inclusionAI's own runs\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- Risk, 55 against 50\n- Agent interface, 75 against 70\n- Documentation and upkeep, 97 against 43\n\nWatch for: OpenBMB documents only a Think mode for the 2B, so every answer starts with reasoning\n\n\n## Score by category\n\n| Category | Weight | LBS-27B | MiniCPM5-2B | Edge |\n| --- | --- | --- | --- | --- |\n| Capability | 35%, pending | pending | pending | not scored in this run |\n| Reach | 25% (25 this run) | 55 | 90 | MiniCPM5-2B +35 |\n| Risk | 20% (20 this run) | 50 | 55 | MiniCPM5-2B +5 |\n| Agent interface | 10% (10 this run) | 70 | 75 | MiniCPM5-2B +5 |\n| Documentation and upkeep | 10% (10 this run) | 43 | 97 | MiniCPM5-2B +54 |\n| Negative events | ≤15 | 0 | 0 | |\n| **Total** | | **53.9 · D** | **60.2 · C** | |\n\n## Facts side by side\n\n| Fact | LBS-27B | MiniCPM5-2B |\n| --- | --- | --- |\n| Kind | Open-weight model | Open-weight model |\n| Vendor | inclusionAI (Ant Group) | OpenBMB |\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 (the card's metadata and licence section; the LICENSE file sits in the GitHub repository inclusionAI/UI-Venus on its LBS branch, not in the Hugging Face repository) | Apache-2.0 |\n| Read-only variant documented | no | no |\n| llms.txt | no | no |\n| Last release | 2026-10-26 | 2026-09-29 |\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 | none | 3/5 (4) |\n\n## Verdicts\n\n**LBS-27B.** A 27B Qwen3.8 fine-tune for GUI grounding that zooms into screenshots over a few turns before naming a point, and inclusionAI says it also helps with fine detail in large images. It needs about 96 GB at BF16 and a client that runs its crop actions. Every result so far is inclusionAI's own, with no safety results or injection guidance.\n\n**MiniCPM5-2B.** A tiny dense cousin for local tool calling and long context, with published training data and an active publisher. OpenBMB's own 4-bit builds need about 2 GB, so it runs on a laptop or phone in vLLM, SGLang, llama.cpp, Ollama or Transformers. The main risks are always-on thinking, no safety results and use conditions beyond Apache 2.0.\n\n## Before you call either\n\n### LBS-27B\n\n1. Serve with `vllm serve inclusionAI/LBS-27B --tensor-parallel-size 4 --max-model-len 65536`, which is what the card's wrapper script runs; keep the context at 32,768 or more for multi-turn images\n2. Build the system prompt with `build_system_prompt` from the LBS branch's `zoomin_grounding_protocol.py`, send the screenshot after `image_path: \u003cname\u003e`, and don't pass `tools`; the model answers in plain text\n3. Parse `\u003caction\u003ecrop_image(image_path=..., x1=..., y1=..., x2=..., y2=...)\u003c/action\u003e`, cut the crop yourself and return it with its mapping to the original image; allow at most two crops per turn and three per episode\n4. Read the final answer as `[x.xx,y.yy]` on a 0 to 1000 scale of the original image, and use your own executor to click\n5. Pass `reasoning_effort` as `xhigh`, `medium` or `low` only, since the template raises an error for `high`, and don't count on `thinking_budget`, which the template ignores\n6. Don't turn on MTP speculative decoding; the MTP weights aren't in the repository though config.json names one MTP layer\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## Questions\n\n### Which is better for AI agents, LBS-27B or MiniCPM5-2B?\n\nMiniCPM5-2B scores 60.2 (C) on agent readiness against LBS-27B's 53.9 (D), and leads in every scored category.\n\n\n## For agents\n\n- This comparison as JSON: https://www.anchorterminal.com/compare/lbs-27b-vs-minicpm5-2b.json, and with the fewest tokens: https://www.anchorterminal.com/compare/lbs-27b-vs-minicpm5-2b.min.md\n- Over MCP at https://www.anchorterminal.com/mcp (no key): `compare_tools {\"a\": \"lbs-27b\", \"b\": \"minicpm5-2b\"}`. From a terminal: `anchor compare lbs-27b minicpm5-2b`\n- Each listing in full: https://www.anchorterminal.com/api/v1/tools/lbs-27b.json and https://www.anchorterminal.com/api/v1/tools/minicpm5-2b.json\n\n## Other comparisons with LBS-27B or MiniCPM5-2B\n\n- [Agents-A1-4B vs LBS-27B](https://www.anchorterminal.com/compare/agents-a1-4b-vs-lbs-27b.md)\n- [Agents-A1-4B vs MiniCPM5-2B](https://www.anchorterminal.com/compare/agents-a1-4b-vs-minicpm5-2b.md)\n- [Apertus v1.5 8B vs LBS-27B](https://www.anchorterminal.com/compare/apertus-v1-5-8b-vs-lbs-27b.md)\n- [Apertus v1.5 8B vs MiniCPM5-2B](https://www.anchorterminal.com/compare/apertus-v1-5-8b-vs-minicpm5-2b.md)\n- [Apodex-1.1-mini vs LBS-27B](https://www.anchorterminal.com/compare/apodex-1-1-mini-vs-lbs-27b.md)\n- [Apodex-1.1-mini vs MiniCPM5-2B](https://www.anchorterminal.com/compare/apodex-1-1-mini-vs-minicpm5-2b.md)\n- [BigBang-v1 vs LBS-27B](https://www.anchorterminal.com/compare/bigbang-v1-vs-lbs-27b.md)\n- [BigBang-v1 vs MiniCPM5-2B](https://www.anchorterminal.com/compare/bigbang-v1-vs-minicpm5-2b.md)\n- [Carbon-X vs LBS-27B](https://www.anchorterminal.com/compare/carbon-x-vs-lbs-27b.md)\n- [Carbon-X vs MiniCPM5-2B](https://www.anchorterminal.com/compare/carbon-x-vs-minicpm5-2b.md)\n- [Cosmos-Reason2-2B vs LBS-27B](https://www.anchorterminal.com/compare/cosmos-reason2-2b-vs-lbs-27b.md)\n- [Cosmos-Reason2-2B vs MiniCPM5-2B](https://www.anchorterminal.com/compare/cosmos-reason2-2b-vs-minicpm5-2b.md)\n- [Darwin-36B-Opus vs LBS-27B](https://www.anchorterminal.com/compare/darwin-36b-opus-vs-lbs-27b.md)\n- [Darwin-36B-Opus vs MiniCPM5-2B](https://www.anchorterminal.com/compare/darwin-36b-opus-vs-minicpm5-2b.md)\n- [DeepSeek-V3.2 vs LBS-27B](https://www.anchorterminal.com/compare/deepseek-v3-2-vs-lbs-27b.md)\n- [DeepSeek-V3.2 vs MiniCPM5-2B](https://www.anchorterminal.com/compare/deepseek-v3-2-vs-minicpm5-2b.md)\n- [DeepSeek V4.1 Flash vs LBS-27B](https://www.anchorterminal.com/compare/deepseek-v4-1-flash-vs-lbs-27b.md)\n- [DeepSeek V4.1 Flash vs MiniCPM5-2B](https://www.anchorterminal.com/compare/deepseek-v4-1-flash-vs-minicpm5-2b.md)\n- [DeepSeek-V4-Flash-0731 vs LBS-27B](https://www.anchorterminal.com/compare/deepseek-v4-flash-0731-vs-lbs-27b.md)\n- [DeepSeek-V4-Flash-0731 vs MiniCPM5-2B](https://www.anchorterminal.com/compare/deepseek-v4-flash-0731-vs-minicpm5-2b.md)\n- [DiffusionGemma 26B A4B IT vs LBS-27B](https://www.anchorterminal.com/compare/diffusiongemma-26b-a4b-it-vs-lbs-27b.md)\n- [DiffusionGemma 26B A4B IT vs MiniCPM5-2B](https://www.anchorterminal.com/compare/diffusiongemma-26b-a4b-it-vs-minicpm5-2b.md)\n- [Gemma 4 12B IT vs LBS-27B](https://www.anchorterminal.com/compare/gemma-4-12b-it-vs-lbs-27b.md)\n- [Gemma 4 12B IT vs MiniCPM5-2B](https://www.anchorterminal.com/compare/gemma-4-12b-it-vs-minicpm5-2b.md)\n- [Gemma 4 26B A4B IT vs LBS-27B](https://www.anchorterminal.com/compare/gemma-4-26b-a4b-it-vs-lbs-27b.md)\n- [Gemma 4 26B A4B IT vs MiniCPM5-2B](https://www.anchorterminal.com/compare/gemma-4-26b-a4b-it-vs-minicpm5-2b.md)\n- [Gemma 4 31B IT vs LBS-27B](https://www.anchorterminal.com/compare/gemma-4-31b-it-vs-lbs-27b.md)\n- [Gemma 4 31B IT vs MiniCPM5-2B](https://www.anchorterminal.com/compare/gemma-4-31b-it-vs-minicpm5-2b.md)\n- [Gemma 4 E2B IT vs LBS-27B](https://www.anchorterminal.com/compare/gemma-4-e2b-it-vs-lbs-27b.md)\n- [Gemma 4 E2B IT vs MiniCPM5-2B](https://www.anchorterminal.com/compare/gemma-4-e2b-it-vs-minicpm5-2b.md)\n- [Gemma 4 E4B IT vs LBS-27B](https://www.anchorterminal.com/compare/gemma-4-e4b-it-vs-lbs-27b.md)\n- [Gemma 4 E4B IT vs MiniCPM5-2B](https://www.anchorterminal.com/compare/gemma-4-e4b-it-vs-minicpm5-2b.md)\n- [GLM-4.5-Air vs LBS-27B](https://www.anchorterminal.com/compare/glm-4-5-air-vs-lbs-27b.md)\n- [GLM-4.5-Air vs MiniCPM5-2B](https://www.anchorterminal.com/compare/glm-4-5-air-vs-minicpm5-2b.md)\n- [GLM-4.7-Flash vs LBS-27B](https://www.anchorterminal.com/compare/glm-4-7-flash-vs-lbs-27b.md)\n- [GLM-4.7-Flash vs MiniCPM5-2B](https://www.anchorterminal.com/compare/glm-4-7-flash-vs-minicpm5-2b.md)\n- [GLM-5.3-Flash vs LBS-27B](https://www.anchorterminal.com/compare/glm-5-3-flash-vs-lbs-27b.md)\n- [GLM-5.3-Flash vs MiniCPM5-2B](https://www.anchorterminal.com/compare/glm-5-3-flash-vs-minicpm5-2b.md)\n- [GLM-5.3 vs LBS-27B](https://www.anchorterminal.com/compare/glm-5-3-vs-lbs-27b.md)\n- [GLM-5.3 vs MiniCPM5-2B](https://www.anchorterminal.com/compare/glm-5-3-vs-minicpm5-2b.md)\n- [gpt-oss-120b vs LBS-27B](https://www.anchorterminal.com/compare/gpt-oss-120b-vs-lbs-27b.md)\n- [gpt-oss-120b vs MiniCPM5-2B](https://www.anchorterminal.com/compare/gpt-oss-120b-vs-minicpm5-2b.md)\n- [gpt-oss-20b vs LBS-27B](https://www.anchorterminal.com/compare/gpt-oss-20b-vs-lbs-27b.md)\n- [gpt-oss-20b vs MiniCPM5-2B](https://www.anchorterminal.com/compare/gpt-oss-20b-vs-minicpm5-2b.md)\n- [Granite 4.2 3B vs LBS-27B](https://www.anchorterminal.com/compare/granite-4-2-3b-vs-lbs-27b.md)\n- [Granite 4.2 3B vs MiniCPM5-2B](https://www.anchorterminal.com/compare/granite-4-2-3b-vs-minicpm5-2b.md)\n- [Hy3 vs LBS-27B](https://www.anchorterminal.com/compare/hy3-vs-lbs-27b.md)\n- [Hy3 vs MiniCPM5-2B](https://www.anchorterminal.com/compare/hy3-vs-minicpm5-2b.md)\n- [Inkling-Small vs LBS-27B](https://www.anchorterminal.com/compare/inkling-small-vs-lbs-27b.md)\n- [Inkling-Small vs MiniCPM5-2B](https://www.anchorterminal.com/compare/inkling-small-vs-minicpm5-2b.md)\n- [Inkling vs LBS-27B](https://www.anchorterminal.com/compare/inkling-vs-lbs-27b.md)\n- [Inkling vs MiniCPM5-2B](https://www.anchorterminal.com/compare/inkling-vs-minicpm5-2b.md)\n- [InternVL3.5-GPT-OSS-20B-A4B-Preview vs LBS-27B](https://www.anchorterminal.com/compare/internvl3-5-gpt-oss-20b-a4b-preview-vs-lbs-27b.md)\n- [InternVL3.5-GPT-OSS-20B-A4B-Preview vs MiniCPM5-2B](https://www.anchorterminal.com/compare/internvl3-5-gpt-oss-20b-a4b-preview-vs-minicpm5-2b.md)\n- [Kimi K3 vs LBS-27B](https://www.anchorterminal.com/compare/kimi-k3-vs-lbs-27b.md)\n- [Kimi K3 vs MiniCPM5-2B](https://www.anchorterminal.com/compare/kimi-k3-vs-minicpm5-2b.md)\n- [Kolibri-1 vs LBS-27B](https://www.anchorterminal.com/compare/kolibri-1-vs-lbs-27b.md)\n- [Kolibri-1 vs MiniCPM5-2B](https://www.anchorterminal.com/compare/kolibri-1-vs-minicpm5-2b.md)\n- [Kronos vs LBS-27B](https://www.anchorterminal.com/compare/kronos-vs-lbs-27b.md)\n- [Kronos vs MiniCPM5-2B](https://www.anchorterminal.com/compare/kronos-vs-minicpm5-2b.md)\n- [Laguna M.1 vs LBS-27B](https://www.anchorterminal.com/compare/laguna-m-1-vs-lbs-27b.md)\n- [Laguna M.1 vs MiniCPM5-2B](https://www.anchorterminal.com/compare/laguna-m-1-vs-minicpm5-2b.md)\n- [Laguna S 2.1 vs LBS-27B](https://www.anchorterminal.com/compare/laguna-s-2-1-vs-lbs-27b.md)\n- [Laguna S 2.1 vs MiniCPM5-2B](https://www.anchorterminal.com/compare/laguna-s-2-1-vs-minicpm5-2b.md)\n- [Laguna XS 2.1 vs LBS-27B](https://www.anchorterminal.com/compare/laguna-xs-2-1-vs-lbs-27b.md)\n- [Laguna XS 2.1 vs MiniCPM5-2B](https://www.anchorterminal.com/compare/laguna-xs-2-1-vs-minicpm5-2b.md)\n- [LBS-27B vs LFM2.5-2.6B](https://www.anchorterminal.com/compare/lbs-27b-vs-lfm2-5-2-6b.md)\n- [LBS-27B vs Ling-3.0-tiny](https://www.anchorterminal.com/compare/lbs-27b-vs-ling-3-0-tiny.md)\n- [LBS-27B vs MiMo-V2.6 Distill Qwen 9B](https://www.anchorterminal.com/compare/lbs-27b-vs-mimo-v2-6-distill-qwen-9b.md)\n- [LBS-27B vs MiniCPM-o 4.5](https://www.anchorterminal.com/compare/lbs-27b-vs-minicpm-o-4-5.md)\n- [LBS-27B vs MiniMax-M2.5](https://www.anchorterminal.com/compare/lbs-27b-vs-minimax-m2-5.md)\n- [LBS-27B vs MiniMax-M2.7](https://www.anchorterminal.com/compare/lbs-27b-vs-minimax-m2-7.md)\n- [LBS-27B vs MiniMax-M3.1-Flash](https://www.anchorterminal.com/compare/lbs-27b-vs-minimax-m3-1-flash.md)\n- [LBS-27B vs Muse Glimmer 30B](https://www.anchorterminal.com/compare/lbs-27b-vs-muse-glimmer-30b.md)\n- [LBS-27B vs Nanbeige4.3-33B](https://www.anchorterminal.com/compare/lbs-27b-vs-nanbeige-4-3-33b.md)\n- [LBS-27B vs NVIDIA Nemotron 3.5 Bolt E4B 4GB](https://www.anchorterminal.com/compare/lbs-27b-vs-nemotron-3-5-bolt-e4b-4gb.md)\n- [LBS-27B vs Nemotron 3.5 Lightning 30B A3B](https://www.anchorterminal.com/compare/lbs-27b-vs-nemotron-3-5-lightning-30b-a3b.md)\n- [LBS-27B vs Nemotron 3 Nano 30B A3B](https://www.anchorterminal.com/compare/lbs-27b-vs-nemotron-3-nano-30b-a3b.md)\n- [LBS-27B vs Nemotron 3 Nano 4B](https://www.anchorterminal.com/compare/lbs-27b-vs-nemotron-3-nano-4b.md)\n- [LBS-27B vs Nemotron 3 Nano Omni 30B A3B Reasoning](https://www.anchorterminal.com/compare/lbs-27b-vs-nemotron-3-nano-omni-30b-a3b-reasoning.md)\n- [LBS-27B vs Nemotron 3 Super 120B A12B](https://www.anchorterminal.com/compare/lbs-27b-vs-nemotron-3-super-120b-a12b.md)\n- [LBS-27B vs Nemotron 3 Ultra 550B A55B](https://www.anchorterminal.com/compare/lbs-27b-vs-nemotron-3-ultra-550b-a55b.md)\n- [LBS-27B vs occamy-1.0](https://www.anchorterminal.com/compare/lbs-27b-vs-occamy-1-0.md)\n- [LBS-27B vs Olmo 3 7B Think](https://www.anchorterminal.com/compare/lbs-27b-vs-olmo-3-7b-think.md)\n- [LBS-27B vs Ornith-1.5-35B-A3B](https://www.anchorterminal.com/compare/lbs-27b-vs-ornith-1-5-35b-a3b.md)\n- [LBS-27B vs Ornith-1.5-397B](https://www.anchorterminal.com/compare/lbs-27b-vs-ornith-1-5-397b.md)\n- [LBS-27B vs Ornith-1.5-9B](https://www.anchorterminal.com/compare/lbs-27b-vs-ornith-1-5-9b.md)\n- [LBS-27B vs Qwen3-30B-A3B-Instruct-2507](https://www.anchorterminal.com/compare/lbs-27b-vs-qwen3-30b-a3b-instruct-2507.md)\n- [LBS-27B vs Qwen3-4B-Instruct-2507](https://www.anchorterminal.com/compare/lbs-27b-vs-qwen3-4b-instruct-2507.md)\n- [LBS-27B vs Qwen3.5-0.8B](https://www.anchorterminal.com/compare/lbs-27b-vs-qwen3-5-0-8b.md)\n- [LBS-27B vs Qwen3.5-122B-A10B](https://www.anchorterminal.com/compare/lbs-27b-vs-qwen3-5-122b-a10b.md)\n- [LBS-27B vs Qwen3.5-2B](https://www.anchorterminal.com/compare/lbs-27b-vs-qwen3-5-2b.md)\n- [LBS-27B vs Qwen3.5-397B-A17B](https://www.anchorterminal.com/compare/lbs-27b-vs-qwen3-5-397b-a17b.md)\n- [LBS-27B vs Qwen3.5-4B](https://www.anchorterminal.com/compare/lbs-27b-vs-qwen3-5-4b.md)\n- [LBS-27B vs Qwen3.5-9B](https://www.anchorterminal.com/compare/lbs-27b-vs-qwen3-5-9b.md)\n- [LBS-27B vs Qwen3.6-27B](https://www.anchorterminal.com/compare/lbs-27b-vs-qwen3-6-27b.md)\n- [LBS-27B vs Qwen3.6-35B-A3B](https://www.anchorterminal.com/compare/lbs-27b-vs-qwen3-6-35b-a3b.md)\n- [LBS-27B vs Qwen3.8-27B](https://www.anchorterminal.com/compare/lbs-27b-vs-qwen3-8-27b.md)\n- [LBS-27B vs Qwen3.8-Flash-Next](https://www.anchorterminal.com/compare/lbs-27b-vs-qwen3-8-flash-next.md)\n- [LBS-27B vs Qwen3-Coder-30B-A3B-Instruct](https://www.anchorterminal.com/compare/lbs-27b-vs-qwen3-coder-30b-a3b-instruct.md)\n- [LBS-27B vs Qwen3-Coder-Next](https://www.anchorterminal.com/compare/lbs-27b-vs-qwen3-coder-next.md)\n- [LBS-27B vs Qwen3-Omni-30B-A3B-Instruct](https://www.anchorterminal.com/compare/lbs-27b-vs-qwen3-omni-30b-a3b-instruct.md)\n- [LBS-27B vs Qwen3-VL-2B-Instruct](https://www.anchorterminal.com/compare/lbs-27b-vs-qwen3-vl-2b-instruct.md)\n- [LBS-27B vs Qwen3-VL-30B-A3B-Instruct](https://www.anchorterminal.com/compare/lbs-27b-vs-qwen3-vl-30b-a3b-instruct.md)\n- [LBS-27B vs Qwen3-VL-32B-Instruct](https://www.anchorterminal.com/compare/lbs-27b-vs-qwen3-vl-32b-instruct.md)\n- [LBS-27B vs Qwen3-VL-4B-Instruct](https://www.anchorterminal.com/compare/lbs-27b-vs-qwen3-vl-4b-instruct.md)\n- [LBS-27B vs Qwen3-VL-8B-Instruct](https://www.anchorterminal.com/compare/lbs-27b-vs-qwen3-vl-8b-instruct.md)\n- [LBS-27B vs Qwopus3.8-27B-Flash-V2](https://www.anchorterminal.com/compare/lbs-27b-vs-qwopus3-8-27b-flash-v2.md)\n- [LBS-27B vs Recursive Flint](https://www.anchorterminal.com/compare/lbs-27b-vs-recursive-flint.md)\n- [LBS-27B vs SmolLM3-3B](https://www.anchorterminal.com/compare/lbs-27b-vs-smollm3-3b.md)\n- [LBS-27B vs Spark-X2.6-4B](https://www.anchorterminal.com/compare/lbs-27b-vs-spark-x2-6-4b.md)\n- [LBS-27B vs Swift 1.5 Qwen3.8-27B](https://www.anchorterminal.com/compare/lbs-27b-vs-swift-1-5-qwen3-8-27b.md)\n- [LBS-27B vs Swift 1.5 Qwen3.8-Flash-Next](https://www.anchorterminal.com/compare/lbs-27b-vs-swift-1-5-qwen3-8-flash-next.md)\n- [LBS-27B vs ThinkingCap (Qwen3.8 27B)](https://www.anchorterminal.com/compare/lbs-27b-vs-thinkingcap-qwen3-8-27b.md)\n- [LBS-27B vs Baidu Unlimited-OCR-2](https://www.anchorterminal.com/compare/lbs-27b-vs-unlimited-ocr-2.md)\n- [LFM2.5-2.6B vs MiniCPM5-2B](https://www.anchorterminal.com/compare/lfm2-5-2-6b-vs-minicpm5-2b.md)\n- [Ling-3.0-tiny vs MiniCPM5-2B](https://www.anchorterminal.com/compare/ling-3-0-tiny-vs-minicpm5-2b.md)\n- [MiMo-V2.6 Distill Qwen 9B vs MiniCPM5-2B](https://www.anchorterminal.com/compare/mimo-v2-6-distill-qwen-9b-vs-minicpm5-2b.md)\n- [MiniCPM-o 4.5 vs MiniCPM5-2B](https://www.anchorterminal.com/compare/minicpm-o-4-5-vs-minicpm5-2b.md)\n- [MiniCPM5-2B vs MiniMax-M2.5](https://www.anchorterminal.com/compare/minicpm5-2b-vs-minimax-m2-5.md)\n- [MiniCPM5-2B vs MiniMax-M2.7](https://www.anchorterminal.com/compare/minicpm5-2b-vs-minimax-m2-7.md)\n- [MiniCPM5-2B vs MiniMax-M3.1-Flash](https://www.anchorterminal.com/compare/minicpm5-2b-vs-minimax-m3-1-flash.md)\n- [MiniCPM5-2B vs Muse Glimmer 30B](https://www.anchorterminal.com/compare/minicpm5-2b-vs-muse-glimmer-30b.md)\n- [MiniCPM5-2B vs Nanbeige4.3-33B](https://www.anchorterminal.com/compare/minicpm5-2b-vs-nanbeige-4-3-33b.md)\n- [MiniCPM5-2B vs NVIDIA Nemotron 3.5 Bolt E4B 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