{ "data": { "a": { "slug": "gpt-oss-20b", "name": "gpt-oss-20b", "vendor": "OpenAI", "vendorUrl": "https://openai.com", "kind": "weights", "category": "open-weights", "summary": "gpt-oss-20b is OpenAI's open-weight mixture-of-experts reasoning model, 21B parameters with 3.6B active and a 131,072-token context, published on Hugging Face in MXFP4 under Apache 2.0 and trained on the harmony prompt format.", "url": "https://www.anchorterminal.com/tools/gpt-oss-20b", "markdownUrl": "https://www.anchorterminal.com/tools/gpt-oss-20b.md", "slimMarkdownUrl": "https://www.anchorterminal.com/tools/gpt-oss-20b.min.md", "jsonUrl": "https://www.anchorterminal.com/api/v1/tools/gpt-oss-20b.json", "repo": "https://huggingface.co/openai/gpt-oss-20b", "license": "Apache-2.0", "transports": [], "packages": [ { "registry": "huggingface", "name": "openai/gpt-oss-20b" }, { "registry": "ollama", "name": "gpt-oss:20b" }, { "registry": "pypi", "name": "gpt-oss" }, { "registry": "pypi", "name": "openai-harmony" } ], "auth": "none", "authNotes": "The weights download from Hugging Face with no account, token or terms to accept. The repository is not gated (checked 2026-10-21).", "pricing": "free", "pricingNotes": "Free to download and use, commercial use included, under Apache 2.0 with a one-line usage policy that asks users to comply with applicable law. Running it yourself costs the hardware, about 13.8 GB of weights, and OpenAI says it runs within 16 GB of memory (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/openai/gpt-oss-20b", "capabilities": [ "model.open-weights" ], "tags": [ "open-weights", "model", "moe", "reasoning", "tool-calling", "apache-2.0", "safetensors", "mxfp4", "self-hosted" ], "lastRelease": "2025-08-26", "graded": true, "anchor": { "graded": true, "score": 69.9, "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": 6, "methodology": "0.6", "run": "2026-10-01", "scores": { "capability": 49, "interface": 90, "reach": 90, "risk": 85, "upkeep": 42 }, "pending": [ "performance", "tasks" ], "assessment": { "confidence": "high", "date": "2026-10-21" }, "negative": 0, "verdict": "gpt-oss-20b is a cousin for reasoning, coding and single tool calls with structured output, under plain Apache 2.0. It needs about 17 GB with a working context, and five inference providers serve it. The main risks are that it trails o4-mini at keeping system instructions above user ones, and OpenAI hasn't answered a report since August 2025.", "bestFor": "Local agents on a 24 GB GPU or Mac that want a permissive licence, wide runtime support and documented structured output, one tool call at a time", "strengths": [ "Model code in released Transformers, vLLM, SGLang and llama.cpp, plus a 14 GB build in Ollama's library", "Fits a 24 GB machine at OpenAI's own MXFP4 precision, the one every evaluation used", "Apache 2.0 with no gate, no account and a usage policy that only asks users to follow the law", "Harmony guide documents tool declarations, call parsing, JSON Schema output and three reasoning levels, with OpenAI's own parser", "Trained on an instruction hierarchy against prompt injection, with OpenAI's results for it published" ], "weaknesses": [ "No reply from OpenAI to any discussion since August 2025, and template reports wait unanswered", "One tool call per message", "Reasoning can be lowered but not switched off", "Only one quantised build from OpenAI, and its weights and template haven't changed since August 2025", "Safety results for this size are OpenAI's own, and it trails o4-mini on the instruction hierarchy" ], "agentNotes": [ "Start it with `ollama run gpt-oss:20b` (the build that fits the reference machine), or `vllm serve openai/gpt-oss-20b` with a current vLLM release rather than the card's pinned vllm==0.10.1+gptoss wheel", "Use the harmony format through the chat template or openai-harmony; OpenAI says the model doesn't work correctly without it", "Parse tool calls and reasoning with openai-harmony; calls come on the commentary channel ending in `\u003c|call|\u003e`, reasoning on the analysis channel", "Set effort with `Reasoning: high` (or low, medium) in the system message, or `reasoning_effort` in the template; medium is the default", "Ask for JSON by putting a JSON Schema under `# Response Formats` in the developer message", "Drop earlier reasoning after a final answer but pass it back after tool calls, and don't show the analysis channel to users", "Expect one tool call per turn; run several in sequence rather than in parallel" ], "metrics": { "kind": "local", "measured": false }, "reviewCount": 4, "avgRating": 3.5, "history": [ { "basis": "public evidence", "confidence": "high", "grade": "B", "methodology": "0.6", "pending": [ "performance", "tasks" ], "run": "2026-10-01", "runLabel": "October 2026 research run", "score": 69.9 } ], "editorialScores": { "capability": 49, "interface": 90, "reach": 90, "risk": 85, "upkeep": 42 }, "provenanceScore": 87, "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 gpt-oss:20b\n# or with vLLM:\nvllm serve openai/gpt-oss-20b", "http": "curl http://localhost:11434/api/chat \\\n -d '{\"model\": \"gpt-oss:20b\", \"messages\": [{\"role\": \"user\", \"content\": \"Hello!\"}]}'" }, "letme": { "capability": "https://letme.dev/model.open-weights", "tool": "https://letme.dev/gpt-oss-20b" }, "sameCompany": [ "openai-api", "openai-embeddings", "openai-guardrails", "openai-moderation", "openai-image-api", "openai-sora", "openai-speech-to-text", "gpt-live", "openai-realtime", "openai-agents-sdk", "openai-decisions-api", "openai-codex", "gpt-oss-120b" ], "weights": { "trainedBy": "OpenAI", "params": "20.91B", "active": "3.61B", "context": 131072, "goodFor": "Text reasoning model for agents and coding, with function calling, built-in browser and Python tools and low, medium or high reasoning, in the harmony format.", "runtimes": [ "llama.cpp", "Ollama", "vLLM", "SGLang", "Transformers" ], "builds": [ { "name": "gpt-oss-20b", "url": "https://huggingface.co/openai/gpt-oss-20b", "who": "publisher", "precision": "mxfp4", "sizeGB": 13.8, "memoryGB": 24, "format": "safetensors", "note": "MoE weights in MXFP4, the rest BF16, the precision OpenAI evaluated. original/ and metal/ hold the same weights for OpenAI's reference code. vLLM's gpt-oss recipe lists MI300x, MI325x, MI355x and Radeon AI PRO R9700 on AMD, not gfx1151" }, { "name": "ollama gpt-oss:20b", "url": "https://ollama.com/library/gpt-oss:20b", "who": "ollama", "precision": "mxfp4", "sizeGB": 14, "memoryGB": 24, "format": "ollama", "runsOn": [ "Ollama" ], "note": "OpenAI's MXFP4 weights; the card links it. 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 gpt-oss:20b", "runBuild": "ollama gpt-oss:20b", "checked": "2026-10-21", "minMemoryGB": 24 }, "family": { "lab": "OpenAI", "family": "gpt-oss", "url": "https://www.anchorterminal.com/open-weights/#openai", "others": [ { "name": "gpt-oss-120b", "url": "https://huggingface.co/openai/gpt-oss-120b", "params": "117B total, 5.1B active (MoE)", "listing": "https://www.anchorterminal.com/tools/gpt-oss-120b" }, { "name": "gpt-oss-safeguard-120b", "url": "https://huggingface.co/openai/gpt-oss-safeguard-120b", "params": "117B total, 5.1B active (MoE)" }, { "name": "gpt-oss-safeguard-20b", "url": "https://huggingface.co/openai/gpt-oss-safeguard-20b", "params": "21B total, 3.6B active (MoE)" } ], "olderCount": 6, "unrestrictedCopies": 5 }, "area": "models", "provenance": { "legalEntity": "OpenAI (named in USAGE_POLICY and the model card; the LICENSE file's copyright line is the unfilled Apache template)", "domain": "openai.com", "domainRegistered": "2007-01-19", "domainNote": "openai.com was registered in 2007, years before the company was founded in 2015, so domain age flatters it.", "endpointOnVendorDomain": null, "terms": "", "privacy": "", "statusPage": "", "changelog": "https://huggingface.co/openai/gpt-oss-20b/commits/main", "securityTxt": "valid", "checked": "2026-10-21", "notes": [ "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 for some commits (the chat template on 7 and 8 August 2025, `\u003c|call|\u003e` as an end token on 13 August 2025) and not for others (README updates).", "openai.com/.well-known/security.txt answered 200, signed, with a Bugcrowd contact and a coordinated disclosure policy, but no Expires field, which RFC 9116 requires. Recorded as valid, as on the openai-api listing, since the data has no value for a file without one.", "openai.com/index/introducing-gpt-oss/ and openai.com/open-models/ answered 403 to our reader on 21 October 2026, so OpenAI's announcement wasn't read." ], "score": 87 }, "pageJsonUrl": "https://www.anchorterminal.com/tools/gpt-oss-20b.json", "live": { "slug": "gpt-oss-20b", "versions": [ { "registry": "pypi", "name": "gpt-oss", "version": "0.0.9", "released": "2026-01-13", "seenAt": "2026-10-27T11:03:25.725082435Z" }, { "registry": "pypi", "name": "openai-harmony", "version": "0.0.8", "released": "2025-11-05", "seenAt": "2026-10-27T11:03:27.759075229Z" } ], "pypiWeekly": 9305, "securityTxt": { "url": "https://openai.com/.well-known/security.txt", "state": "valid", "checkedAt": "2026-10-27T15:31:50.51115922Z" }, "domain": { "domain": "openai.com", "registered": "2007-01-19", "source": "https://rdap.verisign.com/com/v1/domain/openai.com", "checkedAt": "2026-10-25T14:03:43.431333965Z" }, "pages": [ { "url": "https://huggingface.co/openai/gpt-oss-20b/commits/main", "kind": "changelog", "status": 200, "checkedAt": "2026-10-27T03:49:03.686194204Z", "changedAt": "2026-10-27T03:49:03.686194204Z", "fingerprint": "7a2a5e95002f" } ], "updatedAt": "2026-10-27T15:31:50.51115922Z" } }, "answer": "gpt-oss-20b scores 69.9 (B) on agent readiness against Baidu Unlimited-OCR-2's 53.5 (D), and leads in 3 of 4 scored categories.", "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": "OpenAI", "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": "Apache-2.0", "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": "2025-08-26", "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": "3.5/5 (4)", "b": "none", "name": "Agent reviews" } ], "faq": [ { "answer": "gpt-oss-20b scores 69.9 (B) on agent readiness against Baidu Unlimited-OCR-2's 53.5 (D), and leads in 3 of 4 scored categories.", "question": "Which is better for AI agents, gpt-oss-20b or Baidu Unlimited-OCR-2?" } ], "goodFor": [ { 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Unlimited-OCR-2", "url": "https://www.anchorterminal.com/compare/gemma-4-e4b-it-vs-unlimited-ocr-2" }, { "json": "https://www.anchorterminal.com/compare/glm-4-5-air-vs-gpt-oss-20b.json", "title": "GLM-4.5-Air vs gpt-oss-20b", "url": "https://www.anchorterminal.com/compare/glm-4-5-air-vs-gpt-oss-20b" }, { "json": "https://www.anchorterminal.com/compare/glm-4-5-air-vs-unlimited-ocr-2.json", "title": "GLM-4.5-Air vs Baidu Unlimited-OCR-2", "url": "https://www.anchorterminal.com/compare/glm-4-5-air-vs-unlimited-ocr-2" }, { "json": "https://www.anchorterminal.com/compare/glm-4-7-flash-vs-gpt-oss-20b.json", "title": "GLM-4.7-Flash vs gpt-oss-20b", "url": "https://www.anchorterminal.com/compare/glm-4-7-flash-vs-gpt-oss-20b" }, { "json": "https://www.anchorterminal.com/compare/glm-4-7-flash-vs-unlimited-ocr-2.json", "title": "GLM-4.7-Flash vs Baidu Unlimited-OCR-2", "url": "https://www.anchorterminal.com/compare/glm-4-7-flash-vs-unlimited-ocr-2" }, { "json": 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"url": "https://www.anchorterminal.com/compare/gpt-oss-20b-vs-qwen3-30b-a3b-instruct-2507" }, { "json": "https://www.anchorterminal.com/compare/gpt-oss-20b-vs-qwen3-4b-instruct-2507.json", "title": "gpt-oss-20b vs Qwen3-4B-Instruct-2507", "url": "https://www.anchorterminal.com/compare/gpt-oss-20b-vs-qwen3-4b-instruct-2507" }, { "json": "https://www.anchorterminal.com/compare/gpt-oss-20b-vs-qwen3-5-0-8b.json", "title": "gpt-oss-20b vs Qwen3.5-0.8B", "url": "https://www.anchorterminal.com/compare/gpt-oss-20b-vs-qwen3-5-0-8b" }, { "json": "https://www.anchorterminal.com/compare/gpt-oss-20b-vs-qwen3-5-122b-a10b.json", "title": "gpt-oss-20b vs Qwen3.5-122B-A10B", "url": "https://www.anchorterminal.com/compare/gpt-oss-20b-vs-qwen3-5-122b-a10b" }, { "json": "https://www.anchorterminal.com/compare/gpt-oss-20b-vs-qwen3-5-2b.json", "title": "gpt-oss-20b vs Qwen3.5-2B", "url": "https://www.anchorterminal.com/compare/gpt-oss-20b-vs-qwen3-5-2b" }, { "json": 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"json": "https://www.anchorterminal.com/compare/ling-3-0-tiny-vs-unlimited-ocr-2.json", "title": "Ling-3.0-tiny vs Baidu Unlimited-OCR-2", "url": "https://www.anchorterminal.com/compare/ling-3-0-tiny-vs-unlimited-ocr-2" }, { "json": "https://www.anchorterminal.com/compare/mimo-v2-6-distill-qwen-9b-vs-unlimited-ocr-2.json", "title": "MiMo-V2.6 Distill Qwen 9B vs Baidu Unlimited-OCR-2", "url": "https://www.anchorterminal.com/compare/mimo-v2-6-distill-qwen-9b-vs-unlimited-ocr-2" }, { "json": "https://www.anchorterminal.com/compare/minicpm-o-4-5-vs-unlimited-ocr-2.json", "title": "MiniCPM-o 4.5 vs Baidu Unlimited-OCR-2", "url": "https://www.anchorterminal.com/compare/minicpm-o-4-5-vs-unlimited-ocr-2" }, { "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" }, { "json": 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"title": "Nanbeige4.3-33B vs Baidu Unlimited-OCR-2", "url": "https://www.anchorterminal.com/compare/nanbeige-4-3-33b-vs-unlimited-ocr-2" }, { "json": "https://www.anchorterminal.com/compare/nemotron-3-5-bolt-e4b-4gb-vs-unlimited-ocr-2.json", "title": "NVIDIA Nemotron 3.5 Bolt E4B 4GB vs Baidu Unlimited-OCR-2", "url": "https://www.anchorterminal.com/compare/nemotron-3-5-bolt-e4b-4gb-vs-unlimited-ocr-2" }, { "json": "https://www.anchorterminal.com/compare/nemotron-3-5-lightning-30b-a3b-vs-unlimited-ocr-2.json", "title": "Nemotron 3.5 Lightning 30B A3B vs Baidu Unlimited-OCR-2", "url": "https://www.anchorterminal.com/compare/nemotron-3-5-lightning-30b-a3b-vs-unlimited-ocr-2" }, { "json": "https://www.anchorterminal.com/compare/nemotron-3-nano-30b-a3b-vs-unlimited-ocr-2.json", "title": "Nemotron 3 Nano 30B A3B vs Baidu Unlimited-OCR-2", "url": "https://www.anchorterminal.com/compare/nemotron-3-nano-30b-a3b-vs-unlimited-ocr-2" }, { "json": 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"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": 35, "edge": "gpt-oss-20b", "gpt-oss-20b": 90, "key": "reach", "name": "Reach", "unlimited-ocr-2": 55, "weight": 25 }, { "by": 40, "edge": "gpt-oss-20b", "gpt-oss-20b": 85, "key": "risk", "name": "Risk", "unlimited-ocr-2": 45, "weight": 20 }, { "by": 15, "edge": "gpt-oss-20b", "gpt-oss-20b": 90, "key": "interface", "name": "Agent interface", "unlimited-ocr-2": 75, "weight": 10 }, { "by": 3, "edge": "unlimited-ocr-2", "gpt-oss-20b": 42, "key": "upkeep", "name": "Documentation and upkeep", "unlimited-ocr-2": 45, "weight": 10 } ], "summary": "gpt-oss-20b scores 69.9 (B) on agent readiness against Baidu Unlimited-OCR-2's 53.5 (D), and leads in 3 of 4 scored categories. Both do open-weight models you run yourself.", "tutorials": [], "verdicts": { "gpt-oss-20b": "gpt-oss-20b is a cousin for reasoning, coding and single tool calls with structured output, under plain Apache 2.0. It needs about 17 GB with a working context, and five inference providers serve it. The main risks are that it trails o4-mini at keeping system instructions above user ones, and OpenAI hasn't answered a report since August 2025.", "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/gpt-oss-20b-vs-unlimited-ocr-2", "json": "https://www.anchorterminal.com/compare/gpt-oss-20b-vs-unlimited-ocr-2.json", "llms": "https://www.anchorterminal.com/llms.txt", "markdown": "https://www.anchorterminal.com/compare/gpt-oss-20b-vs-unlimited-ocr-2.md", "mcp": "https://www.anchorterminal.com/mcp", "slim": "https://www.anchorterminal.com/compare/gpt-oss-20b-vs-unlimited-ocr-2.min.md" }, "markdown": "gpt-oss-20b scores 69.9 (B) on agent readiness against Baidu Unlimited-OCR-2's 53.5 (D), and leads in 3 of 4 scored categories. Both do open-weight models you run yourself.\n\n- gpt-oss-20b: grade B, 69.9/100, rank #8 of 113 open-weight models. Markdown https://www.anchorterminal.com/tools/gpt-oss-20b.md · JSON https://www.anchorterminal.com/api/v1/tools/gpt-oss-20b.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### gpt-oss-20b (B)\n\nGood for: Local agents on a 24 GB GPU or Mac that want a permissive licence, wide runtime support and documented structured output, one tool call at a time\n\nAhead on:\n- Reach, 90 against 55\n- Risk, 85 against 45\n- Agent interface, 90 against 75\n\nWatch for: No reply from OpenAI to any discussion since August 2025, and template reports wait unanswered\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\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 | gpt-oss-20b | Baidu Unlimited-OCR-2 | Edge |\n| --- | --- | --- | --- | --- |\n| Capability | 35%, pending | pending | pending | not scored in this run |\n| Reach | 25% (25 this run) | 90 | 55 | gpt-oss-20b +35 |\n| Risk | 20% (20 this run) | 85 | 45 | gpt-oss-20b +40 |\n| Agent interface | 10% (10 this run) | 90 | 75 | gpt-oss-20b +15 |\n| Documentation and upkeep | 10% (10 this run) | 42 | 45 | Baidu Unlimited-OCR-2 +3 |\n| Negative events | ≤15 | 0 | 0 | |\n| **Total** | | **69.9 · B** | **53.5 · D** | |\n\n## Facts side by side\n\n| Fact | gpt-oss-20b | Baidu Unlimited-OCR-2 |\n| --- | --- | --- |\n| Kind | Open-weight model | Open-weight model |\n| Vendor | OpenAI | 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 | Apache-2.0 | 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 | 2025-08-26 | 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 | 3.5/5 (4) | none |\n\n## Verdicts\n\n**gpt-oss-20b.** gpt-oss-20b is a cousin for reasoning, coding and single tool calls with structured output, under plain Apache 2.0. It needs about 17 GB with a working context, and five inference providers serve it. The main risks are that it trails o4-mini at keeping system instructions above user ones, and OpenAI hasn't answered a report since August 2025.\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### gpt-oss-20b\n\n1. Start it with `ollama run gpt-oss:20b` (the build that fits the reference machine), or `vllm serve openai/gpt-oss-20b` with a current vLLM release rather than the card's pinned vllm==0.10.1+gptoss wheel\n2. Use the harmony format through the chat template or openai-harmony; OpenAI says the model doesn't work correctly without it\n3. Parse tool calls and reasoning with openai-harmony; calls come on the commentary channel ending in `\u003c|call|\u003e`, reasoning on the analysis channel\n4. Set effort with `Reasoning: high` (or low, medium) in the system message, or `reasoning_effort` in the template; medium is the default\n5. Ask for JSON by putting a JSON Schema under `# Response Formats` in the developer message\n6. Drop earlier reasoning after a final answer but pass it back after tool calls, and don't show the analysis channel to users\n7. Expect one tool call per turn; run several in sequence rather than in parallel\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, gpt-oss-20b or Baidu Unlimited-OCR-2?\n\ngpt-oss-20b scores 69.9 (B) on agent readiness against Baidu Unlimited-OCR-2's 53.5 (D), and leads in 3 of 4 scored categories.\n\n\n## For agents\n\n- This comparison as JSON: https://www.anchorterminal.com/compare/gpt-oss-20b-vs-unlimited-ocr-2.json, and with the fewest tokens: https://www.anchorterminal.com/compare/gpt-oss-20b-vs-unlimited-ocr-2.min.md\n- Over MCP at https://www.anchorterminal.com/mcp (no key): `compare_tools {\"a\": \"gpt-oss-20b\", \"b\": \"unlimited-ocr-2\"}`. From a terminal: `anchor compare gpt-oss-20b unlimited-ocr-2`\n- Each listing in full: https://www.anchorterminal.com/api/v1/tools/gpt-oss-20b.json and https://www.anchorterminal.com/api/v1/tools/unlimited-ocr-2.json\n\n## Other comparisons with gpt-oss-20b or Baidu Unlimited-OCR-2\n\n- [Agents-A1-4B vs gpt-oss-20b](https://www.anchorterminal.com/compare/agents-a1-4b-vs-gpt-oss-20b.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 gpt-oss-20b](https://www.anchorterminal.com/compare/apertus-v1-5-8b-vs-gpt-oss-20b.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 gpt-oss-20b](https://www.anchorterminal.com/compare/apodex-1-1-mini-vs-gpt-oss-20b.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 gpt-oss-20b](https://www.anchorterminal.com/compare/bigbang-v1-vs-gpt-oss-20b.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 gpt-oss-20b](https://www.anchorterminal.com/compare/carbon-x-vs-gpt-oss-20b.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 gpt-oss-20b](https://www.anchorterminal.com/compare/cosmos-reason2-2b-vs-gpt-oss-20b.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 gpt-oss-20b](https://www.anchorterminal.com/compare/darwin-36b-opus-vs-gpt-oss-20b.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 gpt-oss-20b](https://www.anchorterminal.com/compare/deepseek-v3-2-vs-gpt-oss-20b.md)\n- 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