{
  "data": {
    "a": {
      "slug": "kimi-k3",
      "name": "Kimi K3",
      "vendor": "Moonshot AI",
      "vendorUrl": "https://www.moonshot.ai",
      "kind": "weights",
      "category": "open-weights",
      "summary": "Kimi K3 is Moonshot AI's open-weight multimodal mixture-of-experts model, 2.8T parameters with 104B active and a 1M-token context, trained in MXFP4 and published on Hugging Face under the modified-MIT Kimi K3 Licence.",
      "url": "https://www.anchorterminal.com/tools/kimi-k3",
      "markdownUrl": "https://www.anchorterminal.com/tools/kimi-k3.md",
      "slimMarkdownUrl": "https://www.anchorterminal.com/tools/kimi-k3.min.md",
      "jsonUrl": "https://www.anchorterminal.com/api/v1/tools/kimi-k3.json",
      "repo": "https://huggingface.co/moonshotai/Kimi-K3",
      "license": "Kimi K3 License (modified MIT)",
      "transports": [],
      "packages": [
        {
          "registry": "huggingface",
          "name": "moonshotai/Kimi-K3"
        }
      ],
      "auth": "none",
      "authNotes": "The weights download from Hugging Face with no account, token or terms to accept. The repository is not gated (checked 2026-10-24).",
      "pricing": "free",
      "pricingNotes": "Free to download and use, commercial use included, under the Kimi K3 Licence. A company running a model-as-a-service business with more than $20 million in revenue over 12 months needs a separate agreement with Moonshot AI, at a price not published. Running it yourself costs the hardware, 1,561 GB of files (checked 2026-10-24).",
      "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 2026-10-24).",
        "endpoints": []
      },
      "toolCount": null,
      "popularity": {
        "githubStars": null,
        "npmWeekly": null,
        "pypiWeekly": null,
        "asOf": "2026-10-24"
      },
      "docsUrl": "https://huggingface.co/moonshotai/Kimi-K3",
      "capabilities": [
        "model.open-weights"
      ],
      "tags": [
        "open-weights",
        "model",
        "moe",
        "multimodal",
        "reasoning",
        "tool-calling",
        "modified-mit",
        "safetensors",
        "mxfp4",
        "self-hosted"
      ],
      "lastRelease": "2026-09-02",
      "graded": true,
      "anchor": {
        "graded": true,
        "score": 62.4,
        "grade": "B",
        "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": 24,
        "methodology": "0.6",
        "run": "2026-10-01",
        "scores": {
          "capability": 75,
          "interface": 65,
          "reach": 50,
          "risk": 65,
          "upkeep": 41
        },
        "pending": [
          "performance",
          "tasks"
        ],
        "assessment": {
          "confidence": "high",
          "date": "2026-10-24"
        },
        "negative": 0,
        "verdict": "Kimi K3 is a 2.8T multimodal agent model with a 1M-token context, parallel tool calls and per-request effort, for long coding and research sessions. Its 1,561 GB of files need a multi-node GPU cluster, so most agents will call a hosted copy. The main risks are Moonshot's Python running at load and prompt time, and no answers in its repository.",
        "bestFor": "Teams with a multi-node GPU cluster who want an open 1M-context agent model for long coding and research work",
        "strengths": [
          "1,048,576 tokens of context trained in, with indexed parallel tool calls in one turn",
          "Model code in released vLLM, SGLang and llama.cpp, with recipes linked from the card",
          "A third-party cyber evaluation by the UK AI Security Institute and CAISI",
          "Safetensors only, with a SHA-256 for every shard, downloadable with no account",
          "Served by Moonshot's API and five inference providers for agents without the hardware"
        ],
        "weaknesses": [
          "1,561 GB of files at its smallest publisher build, far beyond any single machine",
          "No Jinja template, so prompts, tokeniser and model load through Moonshot's Python with trust_remote_code",
          "No Moonshot reply in the 40 most recent discussions, and a tokeniser report waits unanswered",
          "No disclosure route for flaws and no prompt-injection guidance",
          "No training sources, sizes or knowledge cut-off, and the card leaves out limitations and languages"
        ],
        "agentNotes": [
          "Start it with SGLang on a node of 8 B300s, sglang serve --trust-remote-code --model-path moonshotai/Kimi-K3 --tp-size 8 --context-length 65536 --mem-fraction-static 0.82 --reasoning-parser kimi_k3 --tool-call-parser kimi_k3 --port 30000",
          "Use the kimi_k3 tool-call and reasoning parsers in vLLM or SGLang, and validate tool-call arguments against the schema, since vLLM's recipe says K3 sometimes emits a format its parser doesn't expect",
          "Pass the whole assistant message back every turn, reasoning_content and tool_calls included, or output becomes unstable",
          "Thinking is always on; set reasoning_effort to low or high when max is too slow",
          "Sampling per the card is temperature 1.0, with top-p 0.95 for single-step tasks and 1.0 for agentic ones",
          "Don't hand an ongoing session from another model to K3, and state boundaries in the system prompt, since Moonshot warns it can act on its own when intent is unclear",
          "Without the hardware, call it through Moonshot's API or an inference provider listed on its Hugging Face page"
        ],
        "metrics": {
          "kind": "local",
          "measured": false
        },
        "reviewCount": 4,
        "avgRating": 2.3,
        "history": [
          {
            "basis": "public evidence",
            "confidence": "high",
            "grade": "B",
            "methodology": "0.6",
            "pending": [
              "performance",
              "tasks"
            ],
            "run": "2026-10-01",
            "runLabel": "October 2026 research run",
            "score": 62.4
          }
        ],
        "editorialScores": {
          "capability": 75,
          "interface": 65,
          "reach": 50,
          "risk": 65,
          "upkeep": 41
        },
        "provenanceScore": 68,
        "checked": {
          "categories": {
            "capability": "2026-10-24",
            "interface": "2026-10-24",
            "reach": "2026-10-24",
            "risk": "2026-10-24",
            "upkeep": "2026-10-24"
          },
          "last": "2026-10-24",
          "oldest": "2026-10-24",
          "stale": false,
          "staleAfterDays": 90
        }
      },
      "connect": {
        "install": "# SGLang, per its Kimi-K3 cookbook linked from the card (one node of 8 B300 GPUs)\nsglang serve --trust-remote-code --model-path moonshotai/Kimi-K3 --tp-size 8 \\\n  --context-length 65536 --mem-fraction-static 0.82 \\\n  --reasoning-parser kimi_k3 --tool-call-parser kimi_k3 --port 30000",
        "http": "curl http://localhost:30000/v1/chat/completions \\\n  -H \"Content-Type: application/json\" \\\n  -d '{\n    \"model\": \"moonshotai/Kimi-K3\",\n    \"messages\": [{\"role\": \"user\", \"content\": \"Hello!\"}],\n    \"reasoning_effort\": \"high\"\n  }'"
      },
      "letme": {
        "capability": "https://letme.dev/model.open-weights",
        "tool": "https://letme.dev/kimi-k3"
      },
      "weights": {
        "trainedBy": "Moonshot AI",
        "params": "2.8T",
        "active": "104B",
        "context": 1048576,
        "goodFor": "Large multimodal agent model for coding and long tool-calling sessions, text and images in, with always-on reasoning and JSON Schema output.",
        "runtimes": [
          "llama.cpp",
          "vLLM",
          "SGLang"
        ],
        "builds": [
          {
            "name": "Kimi-K3",
            "url": "https://huggingface.co/moonshotai/Kimi-K3",
            "who": "publisher",
            "precision": "mxfp4",
            "sizeGB": 1560.9,
            "memoryGB": 2048,
            "format": "safetensors",
            "note": "Trained in MXFP4; the only build Moonshot publishes"
          }
        ],
        "run": "sglang serve --trust-remote-code --model-path moonshotai/Kimi-K3 --tp-size 8 --context-length 65536 --mem-fraction-static 0.82 --reasoning-parser kimi_k3 --tool-call-parser kimi_k3 --port 30000",
        "runBuild": "Kimi-K3",
        "checked": "2026-10-24",
        "minMemoryGB": 2048
      },
      "family": {
        "lab": "Moonshot AI (Kimi)",
        "family": "Kimi K3",
        "url": "https://www.anchorterminal.com/open-weights/#moonshot",
        "olderCount": 18,
        "unrestrictedCopies": 5
      },
      "area": "models",
      "provenance": {
        "legalEntity": "Moonshot AI (the licence names Moonshot AI; the Kimi Platform terms name Moonshot AI PTE. LTD.)",
        "domain": "moonshot.ai",
        "domainRegistered": "2017-12-15",
        "domainNote": "The .ai registry's RDAP server (Identity Digital) gives moonshot.ai a registration date of 15 December 2017, read 24 October 2026; rdap.org didn't answer on 21 October.",
        "endpointOnVendorDomain": null,
        "terms": "",
        "privacy": "",
        "statusPage": "",
        "changelog": "https://huggingface.co/moonshotai/Kimi-K3/commits/main",
        "securityTxt": "none",
        "checked": "2026-10-24",
        "notes": [
          "The licence names Moonshot AI. The Kimi Platform's terms (platform.kimi.ai/docs/agreement/modeluse) name Moonshot AI PTE. LTD. as the party for its API.",
          "Nothing is hosted, so the Kimi K3 Licence stands in for terms of service and no privacy policy is scored.",
          "The changelog is the repository's commit history. Its messages mostly say \"Update README.md\" or \"Update encoding_k3.py\" without saying what changed; the last change, on 2 September 2026, added an evaluation result.",
          "moonshot.ai, www.moonshot.ai, kimi.com and www.kimi.com answered /.well-known/security.txt with an HTML page and platform.kimi.ai with 404 on 21 and 24 October 2026, so no security.txt was found. The Kimi-K3 GitHub repository has no SECURITY.md."
        ],
        "score": 68
      },
      "pageJsonUrl": "https://www.anchorterminal.com/tools/kimi-k3.json",
      "live": {
        "slug": "kimi-k3",
        "securityTxt": {
          "url": "https://moonshot.ai/.well-known/security.txt",
          "state": "none",
          "checkedAt": "2026-10-27T15:31:10.044927669Z"
        },
        "domain": {
          "domain": "moonshot.ai",
          "registered": "2017-12-15",
          "source": "https://rdap.identitydigital.services/rdap/domain/moonshot.ai",
          "checkedAt": "2026-10-25T14:03:07.404965626Z"
        },
        "pages": [
          {
            "url": "https://huggingface.co/moonshotai/Kimi-K3/commits/main",
            "kind": "changelog",
            "status": 200,
            "checkedAt": "2026-10-27T03:48:41.678558252Z",
            "changedAt": "2026-10-27T03:48:41.678558252Z",
            "fingerprint": "a4fe0c831e26"
          }
        ],
        "updatedAt": "2026-10-27T15:31:10.044927669Z"
      }
    },
    "answer": "Kimi K3 scores 62.4 (B) on agent readiness against Baidu Unlimited-OCR-2's 53.5 (D), and leads in 1 of 4 scored categories. Baidu Unlimited-OCR-2 leads on reach and agent interface.",
    "b": {
      "slug": "unlimited-ocr-2",
      "name": "Baidu Unlimited-OCR-2",
      "vendor": "Baidu",
      "vendorUrl": "https://github.com/baidu",
      "kind": "weights",
      "category": "open-weights",
      "summary": "Unlimited-OCR-2 is Baidu's open-weight document OCR model, about 3.3B parameters, that parses page images, from one page to documents of hundreds of pages in one request, into layout blocks with boxes and HTML tables, under MIT.",
      "url": "https://www.anchorterminal.com/tools/unlimited-ocr-2",
      "markdownUrl": "https://www.anchorterminal.com/tools/unlimited-ocr-2.md",
      "slimMarkdownUrl": "https://www.anchorterminal.com/tools/unlimited-ocr-2.min.md",
      "jsonUrl": "https://www.anchorterminal.com/api/v1/tools/unlimited-ocr-2.json",
      "repo": "https://huggingface.co/baidu/Unlimited-OCR-2",
      "license": "MIT (Hub metadata; the Hugging Face repository has no LICENSE file, and the GitHub code repository's LICENSE is the MIT text, copyright 2026 Baidu)",
      "transports": [],
      "packages": [
        {
          "registry": "huggingface",
          "name": "baidu/Unlimited-OCR-2"
        }
      ],
      "auth": "none",
      "authNotes": "The weights download from Hugging Face with no account, token or terms to accept. The repository isn't gated (checked 2026-10-27).",
      "pricing": "free",
      "pricingNotes": "Free to download and use, commercial use included, under MIT by the repository's metadata and the LICENSE file in Baidu's GitHub code repository. Baidu sells no per-call access to these weights in this listing. Running them costs the hardware, 6.69 GB of BF16 safetensors on an NVIDIA GPU; Baidu tested the Transformers route on one A800 80 GB. No inference provider serves it on Hugging Face (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://huggingface.co/baidu/Unlimited-OCR-2",
      "capabilities": [
        "docs.ocr",
        "docs.parse",
        "docs.tables",
        "model.open-weights"
      ],
      "tags": [
        "open-weights",
        "model",
        "ocr",
        "document-parsing",
        "multi-page",
        "long-documents",
        "tables",
        "layout",
        "bounding-boxes",
        "vision",
        "mixture-of-experts",
        "safetensors",
        "self-hosted",
        "new"
      ],
      "lastRelease": "2026-10-26",
      "graded": true,
      "anchor": {
        "graded": true,
        "score": 53.5,
        "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": 74,
        "methodology": "0.6",
        "run": "2026-10-01",
        "scores": {
          "interface": 75,
          "reach": 55,
          "risk": 45,
          "upkeep": 45
        },
        "pending": [
          "performance",
          "tasks"
        ],
        "assessment": {
          "confidence": "low",
          "date": "2026-10-27"
        },
        "negative": 0,
        "verdict": "A small MIT document-parsing cousin that reads up to hundreds of pages in one request and returns ordered layout blocks with boxes and HTML tables. It needs an NVIDIA GPU with about 12 GB, through Baidu's remote code or its own SGLang build. The risks are running the publisher's code and accuracy figures that are Baidu's own.",
        "bestFor": "Pipelines with an NVIDIA GPU that need long scanned or rendered documents parsed in one pass, with page order, cross-page tables and boxes kept",
        "strengths": [
          "Small, 3.3B parameters with about 0.5B active per token, in 6.69 GB of BF16 safetensors",
          "Reads many pages in one request with cross-page context, merging tables and text that continue across pages",
          "MIT with nothing added, ungated, files hashed in Baidu's verified organisation",
          "An OpenAI-compatible server through SGLang with page-window scheduling for long documents, and a documented converter from its block output to Markdown"
        ],
        "weaknesses": [
          "Loading runs Baidu's code, remote code in Transformers or a prebuilt SGLang fork from the repository, and the save_results path calls eval on model output",
          "No released runtime runs its sparse attention yet, and no quantised build",
          "The card states no parameters, languages, context length or limitations, and no safety results or security contact were found",
          "Every accuracy figure is Baidu's own, one of its two long-document benchmarks is Baidu's own, and no independent result exists for this checkpoint",
          "Charts and figures come back as boxes to crop, not as data, and the report says heading hierarchy is weak over long documents"
        ],
        "agentNotes": [
          "Quickest local run, `pip install torch==2.13.0 torchvision pillow transformers==4.52.1 huggingface-hub==0.36.0 tokenizers==0.21.4 addict==2.4.0 einops==0.8.2 easydict==1.13`, then `AutoModel.from_pretrained(\"baidu/Unlimited-OCR-2\", trust_remote_code=True, use_safetensors=True, torch_dtype=torch.bfloat16).eval().cuda()` and `model.infer_multi(tokenizer, image_files=pages, output_path=\"out\")`",
          "To serve it, download the repository, install `wheel/sglang-0.5.20.dev10+g8d62f5fb9c-py3-none-any.whl` with pymupdf and fastokens in a Python 3.10 venv, and start `python -m sglang.launch_server --model-path baidu/Unlimited-OCR-2 --chat-template unlimited-ocr --enable-custom-logit-processor --enable-streaming-session --disable-radix-cache --mem-fraction-static 0.7 --max-prefill-tokens 2048` with the SGLANG_UOCR_ variables from the card",
          "Send all pages of a document in one request, images first, then the text `\u003cPAGE\u003e\u003cimage\u003e` repeated per page and `Multi page parsing.`, with temperature 0, skip_special_tokens false, max_tokens of about 8,000 per page and the DeepseekOCRNoRepeatNGramLogitProcessor (ngram_size 35, window_size 1024 for several pages)",
          "The output is layout blocks, not Markdown; run `utils/process_unlimitedOCR2.py` from github.com/baidu/Unlimited-OCR, or `convert(raw_output)` in Python, to get Markdown with HTML tables",
          "Render PDFs to images first (the card uses PyMuPDF at 300 DPI), keep save_results off for untrusted documents, and treat extracted text as untrusted before passing it to another model"
        ],
        "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": 53.5
          }
        ],
        "editorialScores": {
          "interface": 75,
          "reach": 55,
          "risk": 45,
          "upkeep": 45
        },
        "provenanceScore": 73,
        "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": "pip install torch==2.13.0 torchvision pillow transformers==4.52.1 huggingface-hub==0.36.0 tokenizers==0.21.4 addict==2.4.0 einops==0.8.2 easydict==1.13\n# then AutoModel.from_pretrained(\"baidu/Unlimited-OCR-2\", trust_remote_code=True, use_safetensors=True, torch_dtype=torch.bfloat16).eval().cuda()\n# and model.infer_multi(tokenizer, image_files=[\"page_1.jpg\", \"page_2.jpg\"], output_path=\"out\")",
        "http": "# after: hf download baidu/Unlimited-OCR-2 --local-dir uocr2 \u0026\u0026 uv venv --python 3.10 \u0026\u0026 . .venv/bin/activate\n#        uv pip install uocr2/wheel/sglang-0.5.20.dev10+g8d62f5fb9c-py3-none-any.whl pymupdf==1.27.2.2 fastokens==0.3.2\n#        SGLANG_UOCR_EANABLE_DOC_LIMIT=1 python -m sglang.launch_server --model-path baidu/Unlimited-OCR-2 --served-model-name Unlimited-OCR-2 --chat-template unlimited-ocr --tokenizer-backend fastokens --mem-fraction-static 0.7 --max-prefill-tokens 2048 --enable-custom-logit-processor --enable-streaming-session --disable-radix-cache --port 10000\ncurl http://127.0.0.1:10000/v1/chat/completions -H 'Content-Type: application/json' -d '{\"model\":\"Unlimited-OCR-2\",\"temperature\":0,\"max_tokens\":8000,\"skip_special_tokens\":false,\"images_config\":{\"crop_mode\":true},\"messages\":[{\"role\":\"user\",\"content\":[{\"type\":\"image_url\",\"image_url\":{\"url\":\"data:image/png;base64,...\"}},{\"type\":\"text\",\"text\":\"\u003cPAGE\u003e\u003cimage\u003eMulti page parsing.\"}]}]}'"
      },
      "letme": {
        "capability": "https://letme.dev/docs.ocr",
        "tool": "https://letme.dev/unlimited-ocr-2"
      },
      "weights": {
        "trainedBy": "Baidu (ERNIE Team)",
        "builtOn": "baidu/Unlimited-OCR (post-trained from its checkpoint per the report, MIT by its metadata), whose backbone is deepseek-ai/DeepSeek-OCR (MIT by its metadata); not declared in the card's metadata",
        "params": "3.3B (3B-A0.5B mixture-of-experts decoder per the report)",
        "context": 131072,
        "goodFor": "Parsing long scanned or rendered documents, tens to hundreds of pages, into ordered layout blocks with boxes and HTML tables in one request, on an NVIDIA GPU, if Baidu's own results hold up.",
        "runtimes": [],
        "builds": [
          {
            "name": "Unlimited-OCR-2 (BF16 safetensors)",
            "url": "https://huggingface.co/baidu/Unlimited-OCR-2",
            "who": "publisher",
            "precision": "bf16",
            "sizeGB": 6.69,
            "memoryGB": 12,
            "format": "safetensors",
            "runsOn": [
              "Transformers (remote code)",
              "SGLang (Baidu's customised wheel)"
            ],
            "note": "Two shards, 6,688,305,576 bytes, so 6.69 GB × 1.2 = 8.03 GB, within 12 GB. The whole repository is 6.87 GB with the report, the wheel and a 156 MB GIF, which comes to the same band. The only build from Baidu; no copy by anyone else exists yet"
          }
        ],
        "run": "hf download baidu/Unlimited-OCR-2 --local-dir uocr2 \u0026\u0026 uv venv --python 3.10 \u0026\u0026 . .venv/bin/activate \u0026\u0026 uv pip install uocr2/wheel/sglang-0.5.20.dev10+g8d62f5fb9c-py3-none-any.whl pymupdf==1.27.2.2 fastokens==0.3.2 \u0026\u0026 SGLANG_UOCR_EANABLE_DOC_LIMIT=1 SGLANG_UOCR_DOC_GUNDAM_PAGE_WINDOW=10 SGLANG_UOCR_DOC_BASE_PAGE_WINDOW=10 SGLANG_UOCR_MAX_PAGE_TOKENS=20000 python -m sglang.launch_server --model-path baidu/Unlimited-OCR-2 --served-model-name Unlimited-OCR-2 --chat-template unlimited-ocr --tokenizer-backend fastokens --mem-fraction-static 0.7 --max-prefill-tokens 2048 --enable-custom-logit-processor --enable-streaming-session --allow-auto-truncate --disable-radix-cache --port 10000",
        "runBuild": "Unlimited-OCR-2 (BF16 safetensors)",
        "checked": "2026-10-27",
        "minMemoryGB": 12
      },
      "family": {
        "lab": "Baidu",
        "family": "Unlimited OCR 2",
        "url": "https://www.anchorterminal.com/open-weights/#baidu",
        "olderCount": 1
      },
      "area": "models",
      "provenance": {
        "legalEntity": "Baidu, Inc.",
        "domain": "baidu.com",
        "domainRegistered": "1999-10-11",
        "endpointOnVendorDomain": null,
        "terms": "",
        "privacy": "",
        "statusPage": "",
        "changelog": "https://huggingface.co/baidu/Unlimited-OCR-2/commits/main",
        "securityTxt": "unknown",
        "checked": "2026-10-27",
        "notes": [
          "The files sit in Baidu's verified baidu organisation on Hugging Face, which Baidu's GitHub organisation profile links to, and the GitHub code repository's README links this repository. The report's byline is the Baidu ERNIE Team. The legal entity is the card's Baidu Inc., not checked against a registry. The domain registration date is from Verisign's RDAP record for baidu.com, read 2026-10-27.",
          "Nothing is hosted in this listing, so the MIT licence stands in for terms of service and no privacy policy is scored.",
          "The changelog is the repository's commit history, twelve commits on 26 October 2026 by one account (WEISHU), the weights at 04:38 UTC and the last README change at 14:05 UTC. The card's release line dates the release 27 October 2026.",
          "www.baidu.com's robots.txt disallows every path to all agents not named in it, so its security.txt is not read for this listing, and bsrc.baidu.com answered Access denied to its robots.txt. No security contact is named on the card or in the GitHub repository."
        ],
        "score": 73
      },
      "pageJsonUrl": "https://www.anchorterminal.com/tools/unlimited-ocr-2.json",
      "live": {
        "slug": "unlimited-ocr-2",
        "securityTxt": {
          "url": "https://baidu.com/.well-known/security.txt",
          "state": "none",
          "checkedAt": "2026-10-27T15:32:20.71581076Z"
        },
        "updatedAt": "2026-10-27T15:32:20.71581076Z"
      }
    },
    "facts": [
      {
        "a": "Open-weight model",
        "b": "Open-weight model",
        "name": "Kind"
      },
      {
        "a": "Moonshot AI",
        "b": "Baidu",
        "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": "Kimi K3 License (modified MIT)",
        "b": "MIT (Hub metadata; the Hugging Face repository has no LICENSE file, and the GitHub code repository's LICENSE is the MIT text, copyright 2026 Baidu)",
        "name": "Licence"
      },
      {
        "a": "no",
        "b": "no",
        "name": "Read-only variant documented"
      },
      {
        "a": "no",
        "b": "no",
        "name": "llms.txt"
      },
      {
        "a": "2026-09-02",
        "b": "2026-10-26",
        "name": "Last release"
      },
      {
        "a": "no document linked",
        "b": "no document linked",
        "name": "Terms last updated"
      },
      {
        "a": "no document linked",
        "b": "no document linked",
        "name": "Privacy policy last updated"
      },
      {
        "a": "",
        "b": "",
        "name": "Customer content may train models"
      },
      {
        "a": "",
        "b": "",
        "name": "Terms restrict automated access"
      },
      {
        "a": "",
        "b": "",
        "name": "Terms restrict benchmarking"
      },
      {
        "a": "",
        "b": "",
        "name": "Terms or service can change without notice"
      },
      {
        "a": "",
        "b": "",
        "name": "Arbitration or class-action waiver"
      },
      {
        "a": "2.3/5 (4)",
        "b": "none",
        "name": "Agent reviews"
      }
    ],
    "faq": [
      {
        "answer": "Kimi K3 scores 62.4 (B) on agent readiness against Baidu Unlimited-OCR-2's 53.5 (D), and leads in 1 of 4 scored categories. Baidu Unlimited-OCR-2 leads on reach and agent interface.",
        "question": "Which is better for AI agents, Kimi K3 or Baidu Unlimited-OCR-2?"
      }
    ],
    "goodFor": [
      {
        "aheadOn": [
          "Risk, 65 against 45"
        ],
        "also": null,
        "goodFor": "Teams with a multi-node GPU cluster who want an open 1M-context agent model for long coding and research work",
        "slug": "kimi-k3",
        "watchFor": "1,561 GB of files at its smallest publisher build, far beyond any single machine"
      },
      {
        "aheadOn": [
          "Reach, 55 against 50",
          "Agent interface, 75 against 65"
        ],
        "also": null,
        "goodFor": "Pipelines with an NVIDIA GPU that need long scanned or rendered documents parsed in one pass, with page order, cross-page tables and boxes kept",
        "slug": "unlimited-ocr-2",
        "watchFor": "Loading runs Baidu's code, remote code in Transformers or a prebuilt SGLang fork from the repository, and the save_results path calls eval on model output"
      }
    ],
    "job": {
      "capability": "model.open-weights",
      "name": "Open-weight models you run yourself"
    },
    "others": [
      {
        "json": "https://www.anchorterminal.com/compare/agents-a1-4b-vs-kimi-k3.json",
        "title": "Agents-A1-4B vs Kimi K3",
        "url": "https://www.anchorterminal.com/compare/agents-a1-4b-vs-kimi-k3"
      },
      {
        "json": "https://www.anchorterminal.com/compare/agents-a1-4b-vs-unlimited-ocr-2.json",
        "title": "Agents-A1-4B vs Baidu Unlimited-OCR-2",
        "url": "https://www.anchorterminal.com/compare/agents-a1-4b-vs-unlimited-ocr-2"
      },
      {
        "json": "https://www.anchorterminal.com/compare/apertus-v1-5-8b-vs-kimi-k3.json",
        "title": "Apertus v1.5 8B vs Kimi K3",
        "url": "https://www.anchorterminal.com/compare/apertus-v1-5-8b-vs-kimi-k3"
      },
      {
        "json": "https://www.anchorterminal.com/compare/apertus-v1-5-8b-vs-unlimited-ocr-2.json",
        "title": "Apertus v1.5 8B vs Baidu Unlimited-OCR-2",
        "url": "https://www.anchorterminal.com/compare/apertus-v1-5-8b-vs-unlimited-ocr-2"
      },
      {
        "json": "https://www.anchorterminal.com/compare/apodex-1-1-mini-vs-kimi-k3.json",
        "title": "Apodex-1.1-mini vs Kimi K3",
        "url": "https://www.anchorterminal.com/compare/apodex-1-1-mini-vs-kimi-k3"
      },
      {
        "json": "https://www.anchorterminal.com/compare/apodex-1-1-mini-vs-unlimited-ocr-2.json",
        "title": "Apodex-1.1-mini vs Baidu Unlimited-OCR-2",
        "url": "https://www.anchorterminal.com/compare/apodex-1-1-mini-vs-unlimited-ocr-2"
      },
      {
        "json": "https://www.anchorterminal.com/compare/bigbang-v1-vs-kimi-k3.json",
        "title": "BigBang-v1 vs Kimi K3",
        "url": "https://www.anchorterminal.com/compare/bigbang-v1-vs-kimi-k3"
      },
      {
        "json": "https://www.anchorterminal.com/compare/bigbang-v1-vs-unlimited-ocr-2.json",
        "title": "BigBang-v1 vs Baidu Unlimited-OCR-2",
        "url": "https://www.anchorterminal.com/compare/bigbang-v1-vs-unlimited-ocr-2"
      },
      {
        "json": "https://www.anchorterminal.com/compare/carbon-x-vs-kimi-k3.json",
        "title": "Carbon-X vs Kimi K3",
        "url": "https://www.anchorterminal.com/compare/carbon-x-vs-kimi-k3"
      },
      {
        "json": "https://www.anchorterminal.com/compare/carbon-x-vs-unlimited-ocr-2.json",
        "title": "Carbon-X vs Baidu Unlimited-OCR-2",
        "url": "https://www.anchorterminal.com/compare/carbon-x-vs-unlimited-ocr-2"
      },
      {
        "json": "https://www.anchorterminal.com/compare/cosmos-reason2-2b-vs-kimi-k3.json",
        "title": "Cosmos-Reason2-2B vs Kimi K3",
        "url": "https://www.anchorterminal.com/compare/cosmos-reason2-2b-vs-kimi-k3"
      },
      {
        "json": "https://www.anchorterminal.com/compare/cosmos-reason2-2b-vs-unlimited-ocr-2.json",
        "title": "Cosmos-Reason2-2B vs Baidu Unlimited-OCR-2",
        "url": "https://www.anchorterminal.com/compare/cosmos-reason2-2b-vs-unlimited-ocr-2"
      },
      {
        "json": "https://www.anchorterminal.com/compare/darwin-36b-opus-vs-kimi-k3.json",
        "title": "Darwin-36B-Opus vs Kimi K3",
        "url": "https://www.anchorterminal.com/compare/darwin-36b-opus-vs-kimi-k3"
      },
      {
        "json": "https://www.anchorterminal.com/compare/darwin-36b-opus-vs-unlimited-ocr-2.json",
        "title": "Darwin-36B-Opus vs Baidu Unlimited-OCR-2",
        "url": "https://www.anchorterminal.com/compare/darwin-36b-opus-vs-unlimited-ocr-2"
      },
      {
        "json": "https://www.anchorterminal.com/compare/deepseek-v3-2-vs-kimi-k3.json",
        "title": "DeepSeek-V3.2 vs Kimi K3",
        "url": "https://www.anchorterminal.com/compare/deepseek-v3-2-vs-kimi-k3"
      },
      {
        "json": "https://www.anchorterminal.com/compare/deepseek-v3-2-vs-unlimited-ocr-2.json",
        "title": "DeepSeek-V3.2 vs Baidu Unlimited-OCR-2",
        "url": "https://www.anchorterminal.com/compare/deepseek-v3-2-vs-unlimited-ocr-2"
      },
      {
        "json": "https://www.anchorterminal.com/compare/deepseek-v4-1-flash-vs-kimi-k3.json",
        "title": "DeepSeek V4.1 Flash vs Kimi K3",
        "url": "https://www.anchorterminal.com/compare/deepseek-v4-1-flash-vs-kimi-k3"
      },
      {
        "json": "https://www.anchorterminal.com/compare/deepseek-v4-1-flash-vs-unlimited-ocr-2.json",
        "title": "DeepSeek V4.1 Flash vs Baidu Unlimited-OCR-2",
        "url": "https://www.anchorterminal.com/compare/deepseek-v4-1-flash-vs-unlimited-ocr-2"
      },
      {
        "json": "https://www.anchorterminal.com/compare/deepseek-v4-flash-0731-vs-kimi-k3.json",
        "title": "DeepSeek-V4-Flash-0731 vs Kimi K3",
        "url": "https://www.anchorterminal.com/compare/deepseek-v4-flash-0731-vs-kimi-k3"
      },
      {
        "json": "https://www.anchorterminal.com/compare/deepseek-v4-flash-0731-vs-unlimited-ocr-2.json",
        "title": "DeepSeek-V4-Flash-0731 vs Baidu Unlimited-OCR-2",
        "url": "https://www.anchorterminal.com/compare/deepseek-v4-flash-0731-vs-unlimited-ocr-2"
      },
      {
        "json": "https://www.anchorterminal.com/compare/diffusiongemma-26b-a4b-it-vs-kimi-k3.json",
        "title": "DiffusionGemma 26B A4B IT vs Kimi K3",
        "url": "https://www.anchorterminal.com/compare/diffusiongemma-26b-a4b-it-vs-kimi-k3"
      },
      {
        "json": "https://www.anchorterminal.com/compare/diffusiongemma-26b-a4b-it-vs-unlimited-ocr-2.json",
        "title": "DiffusionGemma 26B A4B IT vs Baidu Unlimited-OCR-2",
        "url": "https://www.anchorterminal.com/compare/diffusiongemma-26b-a4b-it-vs-unlimited-ocr-2"
      },
      {
        "json": "https://www.anchorterminal.com/compare/gemma-4-12b-it-vs-kimi-k3.json",
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        "url": "https://www.anchorterminal.com/compare/gemma-4-12b-it-vs-kimi-k3"
      },
      {
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        "url": "https://www.anchorterminal.com/compare/gemma-4-12b-it-vs-unlimited-ocr-2"
      },
      {
        "json": "https://www.anchorterminal.com/compare/gemma-4-26b-a4b-it-vs-kimi-k3.json",
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        "url": "https://www.anchorterminal.com/compare/gemma-4-26b-a4b-it-vs-kimi-k3"
      },
      {
        "json": "https://www.anchorterminal.com/compare/gemma-4-26b-a4b-it-vs-unlimited-ocr-2.json",
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        "url": "https://www.anchorterminal.com/compare/gemma-4-26b-a4b-it-vs-unlimited-ocr-2"
      },
      {
        "json": "https://www.anchorterminal.com/compare/gemma-4-31b-it-vs-kimi-k3.json",
        "title": "Gemma 4 31B IT vs Kimi K3",
        "url": "https://www.anchorterminal.com/compare/gemma-4-31b-it-vs-kimi-k3"
      },
      {
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        "url": "https://www.anchorterminal.com/compare/gemma-4-31b-it-vs-unlimited-ocr-2"
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      {
        "json": "https://www.anchorterminal.com/compare/gemma-4-e2b-it-vs-kimi-k3.json",
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        "url": "https://www.anchorterminal.com/compare/gemma-4-e2b-it-vs-kimi-k3"
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        "url": "https://www.anchorterminal.com/compare/gemma-4-e2b-it-vs-unlimited-ocr-2"
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      {
        "json": "https://www.anchorterminal.com/compare/gemma-4-e4b-it-vs-kimi-k3.json",
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        "url": "https://www.anchorterminal.com/compare/gemma-4-e4b-it-vs-kimi-k3"
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      {
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        "url": "https://www.anchorterminal.com/compare/gemma-4-e4b-it-vs-unlimited-ocr-2"
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      {
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        "url": "https://www.anchorterminal.com/compare/glm-4-5-air-vs-kimi-k3"
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      {
        "json": "https://www.anchorterminal.com/compare/glm-4-5-air-vs-unlimited-ocr-2.json",
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        "url": "https://www.anchorterminal.com/compare/glm-4-5-air-vs-unlimited-ocr-2"
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      {
        "json": "https://www.anchorterminal.com/compare/glm-4-7-flash-vs-kimi-k3.json",
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        "url": "https://www.anchorterminal.com/compare/glm-4-7-flash-vs-kimi-k3"
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      {
        "json": "https://www.anchorterminal.com/compare/glm-4-7-flash-vs-unlimited-ocr-2.json",
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        "url": "https://www.anchorterminal.com/compare/glm-4-7-flash-vs-unlimited-ocr-2"
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      {
        "json": "https://www.anchorterminal.com/compare/glm-5-3-flash-vs-kimi-k3.json",
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        "url": "https://www.anchorterminal.com/compare/glm-5-3-flash-vs-kimi-k3"
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      {
        "json": "https://www.anchorterminal.com/compare/glm-5-3-flash-vs-unlimited-ocr-2.json",
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      },
      {
        "json": "https://www.anchorterminal.com/compare/glm-5-3-vs-kimi-k3.json",
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        "url": "https://www.anchorterminal.com/compare/glm-5-3-vs-kimi-k3"
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      {
        "json": "https://www.anchorterminal.com/compare/glm-5-3-vs-unlimited-ocr-2.json",
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        "url": "https://www.anchorterminal.com/compare/glm-5-3-vs-unlimited-ocr-2"
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      {
        "json": "https://www.anchorterminal.com/compare/gpt-oss-120b-vs-kimi-k3.json",
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        "url": "https://www.anchorterminal.com/compare/gpt-oss-120b-vs-kimi-k3"
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      {
        "json": "https://www.anchorterminal.com/compare/gpt-oss-120b-vs-unlimited-ocr-2.json",
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        "url": "https://www.anchorterminal.com/compare/gpt-oss-120b-vs-unlimited-ocr-2"
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      {
        "json": "https://www.anchorterminal.com/compare/gpt-oss-20b-vs-kimi-k3.json",
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        "url": "https://www.anchorterminal.com/compare/gpt-oss-20b-vs-kimi-k3"
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      {
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      {
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        "json": "https://www.anchorterminal.com/compare/inkling-vs-kimi-k3.json",
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      {
        "json": "https://www.anchorterminal.com/compare/inkling-vs-unlimited-ocr-2.json",
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        "url": "https://www.anchorterminal.com/compare/inkling-vs-unlimited-ocr-2"
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      {
        "json": "https://www.anchorterminal.com/compare/internvl3-5-gpt-oss-20b-a4b-preview-vs-kimi-k3.json",
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        "url": "https://www.anchorterminal.com/compare/internvl3-5-gpt-oss-20b-a4b-preview-vs-kimi-k3"
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        "json": "https://www.anchorterminal.com/compare/internvl3-5-gpt-oss-20b-a4b-preview-vs-unlimited-ocr-2.json",
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        "json": "https://www.anchorterminal.com/compare/kimi-k3-vs-kolibri-1.json",
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      {
        "json": "https://www.anchorterminal.com/compare/kimi-k3-vs-kronos.json",
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        "json": "https://www.anchorterminal.com/compare/kimi-k3-vs-laguna-m-1.json",
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        "json": "https://www.anchorterminal.com/compare/kimi-k3-vs-laguna-s-2-1.json",
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        "url": "https://www.anchorterminal.com/compare/kimi-k3-vs-laguna-s-2-1"
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        "json": "https://www.anchorterminal.com/compare/kimi-k3-vs-laguna-xs-2-1.json",
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        "json": "https://www.anchorterminal.com/compare/kimi-k3-vs-lbs-27b.json",
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        "url": "https://www.anchorterminal.com/compare/kimi-k3-vs-lbs-27b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/kimi-k3-vs-lfm2-5-2-6b.json",
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        "url": "https://www.anchorterminal.com/compare/kimi-k3-vs-lfm2-5-2-6b"
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        "json": "https://www.anchorterminal.com/compare/kimi-k3-vs-ling-3-0-tiny.json",
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      {
        "json": "https://www.anchorterminal.com/compare/kimi-k3-vs-mimo-v2-6-distill-qwen-9b.json",
        "title": "Kimi K3 vs MiMo-V2.6 Distill Qwen 9B",
        "url": "https://www.anchorterminal.com/compare/kimi-k3-vs-mimo-v2-6-distill-qwen-9b"
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        "json": "https://www.anchorterminal.com/compare/kimi-k3-vs-minicpm-o-4-5.json",
        "title": "Kimi K3 vs MiniCPM-o 4.5",
        "url": "https://www.anchorterminal.com/compare/kimi-k3-vs-minicpm-o-4-5"
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        "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"
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        "json": "https://www.anchorterminal.com/compare/kimi-k3-vs-minimax-m2-5.json",
        "title": "Kimi K3 vs MiniMax-M2.5",
        "url": "https://www.anchorterminal.com/compare/kimi-k3-vs-minimax-m2-5"
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        "json": "https://www.anchorterminal.com/compare/kimi-k3-vs-minimax-m2-7.json",
        "title": "Kimi K3 vs MiniMax-M2.7",
        "url": "https://www.anchorterminal.com/compare/kimi-k3-vs-minimax-m2-7"
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        "json": "https://www.anchorterminal.com/compare/kimi-k3-vs-minimax-m3-1-flash.json",
        "title": "Kimi K3 vs MiniMax-M3.1-Flash",
        "url": "https://www.anchorterminal.com/compare/kimi-k3-vs-minimax-m3-1-flash"
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      {
        "json": "https://www.anchorterminal.com/compare/kimi-k3-vs-muse-glimmer-30b.json",
        "title": "Kimi K3 vs Muse Glimmer 30B",
        "url": "https://www.anchorterminal.com/compare/kimi-k3-vs-muse-glimmer-30b"
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        "json": "https://www.anchorterminal.com/compare/kimi-k3-vs-nanbeige-4-3-33b.json",
        "title": "Kimi K3 vs Nanbeige4.3-33B",
        "url": "https://www.anchorterminal.com/compare/kimi-k3-vs-nanbeige-4-3-33b"
      },
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        "json": "https://www.anchorterminal.com/compare/kimi-k3-vs-nemotron-3-5-bolt-e4b-4gb.json",
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        "url": "https://www.anchorterminal.com/compare/kimi-k3-vs-nemotron-3-5-bolt-e4b-4gb"
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        "json": "https://www.anchorterminal.com/compare/kimi-k3-vs-nemotron-3-5-lightning-30b-a3b.json",
        "title": "Kimi K3 vs Nemotron 3.5 Lightning 30B A3B",
        "url": "https://www.anchorterminal.com/compare/kimi-k3-vs-nemotron-3-5-lightning-30b-a3b"
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        "json": "https://www.anchorterminal.com/compare/kimi-k3-vs-nemotron-3-nano-30b-a3b.json",
        "title": "Kimi K3 vs Nemotron 3 Nano 30B A3B",
        "url": "https://www.anchorterminal.com/compare/kimi-k3-vs-nemotron-3-nano-30b-a3b"
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        "json": "https://www.anchorterminal.com/compare/kimi-k3-vs-nemotron-3-nano-4b.json",
        "title": "Kimi K3 vs Nemotron 3 Nano 4B",
        "url": "https://www.anchorterminal.com/compare/kimi-k3-vs-nemotron-3-nano-4b"
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        "json": "https://www.anchorterminal.com/compare/kimi-k3-vs-nemotron-3-nano-omni-30b-a3b-reasoning.json",
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        "url": "https://www.anchorterminal.com/compare/kimi-k3-vs-nemotron-3-nano-omni-30b-a3b-reasoning"
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        "json": "https://www.anchorterminal.com/compare/kimi-k3-vs-nemotron-3-super-120b-a12b.json",
        "title": "Kimi K3 vs Nemotron 3 Super 120B A12B",
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        "json": "https://www.anchorterminal.com/compare/kimi-k3-vs-nemotron-3-ultra-550b-a55b.json",
        "title": "Kimi K3 vs Nemotron 3 Ultra 550B A55B",
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        "json": "https://www.anchorterminal.com/compare/kimi-k3-vs-occamy-1-0.json",
        "title": "Kimi K3 vs occamy-1.0",
        "url": "https://www.anchorterminal.com/compare/kimi-k3-vs-occamy-1-0"
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        "json": "https://www.anchorterminal.com/compare/kimi-k3-vs-olmo-3-7b-think.json",
        "title": "Kimi K3 vs Olmo 3 7B Think",
        "url": "https://www.anchorterminal.com/compare/kimi-k3-vs-olmo-3-7b-think"
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        "json": "https://www.anchorterminal.com/compare/kimi-k3-vs-ornith-1-5-35b-a3b.json",
        "title": "Kimi K3 vs Ornith-1.5-35B-A3B",
        "url": "https://www.anchorterminal.com/compare/kimi-k3-vs-ornith-1-5-35b-a3b"
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      {
        "json": "https://www.anchorterminal.com/compare/kimi-k3-vs-ornith-1-5-397b.json",
        "title": "Kimi K3 vs Ornith-1.5-397B",
        "url": "https://www.anchorterminal.com/compare/kimi-k3-vs-ornith-1-5-397b"
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        "json": "https://www.anchorterminal.com/compare/kimi-k3-vs-ornith-1-5-9b.json",
        "title": "Kimi K3 vs Ornith-1.5-9B",
        "url": "https://www.anchorterminal.com/compare/kimi-k3-vs-ornith-1-5-9b"
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      {
        "json": "https://www.anchorterminal.com/compare/kimi-k3-vs-qwen3-30b-a3b-instruct-2507.json",
        "title": "Kimi K3 vs Qwen3-30B-A3B-Instruct-2507",
        "url": "https://www.anchorterminal.com/compare/kimi-k3-vs-qwen3-30b-a3b-instruct-2507"
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        "json": "https://www.anchorterminal.com/compare/kimi-k3-vs-qwen3-4b-instruct-2507.json",
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        "url": "https://www.anchorterminal.com/compare/kimi-k3-vs-qwen3-4b-instruct-2507"
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        "json": "https://www.anchorterminal.com/compare/kimi-k3-vs-qwen3-5-0-8b.json",
        "title": "Kimi K3 vs Qwen3.5-0.8B",
        "url": "https://www.anchorterminal.com/compare/kimi-k3-vs-qwen3-5-0-8b"
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        "json": "https://www.anchorterminal.com/compare/kimi-k3-vs-qwen3-5-122b-a10b.json",
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        "url": "https://www.anchorterminal.com/compare/kimi-k3-vs-qwen3-5-2b"
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        "json": "https://www.anchorterminal.com/compare/kimi-k3-vs-qwen3-5-397b-a17b.json",
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        "json": "https://www.anchorterminal.com/compare/kimi-k3-vs-qwen3-5-4b.json",
        "title": "Kimi K3 vs Qwen3.5-4B",
        "url": "https://www.anchorterminal.com/compare/kimi-k3-vs-qwen3-5-4b"
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        "json": "https://www.anchorterminal.com/compare/kimi-k3-vs-qwen3-5-9b.json",
        "title": "Kimi K3 vs Qwen3.5-9B",
        "url": "https://www.anchorterminal.com/compare/kimi-k3-vs-qwen3-5-9b"
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        "json": "https://www.anchorterminal.com/compare/kimi-k3-vs-qwen3-6-27b.json",
        "title": "Kimi K3 vs Qwen3.6-27B",
        "url": "https://www.anchorterminal.com/compare/kimi-k3-vs-qwen3-6-27b"
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        "json": "https://www.anchorterminal.com/compare/kimi-k3-vs-qwen3-6-35b-a3b.json",
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        "url": "https://www.anchorterminal.com/compare/kimi-k3-vs-qwen3-6-35b-a3b"
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        "json": "https://www.anchorterminal.com/compare/kimi-k3-vs-qwen3-8-27b.json",
        "title": "Kimi K3 vs Qwen3.8-27B",
        "url": "https://www.anchorterminal.com/compare/kimi-k3-vs-qwen3-8-27b"
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        "json": "https://www.anchorterminal.com/compare/kimi-k3-vs-qwen3-8-flash-next.json",
        "title": "Kimi K3 vs Qwen3.8-Flash-Next",
        "url": "https://www.anchorterminal.com/compare/kimi-k3-vs-qwen3-8-flash-next"
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        "json": "https://www.anchorterminal.com/compare/kimi-k3-vs-qwen3-coder-30b-a3b-instruct.json",
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        "json": "https://www.anchorterminal.com/compare/kimi-k3-vs-qwen3-coder-next.json",
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        "url": "https://www.anchorterminal.com/compare/kimi-k3-vs-qwen3-coder-next"
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        "json": "https://www.anchorterminal.com/compare/kimi-k3-vs-qwen3-omni-30b-a3b-instruct.json",
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        "json": "https://www.anchorterminal.com/compare/kimi-k3-vs-qwen3-vl-30b-a3b-instruct.json",
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        "json": "https://www.anchorterminal.com/compare/kimi-k3-vs-qwopus3-8-27b-flash-v2.json",
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        "json": "https://www.anchorterminal.com/compare/kimi-k3-vs-smollm3-3b.json",
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        "url": "https://www.anchorterminal.com/compare/lbs-27b-vs-unlimited-ocr-2"
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        "url": "https://www.anchorterminal.com/compare/mimo-v2-6-distill-qwen-9b-vs-unlimited-ocr-2"
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        "json": "https://www.anchorterminal.com/compare/minicpm5-2b-vs-unlimited-ocr-2.json",
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        "url": "https://www.anchorterminal.com/compare/minicpm5-2b-vs-unlimited-ocr-2"
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        "json": "https://www.anchorterminal.com/compare/ornith-1-5-9b-vs-unlimited-ocr-2.json",
        "title": "Ornith-1.5-9B vs Baidu Unlimited-OCR-2",
        "url": "https://www.anchorterminal.com/compare/ornith-1-5-9b-vs-unlimited-ocr-2"
      },
      {
        "json": "https://www.anchorterminal.com/compare/qwen3-30b-a3b-instruct-2507-vs-unlimited-ocr-2.json",
        "title": "Qwen3-30B-A3B-Instruct-2507 vs Baidu Unlimited-OCR-2",
        "url": "https://www.anchorterminal.com/compare/qwen3-30b-a3b-instruct-2507-vs-unlimited-ocr-2"
      },
      {
        "json": "https://www.anchorterminal.com/compare/qwen3-4b-instruct-2507-vs-unlimited-ocr-2.json",
        "title": "Qwen3-4B-Instruct-2507 vs Baidu Unlimited-OCR-2",
        "url": "https://www.anchorterminal.com/compare/qwen3-4b-instruct-2507-vs-unlimited-ocr-2"
      },
      {
        "json": "https://www.anchorterminal.com/compare/qwen3-5-0-8b-vs-unlimited-ocr-2.json",
        "title": "Qwen3.5-0.8B vs Baidu Unlimited-OCR-2",
        "url": "https://www.anchorterminal.com/compare/qwen3-5-0-8b-vs-unlimited-ocr-2"
      },
      {
        "json": "https://www.anchorterminal.com/compare/qwen3-5-122b-a10b-vs-unlimited-ocr-2.json",
        "title": "Qwen3.5-122B-A10B vs Baidu Unlimited-OCR-2",
        "url": "https://www.anchorterminal.com/compare/qwen3-5-122b-a10b-vs-unlimited-ocr-2"
      },
      {
        "json": "https://www.anchorterminal.com/compare/qwen3-5-2b-vs-unlimited-ocr-2.json",
        "title": "Qwen3.5-2B vs Baidu Unlimited-OCR-2",
        "url": "https://www.anchorterminal.com/compare/qwen3-5-2b-vs-unlimited-ocr-2"
      },
      {
        "json": "https://www.anchorterminal.com/compare/qwen3-5-397b-a17b-vs-unlimited-ocr-2.json",
        "title": "Qwen3.5-397B-A17B vs Baidu Unlimited-OCR-2",
        "url": "https://www.anchorterminal.com/compare/qwen3-5-397b-a17b-vs-unlimited-ocr-2"
      },
      {
        "json": "https://www.anchorterminal.com/compare/qwen3-5-4b-vs-unlimited-ocr-2.json",
        "title": "Qwen3.5-4B vs Baidu Unlimited-OCR-2",
        "url": "https://www.anchorterminal.com/compare/qwen3-5-4b-vs-unlimited-ocr-2"
      },
      {
        "json": "https://www.anchorterminal.com/compare/qwen3-5-9b-vs-unlimited-ocr-2.json",
        "title": "Qwen3.5-9B vs Baidu Unlimited-OCR-2",
        "url": "https://www.anchorterminal.com/compare/qwen3-5-9b-vs-unlimited-ocr-2"
      },
      {
        "json": "https://www.anchorterminal.com/compare/qwen3-6-27b-vs-unlimited-ocr-2.json",
        "title": "Qwen3.6-27B vs Baidu Unlimited-OCR-2",
        "url": "https://www.anchorterminal.com/compare/qwen3-6-27b-vs-unlimited-ocr-2"
      },
      {
        "json": "https://www.anchorterminal.com/compare/qwen3-6-35b-a3b-vs-unlimited-ocr-2.json",
        "title": "Qwen3.6-35B-A3B vs Baidu Unlimited-OCR-2",
        "url": "https://www.anchorterminal.com/compare/qwen3-6-35b-a3b-vs-unlimited-ocr-2"
      },
      {
        "json": "https://www.anchorterminal.com/compare/qwen3-8-27b-vs-unlimited-ocr-2.json",
        "title": "Qwen3.8-27B vs Baidu Unlimited-OCR-2",
        "url": "https://www.anchorterminal.com/compare/qwen3-8-27b-vs-unlimited-ocr-2"
      },
      {
        "json": "https://www.anchorterminal.com/compare/qwen3-8-flash-next-vs-unlimited-ocr-2.json",
        "title": "Qwen3.8-Flash-Next vs Baidu Unlimited-OCR-2",
        "url": "https://www.anchorterminal.com/compare/qwen3-8-flash-next-vs-unlimited-ocr-2"
      },
      {
        "json": "https://www.anchorterminal.com/compare/qwen3-coder-30b-a3b-instruct-vs-unlimited-ocr-2.json",
        "title": "Qwen3-Coder-30B-A3B-Instruct vs Baidu Unlimited-OCR-2",
        "url": "https://www.anchorterminal.com/compare/qwen3-coder-30b-a3b-instruct-vs-unlimited-ocr-2"
      },
      {
        "json": "https://www.anchorterminal.com/compare/qwen3-coder-next-vs-unlimited-ocr-2.json",
        "title": "Qwen3-Coder-Next vs Baidu Unlimited-OCR-2",
        "url": "https://www.anchorterminal.com/compare/qwen3-coder-next-vs-unlimited-ocr-2"
      },
      {
        "json": "https://www.anchorterminal.com/compare/qwen3-vl-2b-instruct-vs-unlimited-ocr-2.json",
        "title": "Qwen3-VL-2B-Instruct vs Baidu Unlimited-OCR-2",
        "url": "https://www.anchorterminal.com/compare/qwen3-vl-2b-instruct-vs-unlimited-ocr-2"
      },
      {
        "json": "https://www.anchorterminal.com/compare/qwen3-vl-30b-a3b-instruct-vs-unlimited-ocr-2.json",
        "title": "Qwen3-VL-30B-A3B-Instruct vs Baidu Unlimited-OCR-2",
        "url": "https://www.anchorterminal.com/compare/qwen3-vl-30b-a3b-instruct-vs-unlimited-ocr-2"
      },
      {
        "json": "https://www.anchorterminal.com/compare/qwen3-vl-32b-instruct-vs-unlimited-ocr-2.json",
        "title": "Qwen3-VL-32B-Instruct vs Baidu Unlimited-OCR-2",
        "url": "https://www.anchorterminal.com/compare/qwen3-vl-32b-instruct-vs-unlimited-ocr-2"
      },
      {
        "json": "https://www.anchorterminal.com/compare/qwen3-vl-4b-instruct-vs-unlimited-ocr-2.json",
        "title": "Qwen3-VL-4B-Instruct vs Baidu Unlimited-OCR-2",
        "url": "https://www.anchorterminal.com/compare/qwen3-vl-4b-instruct-vs-unlimited-ocr-2"
      },
      {
        "json": "https://www.anchorterminal.com/compare/qwen3-vl-8b-instruct-vs-unlimited-ocr-2.json",
        "title": "Qwen3-VL-8B-Instruct vs Baidu Unlimited-OCR-2",
        "url": "https://www.anchorterminal.com/compare/qwen3-vl-8b-instruct-vs-unlimited-ocr-2"
      },
      {
        "json": "https://www.anchorterminal.com/compare/qwopus3-8-27b-flash-v2-vs-unlimited-ocr-2.json",
        "title": "Qwopus3.8-27B-Flash-V2 vs Baidu Unlimited-OCR-2",
        "url": "https://www.anchorterminal.com/compare/qwopus3-8-27b-flash-v2-vs-unlimited-ocr-2"
      },
      {
        "json": "https://www.anchorterminal.com/compare/recursive-flint-vs-unlimited-ocr-2.json",
        "title": "Recursive Flint vs Baidu Unlimited-OCR-2",
        "url": "https://www.anchorterminal.com/compare/recursive-flint-vs-unlimited-ocr-2"
      },
      {
        "json": "https://www.anchorterminal.com/compare/smollm3-3b-vs-unlimited-ocr-2.json",
        "title": "SmolLM3-3B vs Baidu Unlimited-OCR-2",
        "url": "https://www.anchorterminal.com/compare/smollm3-3b-vs-unlimited-ocr-2"
      },
      {
        "json": "https://www.anchorterminal.com/compare/spark-x2-6-4b-vs-unlimited-ocr-2.json",
        "title": "Spark-X2.6-4B vs Baidu Unlimited-OCR-2",
        "url": "https://www.anchorterminal.com/compare/spark-x2-6-4b-vs-unlimited-ocr-2"
      },
      {
        "json": "https://www.anchorterminal.com/compare/swift-1-5-qwen3-8-27b-vs-unlimited-ocr-2.json",
        "title": "Swift 1.5 Qwen3.8-27B vs Baidu Unlimited-OCR-2",
        "url": "https://www.anchorterminal.com/compare/swift-1-5-qwen3-8-27b-vs-unlimited-ocr-2"
      },
      {
        "json": "https://www.anchorterminal.com/compare/swift-1-5-qwen3-8-flash-next-vs-unlimited-ocr-2.json",
        "title": "Swift 1.5 Qwen3.8-Flash-Next vs Baidu Unlimited-OCR-2",
        "url": "https://www.anchorterminal.com/compare/swift-1-5-qwen3-8-flash-next-vs-unlimited-ocr-2"
      },
      {
        "json": "https://www.anchorterminal.com/compare/thinkingcap-qwen3-8-27b-vs-unlimited-ocr-2.json",
        "title": "ThinkingCap (Qwen3.8 27B) vs Baidu Unlimited-OCR-2",
        "url": "https://www.anchorterminal.com/compare/thinkingcap-qwen3-8-27b-vs-unlimited-ocr-2"
      }
    ],
    "scores": [
      {
        "key": "capability",
        "name": "Capability",
        "pending": true,
        "weight": 35
      },
      {
        "by": 5,
        "edge": "unlimited-ocr-2",
        "key": "reach",
        "kimi-k3": 50,
        "name": "Reach",
        "unlimited-ocr-2": 55,
        "weight": 25
      },
      {
        "by": 20,
        "edge": "kimi-k3",
        "key": "risk",
        "kimi-k3": 65,
        "name": "Risk",
        "unlimited-ocr-2": 45,
        "weight": 20
      },
      {
        "by": 10,
        "edge": "unlimited-ocr-2",
        "key": "interface",
        "kimi-k3": 65,
        "name": "Agent interface",
        "unlimited-ocr-2": 75,
        "weight": 10
      },
      {
        "by": 4,
        "edge": "unlimited-ocr-2",
        "key": "upkeep",
        "kimi-k3": 41,
        "name": "Documentation and upkeep",
        "unlimited-ocr-2": 45,
        "weight": 10
      }
    ],
    "summary": "Kimi K3 scores 62.4 (B) on agent readiness against Baidu Unlimited-OCR-2's 53.5 (D), and leads in 1 of 4 scored categories. Baidu Unlimited-OCR-2 leads on reach and agent interface. Both do open-weight models you run yourself.",
    "tutorials": [],
    "verdicts": {
      "kimi-k3": "Kimi K3 is a 2.8T multimodal agent model with a 1M-token context, parallel tool calls and per-request effort, for long coding and research sessions. Its 1,561 GB of files need a multi-node GPU cluster, so most agents will call a hosted copy. The main risks are Moonshot's Python running at load and prompt time, and no answers in its repository.",
      "unlimited-ocr-2": "A small MIT document-parsing cousin that reads up to hundreds of pages in one request and returns ordered layout blocks with boxes and HTML tables. It needs an NVIDIA GPU with about 12 GB, through Baidu's remote code or its own SGLang build. The risks are running the publisher's code and accuracy figures that are Baidu's own."
    }
  },
  "kind": "anchor.page",
  "links": {
    "api": "https://www.anchorterminal.com/api/v1/index.json",
    "html": "https://www.anchorterminal.com/compare/kimi-k3-vs-unlimited-ocr-2",
    "json": "https://www.anchorterminal.com/compare/kimi-k3-vs-unlimited-ocr-2.json",
    "llms": "https://www.anchorterminal.com/llms.txt",
    "markdown": "https://www.anchorterminal.com/compare/kimi-k3-vs-unlimited-ocr-2.md",
    "mcp": "https://www.anchorterminal.com/mcp",
    "slim": "https://www.anchorterminal.com/compare/kimi-k3-vs-unlimited-ocr-2.min.md"
  },
  "markdown": "Kimi K3 scores 62.4 (B) on agent readiness against Baidu Unlimited-OCR-2's 53.5 (D), and leads in 1 of 4 scored categories. Baidu Unlimited-OCR-2 leads on reach and agent interface. Both do open-weight models you run yourself.\n\n- Kimi K3: grade B, 62.4/100, rank #30 of 113 open-weight models. Markdown https://www.anchorterminal.com/tools/kimi-k3.md · JSON https://www.anchorterminal.com/api/v1/tools/kimi-k3.json\n- Baidu Unlimited-OCR-2: grade D, 53.5/100, rank #92 of 113 open-weight models. Markdown https://www.anchorterminal.com/tools/unlimited-ocr-2.md · JSON https://www.anchorterminal.com/api/v1/tools/unlimited-ocr-2.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### Kimi K3 (B)\n\nGood for: Teams with a multi-node GPU cluster who want an open 1M-context agent model for long coding and research work\n\nAhead on:\n- Risk, 65 against 45\n\nWatch for: 1,561 GB of files at its smallest publisher build, far beyond any single machine\n\n### Baidu Unlimited-OCR-2 (D)\n\nGood for: Pipelines with an NVIDIA GPU that need long scanned or rendered documents parsed in one pass, with page order, cross-page tables and boxes kept\n\nAhead on:\n- Reach, 55 against 50\n- Agent interface, 75 against 65\n\nWatch for: Loading runs Baidu's code, remote code in Transformers or a prebuilt SGLang fork from the repository, and the save_results path calls eval on model output\n\n\n## Score by category\n\n| Category | Weight | Kimi K3 | Baidu Unlimited-OCR-2 | Edge |\n| --- | --- | --- | --- | --- |\n| Capability | 35%, pending | pending | pending | not scored in this run |\n| Reach | 25% (25 this run) | 50 | 55 | Baidu Unlimited-OCR-2 +5 |\n| Risk | 20% (20 this run) | 65 | 45 | Kimi K3 +20 |\n| Agent interface | 10% (10 this run) | 65 | 75 | Baidu Unlimited-OCR-2 +10 |\n| Documentation and upkeep | 10% (10 this run) | 41 | 45 | Baidu Unlimited-OCR-2 +4 |\n| Negative events | ≤15 | 0 | 0 | |\n| **Total** | | **62.4 · B** | **53.5 · D** | |\n\n## Facts side by side\n\n| Fact | Kimi K3 | Baidu Unlimited-OCR-2 |\n| --- | --- | --- |\n| Kind | Open-weight model | Open-weight model |\n| Vendor | Moonshot AI | Baidu |\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 | Kimi K3 License (modified MIT) | MIT (Hub metadata; the Hugging Face repository has no LICENSE file, and the GitHub code repository's LICENSE is the MIT text, copyright 2026 Baidu) |\n| Read-only variant documented | no | no |\n| llms.txt | no | no |\n| Last release | 2026-09-02 | 2026-10-26 |\n| Terms last updated | no document linked | no document linked |\n| Privacy policy last updated | no document linked | no document linked |\n| Customer content may train models |  |  |\n| Terms restrict automated access |  |  |\n| Terms restrict benchmarking |  |  |\n| Terms or service can change without notice |  |  |\n| Arbitration or class-action waiver |  |  |\n| Agent reviews | 2.3/5 (4) | none |\n\n## Verdicts\n\n**Kimi K3.** Kimi K3 is a 2.8T multimodal agent model with a 1M-token context, parallel tool calls and per-request effort, for long coding and research sessions. Its 1,561 GB of files need a multi-node GPU cluster, so most agents will call a hosted copy. The main risks are Moonshot's Python running at load and prompt time, and no answers in its repository.\n\n**Baidu Unlimited-OCR-2.** A small MIT document-parsing cousin that reads up to hundreds of pages in one request and returns ordered layout blocks with boxes and HTML tables. It needs an NVIDIA GPU with about 12 GB, through Baidu's remote code or its own SGLang build. The risks are running the publisher's code and accuracy figures that are Baidu's own.\n\n## Before you call either\n\n### Kimi K3\n\n1. Start it with SGLang on a node of 8 B300s, sglang serve --trust-remote-code --model-path moonshotai/Kimi-K3 --tp-size 8 --context-length 65536 --mem-fraction-static 0.82 --reasoning-parser kimi_k3 --tool-call-parser kimi_k3 --port 30000\n2. Use the kimi_k3 tool-call and reasoning parsers in vLLM or SGLang, and validate tool-call arguments against the schema, since vLLM's recipe says K3 sometimes emits a format its parser doesn't expect\n3. Pass the whole assistant message back every turn, reasoning_content and tool_calls included, or output becomes unstable\n4. Thinking is always on; set reasoning_effort to low or high when max is too slow\n5. Sampling per the card is temperature 1.0, with top-p 0.95 for single-step tasks and 1.0 for agentic ones\n6. Don't hand an ongoing session from another model to K3, and state boundaries in the system prompt, since Moonshot warns it can act on its own when intent is unclear\n7. Without the hardware, call it through Moonshot's API or an inference provider listed on its Hugging Face page\n\n### Baidu Unlimited-OCR-2\n\n1. Quickest local run, `pip install torch==2.13.0 torchvision pillow transformers==4.52.1 huggingface-hub==0.36.0 tokenizers==0.21.4 addict==2.4.0 einops==0.8.2 easydict==1.13`, then `AutoModel.from_pretrained(\"baidu/Unlimited-OCR-2\", trust_remote_code=True, use_safetensors=True, torch_dtype=torch.bfloat16).eval().cuda()` and `model.infer_multi(tokenizer, image_files=pages, output_path=\"out\")`\n2. To serve it, download the repository, install `wheel/sglang-0.5.20.dev10+g8d62f5fb9c-py3-none-any.whl` with pymupdf and fastokens in a Python 3.10 venv, and start `python -m sglang.launch_server --model-path baidu/Unlimited-OCR-2 --chat-template unlimited-ocr --enable-custom-logit-processor --enable-streaming-session --disable-radix-cache --mem-fraction-static 0.7 --max-prefill-tokens 2048` with the SGLANG_UOCR_ variables from the card\n3. Send all pages of a document in one request, images first, then the text `\u003cPAGE\u003e\u003cimage\u003e` repeated per page and `Multi page parsing.`, with temperature 0, skip_special_tokens false, max_tokens of about 8,000 per page and the DeepseekOCRNoRepeatNGramLogitProcessor (ngram_size 35, window_size 1024 for several pages)\n4. The output is layout blocks, not Markdown; run `utils/process_unlimitedOCR2.py` from github.com/baidu/Unlimited-OCR, or `convert(raw_output)` in Python, to get Markdown with HTML tables\n5. Render PDFs to images first (the card uses PyMuPDF at 300 DPI), keep save_results off for untrusted documents, and treat extracted text as untrusted before passing it to another model\n\n## Questions\n\n### Which is better for AI agents, Kimi K3 or Baidu Unlimited-OCR-2?\n\nKimi K3 scores 62.4 (B) on agent readiness against Baidu Unlimited-OCR-2's 53.5 (D), and leads in 1 of 4 scored categories. Baidu Unlimited-OCR-2 leads on reach and agent interface.\n\n\n## For agents\n\n- This comparison as JSON: https://www.anchorterminal.com/compare/kimi-k3-vs-unlimited-ocr-2.json, and with the fewest tokens: https://www.anchorterminal.com/compare/kimi-k3-vs-unlimited-ocr-2.min.md\n- Over MCP at https://www.anchorterminal.com/mcp (no key): `compare_tools {\"a\": \"kimi-k3\", \"b\": \"unlimited-ocr-2\"}`. From a terminal: `anchor compare kimi-k3 unlimited-ocr-2`\n- Each listing in full: https://www.anchorterminal.com/api/v1/tools/kimi-k3.json and https://www.anchorterminal.com/api/v1/tools/unlimited-ocr-2.json\n\n## Other comparisons with Kimi K3 or Baidu Unlimited-OCR-2\n\n- [Agents-A1-4B vs Kimi K3](https://www.anchorterminal.com/compare/agents-a1-4b-vs-kimi-k3.md)\n- [Agents-A1-4B vs Baidu Unlimited-OCR-2](https://www.anchorterminal.com/compare/agents-a1-4b-vs-unlimited-ocr-2.md)\n- [Apertus v1.5 8B vs Kimi K3](https://www.anchorterminal.com/compare/apertus-v1-5-8b-vs-kimi-k3.md)\n- [Apertus v1.5 8B vs Baidu Unlimited-OCR-2](https://www.anchorterminal.com/compare/apertus-v1-5-8b-vs-unlimited-ocr-2.md)\n- [Apodex-1.1-mini vs Kimi K3](https://www.anchorterminal.com/compare/apodex-1-1-mini-vs-kimi-k3.md)\n- [Apodex-1.1-mini vs Baidu Unlimited-OCR-2](https://www.anchorterminal.com/compare/apodex-1-1-mini-vs-unlimited-ocr-2.md)\n- [BigBang-v1 vs Kimi K3](https://www.anchorterminal.com/compare/bigbang-v1-vs-kimi-k3.md)\n- [BigBang-v1 vs Baidu Unlimited-OCR-2](https://www.anchorterminal.com/compare/bigbang-v1-vs-unlimited-ocr-2.md)\n- [Carbon-X vs Kimi K3](https://www.anchorterminal.com/compare/carbon-x-vs-kimi-k3.md)\n- [Carbon-X vs Baidu Unlimited-OCR-2](https://www.anchorterminal.com/compare/carbon-x-vs-unlimited-ocr-2.md)\n- [Cosmos-Reason2-2B vs Kimi K3](https://www.anchorterminal.com/compare/cosmos-reason2-2b-vs-kimi-k3.md)\n- [Cosmos-Reason2-2B vs Baidu Unlimited-OCR-2](https://www.anchorterminal.com/compare/cosmos-reason2-2b-vs-unlimited-ocr-2.md)\n- [Darwin-36B-Opus vs Kimi K3](https://www.anchorterminal.com/compare/darwin-36b-opus-vs-kimi-k3.md)\n- [Darwin-36B-Opus vs Baidu Unlimited-OCR-2](https://www.anchorterminal.com/compare/darwin-36b-opus-vs-unlimited-ocr-2.md)\n- [DeepSeek-V3.2 vs Kimi K3](https://www.anchorterminal.com/compare/deepseek-v3-2-vs-kimi-k3.md)\n- [DeepSeek-V3.2 vs Baidu 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      {
        "name": "Kimi K3 vs Baidu Unlimited-OCR-2",
        "url": ""
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    ],
    "description": "Kimi K3 scores 62.4 (B) to Baidu Unlimited-OCR-2's 53.5 (D) for open-weight models you run yourself. Prices, MCP, x402, uptime and agent notes side by side.",
    "facts": [
      "Kimi K3 B 62.4",
      "Baidu Unlimited-OCR-2 D 53.5",
      "scores"
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    "h1": "Kimi K3 vs Baidu Unlimited-OCR-2",
    "image": "https://www.anchorterminal.com/assets/og/compare-kimi-k3-vs-unlimited-ocr-2.png",
    "path": "/compare/kimi-k3-vs-unlimited-ocr-2",
    "published": "2026-10-01",
    "section": "tools",
    "title": "Kimi K3 vs Baidu Unlimited-OCR-2 for AI agents (2026)",
    "toc": null,
    "updated": "2026-10-27",
    "url": "https://www.anchorterminal.com/compare/kimi-k3-vs-unlimited-ocr-2"
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