{ "data": { "a": { "slug": "carbon-x", "name": "Carbon-X", "vendor": "Hugging Face (HuggingFaceBio)", "vendorUrl": "https://huggingface.co/HuggingFaceBio", "kind": "weights", "category": "open-weights", "summary": "Carbon-X is Hugging Face's open-weight 14.8B language model for DNA, a fine-tune of Qwen3-14B that reads raw DNA in a chat and answers in English about variant effects and regulatory regions, with a 40,960-token context, under Apache 2.0.", "url": "https://www.anchorterminal.com/tools/carbon-x", "markdownUrl": "https://www.anchorterminal.com/tools/carbon-x.md", "slimMarkdownUrl": "https://www.anchorterminal.com/tools/carbon-x.min.md", "jsonUrl": "https://www.anchorterminal.com/api/v1/tools/carbon-x.json", "repo": "https://huggingface.co/HuggingFaceBio/Carbon-X", "license": "Apache-2.0", "transports": [], "packages": [ { "registry": "huggingface", "name": "HuggingFaceBio/Carbon-X" }, { "registry": "huggingface", "name": "HuggingFaceBio/Carbon-X-GGUF" } ], "auth": "none", "authNotes": "The weights download from Hugging Face with no account, token or terms to accept. The Hub reports gated false for HuggingFaceBio/Carbon-X and HuggingFaceBio/Carbon-X-GGUF (checked 2026-10-23). The Python tokenizer fetches Qwen/Qwen3-4B-Base's tokenizer at a pinned revision on first load, which is also ungated.", "pricing": "free", "pricingNotes": "Free to download and use, commercial use included, under Apache 2.0, and the base Qwen3-14B is Apache 2.0 too. Hugging Face sells no per-call access to it and no inference provider serves it. Running it costs the hardware, 29.6 GB for the BF16 safetensors and 9.6 GB for the publisher's smallest GGUF, Q4_K_M (checked 2026-10-23).", "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 2026-10-23).", "endpoints": [] }, "toolCount": null, "popularity": { "githubStars": null, "npmWeekly": null, "pypiWeekly": null, "asOf": "2026-10-23" }, "docsUrl": "https://huggingface.co/HuggingFaceBio/Carbon-X", "capabilities": [ "model.open-weights" ], "tags": [ "open-weights", "model", "dense", "dna", "genomics", "biology", "fine-tune", "apache-2.0", "safetensors", "gguf", "self-hosted" ], "lastRelease": "2026-10-22", "graded": true, "anchor": { "graded": true, "score": 61, "grade": "C", "agentReady": false, "rank": 0, "ranked": false, "notRankedWhy": "An open-weight model, graded by the open-weight checklist and ranked among open-weight models, not against tools", "rankOf": 1217, "categoryRank": 30, "methodology": "0.6", "run": "2026-10-01", "scores": { "interface": 35, "reach": 90, "risk": 65, "upkeep": 77 }, "pending": [ "performance", "tasks" ], "assessment": { "confidence": "low", "date": "2026-10-23" }, "negative": 0, "verdict": "A DNA specialist cousin that another agent calls for variant-effect and sequence questions, with DNA kept on the machine. Hugging Face's Q4_K_M GGUF needs about 12 GB and Q8_0 about 19 GB, on llama.cpp b11742 or later. It isn't clinically validated, it isn't trained for tool calls or reasoning, and the card contradicts its own GGUF repository on llama.cpp support.", "bestFor": "Agents that need a second opinion on DNA variants and regulatory regions on a 16 to 24 GB machine, without sending sequences to a hosted model.", "strengths": [ "Hugging Face's own GGUFs at four precisions, the smallest about 12 GB with a fifth added", "Runs in released llama.cpp, vLLM, SGLang and Transformers", "Apache 2.0 on the model and its Qwen3-14B base, nothing gated", "A ready-made skill, an OpenAI-style tool example and an Inspect example for calling it from another agent", "Mid-training data listed by source with shares of 302B tokens" ], "weaknesses": [ "Not clinically validated and no wet-lab validation reported", "The Python tokenizer needs trust_remote_code, and llama.cpp before b11742 tokenizes DNA wrongly", "Not trained for tool calling, structured output or reasoning", "The card says llama.cpp is unsupported while the publisher's GGUF repository says it is", "No inference provider or hosted API, and no knowledge cut-off" ], "agentNotes": [ "Quickest start is `llama-server -hf HuggingFaceBio/Carbon-X-GGUF:Q8_0 -ngl 99 -c 40960 --jinja --chat-template-kwargs '{\"enable_thinking\": false}' --temp 0.6 --top-p 0.95 --top-k 20 --min-p 0`, on llama.cpp b11742 or later", "With vLLM or Transformers pass trust_remote_code, and expect the tokenizer to fetch Qwen/Qwen3-4B-Base at a pinned revision on first load", "Keep enable_thinking false and the card's sampling (temperature 0.6, top_p 0.95, top_k 20), the settings every reported result used", "Keep DNA in files and pass sequences by name, compute positions and base changes in code and send them as context, the card says the model miscounts long sequences", "Only A, C, G and T form 6-mers, so filter N and other IUPAC codes first or they become a single oov token", "Strip the dna tags from answers if you need bare sequence, llama.cpp keeps them in the text", "Cap max_tokens for next-base questions, long DNA generation is slow and degrades" ], "metrics": { "kind": "local", "measured": false }, "reviewCount": 4, "avgRating": 3, "history": [ { "basis": "public evidence", "confidence": "low", "grade": "C", "methodology": "0.6", "pending": [ "performance", "tasks" ], "run": "2026-10-01", "runLabel": "October 2026 research run", "score": 61 } ], "editorialScores": { "interface": 35, "reach": 90, "risk": 65, "upkeep": 77 }, "provenanceScore": 53, "checked": { "categories": { "interface": "2026-10-23", "reach": "2026-10-23", "risk": "2026-10-23", "upkeep": "2026-10-23" }, "last": "2026-10-23", "oldest": "2026-10-23", "stale": false, "staleAfterDays": 90 } }, "connect": { "install": "# llama.cpp b11742 or later (older builds tokenize DNA wrongly):\nllama-server -hf HuggingFaceBio/Carbon-X-GGUF:Q8_0 -ngl 99 -c 40960 --jinja \\\n --chat-template-kwargs '{\"enable_thinking\": false}' \\\n --temp 0.6 --top-p 0.95 --top-k 20 --min-p 0 --port 8080\n# or, with vLLM:\nvllm serve HuggingFaceBio/Carbon-X --trust-remote-code", "http": "curl http://localhost:8080/v1/chat/completions -H 'Content-Type: application/json' \\\n -d '{\"messages\": [{\"role\": \"user\", \"content\": \"Is this sequence more likely coding or non-coding? ATGGCGCTGTGGATGCGCCTCCTG\"}]}'" }, "letme": { "capability": "https://letme.dev/model.open-weights", "tool": "https://letme.dev/carbon-x" }, "sameCompany": [ "hugging-face-inference-endpoints", "smollm3-3b" ], "weights": { "trainedBy": "Hugging Face with Zhongguancun Academy and TIGEM / University of Naples Federico II", "builtOn": "Qwen/Qwen3-14B (vocabulary extension, mid-training, supervised fine-tune and GRPO; base Apache 2.0, declared in the card's metadata)", "params": "14.8B", "context": 40960, "goodFor": "A DNA specialist another agent calls, for variant-effect questions, regulatory regions and next-base prediction on raw DNA kept on local hardware.", "runtimes": [ "llama.cpp", "vLLM", "SGLang", "Transformers" ], "builds": [ { "name": "Carbon-X-GGUF Q4_K_M", "url": "https://huggingface.co/HuggingFaceBio/Carbon-X-GGUF", "who": "publisher", "precision": "q4_k_m", "sizeGB": 9.64, "memoryGB": 12, "format": "gguf", "runsOn": [ "llama.cpp" ], "note": "carbon-x-q4_k_m.gguf, 9,636,318,080 bytes. Embedding and output tensors stay at Q8_0. The publisher's own runs put it lowest of the builds on FrontierVEP (67.8) and NextBase (38.6)" }, { "name": "Carbon-X-GGUF Q6_K", "url": "https://huggingface.co/HuggingFaceBio/Carbon-X-GGUF", "who": "publisher", "precision": "q6_k", "sizeGB": 12.56, "memoryGB": 16, "format": "gguf", "runsOn": [ "llama.cpp" ], "note": "carbon-x-q6_k.gguf, 12,555,946,880 bytes" }, { "name": "Carbon-X-GGUF Q5_K_M", "url": "https://huggingface.co/HuggingFaceBio/Carbon-X-GGUF", "who": "publisher", "precision": "q5_k_m", "sizeGB": 11.05, "memoryGB": 16, "format": "gguf", "runsOn": [ "llama.cpp" ], "note": "carbon-x-q5_k_m.gguf, 11,051,895,680 bytes" }, { "name": "Carbon-X-GGUF Q8_0", "url": "https://huggingface.co/HuggingFaceBio/Carbon-X-GGUF", "who": "publisher", "precision": "q8_0", "sizeGB": 15.76, "memoryGB": 24, "format": "gguf", "runsOn": [ "llama.cpp" ], "note": "carbon-x-q8_0.gguf, 15,755,742,080 bytes, the build the publisher recommends" }, { "name": "Carbon-X", "url": "https://huggingface.co/HuggingFaceBio/Carbon-X", "who": "publisher", "precision": "bf16", "sizeGB": 29.64, "memoryGB": 48, "format": "safetensors", "runsOn": [ "vLLM", "Transformers" ], "note": "Needs trust_remote_code for the custom HybridDNATokenizer, and Transformers v5 or later. The card says it fits one 80 GB GPU" }, { "name": "Carbon-X-GGUF BF16", "url": "https://huggingface.co/HuggingFaceBio/Carbon-X-GGUF", "who": "publisher", "precision": "bf16", "sizeGB": 29.65, "memoryGB": 48, "format": "gguf", "runsOn": [ "llama.cpp" ], "note": "carbon-x-bf16.gguf, 29,651,012,480 bytes. llama.cpp b11742 or later" } ], "run": "llama-server -hf HuggingFaceBio/Carbon-X-GGUF:Q8_0 -ngl 99 -c 40960 --jinja --chat-template-kwargs '{\"enable_thinking\": false}' --temp 0.6 --top-p 0.95 --top-k 20 --min-p 0 --port 8080", "runBuild": "Carbon-X-GGUF Q8_0", "checked": "2026-10-23", "minMemoryGB": 12 }, "family": { "lab": "Hugging Face (Carbon)", "family": "Carbon", "url": "https://www.anchorterminal.com/open-weights/#huggingface-bio", "others": [ { "name": "Carbon-A-1.2B", "url": "https://huggingface.co/HuggingFaceBio/Carbon-A-1.2B", "params": "1.2B" }, { "name": "Carbon-8B", "url": "https://huggingface.co/HuggingFaceBio/Carbon-8B", "params": "8.3B" }, { "name": "Carbon-3B", "url": "https://huggingface.co/HuggingFaceBio/Carbon-3B", "params": "3.5B" }, { "name": "Carbon-500M", "url": "https://huggingface.co/HuggingFaceBio/Carbon-500M", "params": "0.5B" } ] }, "area": "models", "provenance": { "legalEntity": "Hugging Face (the HuggingFaceBio organisation, named Hugging Face Biology Research on the Hub)", "domain": "huggingface.co", "domainRegistered": "", "endpointOnVendorDomain": null, "terms": "", "privacy": "", "statusPage": "", "changelog": "", "securityTxt": "valid", "checked": "2026-10-23", "notes": [ "The HuggingFaceBio organisation isn't verified on the Hub. It has 27 members, Hugging Face staff among them, and the huggingface/carbon GitHub repository links its Carbon models.", "Nothing is hosted, so the Apache 2.0 licence stands in for terms of service and no privacy policy is scored.", "huggingface.co/.well-known/security.txt names a security contact and expires in 2030.", "No changelog. The main repository's history shows one commit on 22 October 2026; the merged pull requests show earlier commits on 21 and 22 October, so the history was squashed. Registration of huggingface.co wasn't checked." ], "score": 53 }, "pageJsonUrl": "https://www.anchorterminal.com/tools/carbon-x.json", "live": { "slug": "carbon-x", "securityTxt": { "url": "https://huggingface.co/.well-known/security.txt", "state": "valid", "expires": "2030-07-01T08:42:00.000Z", "checkedAt": "2026-10-27T15:31:26.533299918Z" }, "domain": { "domain": "huggingface.co", "checkedAt": "2026-10-25T13:59:29.030902536Z" }, "updatedAt": "2026-10-27T15:31:26.533299918Z" } }, "answer": "Carbon-X scores 61 (C) on agent readiness against Baidu Unlimited-OCR-2's 53.5 (D), and leads in 3 of 4 scored categories. Baidu Unlimited-OCR-2 leads on 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": "Hugging Face (HuggingFaceBio)", "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": "2026-10-22", "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 (4)", "b": "none", "name": "Agent reviews" } ], "faq": [ { "answer": "Carbon-X scores 61 (C) on agent readiness against Baidu Unlimited-OCR-2's 53.5 (D), and leads in 3 of 4 scored categories. Baidu Unlimited-OCR-2 leads on agent interface.", "question": "Which is better for AI agents, Carbon-X or Baidu Unlimited-OCR-2?" } ], "goodFor": [ { "aheadOn": [ "Reach, 90 against 55", "Risk, 65 against 45", "Documentation and upkeep, 77 against 45" ], "also": null, "goodFor": "Agents that need a second opinion on DNA variants and regulatory regions on a 16 to 24 GB machine, without sending sequences to a hosted model.", "slug": "carbon-x", "watchFor": "Not clinically validated and no wet-lab validation reported" }, { "aheadOn": [ "Agent interface, 75 against 35" ], "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-carbon-x.json", "title": "Agents-A1-4B vs Carbon-X", "url": "https://www.anchorterminal.com/compare/agents-a1-4b-vs-carbon-x" }, { "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-carbon-x.json", "title": "Apertus v1.5 8B vs Carbon-X", "url": "https://www.anchorterminal.com/compare/apertus-v1-5-8b-vs-carbon-x" }, { "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-carbon-x.json", "title": "Apodex-1.1-mini vs Carbon-X", "url": "https://www.anchorterminal.com/compare/apodex-1-1-mini-vs-carbon-x" }, { "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-carbon-x.json", "title": "BigBang-v1 vs Carbon-X", "url": "https://www.anchorterminal.com/compare/bigbang-v1-vs-carbon-x" }, { "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-cosmos-reason2-2b.json", "title": "Carbon-X vs Cosmos-Reason2-2B", "url": "https://www.anchorterminal.com/compare/carbon-x-vs-cosmos-reason2-2b" }, { "json": "https://www.anchorterminal.com/compare/carbon-x-vs-darwin-36b-opus.json", "title": "Carbon-X vs Darwin-36B-Opus", "url": "https://www.anchorterminal.com/compare/carbon-x-vs-darwin-36b-opus" }, { "json": "https://www.anchorterminal.com/compare/carbon-x-vs-deepseek-v3-2.json", "title": "Carbon-X vs DeepSeek-V3.2", "url": "https://www.anchorterminal.com/compare/carbon-x-vs-deepseek-v3-2" }, { "json": "https://www.anchorterminal.com/compare/carbon-x-vs-deepseek-v4-1-flash.json", "title": "Carbon-X vs DeepSeek V4.1 Flash", "url": "https://www.anchorterminal.com/compare/carbon-x-vs-deepseek-v4-1-flash" }, { "json": "https://www.anchorterminal.com/compare/carbon-x-vs-deepseek-v4-flash-0731.json", "title": "Carbon-X vs DeepSeek-V4-Flash-0731", "url": "https://www.anchorterminal.com/compare/carbon-x-vs-deepseek-v4-flash-0731" }, { "json": "https://www.anchorterminal.com/compare/carbon-x-vs-diffusiongemma-26b-a4b-it.json", "title": "Carbon-X vs DiffusionGemma 26B A4B IT", "url": "https://www.anchorterminal.com/compare/carbon-x-vs-diffusiongemma-26b-a4b-it" }, { "json": "https://www.anchorterminal.com/compare/carbon-x-vs-gemma-4-12b-it.json", "title": "Carbon-X vs Gemma 4 12B IT", "url": "https://www.anchorterminal.com/compare/carbon-x-vs-gemma-4-12b-it" }, { "json": "https://www.anchorterminal.com/compare/carbon-x-vs-gemma-4-26b-a4b-it.json", "title": "Carbon-X vs Gemma 4 26B A4B IT", "url": "https://www.anchorterminal.com/compare/carbon-x-vs-gemma-4-26b-a4b-it" }, { "json": "https://www.anchorterminal.com/compare/carbon-x-vs-gemma-4-31b-it.json", "title": "Carbon-X vs Gemma 4 31B IT", "url": "https://www.anchorterminal.com/compare/carbon-x-vs-gemma-4-31b-it" }, { "json": "https://www.anchorterminal.com/compare/carbon-x-vs-gemma-4-e2b-it.json", "title": "Carbon-X vs Gemma 4 E2B IT", "url": "https://www.anchorterminal.com/compare/carbon-x-vs-gemma-4-e2b-it" }, { "json": "https://www.anchorterminal.com/compare/carbon-x-vs-gemma-4-e4b-it.json", "title": "Carbon-X vs Gemma 4 E4B IT", "url": "https://www.anchorterminal.com/compare/carbon-x-vs-gemma-4-e4b-it" }, { "json": "https://www.anchorterminal.com/compare/carbon-x-vs-glm-4-5-air.json", "title": "Carbon-X vs GLM-4.5-Air", "url": "https://www.anchorterminal.com/compare/carbon-x-vs-glm-4-5-air" }, { "json": "https://www.anchorterminal.com/compare/carbon-x-vs-glm-4-7-flash.json", "title": "Carbon-X vs GLM-4.7-Flash", "url": "https://www.anchorterminal.com/compare/carbon-x-vs-glm-4-7-flash" }, { "json": "https://www.anchorterminal.com/compare/carbon-x-vs-glm-5-3.json", "title": "Carbon-X vs GLM-5.3", "url": "https://www.anchorterminal.com/compare/carbon-x-vs-glm-5-3" }, { "json": "https://www.anchorterminal.com/compare/carbon-x-vs-glm-5-3-flash.json", "title": "Carbon-X vs GLM-5.3-Flash", "url": "https://www.anchorterminal.com/compare/carbon-x-vs-glm-5-3-flash" }, { "json": "https://www.anchorterminal.com/compare/carbon-x-vs-gpt-oss-120b.json", "title": "Carbon-X vs gpt-oss-120b", "url": "https://www.anchorterminal.com/compare/carbon-x-vs-gpt-oss-120b" }, { "json": "https://www.anchorterminal.com/compare/carbon-x-vs-gpt-oss-20b.json", "title": "Carbon-X vs gpt-oss-20b", "url": "https://www.anchorterminal.com/compare/carbon-x-vs-gpt-oss-20b" }, { "json": "https://www.anchorterminal.com/compare/carbon-x-vs-granite-4-2-3b.json", "title": "Carbon-X vs Granite 4.2 3B", "url": "https://www.anchorterminal.com/compare/carbon-x-vs-granite-4-2-3b" }, { "json": "https://www.anchorterminal.com/compare/carbon-x-vs-hy3.json", "title": "Carbon-X vs Hy3", "url": "https://www.anchorterminal.com/compare/carbon-x-vs-hy3" }, { "json": "https://www.anchorterminal.com/compare/carbon-x-vs-inkling.json", "title": "Carbon-X vs Inkling", "url": "https://www.anchorterminal.com/compare/carbon-x-vs-inkling" }, { "json": "https://www.anchorterminal.com/compare/carbon-x-vs-inkling-small.json", "title": "Carbon-X vs Inkling-Small", "url": "https://www.anchorterminal.com/compare/carbon-x-vs-inkling-small" }, { "json": "https://www.anchorterminal.com/compare/carbon-x-vs-internvl3-5-gpt-oss-20b-a4b-preview.json", "title": "Carbon-X vs InternVL3.5-GPT-OSS-20B-A4B-Preview", "url": "https://www.anchorterminal.com/compare/carbon-x-vs-internvl3-5-gpt-oss-20b-a4b-preview" }, { "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-kolibri-1.json", "title": "Carbon-X vs Kolibri-1", "url": "https://www.anchorterminal.com/compare/carbon-x-vs-kolibri-1" }, { "json": "https://www.anchorterminal.com/compare/carbon-x-vs-kronos.json", "title": "Carbon-X vs Kronos", "url": "https://www.anchorterminal.com/compare/carbon-x-vs-kronos" }, { "json": "https://www.anchorterminal.com/compare/carbon-x-vs-laguna-m-1.json", "title": "Carbon-X vs Laguna M.1", "url": "https://www.anchorterminal.com/compare/carbon-x-vs-laguna-m-1" }, { "json": "https://www.anchorterminal.com/compare/carbon-x-vs-laguna-s-2-1.json", "title": "Carbon-X vs Laguna S 2.1", "url": "https://www.anchorterminal.com/compare/carbon-x-vs-laguna-s-2-1" }, { "json": "https://www.anchorterminal.com/compare/carbon-x-vs-laguna-xs-2-1.json", "title": "Carbon-X vs Laguna XS 2.1", "url": "https://www.anchorterminal.com/compare/carbon-x-vs-laguna-xs-2-1" }, { "json": "https://www.anchorterminal.com/compare/carbon-x-vs-lbs-27b.json", "title": "Carbon-X vs LBS-27B", "url": "https://www.anchorterminal.com/compare/carbon-x-vs-lbs-27b" }, { "json": "https://www.anchorterminal.com/compare/carbon-x-vs-lfm2-5-2-6b.json", "title": "Carbon-X vs LFM2.5-2.6B", "url": "https://www.anchorterminal.com/compare/carbon-x-vs-lfm2-5-2-6b" }, { "json": "https://www.anchorterminal.com/compare/carbon-x-vs-ling-3-0-tiny.json", "title": "Carbon-X vs Ling-3.0-tiny", "url": "https://www.anchorterminal.com/compare/carbon-x-vs-ling-3-0-tiny" }, { "json": "https://www.anchorterminal.com/compare/carbon-x-vs-mimo-v2-6-distill-qwen-9b.json", "title": "Carbon-X vs MiMo-V2.6 Distill Qwen 9B", "url": "https://www.anchorterminal.com/compare/carbon-x-vs-mimo-v2-6-distill-qwen-9b" }, { "json": "https://www.anchorterminal.com/compare/carbon-x-vs-minicpm-o-4-5.json", "title": "Carbon-X vs MiniCPM-o 4.5", "url": "https://www.anchorterminal.com/compare/carbon-x-vs-minicpm-o-4-5" }, { "json": "https://www.anchorterminal.com/compare/carbon-x-vs-minicpm5-2b.json", "title": "Carbon-X vs MiniCPM5-2B", "url": "https://www.anchorterminal.com/compare/carbon-x-vs-minicpm5-2b" }, { "json": "https://www.anchorterminal.com/compare/carbon-x-vs-minimax-m2-5.json", "title": "Carbon-X vs MiniMax-M2.5", "url": "https://www.anchorterminal.com/compare/carbon-x-vs-minimax-m2-5" }, { "json": "https://www.anchorterminal.com/compare/carbon-x-vs-minimax-m2-7.json", "title": "Carbon-X vs MiniMax-M2.7", "url": "https://www.anchorterminal.com/compare/carbon-x-vs-minimax-m2-7" }, { "json": "https://www.anchorterminal.com/compare/carbon-x-vs-minimax-m3-1-flash.json", "title": "Carbon-X vs MiniMax-M3.1-Flash", "url": "https://www.anchorterminal.com/compare/carbon-x-vs-minimax-m3-1-flash" }, { "json": "https://www.anchorterminal.com/compare/carbon-x-vs-muse-glimmer-30b.json", "title": "Carbon-X vs Muse Glimmer 30B", "url": "https://www.anchorterminal.com/compare/carbon-x-vs-muse-glimmer-30b" }, { "json": "https://www.anchorterminal.com/compare/carbon-x-vs-nanbeige-4-3-33b.json", "title": "Carbon-X vs Nanbeige4.3-33B", "url": "https://www.anchorterminal.com/compare/carbon-x-vs-nanbeige-4-3-33b" }, { "json": "https://www.anchorterminal.com/compare/carbon-x-vs-nemotron-3-5-bolt-e4b-4gb.json", "title": "Carbon-X vs NVIDIA Nemotron 3.5 Bolt E4B 4GB", "url": "https://www.anchorterminal.com/compare/carbon-x-vs-nemotron-3-5-bolt-e4b-4gb" }, { "json": "https://www.anchorterminal.com/compare/carbon-x-vs-nemotron-3-5-lightning-30b-a3b.json", "title": "Carbon-X vs Nemotron 3.5 Lightning 30B A3B", "url": "https://www.anchorterminal.com/compare/carbon-x-vs-nemotron-3-5-lightning-30b-a3b" }, { "json": "https://www.anchorterminal.com/compare/carbon-x-vs-nemotron-3-nano-30b-a3b.json", "title": "Carbon-X vs Nemotron 3 Nano 30B A3B", "url": "https://www.anchorterminal.com/compare/carbon-x-vs-nemotron-3-nano-30b-a3b" }, { "json": "https://www.anchorterminal.com/compare/carbon-x-vs-nemotron-3-nano-4b.json", "title": "Carbon-X vs Nemotron 3 Nano 4B", "url": "https://www.anchorterminal.com/compare/carbon-x-vs-nemotron-3-nano-4b" }, { "json": "https://www.anchorterminal.com/compare/carbon-x-vs-nemotron-3-nano-omni-30b-a3b-reasoning.json", "title": "Carbon-X vs Nemotron 3 Nano Omni 30B A3B Reasoning", "url": "https://www.anchorterminal.com/compare/carbon-x-vs-nemotron-3-nano-omni-30b-a3b-reasoning" }, { "json": "https://www.anchorterminal.com/compare/carbon-x-vs-nemotron-3-super-120b-a12b.json", "title": "Carbon-X vs Nemotron 3 Super 120B A12B", "url": "https://www.anchorterminal.com/compare/carbon-x-vs-nemotron-3-super-120b-a12b" }, { "json": "https://www.anchorterminal.com/compare/carbon-x-vs-nemotron-3-ultra-550b-a55b.json", "title": "Carbon-X vs Nemotron 3 Ultra 550B A55B", "url": "https://www.anchorterminal.com/compare/carbon-x-vs-nemotron-3-ultra-550b-a55b" }, { "json": "https://www.anchorterminal.com/compare/carbon-x-vs-occamy-1-0.json", "title": "Carbon-X vs occamy-1.0", "url": "https://www.anchorterminal.com/compare/carbon-x-vs-occamy-1-0" }, { "json": "https://www.anchorterminal.com/compare/carbon-x-vs-olmo-3-7b-think.json", "title": "Carbon-X vs Olmo 3 7B Think", "url": "https://www.anchorterminal.com/compare/carbon-x-vs-olmo-3-7b-think" }, { "json": "https://www.anchorterminal.com/compare/carbon-x-vs-ornith-1-5-35b-a3b.json", "title": "Carbon-X vs Ornith-1.5-35B-A3B", "url": "https://www.anchorterminal.com/compare/carbon-x-vs-ornith-1-5-35b-a3b" }, { "json": "https://www.anchorterminal.com/compare/carbon-x-vs-ornith-1-5-397b.json", "title": "Carbon-X vs Ornith-1.5-397B", "url": "https://www.anchorterminal.com/compare/carbon-x-vs-ornith-1-5-397b" }, { "json": "https://www.anchorterminal.com/compare/carbon-x-vs-ornith-1-5-9b.json", "title": "Carbon-X vs Ornith-1.5-9B", "url": "https://www.anchorterminal.com/compare/carbon-x-vs-ornith-1-5-9b" }, { "json": "https://www.anchorterminal.com/compare/carbon-x-vs-qwen3-30b-a3b-instruct-2507.json", "title": "Carbon-X vs Qwen3-30B-A3B-Instruct-2507", "url": "https://www.anchorterminal.com/compare/carbon-x-vs-qwen3-30b-a3b-instruct-2507" }, { "json": "https://www.anchorterminal.com/compare/carbon-x-vs-qwen3-4b-instruct-2507.json", "title": "Carbon-X vs Qwen3-4B-Instruct-2507", "url": "https://www.anchorterminal.com/compare/carbon-x-vs-qwen3-4b-instruct-2507" }, { "json": "https://www.anchorterminal.com/compare/carbon-x-vs-qwen3-5-0-8b.json", "title": "Carbon-X vs Qwen3.5-0.8B", "url": "https://www.anchorterminal.com/compare/carbon-x-vs-qwen3-5-0-8b" }, { "json": "https://www.anchorterminal.com/compare/carbon-x-vs-qwen3-5-122b-a10b.json", "title": "Carbon-X vs Qwen3.5-122B-A10B", "url": "https://www.anchorterminal.com/compare/carbon-x-vs-qwen3-5-122b-a10b" }, { "json": "https://www.anchorterminal.com/compare/carbon-x-vs-qwen3-5-2b.json", "title": "Carbon-X vs Qwen3.5-2B", "url": "https://www.anchorterminal.com/compare/carbon-x-vs-qwen3-5-2b" }, { "json": "https://www.anchorterminal.com/compare/carbon-x-vs-qwen3-5-397b-a17b.json", "title": "Carbon-X vs Qwen3.5-397B-A17B", "url": "https://www.anchorterminal.com/compare/carbon-x-vs-qwen3-5-397b-a17b" }, { "json": "https://www.anchorterminal.com/compare/carbon-x-vs-qwen3-5-4b.json", "title": "Carbon-X vs Qwen3.5-4B", "url": "https://www.anchorterminal.com/compare/carbon-x-vs-qwen3-5-4b" }, { "json": 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}, { "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-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": "https://www.anchorterminal.com/compare/glm-5-3-flash-vs-unlimited-ocr-2.json", "title": "GLM-5.3-Flash vs Baidu Unlimited-OCR-2", "url": "https://www.anchorterminal.com/compare/glm-5-3-flash-vs-unlimited-ocr-2" }, { "json": "https://www.anchorterminal.com/compare/glm-5-3-vs-unlimited-ocr-2.json", "title": "GLM-5.3 vs Baidu Unlimited-OCR-2", "url": "https://www.anchorterminal.com/compare/glm-5-3-vs-unlimited-ocr-2" }, { "json": "https://www.anchorterminal.com/compare/gpt-oss-120b-vs-unlimited-ocr-2.json", "title": "gpt-oss-120b vs Baidu 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"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, "carbon-x": 90, "edge": "carbon-x", "key": "reach", "name": "Reach", "unlimited-ocr-2": 55, "weight": 25 }, { "by": 20, "carbon-x": 65, "edge": "carbon-x", "key": "risk", "name": "Risk", "unlimited-ocr-2": 45, "weight": 20 }, { "by": 40, "carbon-x": 35, "edge": "unlimited-ocr-2", "key": "interface", "name": "Agent interface", "unlimited-ocr-2": 75, "weight": 10 }, { "by": 32, "carbon-x": 77, "edge": "carbon-x", "key": "upkeep", "name": "Documentation and upkeep", "unlimited-ocr-2": 45, "weight": 10 } ], "summary": "Carbon-X scores 61 (C) on agent readiness against Baidu Unlimited-OCR-2's 53.5 (D), and leads in 3 of 4 scored categories. Baidu Unlimited-OCR-2 leads on agent interface. Both do open-weight models you run yourself.", "tutorials": [], "verdicts": { "carbon-x": "A DNA specialist cousin that another agent calls for variant-effect and sequence questions, with DNA kept on the machine. Hugging Face's Q4_K_M GGUF needs about 12 GB and Q8_0 about 19 GB, on llama.cpp b11742 or later. It isn't clinically validated, it isn't trained for tool calls or reasoning, and the card contradicts its own GGUF repository on llama.cpp support.", "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/carbon-x-vs-unlimited-ocr-2", "json": "https://www.anchorterminal.com/compare/carbon-x-vs-unlimited-ocr-2.json", "llms": "https://www.anchorterminal.com/llms.txt", "markdown": "https://www.anchorterminal.com/compare/carbon-x-vs-unlimited-ocr-2.md", "mcp": "https://www.anchorterminal.com/mcp", "slim": "https://www.anchorterminal.com/compare/carbon-x-vs-unlimited-ocr-2.min.md" }, "markdown": "Carbon-X scores 61 (C) on agent readiness against Baidu Unlimited-OCR-2's 53.5 (D), and leads in 3 of 4 scored categories. Baidu Unlimited-OCR-2 leads on agent interface. Both do open-weight models you run yourself.\n\n- Carbon-X: grade C, 61/100, rank #38 of 113 open-weight models. Markdown https://www.anchorterminal.com/tools/carbon-x.md · JSON https://www.anchorterminal.com/api/v1/tools/carbon-x.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### Carbon-X (C)\n\nGood for: Agents that need a second opinion on DNA variants and regulatory regions on a 16 to 24 GB machine, without sending sequences to a hosted model.\n\nAhead on:\n- Reach, 90 against 55\n- Risk, 65 against 45\n- Documentation and upkeep, 77 against 45\n\nWatch for: Not clinically validated and no wet-lab validation reported\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- Agent interface, 75 against 35\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 | Carbon-X | 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 | Carbon-X +35 |\n| Risk | 20% (20 this run) | 65 | 45 | Carbon-X +20 |\n| Agent interface | 10% (10 this run) | 35 | 75 | Baidu Unlimited-OCR-2 +40 |\n| Documentation and upkeep | 10% (10 this run) | 77 | 45 | Carbon-X +32 |\n| Negative events | ≤15 | 0 | 0 | |\n| **Total** | | **61 · C** | **53.5 · D** | |\n\n## Facts side by side\n\n| Fact | Carbon-X | Baidu Unlimited-OCR-2 |\n| --- | --- | --- |\n| Kind | Open-weight model | Open-weight model |\n| Vendor | Hugging Face (HuggingFaceBio) | 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 | 2026-10-22 | 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 (4) | none |\n\n## Verdicts\n\n**Carbon-X.** A DNA specialist cousin that another agent calls for variant-effect and sequence questions, with DNA kept on the machine. Hugging Face's Q4_K_M GGUF needs about 12 GB and Q8_0 about 19 GB, on llama.cpp b11742 or later. It isn't clinically validated, it isn't trained for tool calls or reasoning, and the card contradicts its own GGUF repository on llama.cpp support.\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### Carbon-X\n\n1. Quickest start is `llama-server -hf HuggingFaceBio/Carbon-X-GGUF:Q8_0 -ngl 99 -c 40960 --jinja --chat-template-kwargs '{\"enable_thinking\": false}' --temp 0.6 --top-p 0.95 --top-k 20 --min-p 0`, on llama.cpp b11742 or later\n2. With vLLM or Transformers pass trust_remote_code, and expect the tokenizer to fetch Qwen/Qwen3-4B-Base at a pinned revision on first load\n3. Keep enable_thinking false and the card's sampling (temperature 0.6, top_p 0.95, top_k 20), the settings every reported result used\n4. Keep DNA in files and pass sequences by name, compute positions and base changes in code and send them as context, the card says the model miscounts long sequences\n5. Only A, C, G and T form 6-mers, so filter N and other IUPAC codes first or they become a single oov token\n6. Strip the dna tags from answers if you need bare sequence, llama.cpp keeps them in the text\n7. Cap max_tokens for next-base questions, long DNA generation is slow and degrades\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, Carbon-X or Baidu Unlimited-OCR-2?\n\nCarbon-X scores 61 (C) on agent readiness against Baidu Unlimited-OCR-2's 53.5 (D), and leads in 3 of 4 scored categories. Baidu Unlimited-OCR-2 leads on agent interface.\n\n\n## For agents\n\n- This comparison as JSON: https://www.anchorterminal.com/compare/carbon-x-vs-unlimited-ocr-2.json, and with the fewest tokens: https://www.anchorterminal.com/compare/carbon-x-vs-unlimited-ocr-2.min.md\n- Over MCP at https://www.anchorterminal.com/mcp (no key): `compare_tools {\"a\": \"carbon-x\", \"b\": \"unlimited-ocr-2\"}`. From a terminal: `anchor compare carbon-x unlimited-ocr-2`\n- Each listing in full: https://www.anchorterminal.com/api/v1/tools/carbon-x.json and https://www.anchorterminal.com/api/v1/tools/unlimited-ocr-2.json\n\n## Other comparisons with Carbon-X or Baidu Unlimited-OCR-2\n\n- [Agents-A1-4B vs Carbon-X](https://www.anchorterminal.com/compare/agents-a1-4b-vs-carbon-x.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 Carbon-X](https://www.anchorterminal.com/compare/apertus-v1-5-8b-vs-carbon-x.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 Carbon-X](https://www.anchorterminal.com/compare/apodex-1-1-mini-vs-carbon-x.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 Carbon-X](https://www.anchorterminal.com/compare/bigbang-v1-vs-carbon-x.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 Cosmos-Reason2-2B](https://www.anchorterminal.com/compare/carbon-x-vs-cosmos-reason2-2b.md)\n- [Carbon-X vs Darwin-36B-Opus](https://www.anchorterminal.com/compare/carbon-x-vs-darwin-36b-opus.md)\n- [Carbon-X vs DeepSeek-V3.2](https://www.anchorterminal.com/compare/carbon-x-vs-deepseek-v3-2.md)\n- [Carbon-X vs DeepSeek V4.1 Flash](https://www.anchorterminal.com/compare/carbon-x-vs-deepseek-v4-1-flash.md)\n- [Carbon-X vs DeepSeek-V4-Flash-0731](https://www.anchorterminal.com/compare/carbon-x-vs-deepseek-v4-flash-0731.md)\n- [Carbon-X vs DiffusionGemma 26B A4B IT](https://www.anchorterminal.com/compare/carbon-x-vs-diffusiongemma-26b-a4b-it.md)\n- [Carbon-X vs Gemma 4 12B IT](https://www.anchorterminal.com/compare/carbon-x-vs-gemma-4-12b-it.md)\n- [Carbon-X vs Gemma 4 26B A4B IT](https://www.anchorterminal.com/compare/carbon-x-vs-gemma-4-26b-a4b-it.md)\n- [Carbon-X vs Gemma 4 31B IT](https://www.anchorterminal.com/compare/carbon-x-vs-gemma-4-31b-it.md)\n- [Carbon-X vs Gemma 4 E2B IT](https://www.anchorterminal.com/compare/carbon-x-vs-gemma-4-e2b-it.md)\n- [Carbon-X vs Gemma 4 E4B IT](https://www.anchorterminal.com/compare/carbon-x-vs-gemma-4-e4b-it.md)\n- [Carbon-X vs GLM-4.5-Air](https://www.anchorterminal.com/compare/carbon-x-vs-glm-4-5-air.md)\n- [Carbon-X vs GLM-4.7-Flash](https://www.anchorterminal.com/compare/carbon-x-vs-glm-4-7-flash.md)\n- [Carbon-X vs GLM-5.3](https://www.anchorterminal.com/compare/carbon-x-vs-glm-5-3.md)\n- [Carbon-X vs GLM-5.3-Flash](https://www.anchorterminal.com/compare/carbon-x-vs-glm-5-3-flash.md)\n- [Carbon-X vs gpt-oss-120b](https://www.anchorterminal.com/compare/carbon-x-vs-gpt-oss-120b.md)\n- [Carbon-X vs gpt-oss-20b](https://www.anchorterminal.com/compare/carbon-x-vs-gpt-oss-20b.md)\n- [Carbon-X vs Granite 4.2 3B](https://www.anchorterminal.com/compare/carbon-x-vs-granite-4-2-3b.md)\n- [Carbon-X vs Hy3](https://www.anchorterminal.com/compare/carbon-x-vs-hy3.md)\n- [Carbon-X vs Inkling](https://www.anchorterminal.com/compare/carbon-x-vs-inkling.md)\n- [Carbon-X vs Inkling-Small](https://www.anchorterminal.com/compare/carbon-x-vs-inkling-small.md)\n- [Carbon-X vs InternVL3.5-GPT-OSS-20B-A4B-Preview](https://www.anchorterminal.com/compare/carbon-x-vs-internvl3-5-gpt-oss-20b-a4b-preview.md)\n- [Carbon-X vs Kimi K3](https://www.anchorterminal.com/compare/carbon-x-vs-kimi-k3.md)\n- [Carbon-X vs Kolibri-1](https://www.anchorterminal.com/compare/carbon-x-vs-kolibri-1.md)\n- [Carbon-X vs Kronos](https://www.anchorterminal.com/compare/carbon-x-vs-kronos.md)\n- [Carbon-X vs Laguna M.1](https://www.anchorterminal.com/compare/carbon-x-vs-laguna-m-1.md)\n- [Carbon-X vs Laguna S 2.1](https://www.anchorterminal.com/compare/carbon-x-vs-laguna-s-2-1.md)\n- [Carbon-X vs Laguna XS 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[Qwen3-Coder-Next vs Baidu Unlimited-OCR-2](https://www.anchorterminal.com/compare/qwen3-coder-next-vs-unlimited-ocr-2.md)\n- [Qwen3-VL-2B-Instruct vs Baidu Unlimited-OCR-2](https://www.anchorterminal.com/compare/qwen3-vl-2b-instruct-vs-unlimited-ocr-2.md)\n- [Qwen3-VL-30B-A3B-Instruct vs Baidu Unlimited-OCR-2](https://www.anchorterminal.com/compare/qwen3-vl-30b-a3b-instruct-vs-unlimited-ocr-2.md)\n- [Qwen3-VL-32B-Instruct vs Baidu Unlimited-OCR-2](https://www.anchorterminal.com/compare/qwen3-vl-32b-instruct-vs-unlimited-ocr-2.md)\n- [Qwen3-VL-4B-Instruct vs Baidu Unlimited-OCR-2](https://www.anchorterminal.com/compare/qwen3-vl-4b-instruct-vs-unlimited-ocr-2.md)\n- [Qwen3-VL-8B-Instruct vs Baidu Unlimited-OCR-2](https://www.anchorterminal.com/compare/qwen3-vl-8b-instruct-vs-unlimited-ocr-2.md)\n- [Qwopus3.8-27B-Flash-V2 vs Baidu Unlimited-OCR-2](https://www.anchorterminal.com/compare/qwopus3-8-27b-flash-v2-vs-unlimited-ocr-2.md)\n- [Recursive Flint vs Baidu 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