{ "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 LBS-27B's 53.9 (D), and leads in 3 of 4 scored categories. LBS-27B leads on agent interface.", "b": { "slug": "lbs-27b", "name": "LBS-27B", "vendor": "inclusionAI (Ant Group)", "vendorUrl": "https://www.inclusion-ai.org", "kind": "weights", "category": "open-weights", "summary": "LBS-27B is an open-weight vision-language model from inclusionAI's UI-Venus line, fine-tuned from Qwen3.8-27B to find what to click on a screenshot by zooming into regions over several turns, and applied to visual questions on large images.", "url": "https://www.anchorterminal.com/tools/lbs-27b", "markdownUrl": "https://www.anchorterminal.com/tools/lbs-27b.md", "slimMarkdownUrl": "https://www.anchorterminal.com/tools/lbs-27b.min.md", "jsonUrl": "https://www.anchorterminal.com/api/v1/tools/lbs-27b.json", "repo": "https://huggingface.co/inclusionAI/LBS-27B", "license": "Apache-2.0 (the card's metadata and licence section; the LICENSE file sits in the GitHub repository inclusionAI/UI-Venus on its LBS branch, not in the Hugging Face repository)", "transports": [], "packages": [ { "registry": "huggingface", "name": "inclusionAI/LBS-27B" } ], "auth": "none", "authNotes": "The weights download from Hugging Face with no account, token or terms to accept. The Hub reports gated false for inclusionAI/LBS-27B (checked 2026-10-27).", "pricing": "free", "pricingNotes": "Free to download and use, commercial use included, under Apache 2.0 as the card states for the weights and the code. Running it costs the hardware, 54.73 GB of BF16 files and no quantised build from the publisher. No hosted API or inference provider serves it (checked 2026-10-27).", "priceSummary": "Free", "where": "local", "x402": { "level": "no", "evidence": "Weights you download and run yourself, so there is nothing to pay per call and no payment protocol (checked 2026-10-27).", "endpoints": [] }, "toolCount": null, "popularity": { "githubStars": null, "npmWeekly": null, "pypiWeekly": null, "asOf": "2026-10-27" }, "docsUrl": "https://github.com/inclusionAI/UI-Venus/tree/LBS", "capabilities": [ "model.open-weights" ], "tags": [ "open-weights", "model", "dense", "qwen", "vision", "gui-grounding", "computer-use", "reasoning", "safetensors", "self-hosted", "new" ], "lastRelease": "2026-10-26", "graded": true, "anchor": { "graded": true, "score": 53.9, "grade": "D", "agentReady": false, "rank": 0, "ranked": false, "notRankedWhy": "An open-weight model, graded by the open-weight checklist and ranked among open-weight models, not against tools", "rankOf": 1217, "categoryRank": 73, "methodology": "0.6", "run": "2026-10-01", "scores": { "interface": 70, "reach": 55, "risk": 50, "upkeep": 43 }, "pending": [ "performance", "tasks" ], "assessment": { "confidence": "low", "date": "2026-10-27" }, "negative": 0, "verdict": "A 27B Qwen3.8 fine-tune for GUI grounding that zooms into screenshots over a few turns before naming a point, and inclusionAI says it also helps with fine detail in large images. It needs about 96 GB at BF16 and a client that runs its crop actions. Every result so far is inclusionAI's own, with no safety results or injection guidance.", "bestFor": "Agents with about 96 GB of GPU memory that need to find click targets on dense professional screenshots, or read fine detail in large images, and can run a small crop loop and wait for independent results.", "strengths": [ "Qwen3.8-27B's stock architecture with no repository code, so released vLLM, SGLang, Transformers and llama.cpp load it", "Apache 2.0 for the weights and the base, ungated, safetensors only", "A simple, documented plain-text crop protocol with a point answer on a 0 to 1000 scale, and the training recipe and evaluation kit published", "Up to two crops per turn, learned in GRPO, and 262,144 tokens of context from the base", "inclusionAI publishes per-item scores and selected trajectories for its own benchmark runs" ], "weaknesses": [ "No independent benchmark result yet; ScreenSpot-Pro, OS-World-G, PerceptionBench and HR-Bench numbers are inclusionAI's own runs", "BF16 only, about 66 GB to load, and no Ollama, LM Studio or quantised build", "The crop loop and system prompt come from the publisher's Python, not a runtime parser or a template", "No safety evaluation, prompt-injection guidance, training data sources or knowledge cut-off", "No hosted API or inference provider serves it" ], "agentNotes": [ "Serve with `vllm serve inclusionAI/LBS-27B --tensor-parallel-size 4 --max-model-len 65536`, which is what the card's wrapper script runs; keep the context at 32,768 or more for multi-turn images", "Build the system prompt with `build_system_prompt` from the LBS branch's `zoomin_grounding_protocol.py`, send the screenshot after `image_path: \u003cname\u003e`, and don't pass `tools`; the model answers in plain text", "Parse `\u003caction\u003ecrop_image(image_path=..., x1=..., y1=..., x2=..., y2=...)\u003c/action\u003e`, cut the crop yourself and return it with its mapping to the original image; allow at most two crops per turn and three per episode", "Read the final answer as `[x.xx,y.yy]` on a 0 to 1000 scale of the original image, and use your own executor to click", "Pass `reasoning_effort` as `xhigh`, `medium` or `low` only, since the template raises an error for `high`, and don't count on `thinking_budget`, which the template ignores", "Don't turn on MTP speculative decoding; the MTP weights aren't in the repository though config.json names one MTP layer" ], "metrics": { "kind": "local", "measured": false }, "reviewCount": 0, "avgRating": 0, "history": [ { "basis": "public evidence", "confidence": "low", "grade": "D", "methodology": "0.6", "pending": [ "performance", "tasks" ], "run": "2026-10-01", "runLabel": "October 2026 research run", "score": 53.9 } ], "editorialScores": { "interface": 70, "reach": 55, "risk": 50, "upkeep": 43 }, "provenanceScore": 57, "checked": { "categories": { "interface": "2026-10-27", "reach": "2026-10-27", "risk": "2026-10-27", "upkeep": "2026-10-27" }, "last": "2026-10-27", "oldest": "2026-10-27", "stale": false, "staleAfterDays": 90 } }, "connect": { "install": "# The card's route clones the LBS branch and wraps vllm serve (four GPUs in its example)\ngit clone --branch LBS --single-branch https://github.com/inclusionAI/UI-Venus.git\ncd UI-Venus/evaluation\nbash scripts/serve_vllm.sh start inclusionAI/LBS-27B --name lbs --tp 4 --dp 1 --daemon\n# the same server without the wrapper (the script's defaults are a 65,536-token context and 64 sequences)\nvllm serve inclusionAI/LBS-27B --served-model-name lbs --tensor-parallel-size 4 --max-model-len 65536", "http": "curl http://localhost:8000/v1/chat/completions -H 'Content-Type: application/json' \\\n -d '{\"model\": \"lbs\", \"max_tokens\": 2560,\n \"messages\": [{\"role\": \"system\", \"content\": \"\u003ctask, image size, crop_image spec and answer format, as build_system_prompt in the LBS branch writes them\u003e\"},\n {\"role\": \"user\", \"content\": [{\"type\": \"text\", \"text\": \"image_path: screenshot.png\"},\n {\"type\": \"image_url\", \"image_url\": {\"url\": \"data:image/png;base64,...\"}}]}],\n \"chat_template_kwargs\": {\"reasoning_effort\": \"xhigh\"}}'" }, "letme": { "capability": "https://letme.dev/model.open-weights", "tool": "https://letme.dev/lbs-27b" }, "sameCompany": [ "ming-3-0-asr-tiny", "ming-3-0-audio-flash", "ming-3-0-audio-tiny", "ming-3-0-tts-tiny", "ling-3-0-tiny" ], "weights": { "trainedBy": "inclusionAI (Ant Group), with Wuhan University of Technology, CASIA and Zhejiang University", "builtOn": "Qwen/Qwen3.8-27B (fine-tune, named in the card's text, not in its base_model metadata; Apache 2.0, copyright Alibaba Cloud)", "params": "27B", "context": 262144, "goodFor": "A cousin that finds the point to click on a screenshot, and answers questions about fine detail in large images, by zooming in over a few turns, on a machine with about 96 GB of memory and a client that runs the crops, if inclusionAI's own results hold up.", "runtimes": [ "vLLM", "SGLang", "Transformers", "llama.cpp" ], "builds": [ { "name": "LBS-27B (BF16)", "url": "https://huggingface.co/inclusionAI/LBS-27B", "who": "publisher", "precision": "bf16", "sizeGB": 54.73, "memoryGB": 96, "format": "safetensors", "runsOn": [ "vLLM", "SGLang", "Transformers" ], "note": "Whole repository, 54.73 GB, almost all of it 12 BF16 shards. 54.73 GB × 1.2 = 65.7 GB, just over 64 GB. The only build; no Ollama, LM Studio or ggml-org build and no copy by anyone else on 27 October 2026" } ], "run": "vllm serve inclusionAI/LBS-27B --served-model-name lbs --tensor-parallel-size 4 --max-model-len 65536", "runBuild": "LBS-27B (BF16)", "checked": "2026-10-27", "minMemoryGB": 96 }, "family": { "lab": "inclusionAI (Ant Group)", "family": "UI-Venus", "url": "https://www.anchorterminal.com/open-weights/#inclusionai", "others": [ { "name": "UI-Venus-2-9B", "url": "https://huggingface.co/inclusionAI/UI-Venus-2-9B", "params": "9B" }, { "name": "UI-Venus-1.5-30B-A3B", "url": "https://huggingface.co/inclusionAI/UI-Venus-1.5-30B-A3B", "params": "30B total, 3B active" }, { "name": "UI-Venus-1.5-8B", "url": "https://huggingface.co/inclusionAI/UI-Venus-1.5-8B", "params": "8B" }, { "name": "UI-Venus-1.5-2B", "url": "https://huggingface.co/inclusionAI/UI-Venus-1.5-2B", "params": "2B" } ], "olderCount": 54 }, "area": "models", "provenance": { "legalEntity": "inclusionAI, Ant Group (named in the site footer of inclusion-ai.org); the work is credited to authors from Wuhan University of Technology, CASIA, Zhejiang University and Ant Group", "domain": "inclusion-ai.org", "domainRegistered": "2025-04-03", "endpointOnVendorDomain": null, "terms": "", "privacy": "", "statusPage": "", "changelog": "https://huggingface.co/inclusionAI/LBS-27B/commits/main", "securityTxt": "none", "checked": "2026-10-27", "notes": [ "inclusion-ai.org links to huggingface.co/inclusionAI and github.com/inclusionAI (read 2026-10-27). The Hub doesn't verify the organisation, which the calibration of 21 October credits as the publisher's own. The domain registration date is carried from the Ming-3.0 listings' check of 21 October 2026.", "The model card links github.com/inclusionAI/UI-Venus on its LBS branch, where the LICENSE, the NOTICE, the training recipe and the evaluation kit sit. The NOTICE reads Copyright 2026 the LBS contributors.", "Nothing is hosted, so the Apache 2.0 licence stands in for terms of service and no privacy policy is scored.", "The changelog is the Hugging Face commit history, two commits on 26 October 2026 (initial commit and one upload).", "inclusion-ai.org/.well-known/security.txt reset the connection on 27 October 2026 and answered 404 on 21 October. The LBS branch has no SECURITY.md. Ant Group runs a company-wide security response centre, AntSRC (https://security.alipay.com/, answering on 27 October 2026); nothing on the card or the branch links it." ], "score": 57 }, "pageJsonUrl": "https://www.anchorterminal.com/tools/lbs-27b.json", "live": { "slug": "lbs-27b", "securityTxt": { "url": "https://inclusion-ai.org/.well-known/security.txt", "state": "unknown", "checkedAt": "2026-10-27T15:31:25.810013407Z" }, "updatedAt": "2026-10-27T15:31:25.810013407Z" } }, "facts": [ { "a": "Open-weight model", "b": "Open-weight model", "name": "Kind" }, { "a": "Hugging Face (HuggingFaceBio)", "b": "inclusionAI (Ant Group)", "name": "Vendor" }, { "a": "no (local only)", "b": "no (local only)", "name": "Hosted endpoint" }, { "a": "", "b": "", "name": "Transports" }, { "a": "None", "b": "None", "name": "Auth" }, { "a": "Free", "b": "Free", "name": "Pricing" }, { "a": "no", "b": "no", "name": "x402" }, { "a": "Apache-2.0", "b": "Apache-2.0 (the card's metadata and licence section; the LICENSE file sits in the GitHub repository inclusionAI/UI-Venus on its LBS branch, not in the Hugging Face repository)", "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 LBS-27B's 53.9 (D), and leads in 3 of 4 scored categories. LBS-27B leads on agent interface.", "question": "Which is better for AI agents, Carbon-X or LBS-27B?" } ], "goodFor": [ { "aheadOn": [ "Reach, 90 against 55", "Risk, 65 against 50", "Documentation and upkeep, 77 against 43" ], "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, 70 against 35" ], "also": null, "goodFor": "Agents with about 96 GB of GPU memory that need to find click targets on dense professional screenshots, or read fine detail in large images, and can run a small crop loop and wait for independent results.", "slug": "lbs-27b", "watchFor": "No independent benchmark result yet; ScreenSpot-Pro, OS-World-G, PerceptionBench and HR-Bench numbers are inclusionAI's own runs" } ], "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-lbs-27b.json", "title": "Agents-A1-4B vs LBS-27B", "url": "https://www.anchorterminal.com/compare/agents-a1-4b-vs-lbs-27b" }, { "json": "https://www.anchorterminal.com/compare/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-lbs-27b.json", "title": "Apertus v1.5 8B vs LBS-27B", "url": "https://www.anchorterminal.com/compare/apertus-v1-5-8b-vs-lbs-27b" }, { "json": "https://www.anchorterminal.com/compare/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-lbs-27b.json", "title": "Apodex-1.1-mini vs LBS-27B", "url": "https://www.anchorterminal.com/compare/apodex-1-1-mini-vs-lbs-27b" }, { "json": "https://www.anchorterminal.com/compare/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-lbs-27b.json", "title": "BigBang-v1 vs LBS-27B", "url": "https://www.anchorterminal.com/compare/bigbang-v1-vs-lbs-27b" }, { "json": "https://www.anchorterminal.com/compare/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-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": "https://www.anchorterminal.com/compare/carbon-x-vs-qwen3-5-9b.json", "title": "Carbon-X vs Qwen3.5-9B", "url": "https://www.anchorterminal.com/compare/carbon-x-vs-qwen3-5-9b" }, { "json": "https://www.anchorterminal.com/compare/carbon-x-vs-qwen3-6-27b.json", "title": "Carbon-X vs Qwen3.6-27B", "url": "https://www.anchorterminal.com/compare/carbon-x-vs-qwen3-6-27b" }, { "json": "https://www.anchorterminal.com/compare/carbon-x-vs-qwen3-6-35b-a3b.json", "title": "Carbon-X vs Qwen3.6-35B-A3B", "url": "https://www.anchorterminal.com/compare/carbon-x-vs-qwen3-6-35b-a3b" }, { "json": "https://www.anchorterminal.com/compare/carbon-x-vs-qwen3-8-27b.json", "title": "Carbon-X vs Qwen3.8-27B", "url": "https://www.anchorterminal.com/compare/carbon-x-vs-qwen3-8-27b" }, { "json": "https://www.anchorterminal.com/compare/carbon-x-vs-qwen3-8-flash-next.json", "title": "Carbon-X vs Qwen3.8-Flash-Next", "url": "https://www.anchorterminal.com/compare/carbon-x-vs-qwen3-8-flash-next" }, { "json": "https://www.anchorterminal.com/compare/carbon-x-vs-qwen3-coder-30b-a3b-instruct.json", "title": "Carbon-X vs Qwen3-Coder-30B-A3B-Instruct", "url": "https://www.anchorterminal.com/compare/carbon-x-vs-qwen3-coder-30b-a3b-instruct" }, { "json": "https://www.anchorterminal.com/compare/carbon-x-vs-qwen3-coder-next.json", "title": "Carbon-X vs Qwen3-Coder-Next", "url": "https://www.anchorterminal.com/compare/carbon-x-vs-qwen3-coder-next" }, { "json": "https://www.anchorterminal.com/compare/carbon-x-vs-qwen3-omni-30b-a3b-instruct.json", "title": "Carbon-X vs Qwen3-Omni-30B-A3B-Instruct", "url": "https://www.anchorterminal.com/compare/carbon-x-vs-qwen3-omni-30b-a3b-instruct" }, { "json": "https://www.anchorterminal.com/compare/carbon-x-vs-qwen3-vl-2b-instruct.json", "title": "Carbon-X vs Qwen3-VL-2B-Instruct", "url": "https://www.anchorterminal.com/compare/carbon-x-vs-qwen3-vl-2b-instruct" }, { "json": "https://www.anchorterminal.com/compare/carbon-x-vs-qwen3-vl-30b-a3b-instruct.json", "title": "Carbon-X vs Qwen3-VL-30B-A3B-Instruct", "url": "https://www.anchorterminal.com/compare/carbon-x-vs-qwen3-vl-30b-a3b-instruct" }, { "json": "https://www.anchorterminal.com/compare/carbon-x-vs-qwen3-vl-32b-instruct.json", "title": "Carbon-X vs Qwen3-VL-32B-Instruct", "url": "https://www.anchorterminal.com/compare/carbon-x-vs-qwen3-vl-32b-instruct" }, { "json": "https://www.anchorterminal.com/compare/carbon-x-vs-qwen3-vl-4b-instruct.json", "title": "Carbon-X vs Qwen3-VL-4B-Instruct", "url": "https://www.anchorterminal.com/compare/carbon-x-vs-qwen3-vl-4b-instruct" }, { "json": "https://www.anchorterminal.com/compare/carbon-x-vs-qwen3-vl-8b-instruct.json", "title": "Carbon-X vs Qwen3-VL-8B-Instruct", "url": "https://www.anchorterminal.com/compare/carbon-x-vs-qwen3-vl-8b-instruct" }, { "json": "https://www.anchorterminal.com/compare/carbon-x-vs-qwopus3-8-27b-flash-v2.json", "title": "Carbon-X vs Qwopus3.8-27B-Flash-V2", "url": "https://www.anchorterminal.com/compare/carbon-x-vs-qwopus3-8-27b-flash-v2" }, { "json": "https://www.anchorterminal.com/compare/carbon-x-vs-recursive-flint.json", "title": "Carbon-X vs Recursive Flint", 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"json": "https://www.anchorterminal.com/compare/lbs-27b-vs-olmo-3-7b-think.json", "title": "LBS-27B vs Olmo 3 7B Think", "url": "https://www.anchorterminal.com/compare/lbs-27b-vs-olmo-3-7b-think" }, { "json": "https://www.anchorterminal.com/compare/lbs-27b-vs-ornith-1-5-35b-a3b.json", "title": "LBS-27B vs Ornith-1.5-35B-A3B", "url": "https://www.anchorterminal.com/compare/lbs-27b-vs-ornith-1-5-35b-a3b" }, { "json": "https://www.anchorterminal.com/compare/lbs-27b-vs-ornith-1-5-397b.json", "title": "LBS-27B vs Ornith-1.5-397B", "url": "https://www.anchorterminal.com/compare/lbs-27b-vs-ornith-1-5-397b" }, { "json": "https://www.anchorterminal.com/compare/lbs-27b-vs-ornith-1-5-9b.json", "title": "LBS-27B vs Ornith-1.5-9B", "url": "https://www.anchorterminal.com/compare/lbs-27b-vs-ornith-1-5-9b" }, { "json": "https://www.anchorterminal.com/compare/lbs-27b-vs-qwen3-30b-a3b-instruct-2507.json", "title": "LBS-27B vs Qwen3-30B-A3B-Instruct-2507", "url": 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"https://www.anchorterminal.com/compare/lbs-27b-vs-qwen3-8-27b" }, { "json": "https://www.anchorterminal.com/compare/lbs-27b-vs-qwen3-8-flash-next.json", "title": "LBS-27B vs Qwen3.8-Flash-Next", "url": "https://www.anchorterminal.com/compare/lbs-27b-vs-qwen3-8-flash-next" }, { "json": "https://www.anchorterminal.com/compare/lbs-27b-vs-qwen3-coder-30b-a3b-instruct.json", "title": "LBS-27B vs Qwen3-Coder-30B-A3B-Instruct", "url": "https://www.anchorterminal.com/compare/lbs-27b-vs-qwen3-coder-30b-a3b-instruct" }, { "json": "https://www.anchorterminal.com/compare/lbs-27b-vs-qwen3-coder-next.json", "title": "LBS-27B vs Qwen3-Coder-Next", "url": "https://www.anchorterminal.com/compare/lbs-27b-vs-qwen3-coder-next" }, { "json": "https://www.anchorterminal.com/compare/lbs-27b-vs-qwen3-omni-30b-a3b-instruct.json", "title": "LBS-27B vs Qwen3-Omni-30B-A3B-Instruct", "url": "https://www.anchorterminal.com/compare/lbs-27b-vs-qwen3-omni-30b-a3b-instruct" }, { "json": "https://www.anchorterminal.com/compare/lbs-27b-vs-qwen3-vl-2b-instruct.json", "title": "LBS-27B vs Qwen3-VL-2B-Instruct", "url": "https://www.anchorterminal.com/compare/lbs-27b-vs-qwen3-vl-2b-instruct" }, { "json": "https://www.anchorterminal.com/compare/lbs-27b-vs-qwen3-vl-30b-a3b-instruct.json", "title": "LBS-27B vs Qwen3-VL-30B-A3B-Instruct", "url": "https://www.anchorterminal.com/compare/lbs-27b-vs-qwen3-vl-30b-a3b-instruct" }, { "json": "https://www.anchorterminal.com/compare/lbs-27b-vs-qwen3-vl-32b-instruct.json", "title": "LBS-27B vs Qwen3-VL-32B-Instruct", "url": "https://www.anchorterminal.com/compare/lbs-27b-vs-qwen3-vl-32b-instruct" }, { "json": "https://www.anchorterminal.com/compare/lbs-27b-vs-qwen3-vl-4b-instruct.json", "title": "LBS-27B vs Qwen3-VL-4B-Instruct", "url": "https://www.anchorterminal.com/compare/lbs-27b-vs-qwen3-vl-4b-instruct" }, { "json": "https://www.anchorterminal.com/compare/lbs-27b-vs-qwen3-vl-8b-instruct.json", "title": "LBS-27B vs Qwen3-VL-8B-Instruct", "url": "https://www.anchorterminal.com/compare/lbs-27b-vs-qwen3-vl-8b-instruct" }, { "json": "https://www.anchorterminal.com/compare/lbs-27b-vs-qwopus3-8-27b-flash-v2.json", "title": "LBS-27B vs Qwopus3.8-27B-Flash-V2", "url": "https://www.anchorterminal.com/compare/lbs-27b-vs-qwopus3-8-27b-flash-v2" }, { "json": "https://www.anchorterminal.com/compare/lbs-27b-vs-recursive-flint.json", "title": "LBS-27B vs Recursive Flint", "url": "https://www.anchorterminal.com/compare/lbs-27b-vs-recursive-flint" }, { "json": "https://www.anchorterminal.com/compare/lbs-27b-vs-smollm3-3b.json", "title": "LBS-27B vs SmolLM3-3B", "url": "https://www.anchorterminal.com/compare/lbs-27b-vs-smollm3-3b" }, { "json": "https://www.anchorterminal.com/compare/lbs-27b-vs-spark-x2-6-4b.json", "title": "LBS-27B vs Spark-X2.6-4B", "url": "https://www.anchorterminal.com/compare/lbs-27b-vs-spark-x2-6-4b" }, { "json": "https://www.anchorterminal.com/compare/lbs-27b-vs-swift-1-5-qwen3-8-27b.json", "title": "LBS-27B vs Swift 1.5 Qwen3.8-27B", "url": "https://www.anchorterminal.com/compare/lbs-27b-vs-swift-1-5-qwen3-8-27b" }, { "json": "https://www.anchorterminal.com/compare/lbs-27b-vs-swift-1-5-qwen3-8-flash-next.json", "title": "LBS-27B vs Swift 1.5 Qwen3.8-Flash-Next", "url": "https://www.anchorterminal.com/compare/lbs-27b-vs-swift-1-5-qwen3-8-flash-next" }, { "json": "https://www.anchorterminal.com/compare/lbs-27b-vs-thinkingcap-qwen3-8-27b.json", "title": "LBS-27B vs ThinkingCap (Qwen3.8 27B)", "url": "https://www.anchorterminal.com/compare/lbs-27b-vs-thinkingcap-qwen3-8-27b" }, { "json": "https://www.anchorterminal.com/compare/lbs-27b-vs-unlimited-ocr-2.json", "title": "LBS-27B vs Baidu Unlimited-OCR-2", "url": "https://www.anchorterminal.com/compare/lbs-27b-vs-unlimited-ocr-2" } ], "scores": [ { "key": "capability", "name": "Capability", "pending": true, "weight": 35 }, { "by": 35, "carbon-x": 90, "edge": "carbon-x", "key": "reach", "lbs-27b": 55, "name": "Reach", "weight": 25 }, { "by": 15, "carbon-x": 65, "edge": "carbon-x", "key": "risk", "lbs-27b": 50, "name": "Risk", "weight": 20 }, { "by": 35, "carbon-x": 35, "edge": "lbs-27b", "key": "interface", "lbs-27b": 70, "name": "Agent interface", "weight": 10 }, { "by": 34, "carbon-x": 77, "edge": "carbon-x", "key": "upkeep", "lbs-27b": 43, "name": "Documentation and upkeep", "weight": 10 } ], "summary": "Carbon-X scores 61 (C) on agent readiness against LBS-27B's 53.9 (D), and leads in 3 of 4 scored categories. LBS-27B 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.", "lbs-27b": "A 27B Qwen3.8 fine-tune for GUI grounding that zooms into screenshots over a few turns before naming a point, and inclusionAI says it also helps with fine detail in large images. It needs about 96 GB at BF16 and a client that runs its crop actions. Every result so far is inclusionAI's own, with no safety results or injection guidance." } }, "kind": "anchor.page", "links": { "api": "https://www.anchorterminal.com/api/v1/index.json", "html": "https://www.anchorterminal.com/compare/carbon-x-vs-lbs-27b", "json": "https://www.anchorterminal.com/compare/carbon-x-vs-lbs-27b.json", "llms": "https://www.anchorterminal.com/llms.txt", "markdown": "https://www.anchorterminal.com/compare/carbon-x-vs-lbs-27b.md", "mcp": "https://www.anchorterminal.com/mcp", "slim": "https://www.anchorterminal.com/compare/carbon-x-vs-lbs-27b.min.md" }, "markdown": "Carbon-X scores 61 (C) on agent readiness against LBS-27B's 53.9 (D), and leads in 3 of 4 scored categories. LBS-27B 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- LBS-27B: grade D, 53.9/100, rank #91 of 113 open-weight models. Markdown https://www.anchorterminal.com/tools/lbs-27b.md · JSON https://www.anchorterminal.com/api/v1/tools/lbs-27b.json\n- 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 50\n- Documentation and upkeep, 77 against 43\n\nWatch for: Not clinically validated and no wet-lab validation reported\n\n### LBS-27B (D)\n\nGood for: Agents with about 96 GB of GPU memory that need to find click targets on dense professional screenshots, or read fine detail in large images, and can run a small crop loop and wait for independent results.\n\nAhead on:\n- Agent interface, 70 against 35\n\nWatch for: No independent benchmark result yet; ScreenSpot-Pro, OS-World-G, PerceptionBench and HR-Bench numbers are inclusionAI's own runs\n\n\n## Score by category\n\n| Category | Weight | Carbon-X | LBS-27B | 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 | 50 | Carbon-X +15 |\n| Agent interface | 10% (10 this run) | 35 | 70 | LBS-27B +35 |\n| Documentation and upkeep | 10% (10 this run) | 77 | 43 | Carbon-X +34 |\n| Negative events | ≤15 | 0 | 0 | |\n| **Total** | | **61 · C** | **53.9 · D** | |\n\n## Facts side by side\n\n| Fact | Carbon-X | LBS-27B |\n| --- | --- | --- |\n| Kind | Open-weight model | Open-weight model |\n| Vendor | Hugging Face (HuggingFaceBio) | inclusionAI (Ant Group) |\n| Hosted endpoint | no (local only) | no (local only) |\n| Transports | | |\n| Auth | None | None |\n| Pricing | Free | Free |\n| x402 | no | no |\n| Licence | Apache-2.0 | Apache-2.0 (the card's metadata and licence section; the LICENSE file sits in the GitHub repository inclusionAI/UI-Venus on its LBS branch, not in the Hugging Face repository) |\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**LBS-27B.** A 27B Qwen3.8 fine-tune for GUI grounding that zooms into screenshots over a few turns before naming a point, and inclusionAI says it also helps with fine detail in large images. It needs about 96 GB at BF16 and a client that runs its crop actions. Every result so far is inclusionAI's own, with no safety results or injection guidance.\n\n## 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### LBS-27B\n\n1. Serve with `vllm serve inclusionAI/LBS-27B --tensor-parallel-size 4 --max-model-len 65536`, which is what the card's wrapper script runs; keep the context at 32,768 or more for multi-turn images\n2. Build the system prompt with `build_system_prompt` from the LBS branch's `zoomin_grounding_protocol.py`, send the screenshot after `image_path: \u003cname\u003e`, and don't pass `tools`; the model answers in plain text\n3. Parse `\u003caction\u003ecrop_image(image_path=..., x1=..., y1=..., x2=..., y2=...)\u003c/action\u003e`, cut the crop yourself and return it with its mapping to the original image; allow at most two crops per turn and three per episode\n4. Read the final answer as `[x.xx,y.yy]` on a 0 to 1000 scale of the original image, and use your own executor to click\n5. Pass `reasoning_effort` as `xhigh`, `medium` or `low` only, since the template raises an error for `high`, and don't count on `thinking_budget`, which the template ignores\n6. Don't turn on MTP speculative decoding; the MTP weights aren't in the repository though config.json names one MTP layer\n\n## Questions\n\n### Which is better for AI agents, Carbon-X or LBS-27B?\n\nCarbon-X scores 61 (C) on agent readiness against LBS-27B's 53.9 (D), and leads in 3 of 4 scored categories. LBS-27B leads on agent interface.\n\n\n## For agents\n\n- This comparison as JSON: https://www.anchorterminal.com/compare/carbon-x-vs-lbs-27b.json, and with the fewest tokens: https://www.anchorterminal.com/compare/carbon-x-vs-lbs-27b.min.md\n- Over MCP at https://www.anchorterminal.com/mcp (no key): `compare_tools {\"a\": \"carbon-x\", \"b\": \"lbs-27b\"}`. From a terminal: `anchor compare carbon-x lbs-27b`\n- Each listing in full: https://www.anchorterminal.com/api/v1/tools/carbon-x.json and https://www.anchorterminal.com/api/v1/tools/lbs-27b.json\n\n## Other comparisons with Carbon-X or LBS-27B\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 LBS-27B](https://www.anchorterminal.com/compare/agents-a1-4b-vs-lbs-27b.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 LBS-27B](https://www.anchorterminal.com/compare/apertus-v1-5-8b-vs-lbs-27b.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 LBS-27B](https://www.anchorterminal.com/compare/apodex-1-1-mini-vs-lbs-27b.md)\n- [BigBang-v1 vs Carbon-X](https://www.anchorterminal.com/compare/bigbang-v1-vs-carbon-x.md)\n- [BigBang-v1 vs 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(Qwen3.8 27B)](https://www.anchorterminal.com/compare/lbs-27b-vs-thinkingcap-qwen3-8-27b.md)\n- [LBS-27B vs Baidu Unlimited-OCR-2](https://www.anchorterminal.com/compare/lbs-27b-vs-unlimited-ocr-2.md)\n", "meta": { "attribution": "Anchor Terminal (https://www.anchorterminal.com)", "attributionRequired": true, "credit": "CC BY 4.0, credit Anchor Terminal and link the page or API address you took it from (https://www.anchorterminal.com/terms/#data)", "docs": "https://www.anchorterminal.com/docs/", "generatedAt": "2026-10-27", "license": "CC-BY-4.0", "method": "https://www.anchorterminal.com/benchmark/", "methodology": "0.6", "openapi": "https://www.anchorterminal.com/openapi.json", "preview": false, "run": "2026-10-01", "runLabel": "October 2026 research run", "terms": "https://www.anchorterminal.com/terms/#data" }, "page": { "breadcrumbs": [ { "name": "Home", "url": "https://www.anchorterminal.com/" }, { "name": "Compare", "url": "https://www.anchorterminal.com/compare/" }, { "name": 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