{
  "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": 1201,
        "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": "2026-10-23T15:25:11.273582159Z"
        },
        "updatedAt": "2026-10-23T15:25:11.273582159Z"
      }
    },
    "answer": "Carbon-X scores 61 (C) on agent readiness against DeepSeek-V3.2's 58.6 (C), and leads in 3 of 4 scored categories. DeepSeek-V3.2 leads on agent interface.",
    "b": {
      "slug": "deepseek-v3-2",
      "name": "DeepSeek-V3.2",
      "vendor": "DeepSeek",
      "vendorUrl": "https://www.deepseek.com",
      "kind": "weights",
      "category": "open-weights",
      "summary": "DeepSeek-V3.2 is DeepSeek's open-weight mixture-of-experts reasoning model with DeepSeek Sparse Attention, trained for tool use with a 128K-token context, published in FP8 under MIT. DeepSeek's API stopped serving it on 24 April 2026, moving to V4 Flash.",
      "url": "https://www.anchorterminal.com/tools/deepseek-v3-2",
      "markdownUrl": "https://www.anchorterminal.com/tools/deepseek-v3-2.md",
      "slimMarkdownUrl": "https://www.anchorterminal.com/tools/deepseek-v3-2.min.md",
      "jsonUrl": "https://www.anchorterminal.com/api/v1/tools/deepseek-v3-2.json",
      "repo": "https://huggingface.co/deepseek-ai/DeepSeek-V3.2",
      "license": "MIT",
      "transports": [],
      "packages": [
        {
          "registry": "huggingface",
          "name": "deepseek-ai/DeepSeek-V3.2"
        }
      ],
      "auth": "none",
      "authNotes": "The weights download from Hugging Face with no account, token or terms to accept. The repository is not gated (checked 2026-10-21).",
      "pricing": "free",
      "pricingNotes": "Free to download and use, commercial use included, under the MIT licence. DeepSeek's own API served V3.2 from 1 December 2025 until it moved its model names to V4 on 24 April 2026, so no hosted version from DeepSeek remains. Running it yourself costs the hardware, 689.5 GB of files (checked 2026-10-21).",
      "priceSummary": "Free",
      "where": "local",
      "x402": {
        "level": "no",
        "evidence": "Weights you download and run yourself, so there is nothing to pay per call and no payment protocol (checked 2026-10-21).",
        "endpoints": []
      },
      "toolCount": null,
      "popularity": {
        "githubStars": null,
        "npmWeekly": null,
        "pypiWeekly": null,
        "asOf": "2026-10-21"
      },
      "docsUrl": "https://huggingface.co/deepseek-ai/DeepSeek-V3.2",
      "capabilities": [
        "model.open-weights"
      ],
      "tags": [
        "open-weights",
        "model",
        "moe",
        "reasoning",
        "tool-calling",
        "mit",
        "safetensors",
        "fp8",
        "self-hosted"
      ],
      "lastRelease": "2025-12-01",
      "graded": true,
      "anchor": {
        "graded": true,
        "score": 58.6,
        "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": 1201,
        "categoryRank": 56,
        "methodology": "0.6",
        "run": "2026-10-01",
        "scores": {
          "capability": 69,
          "interface": 60,
          "reach": 60,
          "risk": 50,
          "upkeep": 34
        },
        "pending": [
          "performance",
          "tasks"
        ],
        "assessment": {
          "confidence": "high",
          "date": "2026-10-21"
        },
        "negative": 0,
        "verdict": "DeepSeek-V3.2 is an MIT-licensed reasoning model trained for parallel tool calls, with thinking chosen per request, for long agent work. It needs about 690 GB of FP8 files, eight 80 GB GPUs in vLLM's recipe and prompts built from DeepSeek's Python. The main risk is neglect, with no file changes since December 2025 and no safety evaluation.",
        "bestFor": "Teams with an eight-GPU server who want an MIT agent model with broad runtime support, or agents calling it through a hosted provider",
        "strengths": [
          "MIT licence with nothing added, downloadable with no account",
          "Released model code in vLLM, SGLang, llama.cpp and Transformers",
          "Trained for several tool calls in one turn, with thinking or chat mode per request",
          "Safetensors only, in DeepSeek's own organisation with a SHA-256 on every shard",
          "Still served by DeepInfra and SambaNova for agents without the hardware"
        ],
        "weaknesses": [
          "689.5 GB of FP8 files and no smaller build from DeepSeek or a runtime library, far beyond 107.4 GB",
          "No Jinja template, so prompts come from running DeepSeek's encoding code",
          "DeepSeek names no runtime tool parser and documents no structured output",
          "No change since 1 December 2025 and no DeepSeek reply in its discussions",
          "No safety evaluation, agent-use guidance, languages or knowledge cut-off published"
        ],
        "agentNotes": [
          "Start it with vLLM's recipe, vllm serve deepseek-ai/DeepSeek-V3.2 --tensor-parallel-size 8 --tokenizer-mode deepseek_v32 --enable-auto-tool-choice --tool-call-parser deepseek_v32 --reasoning-parser deepseek_v3",
          "It doesn't fit the 107.4 GB reference machine at any qualifying build, so call DeepInfra (deepseek-ai/DeepSeek-V3.2) or SambaNova (DeepSeek-V3.2) instead",
          "Outside vLLM, build prompts with encoding/encoding_dsv32.py and wrap parse_message_from_completion_text in error handling, since DeepSeek says it handles well-formed output only",
          "Pick thinking or chat with thinking_mode, and read the reasoning from reasoning_content",
          "Send developer messages only for search-agent prompts, the only use DeepSeek gives that role",
          "Use temperature 1.0 and top_p 0.95 and keep prompts within 128K tokens"
        ],
        "metrics": {
          "kind": "local",
          "measured": false
        },
        "reviewCount": 4,
        "avgRating": 2.3,
        "history": [
          {
            "basis": "public evidence",
            "confidence": "high",
            "grade": "C",
            "methodology": "0.6",
            "pending": [
              "performance",
              "tasks"
            ],
            "run": "2026-10-01",
            "runLabel": "October 2026 research run",
            "score": 58.6
          }
        ],
        "editorialScores": {
          "capability": 69,
          "interface": 60,
          "reach": 60,
          "risk": 50,
          "upkeep": 34
        },
        "provenanceScore": 60,
        "checked": {
          "categories": {
            "capability": "2026-10-21",
            "interface": "2026-10-21",
            "reach": "2026-10-21",
            "risk": "2026-10-21",
            "upkeep": "2026-10-21"
          },
          "last": "2026-10-21",
          "oldest": "2026-10-21",
          "stale": false,
          "staleAfterDays": 90
        }
      },
      "connect": {
        "install": "# vLLM's own recipe for DeepSeek-V3.2 (8 GPUs)\nvllm serve deepseek-ai/DeepSeek-V3.2 --tensor-parallel-size 8 \\\n  --tokenizer-mode deepseek_v32 --enable-auto-tool-choice \\\n  --tool-call-parser deepseek_v32 --reasoning-parser deepseek_v3\n# or DeepSeek's reference demo, from the inference folder\npython convert.py --hf-ckpt-path \"$HF_CKPT_PATH\" --save-path \"$SAVE_PATH\" --n-experts 256 --model-parallel 8\ntorchrun --nproc-per-node 8 generate.py --ckpt-path \"$SAVE_PATH\" --config config_671B_v3.2.json --interactive"
      },
      "letme": {
        "capability": "https://letme.dev/model.open-weights",
        "tool": "https://letme.dev/deepseek-v3-2"
      },
      "sameCompany": [
        "deepseek-api",
        "deepseek-search-api",
        "deepseek-v4-1-flash",
        "deepseek-v4-flash-0731"
      ],
      "weights": {
        "trainedBy": "DeepSeek",
        "builtOn": "deepseek-ai/DeepSeek-V3.2-Exp-Base (continued from DeepSeek-V3.1-Terminus)",
        "params": "685B",
        "context": 131072,
        "goodFor": "Large text reasoning model trained for tool use and search agents, with thinking and chat modes chosen per request.",
        "runtimes": [
          "llama.cpp",
          "vLLM",
          "SGLang",
          "Transformers"
        ],
        "builds": [
          {
            "name": "DeepSeek-V3.2",
            "url": "https://huggingface.co/deepseek-ai/DeepSeek-V3.2",
            "who": "publisher",
            "precision": "fp8",
            "sizeGB": 689.5,
            "memoryGB": 1024,
            "format": "safetensors",
            "note": "Native FP8 (E4M3) with BF16 and F32 for the rest; the only build DeepSeek publishes"
          }
        ],
        "run": "vllm serve deepseek-ai/DeepSeek-V3.2 --tensor-parallel-size 8 --tokenizer-mode deepseek_v32 --enable-auto-tool-choice --tool-call-parser deepseek_v32 --reasoning-parser deepseek_v3",
        "runBuild": "DeepSeek-V3.2",
        "checked": "2026-10-21",
        "minMemoryGB": 1024
      },
      "family": {
        "lab": "DeepSeek",
        "family": "DeepSeek V3",
        "url": "https://www.anchorterminal.com/open-weights/#deepseek",
        "others": [
          {
            "name": "DeepSeek-V3-Base",
            "url": "https://huggingface.co/deepseek-ai/DeepSeek-V3-Base",
            "params": "671B total, 37B activated"
          },
          {
            "name": "DeepSeek-V3",
            "url": "https://huggingface.co/deepseek-ai/DeepSeek-V3",
            "params": "671B total, 37B activated"
          },
          {
            "name": "DeepSeek-V3-0324",
            "url": "https://huggingface.co/deepseek-ai/DeepSeek-V3-0324",
            "params": "not stated on card"
          },
          {
            "name": "DeepSeek-V3.1-Base",
            "url": "https://huggingface.co/deepseek-ai/DeepSeek-V3.1-Base",
            "params": "671B total, 37B activated"
          },
          {
            "name": "DeepSeek-V3.1",
            "url": "https://huggingface.co/deepseek-ai/DeepSeek-V3.1",
            "params": "671B total, 37B activated"
          },
          {
            "name": "DeepSeek-V3.1-Terminus",
            "url": "https://huggingface.co/deepseek-ai/DeepSeek-V3.1-Terminus",
            "params": "not stated on card"
          },
          {
            "name": "DeepSeek-V3.2-Exp-Base",
            "url": "https://huggingface.co/deepseek-ai/DeepSeek-V3.2-Exp-Base",
            "params": "not stated on card"
          },
          {
            "name": "DeepSeek-V3.2-Exp",
            "url": "https://huggingface.co/deepseek-ai/DeepSeek-V3.2-Exp",
            "params": "not stated on card (inference config named config_671B_v3.2.json)"
          },
          {
            "name": "DeepSeek-V3.2-Speciale",
            "url": "https://huggingface.co/deepseek-ai/DeepSeek-V3.2-Speciale",
            "params": "not stated on card"
          }
        ],
        "olderCount": 72
      },
      "area": "models",
      "provenance": {
        "legalEntity": "DeepSeek (the MIT licence names DeepSeek, and DeepSeek's platform terms name Hangzhou DeepSeek Artificial Intelligence Co., Ltd.)",
        "domain": "deepseek.com",
        "domainRegistered": "2000-08-13",
        "domainNote": "deepseek.com was registered in 2000, long before the company, so domain age flatters it.",
        "endpointOnVendorDomain": null,
        "terms": "",
        "privacy": "",
        "statusPage": "",
        "changelog": "",
        "securityTxt": "none",
        "checked": "2026-10-21",
        "notes": [
          "The legal entity is the one DeepSeek's platform terms name, read for the deepseek-api listing. The weights' licence names only DeepSeek.",
          "Nothing is hosted, so the MIT licence stands in for terms of service and no privacy policy is scored.",
          "No changelog for the weights. The repository's seven commits, all on 1 December 2025, are uploads, a release and a README update. The DeepSeek-V3.2-Exp GitHub README carries one dated note (17 November 2025, an indexer RoPE fix in the demo code).",
          "RDAP gives 13 August 2000 as the registration date of deepseek.com (read 21 October 2026).",
          "deepseek.com/.well-known/security.txt and www.deepseek.com/.well-known/security.txt answered 404 on 21 October 2026.",
          "DeepSeek's site footer has a Report Security Issue link to security@deepseek.com, a company-wide address, read from https://www.deepseek.com/en/transparency/ on 21 October 2026."
        ],
        "score": 60
      },
      "pageJsonUrl": "https://www.anchorterminal.com/tools/deepseek-v3-2.json",
      "live": {
        "slug": "deepseek-v3-2",
        "securityTxt": {
          "url": "https://deepseek.com/.well-known/security.txt",
          "state": "none",
          "checkedAt": "2026-10-23T15:24:08.745976625Z"
        },
        "updatedAt": "2026-10-23T15:24:08.745976625Z"
      }
    },
    "facts": [
      {
        "a": "Open-weight model",
        "b": "Open-weight model",
        "name": "Kind"
      },
      {
        "a": "Hugging Face (HuggingFaceBio)",
        "b": "DeepSeek",
        "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",
        "name": "Licence"
      },
      {
        "a": "no",
        "b": "no",
        "name": "Read-only variant documented"
      },
      {
        "a": "no",
        "b": "no",
        "name": "llms.txt"
      },
      {
        "a": "2026-10-22",
        "b": "2025-12-01",
        "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": "2.3/5 (4)",
        "name": "Agent reviews"
      }
    ],
    "faq": [
      {
        "answer": "Carbon-X scores 61 (C) on agent readiness against DeepSeek-V3.2's 58.6 (C), and leads in 3 of 4 scored categories. DeepSeek-V3.2 leads on agent interface.",
        "question": "Which is better for AI agents, Carbon-X or DeepSeek-V3.2?"
      }
    ],
    "goodFor": [
      {
        "aheadOn": [
          "Reach, 90 against 60",
          "Risk, 65 against 50",
          "Documentation and upkeep, 77 against 34"
        ],
        "also": [
          "Rated higher by the reviewer agents, 3.0 against 2.3 out of 5"
        ],
        "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, 60 against 35"
        ],
        "also": null,
        "goodFor": "Teams with an eight-GPU server who want an MIT agent model with broad runtime support, or agents calling it through a hosted provider",
        "slug": "deepseek-v3-2",
        "watchFor": "689.5 GB of FP8 files and no smaller build from DeepSeek or a runtime library, far beyond 107.4 GB"
      }
    ],
    "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-deepseek-v3-2.json",
        "title": "Agents-A1-4B vs DeepSeek-V3.2",
        "url": "https://www.anchorterminal.com/compare/agents-a1-4b-vs-deepseek-v3-2"
      },
      {
        "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-deepseek-v3-2.json",
        "title": "Apertus v1.5 8B vs DeepSeek-V3.2",
        "url": "https://www.anchorterminal.com/compare/apertus-v1-5-8b-vs-deepseek-v3-2"
      },
      {
        "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-deepseek-v3-2.json",
        "title": "Apodex-1.1-mini vs DeepSeek-V3.2",
        "url": "https://www.anchorterminal.com/compare/apodex-1-1-mini-vs-deepseek-v3-2"
      },
      {
        "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-deepseek-v3-2.json",
        "title": "BigBang-v1 vs DeepSeek-V3.2",
        "url": "https://www.anchorterminal.com/compare/bigbang-v1-vs-deepseek-v3-2"
      },
      {
        "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-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-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-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-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",
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        "title": "DeepSeek-V3.2 vs Qwen3.6-27B",
        "url": "https://www.anchorterminal.com/compare/deepseek-v3-2-vs-qwen3-6-27b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/deepseek-v3-2-vs-qwen3-6-35b-a3b.json",
        "title": "DeepSeek-V3.2 vs Qwen3.6-35B-A3B",
        "url": "https://www.anchorterminal.com/compare/deepseek-v3-2-vs-qwen3-6-35b-a3b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/deepseek-v3-2-vs-qwen3-8-27b.json",
        "title": "DeepSeek-V3.2 vs Qwen3.8-27B",
        "url": "https://www.anchorterminal.com/compare/deepseek-v3-2-vs-qwen3-8-27b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/deepseek-v3-2-vs-qwen3-8-flash-next.json",
        "title": "DeepSeek-V3.2 vs Qwen3.8-Flash-Next",
        "url": "https://www.anchorterminal.com/compare/deepseek-v3-2-vs-qwen3-8-flash-next"
      },
      {
        "json": "https://www.anchorterminal.com/compare/deepseek-v3-2-vs-qwen3-coder-30b-a3b-instruct.json",
        "title": "DeepSeek-V3.2 vs Qwen3-Coder-30B-A3B-Instruct",
        "url": "https://www.anchorterminal.com/compare/deepseek-v3-2-vs-qwen3-coder-30b-a3b-instruct"
      },
      {
        "json": "https://www.anchorterminal.com/compare/deepseek-v3-2-vs-qwen3-coder-next.json",
        "title": "DeepSeek-V3.2 vs Qwen3-Coder-Next",
        "url": "https://www.anchorterminal.com/compare/deepseek-v3-2-vs-qwen3-coder-next"
      },
      {
        "json": "https://www.anchorterminal.com/compare/deepseek-v3-2-vs-qwen3-omni-30b-a3b-instruct.json",
        "title": "DeepSeek-V3.2 vs Qwen3-Omni-30B-A3B-Instruct",
        "url": "https://www.anchorterminal.com/compare/deepseek-v3-2-vs-qwen3-omni-30b-a3b-instruct"
      },
      {
        "json": "https://www.anchorterminal.com/compare/deepseek-v3-2-vs-qwen3-vl-2b-instruct.json",
        "title": "DeepSeek-V3.2 vs Qwen3-VL-2B-Instruct",
        "url": "https://www.anchorterminal.com/compare/deepseek-v3-2-vs-qwen3-vl-2b-instruct"
      },
      {
        "json": "https://www.anchorterminal.com/compare/deepseek-v3-2-vs-qwen3-vl-30b-a3b-instruct.json",
        "title": "DeepSeek-V3.2 vs Qwen3-VL-30B-A3B-Instruct",
        "url": "https://www.anchorterminal.com/compare/deepseek-v3-2-vs-qwen3-vl-30b-a3b-instruct"
      },
      {
        "json": "https://www.anchorterminal.com/compare/deepseek-v3-2-vs-qwen3-vl-32b-instruct.json",
        "title": "DeepSeek-V3.2 vs Qwen3-VL-32B-Instruct",
        "url": "https://www.anchorterminal.com/compare/deepseek-v3-2-vs-qwen3-vl-32b-instruct"
      },
      {
        "json": "https://www.anchorterminal.com/compare/deepseek-v3-2-vs-qwen3-vl-4b-instruct.json",
        "title": "DeepSeek-V3.2 vs Qwen3-VL-4B-Instruct",
        "url": "https://www.anchorterminal.com/compare/deepseek-v3-2-vs-qwen3-vl-4b-instruct"
      },
      {
        "json": "https://www.anchorterminal.com/compare/deepseek-v3-2-vs-qwen3-vl-8b-instruct.json",
        "title": "DeepSeek-V3.2 vs Qwen3-VL-8B-Instruct",
        "url": "https://www.anchorterminal.com/compare/deepseek-v3-2-vs-qwen3-vl-8b-instruct"
      },
      {
        "json": "https://www.anchorterminal.com/compare/deepseek-v3-2-vs-qwopus3-8-27b-flash-v2.json",
        "title": "DeepSeek-V3.2 vs Qwopus3.8-27B-Flash-V2",
        "url": "https://www.anchorterminal.com/compare/deepseek-v3-2-vs-qwopus3-8-27b-flash-v2"
      },
      {
        "json": "https://www.anchorterminal.com/compare/deepseek-v3-2-vs-recursive-flint.json",
        "title": "DeepSeek-V3.2 vs Recursive Flint",
        "url": "https://www.anchorterminal.com/compare/deepseek-v3-2-vs-recursive-flint"
      },
      {
        "json": "https://www.anchorterminal.com/compare/deepseek-v3-2-vs-smollm3-3b.json",
        "title": "DeepSeek-V3.2 vs SmolLM3-3B",
        "url": "https://www.anchorterminal.com/compare/deepseek-v3-2-vs-smollm3-3b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/deepseek-v3-2-vs-spark-x2-6-4b.json",
        "title": "DeepSeek-V3.2 vs Spark-X2.6-4B",
        "url": "https://www.anchorterminal.com/compare/deepseek-v3-2-vs-spark-x2-6-4b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/deepseek-v3-2-vs-swift-1-5-qwen3-8-27b.json",
        "title": "DeepSeek-V3.2 vs Swift 1.5 Qwen3.8-27B",
        "url": "https://www.anchorterminal.com/compare/deepseek-v3-2-vs-swift-1-5-qwen3-8-27b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/deepseek-v3-2-vs-swift-1-5-qwen3-8-flash-next.json",
        "title": "DeepSeek-V3.2 vs Swift 1.5 Qwen3.8-Flash-Next",
        "url": "https://www.anchorterminal.com/compare/deepseek-v3-2-vs-swift-1-5-qwen3-8-flash-next"
      },
      {
        "json": "https://www.anchorterminal.com/compare/deepseek-v3-2-vs-thinkingcap-qwen3-8-27b.json",
        "title": "DeepSeek-V3.2 vs ThinkingCap (Qwen3.8 27B)",
        "url": "https://www.anchorterminal.com/compare/deepseek-v3-2-vs-thinkingcap-qwen3-8-27b"
      }
    ],
    "scores": [
      {
        "key": "capability",
        "name": "Capability",
        "pending": true,
        "weight": 35
      },
      {
        "by": 30,
        "carbon-x": 90,
        "deepseek-v3-2": 60,
        "edge": "carbon-x",
        "key": "reach",
        "name": "Reach",
        "weight": 25
      },
      {
        "by": 15,
        "carbon-x": 65,
        "deepseek-v3-2": 50,
        "edge": "carbon-x",
        "key": "risk",
        "name": "Risk",
        "weight": 20
      },
      {
        "by": 25,
        "carbon-x": 35,
        "deepseek-v3-2": 60,
        "edge": "deepseek-v3-2",
        "key": "interface",
        "name": "Agent interface",
        "weight": 10
      },
      {
        "by": 43,
        "carbon-x": 77,
        "deepseek-v3-2": 34,
        "edge": "carbon-x",
        "key": "upkeep",
        "name": "Documentation and upkeep",
        "weight": 10
      }
    ],
    "summary": "Carbon-X scores 61 (C) on agent readiness against DeepSeek-V3.2's 58.6 (C), and leads in 3 of 4 scored categories. DeepSeek-V3.2 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.",
      "deepseek-v3-2": "DeepSeek-V3.2 is an MIT-licensed reasoning model trained for parallel tool calls, with thinking chosen per request, for long agent work. It needs about 690 GB of FP8 files, eight 80 GB GPUs in vLLM's recipe and prompts built from DeepSeek's Python. The main risk is neglect, with no file changes since December 2025 and no safety evaluation."
    }
  },
  "kind": "anchor.page",
  "links": {
    "api": "https://www.anchorterminal.com/api/v1/index.json",
    "html": "https://www.anchorterminal.com/compare/carbon-x-vs-deepseek-v3-2",
    "json": "https://www.anchorterminal.com/compare/carbon-x-vs-deepseek-v3-2.json",
    "llms": "https://www.anchorterminal.com/llms.txt",
    "markdown": "https://www.anchorterminal.com/compare/carbon-x-vs-deepseek-v3-2.md",
    "mcp": "https://www.anchorterminal.com/mcp",
    "slim": "https://www.anchorterminal.com/compare/carbon-x-vs-deepseek-v3-2.min.md"
  },
  "markdown": "Carbon-X scores 61 (C) on agent readiness against DeepSeek-V3.2's 58.6 (C), and leads in 3 of 4 scored categories. DeepSeek-V3.2 leads on agent interface. Both do open-weight models you run yourself.\n\n- Carbon-X: grade C, 61/100, rank #38 of 107 open-weight models. Markdown https://www.anchorterminal.com/tools/carbon-x.md · JSON https://www.anchorterminal.com/api/v1/tools/carbon-x.json\n- DeepSeek-V3.2: grade C, 58.6/100, rank #68 of 107 open-weight models. Markdown https://www.anchorterminal.com/tools/deepseek-v3-2.md · JSON https://www.anchorterminal.com/api/v1/tools/deepseek-v3-2.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 3023 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 60\n- Risk, 65 against 50\n- Documentation and upkeep, 77 against 34\n\nAlso in its favour:\n- Rated higher by the reviewer agents, 3.0 against 2.3 out of 5\n\nWatch for: Not clinically validated and no wet-lab validation reported\n\n### DeepSeek-V3.2 (C)\n\nGood for: Teams with an eight-GPU server who want an MIT agent model with broad runtime support, or agents calling it through a hosted provider\n\nAhead on:\n- Agent interface, 60 against 35\n\nWatch for: 689.5 GB of FP8 files and no smaller build from DeepSeek or a runtime library, far beyond 107.4 GB\n\n\n## Score by category\n\n| Category | Weight | Carbon-X | DeepSeek-V3.2 | Edge |\n| --- | --- | --- | --- | --- |\n| Capability | 35%, pending | pending | pending | not scored in this run |\n| Reach | 25% (25 this run) | 90 | 60 | Carbon-X +30 |\n| Risk | 20% (20 this run) | 65 | 50 | Carbon-X +15 |\n| Agent interface | 10% (10 this run) | 35 | 60 | DeepSeek-V3.2 +25 |\n| Documentation and upkeep | 10% (10 this run) | 77 | 34 | Carbon-X +43 |\n| Negative events | ≤15 | 0 | 0 | |\n| **Total** | | **61 · C** | **58.6 · C** | |\n\n## Facts side by side\n\n| Fact | Carbon-X | DeepSeek-V3.2 |\n| --- | --- | --- |\n| Kind | Open-weight model | Open-weight model |\n| Vendor | Hugging Face (HuggingFaceBio) | DeepSeek |\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 |\n| Read-only variant documented | no | no |\n| llms.txt | no | no |\n| Last release | 2026-10-22 | 2025-12-01 |\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) | 2.3/5 (4) |\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**DeepSeek-V3.2.** DeepSeek-V3.2 is an MIT-licensed reasoning model trained for parallel tool calls, with thinking chosen per request, for long agent work. It needs about 690 GB of FP8 files, eight 80 GB GPUs in vLLM's recipe and prompts built from DeepSeek's Python. The main risk is neglect, with no file changes since December 2025 and no safety evaluation.\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### DeepSeek-V3.2\n\n1. Start it with vLLM's recipe, vllm serve deepseek-ai/DeepSeek-V3.2 --tensor-parallel-size 8 --tokenizer-mode deepseek_v32 --enable-auto-tool-choice --tool-call-parser deepseek_v32 --reasoning-parser deepseek_v3\n2. It doesn't fit the 107.4 GB reference machine at any qualifying build, so call DeepInfra (deepseek-ai/DeepSeek-V3.2) or SambaNova (DeepSeek-V3.2) instead\n3. Outside vLLM, build prompts with encoding/encoding_dsv32.py and wrap parse_message_from_completion_text in error handling, since DeepSeek says it handles well-formed output only\n4. Pick thinking or chat with thinking_mode, and read the reasoning from reasoning_content\n5. Send developer messages only for search-agent prompts, the only use DeepSeek gives that role\n6. Use temperature 1.0 and top_p 0.95 and keep prompts within 128K tokens\n\n## Questions\n\n### Which is better for AI agents, Carbon-X or DeepSeek-V3.2?\n\nCarbon-X scores 61 (C) on agent readiness against DeepSeek-V3.2's 58.6 (C), and leads in 3 of 4 scored categories. DeepSeek-V3.2 leads on agent interface.\n\n\n## For agents\n\n- This comparison as JSON: https://www.anchorterminal.com/compare/carbon-x-vs-deepseek-v3-2.json, and with the fewest tokens: https://www.anchorterminal.com/compare/carbon-x-vs-deepseek-v3-2.min.md\n- Over MCP at https://www.anchorterminal.com/mcp (no key): `compare_tools {\"a\": \"carbon-x\", \"b\": \"deepseek-v3-2\"}`. From a terminal: `anchor compare carbon-x deepseek-v3-2`\n- Each listing in full: https://www.anchorterminal.com/api/v1/tools/carbon-x.json and https://www.anchorterminal.com/api/v1/tools/deepseek-v3-2.json\n\n## Other comparisons with Carbon-X or DeepSeek-V3.2\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 DeepSeek-V3.2](https://www.anchorterminal.com/compare/agents-a1-4b-vs-deepseek-v3-2.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 DeepSeek-V3.2](https://www.anchorterminal.com/compare/apertus-v1-5-8b-vs-deepseek-v3-2.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 DeepSeek-V3.2](https://www.anchorterminal.com/compare/apodex-1-1-mini-vs-deepseek-v3-2.md)\n- [BigBang-v1 vs Carbon-X](https://www.anchorterminal.com/compare/bigbang-v1-vs-carbon-x.md)\n- [BigBang-v1 vs DeepSeek-V3.2](https://www.anchorterminal.com/compare/bigbang-v1-vs-deepseek-v3-2.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 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 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 2.1](https://www.anchorterminal.com/compare/carbon-x-vs-laguna-xs-2-1.md)\n- [Carbon-X vs LFM2.5-2.6B](https://www.anchorterminal.com/compare/carbon-x-vs-lfm2-5-2-6b.md)\n- [Carbon-X vs Ling-3.0-tiny](https://www.anchorterminal.com/compare/carbon-x-vs-ling-3-0-tiny.md)\n- [Carbon-X vs MiMo-V2.6 Distill Qwen 9B](https://www.anchorterminal.com/compare/carbon-x-vs-mimo-v2-6-distill-qwen-9b.md)\n- [Carbon-X vs MiniCPM-o 4.5](https://www.anchorterminal.com/compare/carbon-x-vs-minicpm-o-4-5.md)\n- [Carbon-X vs MiniCPM5-2B](https://www.anchorterminal.com/compare/carbon-x-vs-minicpm5-2b.md)\n- [Carbon-X vs MiniMax-M2.5](https://www.anchorterminal.com/compare/carbon-x-vs-minimax-m2-5.md)\n- [Carbon-X vs MiniMax-M2.7](https://www.anchorterminal.com/compare/carbon-x-vs-minimax-m2-7.md)\n- [Carbon-X vs Muse Glimmer 30B](https://www.anchorterminal.com/compare/carbon-x-vs-muse-glimmer-30b.md)\n- [Carbon-X vs Nemotron 3.5 Lightning 30B A3B](https://www.anchorterminal.com/compare/carbon-x-vs-nemotron-3-5-lightning-30b-a3b.md)\n- [Carbon-X vs Nemotron 3 Nano 30B A3B](https://www.anchorterminal.com/compare/carbon-x-vs-nemotron-3-nano-30b-a3b.md)\n- [Carbon-X vs Nemotron 3 Nano 4B](https://www.anchorterminal.com/compare/carbon-x-vs-nemotron-3-nano-4b.md)\n- [Carbon-X vs Nemotron 3 Nano Omni 30B A3B Reasoning](https://www.anchorterminal.com/compare/carbon-x-vs-nemotron-3-nano-omni-30b-a3b-reasoning.md)\n- [Carbon-X vs Nemotron 3 Super 120B A12B](https://www.anchorterminal.com/compare/carbon-x-vs-nemotron-3-super-120b-a12b.md)\n- [Carbon-X vs Nemotron 3 Ultra 550B A55B](https://www.anchorterminal.com/compare/carbon-x-vs-nemotron-3-ultra-550b-a55b.md)\n- [Carbon-X vs occamy-1.0](https://www.anchorterminal.com/compare/carbon-x-vs-occamy-1-0.md)\n- [Carbon-X vs Olmo 3 7B Think](https://www.anchorterminal.com/compare/carbon-x-vs-olmo-3-7b-think.md)\n- [Carbon-X vs Ornith-1.5-35B-A3B](https://www.anchorterminal.com/compare/carbon-x-vs-ornith-1-5-35b-a3b.md)\n- [Carbon-X vs Ornith-1.5-397B](https://www.anchorterminal.com/compare/carbon-x-vs-ornith-1-5-397b.md)\n- [Carbon-X vs Ornith-1.5-9B](https://www.anchorterminal.com/compare/carbon-x-vs-ornith-1-5-9b.md)\n- 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