{
  "data": {
    "a": {
      "slug": "inkling-2-small",
      "name": "Inkling 2 Small",
      "vendor": "Thinking Machines Lab",
      "vendorUrl": "https://thinkingmachines.ai",
      "kind": "weights",
      "category": "open-weights",
      "summary": "Inkling 2 Small is Thinking Machines Lab's open-weight mixture-of-experts model, 594B total and 17B active parameters, taking text and images and returning text, with adjustable thinking effort, published in NVFP4 and MXFP8 under Apache 2.0.",
      "url": "https://www.anchorterminal.com/tools/inkling-2-small",
      "markdownUrl": "https://www.anchorterminal.com/tools/inkling-2-small.md",
      "slimMarkdownUrl": "https://www.anchorterminal.com/tools/inkling-2-small.min.md",
      "jsonUrl": "https://www.anchorterminal.com/api/v1/tools/inkling-2-small.json",
      "dns": "inkling-2-small.grade.anchorterminal.com",
      "repo": "https://huggingface.co/thinkingmachines/Inkling-2-Small",
      "license": "Apache-2.0",
      "transports": [],
      "packages": [
        {
          "registry": "huggingface",
          "name": "thinkingmachines/Inkling-2-Small"
        },
        {
          "registry": "huggingface",
          "name": "thinkingmachines/Inkling-2-Small-MXFP8"
        }
      ],
      "auth": "none",
      "authNotes": "The weights download from Hugging Face with no account, token or terms to accept. Neither repository is gated (checked 2026-11-12). Thinking Machines' Model Acceptable Use Policy, linked from the card, says that downloading or using the weights binds you to it.",
      "pricing": "free",
      "pricingNotes": "Free to download and use, commercial use included, under Apache 2.0 with Thinking Machines' Model Acceptable Use Policy on top. Running it yourself costs the hardware, 393.5 GB of files for the NVFP4 checkpoint and 622.8 GB for MXFP8, which Thinking Machines puts at 500 GB and 800 GB of GPU memory. Thinking Machines' Tinker serves it as a beta serverless inference API at $0.30 per million input tokens, $0.03 cached and $1.00 output (read 2026-11-06).",
      "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 2026-11-12).",
        "endpoints": []
      },
      "toolCount": null,
      "popularity": {
        "githubStars": null,
        "npmWeekly": null,
        "pypiWeekly": null,
        "asOf": "2026-11-12"
      },
      "docsUrl": "https://thinkingmachines.ai/model-card/inkling-2-small/",
      "capabilities": [
        "model.open-weights"
      ],
      "tags": [
        "open-weights",
        "model",
        "moe",
        "multimodal",
        "vision",
        "reasoning",
        "tool-calling",
        "apache-2.0",
        "safetensors",
        "nvfp4",
        "self-hosted",
        "new"
      ],
      "lastRelease": "2026-11-12",
      "graded": true,
      "anchor": {
        "graded": true,
        "score": 58.8,
        "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": 1524,
        "categoryRank": 78,
        "methodology": "0.8",
        "run": "2026-10-01",
        "scores": {
          "interface": 85,
          "reach": 40,
          "risk": 65,
          "upkeep": 67
        },
        "pending": [
          "performance",
          "tasks"
        ],
        "assessment": {
          "confidence": "low",
          "date": "2026-11-12"
        },
        "negative": 0,
        "verdict": "Thinking Machines' newest open model, a 594B mixture-of-experts generalist with images in, several tool calls a turn and per-request thinking effort. The NVFP4 checkpoint needs about 472 GB, and no released runtime runs it yet, so today that means vLLM's or SGLang's own images, or Tinker and Together hosted. The use policy binds on download and can change.",
        "bestFor": "Teams with 512 GB or more of datacentre GPU memory who want Thinking Machines' newest open multimodal agent model and can run a runtime's pre-release image.",
        "strengths": [
          "Safetensors only, with a checksum on every LFS file in the publisher's own organisation",
          "Thinking effort set per request from none to xhigh, several tool calls a turn and a 1M-token context",
          "Two checkpoints from Thinking Machines, NVFP4 and MXFP8, under Apache 2.0 with no gate",
          "Thinking Machines' tml-renderers package renders prompts and parses tool calls for this model",
          "A training-content summary with sources, mix and an October 2026 collection cut-off",
          "Thinking Machines' own Tinker hosts it as beta serverless inference, and the card names seven more API providers"
        ],
        "weaknesses": [
          "The smaller checkpoint needs about 472 GB, and Thinking Machines says 500 GB of GPU memory",
          "No released version of vLLM, SGLang, Transformers, llama.cpp or Ollama runs it on 12 November 2026",
          "Apache 2.0 comes with an acceptable use policy that binds on download and can change at any time",
          "Safety results are Thinking Machines' own, with no harness to rerun them and no prompt-injection guidance",
          "Structured output isn't documented, and the card gives no dated knowledge cut-off",
          "No independent benchmark results were read, so Capability is pending and the total is capped at 61"
        ],
        "agentNotes": [
          "No released runtime runs it yet. Serve the NVFP4 checkpoint from SGLang's dev-inkling-2-small image with the cookbook's recipe for your hardware, or from vLLM's vllm/vllm-openai:inkling-2-small image",
          "In vLLM pass `--reasoning-parser inkling --enable-auto-tool-choice --tool-call-parser inkling`. In SGLang the tool-call parser is `inkling2` and the reasoning parser `inkling`",
          "Transformers' main branch loads only thinkingmachines/Inkling-2-Small-MXFP8, the 622.8 GB checkpoint, and no release has the code yet",
          "Pass `reasoning_effort` as none, minimal, low, medium, high (the default), xhigh or max, or a number from 0 to 0.99",
          "Effort none conditions the model toward no reasoning but doesn't forbid it, and higher effort needs a larger max_tokens",
          "Tool call arguments must reach the template as an object, not a JSON string, or it raises an error",
          "Images should be 40 to 4096 px a side. The model takes no audio, and the template raises an error for an audio part",
          "Use guided decoding or validate JSON yourself, since structured output isn't documented",
          "Without the hardware, call it on Tinker's OpenAI-compatible endpoint with a Tinker key, at $0.30 input and $1.00 output per million tokens as read on 6 November 2026",
          "Read the Model Acceptable Use Policy before deploying, it binds on download and bars some uses that are legal"
        ],
        "metrics": {
          "kind": "local",
          "measured": false
        },
        "reviewCount": 0,
        "avgRating": 0,
        "history": [
          {
            "basis": "public evidence",
            "confidence": "low",
            "grade": "C",
            "methodology": "0.8",
            "pending": [
              "performance",
              "tasks"
            ],
            "run": "2026-10-01",
            "runLabel": "October 2026 research run",
            "score": 58.8
          }
        ],
        "editorialScores": {
          "interface": 85,
          "reach": 40,
          "risk": 65,
          "upkeep": 67
        },
        "provenanceScore": 72,
        "checked": {
          "categories": {
            "interface": "2026-11-12",
            "reach": "2026-11-12",
            "risk": "2026-11-12",
            "upkeep": "2026-11-12"
          },
          "last": "2026-11-12",
          "lastMoved": "2026-11-12",
          "oldest": "2026-11-12",
          "stale": false,
          "staleAfterDays": 90
        }
      },
      "connect": {
        "install": "# per SGLang's cookbook, the NVFP4 checkpoint on 4 B300 GPUs. Not in an SGLang release yet,\n# so run it inside the lmsysorg/sglang:dev-inkling-2-small image:\nSGLANG_OPT_DEEPGEMM_MEGA_MOE_NUM_MAX_TOKENS_PER_RANK=4096 sglang serve \\\n  --model-path thinkingmachines/Inkling-2-Small --tp 4 --ep 4 \\\n  --moe-a2a-backend megamoe --attention-backend fa4 --bf16-gemm-backend torch --dtype bfloat16 \\\n  --page-size 128 --grammar-backend xgrammar --enable-multimodal \\\n  --reasoning-parser inkling --tool-call-parser inkling2",
        "http": "curl http://localhost:30000/v1/chat/completions \\\n  -H \"Content-Type: application/json\" \\\n  -d '{\n    \"model\": \"thinkingmachines/Inkling-2-Small\",\n    \"messages\": [{\"role\": \"user\", \"content\": \"Hello!\"}],\n    \"reasoning_effort\": \"low\"\n  }'"
      },
      "letme": {
        "capability": "https://letme.dev/model.open-weights",
        "tool": "https://letme.dev/inkling-2-small"
      },
      "sameCompany": [
        "inkling",
        "inkling-small"
      ],
      "sameModel": [
        "tinker"
      ],
      "weights": {
        "trainedBy": "Thinking Machines Lab",
        "params": "594B",
        "active": "17B",
        "context": 1048576,
        "goodFor": "Mixture-of-experts generalist for coding, agents and tool use with images in, a 1M-token context and thinking effort set per request.",
        "runtimes": [],
        "builds": [
          {
            "name": "Inkling-2-Small",
            "url": "https://huggingface.co/thinkingmachines/Inkling-2-Small",
            "who": "publisher",
            "precision": "nvfp4",
            "sizeGB": 393.5,
            "memoryGB": 512,
            "format": "safetensors",
            "note": "The main checkpoint, in the precision the model was trained in. Routed experts in NVFP4 for layers 0 to 39 and MXFP8 for layers 40 to 47, per SGLang's cookbook. Thinking Machines states at least 500 GB of GPU memory"
          },
          {
            "name": "Inkling-2-Small-MXFP8",
            "url": "https://huggingface.co/thinkingmachines/Inkling-2-Small-MXFP8",
            "who": "publisher",
            "precision": "mxfp8",
            "sizeGB": 622.8,
            "memoryGB": 1024,
            "format": "safetensors",
            "note": "Every routed expert in MXFP8. Thinking Machines states at least 800 GB of GPU memory and recommends the NVFP4 checkpoint. It's the only checkpoint Transformers' main branch loads"
          }
        ],
        "run": "SGLANG_OPT_DEEPGEMM_MEGA_MOE_NUM_MAX_TOKENS_PER_RANK=4096 sglang serve --model-path thinkingmachines/Inkling-2-Small --tp 4 --ep 4 --moe-a2a-backend megamoe --attention-backend fa4 --bf16-gemm-backend torch --dtype bfloat16 --page-size 128 --grammar-backend xgrammar --enable-multimodal --reasoning-parser inkling --tool-call-parser inkling2",
        "runBuild": "Inkling-2-Small",
        "checked": "2026-11-12",
        "minMemoryGB": 512
      },
      "family": {
        "lab": "Thinking Machines Lab",
        "family": "Inkling 2",
        "url": "https://www.anchorterminal.com/open-weights/#thinking-machines"
      },
      "area": "models",
      "provenance": {
        "legalEntity": "Thinking Machines Lab, Inc. (named as provider on its model card page and in its training-content summary)",
        "domain": "thinkingmachines.ai",
        "domainRegistered": "",
        "domainNote": "Not looked up: RDAP isn't requested under the 1 November 2026 rules.",
        "endpointOnVendorDomain": null,
        "terms": "",
        "privacy": "",
        "statusPage": "",
        "changelog": "https://huggingface.co/thinkingmachines/Inkling-2-Small/commits/main",
        "securityTxt": "valid",
        "checked": "2026-11-12",
        "notes": [
          "Thinking Machines' model card page links both repositories in the thinkingmachines organisation on Hugging Face, which isn't verified by Hugging Face.",
          "Nothing is hosted for this listing, so the Apache 2.0 licence and the Model Acceptable Use Policy stand in for terms of service and no privacy policy is scored.",
          "The changelog is the repository's commit history, 3 commits on 12 November 2026, the upload, a library tag from a merged pull request and a card update.",
          "thinkingmachines.ai/.well-known/security.txt gives a security contact, a PGP key and an expiry in 2029, read on 12 November 2026, and the model card page links a coordinated vulnerability disclosure policy.",
          "Thinking Machines' terms bar scraping the Services. The founder decided on 6 November 2026 that reading at a person's pace is fine, so six pages were read one at a time on 12 November: the acceptable use policy, the training data page and its summary for this model, the model card page, and the tml-renderers and thinking effort guides. thinkingmachines.ai's robots.txt has no rules, and tinker-docs.thinkingmachines.ai answers 404 for robots.txt."
        ],
        "score": 72
      },
      "pageJsonUrl": "https://www.anchorterminal.com/tools/inkling-2-small.json",
      "live": {
        "slug": "inkling-2-small",
        "probe": {
          "target": "https://tinker.thinkingmachines.dev/services/tinker-prod/oai/api/v1",
          "method": "get",
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          "lastOk": true,
          "lastStatus": 404,
          "lastMs": 439,
          "authRequired": false,
          "uptime24h": 100,
          "uptime30d": 100,
          "p50ms24h": 238,
          "p95ms24h": 467,
          "samples24h": 245,
          "samples30d": 1854,
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        "securityTxt": {
          "url": "https://thinkingmachines.ai/.well-known/security.txt",
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          "expires": "2029-07-13T07:00:00.000Z",
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        },
        "llmsTxt": {
          "url": "https://tinker-docs.thinkingmachines.ai/llms.txt",
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        "domain": {
          "domain": "thinkingmachines.ai",
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        "pages": [
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      "streak": {
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        "sinceWatching": true,
        "best": 9
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    },
    "answer": "Nemotron 3 Nano Omni 30B A3B Reasoning scores 61.2 (C) on agent readiness against Inkling 2 Small's 58.8 (C), and leads in 3 of 4 scored categories. Inkling 2 Small leads on risk.",
    "b": {
      "slug": "nemotron-3-nano-omni-30b-a3b-reasoning",
      "name": "Nemotron 3 Nano Omni 30B A3B Reasoning",
      "vendor": "NVIDIA",
      "vendorUrl": "https://developer.nvidia.com/nemotron",
      "kind": "weights",
      "category": "open-weights",
      "summary": "Nemotron 3 Nano Omni is NVIDIA's open-weight multimodal model that takes video, audio, images and text and returns text, a hybrid Mamba-Transformer mixture of experts with about 31B parameters and 3B active, published in BF16, FP8 and NVFP4.",
      "url": "https://www.anchorterminal.com/tools/nemotron-3-nano-omni-30b-a3b-reasoning",
      "markdownUrl": "https://www.anchorterminal.com/tools/nemotron-3-nano-omni-30b-a3b-reasoning.md",
      "slimMarkdownUrl": "https://www.anchorterminal.com/tools/nemotron-3-nano-omni-30b-a3b-reasoning.min.md",
      "jsonUrl": "https://www.anchorterminal.com/api/v1/tools/nemotron-3-nano-omni-30b-a3b-reasoning.json",
      "dns": "nemotron-3-nano-omni-30b-a3b-reasoning.grade.anchorterminal.com",
      "repo": "https://huggingface.co/nvidia/Nemotron-3-Nano-Omni-30B-A3B-Reasoning-BF16",
      "license": "NVIDIA Open Model Agreement (custom, commercial use allowed, not an OSI licence)",
      "transports": [],
      "packages": [
        {
          "registry": "huggingface",
          "name": "nvidia/Nemotron-3-Nano-Omni-30B-A3B-Reasoning-BF16"
        },
        {
          "registry": "huggingface",
          "name": "nvidia/Nemotron-3-Nano-Omni-30B-A3B-Reasoning-FP8"
        },
        {
          "registry": "huggingface",
          "name": "nvidia/Nemotron-3-Nano-Omni-30B-A3B-Reasoning-NVFP4"
        },
        {
          "registry": "ollama",
          "name": "nemotron3"
        }
      ],
      "auth": "none",
      "authNotes": "The weights download from Hugging Face with no account, token or terms to accept. The BF16, FP8 and NVFP4 repositories are not gated (checked 2026-10-21). The card's download section still shows an hf auth login step, which the ungated files don't need.",
      "pricing": "free",
      "pricingNotes": "Free to download and use, commercial use included, under the NVIDIA Open Model Agreement. Running it yourself costs the hardware, 66.1 GB for the BF16 files, 35.2 GB for FP8 and 22.4 GB for NVFP4, per the Hub's file lists. NVIDIA's own API also serves it (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": "2026-11-03"
      },
      "docsUrl": "https://huggingface.co/nvidia/Nemotron-3-Nano-Omni-30B-A3B-Reasoning-BF16",
      "capabilities": [
        "speech.stt",
        "speech.batch",
        "model.open-weights"
      ],
      "tags": [
        "open-weights",
        "model",
        "moe",
        "multimodal",
        "omni",
        "vision",
        "audio",
        "video",
        "reasoning",
        "tool-calling",
        "speech-to-text",
        "safetensors",
        "fp8",
        "nvfp4",
        "self-hosted"
      ],
      "lastRelease": "2026-08-24",
      "graded": true,
      "anchor": {
        "graded": true,
        "score": 61.2,
        "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": 1524,
        "categoryRank": 27,
        "methodology": "0.8",
        "run": "2026-10-01",
        "scores": {
          "capability": 34,
          "interface": 90,
          "reach": 85,
          "risk": 60,
          "upkeep": 70
        },
        "pending": [
          "performance",
          "tasks"
        ],
        "assessment": {
          "confidence": "high",
          "date": "2026-11-03"
        },
        "negative": 0,
        "verdict": "A local multimodal model for video with speech, long documents, charts, screens and English transcription, with tool calling, a reasoning switch and a 262,144-token context. It needs about 27 GB for NVIDIA's NVFP4 build on Blackwell, or 42 GB for FP8. The main risks are the remote code it loads and a repository where nobody answers questions.",
        "bestFor": "Agents with a 32 to 48 GB NVIDIA GPU that need one local model to read video, audio, documents and screens and call tools",
        "strengths": [
          "Video, audio, images and text in one model, with word-level timestamps for transcription per the card",
          "Released support in vLLM, SGLang, llama.cpp, Ollama and LM Studio, plus NVIDIA's own FP8 and NVFP4 builds",
          "Tool calling with a named parser and NVIDIA cookbooks, and thinking that turns off or takes a budget per request",
          "Training data listed by dataset with sample and token counts",
          "Commercial use under an irrevocable licence with no use policy or threshold, ungated, and served by NVIDIA's own API"
        ],
        "weaknesses": [
          "Loads with trust_remote_code in every documented runtime command",
          "English only, no speaker diarisation, translation or streaming input, and video capped at 2 minutes",
          "No published safety results and no agent-specific guidance such as prompt-injection advice",
          "None of the 11 questions in its three repositories has a reply",
          "The NVFP4 build needs NVIDIA Blackwell, and SGLang supports only the BF16 build so far, per the card"
        ],
        "agentNotes": [
          "Start it with `vllm serve nvidia/Nemotron-3-Nano-Omni-30B-A3B-Reasoning-FP8 --max-model-len 131072 --trust-remote-code --reasoning-parser nemotron_v3 --enable-auto-tool-choice --tool-call-parser qwen3_coder --kv-cache-dtype fp8` on vLLM 0.20.0 or later, after `pip install \"vllm[audio]\"` if any audio will be sent",
          "Or run `ollama run nemotron3`; the 33b-nvfp4 and 33b-mlx tags are MLX builds for Apple silicon, and the q4_K_M tag is 28 GB",
          "Set `--media-io-kwargs '{\"video\": {\"fps\": 2, \"num_frames\": 256}}'` at launch, since vLLM otherwise samples about 32 frames per video",
          "Send `chat_template_kwargs: {\"enable_thinking\": false}` for transcription and quick answers, and use temperature 1.0 with top_k 1 for ASR as the card recommends",
          "Render PDF pages to PNG and send them as images, since the API takes no raw PDF",
          "Treat transcripts and text read from images or video as untrusted input before acting on them"
        ],
        "metrics": {
          "kind": "local",
          "measured": false
        },
        "reviewCount": 4,
        "avgRating": 3,
        "history": [
          {
            "basis": "public evidence",
            "confidence": "high",
            "grade": "C",
            "methodology": "0.8",
            "pending": [
              "performance",
              "tasks"
            ],
            "run": "2026-10-01",
            "runLabel": "October 2026 research run",
            "score": 61.2
          }
        ],
        "editorialScores": {
          "capability": 34,
          "interface": 90,
          "reach": 85,
          "risk": 60,
          "upkeep": 70
        },
        "provenanceScore": 72,
        "checked": {
          "categories": {
            "capability": "2026-11-03",
            "interface": "2026-11-03",
            "reach": "2026-11-03",
            "risk": "2026-11-03",
            "upkeep": "2026-11-03"
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          "last": "2026-11-03",
          "lastMoved": "2026-11-03",
          "oldest": "2026-11-03",
          "stale": false,
          "staleAfterDays": 90
        }
      },
      "connect": {
        "install": "ollama run nemotron3\n# or, with vLLM 0.20.0 or later as the card gives it:\npip install \"vllm[audio]\"\nvllm serve nvidia/Nemotron-3-Nano-Omni-30B-A3B-Reasoning-FP8 --max-model-len 131072 \\\n  --trust-remote-code --reasoning-parser nemotron_v3 \\\n  --enable-auto-tool-choice --tool-call-parser qwen3_coder --kv-cache-dtype fp8",
        "http": "curl http://localhost:8000/v1/chat/completions \\\n  -H 'Content-Type: application/json' \\\n  -d '{\"model\": \"nvidia/Nemotron-3-Nano-Omni-30B-A3B-Reasoning-FP8\", \"messages\": [{\"role\": \"user\", \"content\": \"Hello\"}], \"chat_template_kwargs\": {\"enable_thinking\": false}}'"
      },
      "letme": {
        "capability": "https://letme.dev/speech.stt",
        "tool": "https://letme.dev/nemotron-3-nano-omni-30b-a3b-reasoning"
      },
      "sameCompany": [
        "nemotron-3-5-super-vl",
        "nvidia-nemo-retriever",
        "nemo-guardrails",
        "nemotron-3-5-asr-streaming-0-6b",
        "nemotron-3-5-transcribe-30b-a4b",
        "parakeet-tdt-0-6b-v3",
        "parakeet-unified-en-0-6b",
        "nemotron-3-5-parse",
        "cosmos-reason2-2b",
        "nemotron-3-5-bolt-e4b-4gb",
        "nemotron-3-nano-30b-a3b",
        "nemotron-3-nano-4b",
        "nemotron-3-super-120b-a12b",
        "nemotron-3-ultra-550b-a55b",
        "nemotron-3-5-lightning-30b-a3b"
      ],
      "weights": {
        "trainedBy": "NVIDIA",
        "builtOn": "nvidia/NVIDIA-Nemotron-3-Nano-30B-A3B-BF16",
        "params": "31B",
        "active": "3B",
        "context": 262144,
        "goodFor": "Multimodal understanding of video with speech, documents, charts and screens, and English transcription, with tool calling and a reasoning budget.",
        "runtimes": [
          "llama.cpp",
          "Ollama",
          "vLLM",
          "SGLang",
          "LM Studio",
          "Transformers"
        ],
        "builds": [
          {
            "name": "Nemotron-3-Nano-Omni-30B-A3B-Reasoning-NVFP4",
            "url": "https://huggingface.co/nvidia/Nemotron-3-Nano-Omni-30B-A3B-Reasoning-NVFP4",
            "who": "publisher",
            "precision": "nvfp4",
            "sizeGB": 22.4,
            "memoryGB": 32,
            "format": "safetensors",
            "note": "NVFP4 needs NVIDIA Blackwell; the card's minimum is one RTX 5090 32 GB"
          },
          {
            "name": "ollama nemotron3:33b-nvfp4",
            "url": "https://ollama.com/library/nemotron3:33b-nvfp4",
            "who": "ollama",
            "precision": "nvfp4",
            "sizeGB": 21,
            "memoryGB": 32,
            "format": "ollama",
            "runsOn": [
              "Ollama"
            ],
            "note": "MLX build (digest f263b909bfad, the same as 33b-mlx), so Apple silicon only. Size as Ollama's tags page shows it, rounded to whole GB"
          },
          {
            "name": "LM Studio nvidia/nemotron-3-nano-omni Q4_K_M",
            "url": "https://huggingface.co/lmstudio-community/Nemotron-3-Nano-Omni-30B-A3B-Reasoning-GGUF",
            "who": "lmstudio",
            "precision": "q4_k_m",
            "sizeGB": 26.1,
            "memoryGB": 32,
            "format": "gguf",
            "runsOn": [
              "LM Studio",
              "llama.cpp"
            ],
            "note": "Q4_K_M GGUF of 24.52 GB plus the 1.59 GB BF16 vision projector, the build behind LM Studio's catalogue entry"
          },
          {
            "name": "Nemotron-3-Nano-Omni-30B-A3B-Reasoning-FP8",
            "url": "https://huggingface.co/nvidia/Nemotron-3-Nano-Omni-30B-A3B-Reasoning-FP8",
            "who": "publisher",
            "precision": "fp8",
            "sizeGB": 35.2,
            "memoryGB": 48,
            "format": "safetensors",
            "note": "The card says SGLang support for FP8 is still to come"
          },
          {
            "name": "ollama nemotron3:33b-q4_K_M",
            "url": "https://ollama.com/library/nemotron3:33b-q4_K_M",
            "who": "ollama",
            "precision": "q4_k_m",
            "sizeGB": 28,
            "memoryGB": 48,
            "format": "ollama",
            "runsOn": [
              "Ollama"
            ],
            "note": "digest baa676a14e13, text and image input per the tags page. Size as Ollama's tags page shows it, rounded to whole GB"
          },
          {
            "name": "Nemotron-3-Nano-Omni-30B-A3B-Reasoning-BF16",
            "url": "https://huggingface.co/nvidia/Nemotron-3-Nano-Omni-30B-A3B-Reasoning-BF16",
            "who": "publisher",
            "precision": "bf16",
            "sizeGB": 66.1,
            "memoryGB": 96,
            "format": "safetensors",
            "note": "Includes 7.3 MB of sample media; loads with trust_remote_code"
          }
        ],
        "run": "vllm serve nvidia/Nemotron-3-Nano-Omni-30B-A3B-Reasoning-FP8 --max-model-len 131072 --trust-remote-code --video-pruning-rate 0.5 --media-io-kwargs '{\"video\": {\"fps\": 2, \"num_frames\": 256}}' --reasoning-parser nemotron_v3 --enable-auto-tool-choice --tool-call-parser qwen3_coder --kv-cache-dtype fp8",
        "runBuild": "Nemotron-3-Nano-Omni-30B-A3B-Reasoning-FP8",
        "checked": "2026-10-21",
        "minMemoryGB": 32
      },
      "family": {
        "lab": "NVIDIA (Nemotron)",
        "family": "Nemotron 3",
        "url": "https://www.anchorterminal.com/open-weights/#nvidia",
        "others": [
          {
            "name": "Nemotron 3 Nano 30B-A3B",
            "url": "https://huggingface.co/nvidia/NVIDIA-Nemotron-3-Nano-30B-A3B-BF16",
            "params": "30B total, 3B active (31.6B per the safetensors index)",
            "listing": "https://www.anchorterminal.com/tools/nemotron-3-nano-30b-a3b"
          },
          {
            "name": "Nemotron 3 Nano 30B-A3B Base",
            "url": "https://huggingface.co/nvidia/NVIDIA-Nemotron-3-Nano-30B-A3B-Base-BF16",
            "params": "30B total, 3B active"
          },
          {
            "name": "Nemotron 3 Super 120B-A12B",
            "url": "https://huggingface.co/nvidia/NVIDIA-Nemotron-3-Super-120B-A12B-BF16",
            "params": "120B total, 12B active",
            "listing": "https://www.anchorterminal.com/tools/nemotron-3-super-120b-a12b"
          },
          {
            "name": "Nemotron 3 Super 120B-A12B Base",
            "url": "https://huggingface.co/nvidia/NVIDIA-Nemotron-3-Super-120B-A12B-Base-BF16",
            "params": "120B total, 12B active"
          },
          {
            "name": "Nemotron 3 Nano 4B",
            "url": "https://huggingface.co/nvidia/NVIDIA-Nemotron-3-Nano-4B-BF16",
            "params": "4B",
            "listing": "https://www.anchorterminal.com/tools/nemotron-3-nano-4b"
          },
          {
            "name": "Nemotron 3 Ultra 550B-A55B",
            "url": "https://huggingface.co/nvidia/NVIDIA-Nemotron-3-Ultra-550B-A55B-BF16",
            "params": "550B total, 55B active",
            "listing": "https://www.anchorterminal.com/tools/nemotron-3-ultra-550b-a55b"
          },
          {
            "name": "Nemotron 3 Ultra 550B-A55B Base",
            "url": "https://huggingface.co/nvidia/NVIDIA-Nemotron-3-Ultra-550B-A55B-Base-BF16",
            "params": "550B total, 55B active"
          },
          {
            "name": "Nemotron 3 Ultra 550B-A55B GenRM",
            "url": "https://huggingface.co/nvidia/NVIDIA-Nemotron-3-Ultra-550B-A55B-GenRM",
            "params": "550B total, 55B active"
          },
          {
            "name": "Nemotron 3.5 Lightning 30B-A3B",
            "url": "https://huggingface.co/nvidia/NVIDIA-Nemotron-3.5-Lightning-30B-A3B-BF16",
            "params": "30B total, 3B active",
            "listing": "https://www.anchorterminal.com/tools/nemotron-3-5-lightning-30b-a3b"
          },
          {
            "name": "Nemotron 3.5 Lightning 30B-A3B Base",
            "url": "https://huggingface.co/nvidia/NVIDIA-Nemotron-3.5-Lightning-30B-A3B-Base-BF16",
            "params": "30B total, 3B active"
          },
          {
            "name": "Nemotron 3.5 Super VL 120B-A12B",
            "url": "https://huggingface.co/nvidia/NVIDIA-Nemotron-3.5-Super-VL-120B-A12B-BF16",
            "params": "120B total, 12B active",
            "listing": "https://www.anchorterminal.com/tools/nemotron-3-5-super-vl"
          },
          {
            "name": "Nemotron 3.5 Super VL 120B-A12B Base",
            "url": "https://huggingface.co/nvidia/NVIDIA-Nemotron-3.5-Super-VL-120B-A12B-Base-BF16",
            "params": "120B total, 12B active"
          },
          {
            "name": "Nemotron 3.5 Bolt 74B-A9B",
            "url": "https://huggingface.co/nvidia/NVIDIA-Nemotron-3.5-Bolt-74B-A9B-BF16",
            "params": "74B total, 9B active"
          },
          {
            "name": "Nemotron 3.5 Bolt E4B 4GB",
            "url": "https://huggingface.co/nvidia/NVIDIA-Nemotron-3.5-Bolt-E4B-4GB",
            "params": "8B total, 4B effective",
            "listing": "https://www.anchorterminal.com/tools/nemotron-3-5-bolt-e4b-4gb"
          },
          {
            "name": "Nemotron Labs 3 Elastic 30B-A3B",
            "url": "https://huggingface.co/nvidia/NVIDIA-Nemotron-Labs-3-Elastic-30B-A3B-BF16",
            "params": "30B total, 3B active"
          },
          {
            "name": "Nemotron Labs 3 Puzzle 75B-A9B",
            "url": "https://huggingface.co/nvidia/NVIDIA-Nemotron-Labs-3-Puzzle-75B-A9B-BF16",
            "params": "75B total, 9B active"
          },
          {
            "name": "Nemotron 3 Labs Ultra Math SFT",
            "url": "https://huggingface.co/nvidia/Nemotron-3-Labs-Ultra-Math-SFT",
            "params": "550B total, 55B active"
          },
          {
            "name": "Nemotron 3 Labs Ultra Math RL",
            "url": "https://huggingface.co/nvidia/Nemotron-3-Labs-Ultra-Math-RL",
            "params": "550B total, 55B active"
          },
          {
            "name": "Nemotron Labs 3 Competitive Coding 550B-A55B",
            "url": "https://huggingface.co/nvidia/NVIDIA-Nemotron-Labs-3-Competitive-Coding-550B-A55B-NVFP4",
            "params": "550B total, 55B active"
          },
          {
            "name": "nemotron-3.5-asr-streaming-0.6b",
            "url": "https://huggingface.co/nvidia/nemotron-3.5-asr-streaming-0.6b",
            "params": "0.6B (638M per the safetensors count)",
            "listing": "https://www.anchorterminal.com/tools/nemotron-3-5-asr-streaming-0-6b"
          },
          {
            "name": "Nemotron 3.5 Parse",
            "url": "https://huggingface.co/nvidia/Nemotron-3.5-Parse",
            "params": "0.631B (630,800,496 trainable parameters per the card)",
            "listing": "https://www.anchorterminal.com/tools/nemotron-3-5-parse"
          },
          {
            "name": "Nemotron 3.5 Transcribe 30B-A4B",
            "url": "https://huggingface.co/nvidia/NVIDIA-Nemotron-3.5-Transcribe-30B-A4B",
            "params": "30B total, about 4.3B active (33,697,781,029 by the Hub's safetensors count)",
            "listing": "https://www.anchorterminal.com/tools/nemotron-3-5-transcribe-30b-a4b"
          }
        ],
        "olderCount": 47,
        "unrestrictedCopies": 5
      },
      "alsoIn": [
        "speech-to-text"
      ],
      "area": "models",
      "provenance": {
        "legalEntity": "NVIDIA Corporation",
        "domain": "nvidia.com",
        "domainRegistered": "1993-04-20",
        "endpointOnVendorDomain": null,
        "terms": "https://www.nvidia.com/en-us/agreements/enterprise-software/nvidia-open-model-agreement/",
        "privacy": "",
        "statusPage": "",
        "changelog": "https://huggingface.co/nvidia/Nemotron-3-Nano-Omni-30B-A3B-Reasoning-BF16/commits/main",
        "securityTxt": "none",
        "checked": "2026-10-21",
        "notes": [
          "The card says the model was developed by NVIDIA, and the licence names NVIDIA Corporation. The domain registration date is carried from the RDAP check made for nemotron-3-nano-30b-a3b on 21 October 2026.",
          "Nothing is hosted for this listing, so the NVIDIA Open Model Agreement stands in for terms of service and no privacy policy is scored.",
          "The changelog is the BF16 repository's commit history, 30 commits from 20 April to 24 August 2026. Some messages say what changed (Transformers 5.6 support on 27 April, batched audio on 28 April, the C-RADIOv4-H encoder reference on 8 May); the latest reads Update README.md.",
          "www.nvidia.com/.well-known/security.txt answered 403 at the 21 October 2026 check for nemotron-3-nano-30b-a3b. The card links NVIDIA's security vulnerability form, and NVIDIA PSIRT publishes a disclosure policy and bulletins."
        ],
        "score": 72
      },
      "pageJsonUrl": "https://www.anchorterminal.com/tools/nemotron-3-nano-omni-30b-a3b-reasoning.json",
      "live": {
        "slug": "nemotron-3-nano-omni-30b-a3b-reasoning",
        "securityTxt": {
          "url": "https://nvidia.com/.well-known/security.txt",
          "state": "unknown",
          "checkedAt": "2026-11-14T16:17:34.346018248Z"
        },
        "domain": {
          "domain": "nvidia.com",
          "registered": "1993-04-20",
          "source": "https://rdap.verisign.com/com/v1/domain/nvidia.com",
          "checkedAt": "2026-11-15T15:15:54.279575834Z"
        },
        "pages": [
          {
            "url": "https://huggingface.co/nvidia/Nemotron-3-Nano-Omni-30B-A3B-Reasoning-BF16/commits/main",
            "kind": "changelog",
            "status": 200,
            "checkedAt": "2026-11-14T19:06:55.892682215Z",
            "changedAt": "2026-11-14T19:06:55.892682215Z",
            "fingerprint": "b019a0c263fa"
          },
          {
            "url": "https://www.nvidia.com/en-us/agreements/enterprise-software/nvidia-open-model-agreement/",
            "kind": "terms",
            "status": 304,
            "checkedAt": "2026-11-14T19:25:18.344145173Z",
            "changedAt": "2026-10-29T05:25:34.28731257Z",
            "fingerprint": "35918cb1a524"
          }
        ],
        "updatedAt": "2026-11-15T15:15:54.279575834Z"
      }
    },
    "edges": [
      {
        "by": 45,
        "category": "reach",
        "leads": "nemotron-3-nano-omni-30b-a3b-reasoning",
        "name": "Reach",
        "reasons": {
          "a": "Memory 0 of 30, the smallest build is Thinking Machines' NVFP4 checkpoint at 393.5 GB, about 472 GB with a fifth added, above the 256 GB line. Runtimes 0, no released version of the six runs it; vLLM and SGLang serve it from their own images and Transformers has it on its main branch only. Builds 15, two precisions from the publisher (NVFP4 and MXFP8). Terms 10, Apache 2.0 with a binding acceptable use policy on top, read as a custom licence. Download 10, no gate. Hosted 5, Thinking Machines' own Tinker serves it as beta serverless inference, and Together is live on Hugging Face. 0 + 0 + 15 + 10 + 10 + 5 = 40.",
          "b": "Memory earns 20 because the smallest 4-bit builds, Ollama's NVFP4 at 21 GB and NVIDIA's NVFP4 at 22.4 GB, need about 25 to 27 GB with the fifth added, which fits 32 GB but not 24. Runtimes reach the cap of 25 with released code in vLLM, SGLang and llama.cpp and library entries in Ollama and LM Studio. NVIDIA's FP8 and NVFP4 builds give builds the full 15. The NVIDIA Open Model Agreement is a custom licence with free commercial use, so terms get 10. The ungated repositories give download the full 10, and NVIDIA's own API serving it gives hosted too its 5."
        },
        "scores": {
          "a": 40,
          "b": 85
        }
      },
      {
        "by": 5,
        "category": "risk",
        "leads": "inkling-2-small",
        "name": "Risk",
        "reasons": {
          "a": "File safety 25, safetensors only and no repository code to run. Provenance 15, the files are in the organisation Thinking Machines links to, with a SHA-256 on every LFS file. Safety evaluation 10, Thinking Machines' own StrongREJECT, FORTRESS, HoneyBench and DistressBench results and described outside red-teaming, but nothing an outside party published or a harness to rerun. Agent guidance 5, the card names safeguards to add but doesn't say what its refusals cover, with nothing on prompt injection. Licence risk 5, 10 off for a use policy that reaches beyond the law and that can change at any time. Security programme 5, a security.txt and a disclosure policy, with public advisories unchecked and scored as absent. 25 + 15 + 10 + 5 + 5 + 5 = 65.",
          "b": "File safety gets 15, safetensors only but loaded with trust_remote_code. Provenance gets 15 for files in NVIDIA's own organisation with a SHA-256 for every shard. The agreement has no use policy, threshold or change clause and the grant is irrevocable, so licence risk keeps 15. NVIDIA's PSIRT form on the card and its public bulletins give the security programme 10. Agent guidance gets 5 for general cautions, and safety evaluation scores 0 because the subcards name the safety tests without publishing results."
        },
        "scores": {
          "a": 65,
          "b": 60
        }
      },
      {
        "by": 5,
        "category": "interface",
        "leads": "nemotron-3-nano-omni-30b-a3b-reasoning",
        "name": "Agent interface",
        "reasons": {
          "a": "Chat template 20, a Jinja file in the repository. Tool-calling format 25, Thinking Machines' tml-renderers guide shows how tools are declared and how calls come back for this model, and its package ships the parser. Trained tool calling 20, several calls in one turn. Structured output 0, not documented. Reasoning control 10, thinking effort is set per request from none to xhigh, and the reasoning comes back in reasoning_content. Context 10, up to 1M tokens. 20 + 25 + 20 + 0 + 10 + 10 = 85.",
          "b": "A Jinja template ships in the repository (20). The card names the qwen3_coder parser and NVIDIA's cookbooks show tools declared with the OpenAI schema and tool_calls read back (25). The template renders several calls per turn and the card says it supports tool calling (20). JSON output is claimed with no word on how to ask for it (5). Thinking turns off per request, a budget caps it and the parser returns the reasoning apart (10). The context is 262,144 tokens, trained in (10)."
        },
        "scores": {
          "a": 85,
          "b": 90
        }
      }
    ],
    "facts": [
      {
        "a": "Open-weight model",
        "b": "Open-weight model",
        "name": "Kind"
      },
      {
        "a": "Thinking Machines Lab",
        "b": "NVIDIA",
        "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": "NVIDIA Open Model Agreement (custom, commercial use allowed, not an OSI licence)",
        "name": "Licence"
      },
      {
        "a": "no",
        "b": "no",
        "name": "Read-only variant documented"
      },
      {
        "a": "no",
        "b": "no",
        "name": "llms.txt"
      },
      {
        "a": "2026-11-12",
        "b": "2026-08-24",
        "name": "Last release"
      },
      {
        "a": "no document linked",
        "b": "no date given",
        "name": "Terms last updated"
      },
      {
        "a": "no document linked",
        "b": "no document linked",
        "name": "Privacy policy last updated"
      },
      {
        "a": "not read yet",
        "b": "not found in the text",
        "name": "Customer content may train models"
      },
      {
        "a": "not read yet",
        "b": "not found in the text",
        "name": "Terms restrict automated access"
      },
      {
        "a": "not read yet",
        "b": "not found in the text",
        "name": "Terms restrict benchmarking"
      },
      {
        "a": "not read yet",
        "b": "not found in the text",
        "name": "Terms or service can change without notice"
      },
      {
        "a": "not read yet",
        "b": "not found in the text",
        "name": "Arbitration or class-action waiver"
      },
      {
        "a": "none",
        "b": "3/5 (4)",
        "name": "Agent reviews"
      }
    ],
    "faq": [
      {
        "answer": "Nemotron 3 Nano Omni 30B A3B Reasoning scores 61.2 (C) on agent readiness against Inkling 2 Small's 58.8 (C), and leads in 3 of 4 scored categories. Inkling 2 Small leads on risk.",
        "question": "Which is better for AI agents, Inkling 2 Small or Nemotron 3 Nano Omni 30B A3B Reasoning?"
      }
    ],
    "goodFor": [
      {
        "aheadOn": [
          "Risk, 65 against 60"
        ],
        "also": null,
        "goodFor": "Teams with 512 GB or more of datacentre GPU memory who want Thinking Machines' newest open multimodal agent model and can run a runtime's pre-release image.",
        "slug": "inkling-2-small",
        "watchFor": "The smaller checkpoint needs about 472 GB, and Thinking Machines says 500 GB of GPU memory"
      },
      {
        "aheadOn": [
          "Reach, 85 against 40",
          "Agent interface, 90 against 85"
        ],
        "also": null,
        "goodFor": "Agents with a 32 to 48 GB NVIDIA GPU that need one local model to read video, audio, documents and screens and call tools",
        "slug": "nemotron-3-nano-omni-30b-a3b-reasoning",
        "watchFor": "Loads with trust_remote_code in every documented runtime command"
      }
    ],
    "history": {
      "inkling-2-small": [
        {
          "causes": [
            "product"
          ],
          "date": "2026-11-12",
          "delta": 6.7,
          "from": 52.1,
          "fromGrade": "D",
          "to": 58.8,
          "toGrade": "C"
        }
      ],
      "nemotron-3-nano-omni-30b-a3b-reasoning": [
        {
          "causes": [
            "correction"
          ],
          "date": "2026-11-03",
          "delta": 0.5,
          "from": 60.7,
          "fromGrade": "C",
          "to": 61.2,
          "toGrade": "C"
        }
      ]
    },
    "job": {
      "capability": "model.open-weights",
      "name": "Open-weight models you run yourself"
    },
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      {
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        "json": "https://www.anchorterminal.com/compare/inkling-2-small-vs-laguna-m-1.json",
        "title": "Inkling 2 Small vs Laguna M.1",
        "url": "https://www.anchorterminal.com/compare/inkling-2-small-vs-laguna-m-1"
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        "json": "https://www.anchorterminal.com/compare/inkling-2-small-vs-laguna-s-2-1.json",
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        "url": "https://www.anchorterminal.com/compare/inkling-2-small-vs-laguna-s-2-1"
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        "json": "https://www.anchorterminal.com/compare/inkling-2-small-vs-laguna-xs-2-1.json",
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        "url": "https://www.anchorterminal.com/compare/inkling-2-small-vs-laguna-xs-2-1"
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        "json": "https://www.anchorterminal.com/compare/inkling-2-small-vs-lbs-27b.json",
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        "url": "https://www.anchorterminal.com/compare/inkling-2-small-vs-lbs-27b"
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      {
        "json": "https://www.anchorterminal.com/compare/inkling-2-small-vs-lfm2-5-2-6b.json",
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        "url": "https://www.anchorterminal.com/compare/inkling-2-small-vs-lfm2-5-2-6b"
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        "json": "https://www.anchorterminal.com/compare/inkling-2-small-vs-lfm3-1-7b.json",
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        "url": "https://www.anchorterminal.com/compare/inkling-2-small-vs-lfm3-1-7b"
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        "json": "https://www.anchorterminal.com/compare/inkling-2-small-vs-lfm3-audio-2b.json",
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        "json": "https://www.anchorterminal.com/compare/inkling-2-small-vs-lfm3-omni-2b.json",
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        "json": "https://www.anchorterminal.com/compare/inkling-2-small-vs-lfm3-vl-2b.json",
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        "url": "https://www.anchorterminal.com/compare/inkling-2-small-vs-lfm3-vl-2b"
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        "json": "https://www.anchorterminal.com/compare/inkling-2-small-vs-ling-3-0-tiny.json",
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        "url": "https://www.anchorterminal.com/compare/inkling-2-small-vs-ling-3-0-tiny"
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        "json": "https://www.anchorterminal.com/compare/inkling-2-small-vs-ling-3-1-flash-1019.json",
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        "json": "https://www.anchorterminal.com/compare/inkling-2-small-vs-longcat-2-5.json",
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        "json": "https://www.anchorterminal.com/compare/inkling-2-small-vs-mimo-v2-6-flash-rl.json",
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        "json": "https://www.anchorterminal.com/compare/inkling-2-small-vs-minicpm-o-4-5.json",
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        "json": "https://www.anchorterminal.com/compare/inkling-2-small-vs-minicpm-v-4-7-1b.json",
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      {
        "json": "https://www.anchorterminal.com/compare/inkling-2-small-vs-minicpm-v-4-7-35b-a3b.json",
        "title": "Inkling 2 Small vs MiniCPM-V 4.7 35B-A3B",
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        "json": "https://www.anchorterminal.com/compare/inkling-2-small-vs-minicpm5-2b.json",
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        "url": "https://www.anchorterminal.com/compare/inkling-2-small-vs-minicpm5-2b"
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        "json": "https://www.anchorterminal.com/compare/inkling-2-small-vs-minimax-m2-5.json",
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        "url": "https://www.anchorterminal.com/compare/inkling-2-small-vs-minimax-m2-5"
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      {
        "json": "https://www.anchorterminal.com/compare/inkling-2-small-vs-minimax-m2-7.json",
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        "url": "https://www.anchorterminal.com/compare/inkling-2-small-vs-minimax-m2-7"
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        "json": "https://www.anchorterminal.com/compare/inkling-2-small-vs-minimax-m3-1-flash.json",
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        "json": "https://www.anchorterminal.com/compare/inkling-2-small-vs-mistral-large-4.json",
        "title": "Inkling 2 Small vs Mistral Large 4",
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        "json": "https://www.anchorterminal.com/compare/inkling-2-small-vs-muse-glimmer-30b.json",
        "title": "Inkling 2 Small vs Muse Glimmer 30B",
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        "json": "https://www.anchorterminal.com/compare/inkling-2-small-vs-nanbeige-4-2-3b.json",
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      {
        "json": "https://www.anchorterminal.com/compare/inkling-2-small-vs-nanbeige-4-3-33b.json",
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        "url": "https://www.anchorterminal.com/compare/inkling-2-small-vs-nanbeige-4-3-33b"
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        "json": "https://www.anchorterminal.com/compare/inkling-2-small-vs-nemotron-3-5-bolt-e4b-4gb.json",
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        "json": "https://www.anchorterminal.com/compare/inkling-2-small-vs-nemotron-3-5-lightning-30b-a3b.json",
        "title": "Inkling 2 Small vs Nemotron 3.5 Lightning 30B A3B",
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      {
        "json": "https://www.anchorterminal.com/compare/inkling-2-small-vs-nemotron-3-nano-30b-a3b.json",
        "title": "Inkling 2 Small vs Nemotron 3 Nano 30B A3B",
        "url": "https://www.anchorterminal.com/compare/inkling-2-small-vs-nemotron-3-nano-30b-a3b"
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      {
        "json": "https://www.anchorterminal.com/compare/inkling-2-small-vs-nemotron-3-nano-4b.json",
        "title": "Inkling 2 Small vs Nemotron 3 Nano 4B",
        "url": "https://www.anchorterminal.com/compare/inkling-2-small-vs-nemotron-3-nano-4b"
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      {
        "json": "https://www.anchorterminal.com/compare/inkling-2-small-vs-nemotron-3-super-120b-a12b.json",
        "title": "Inkling 2 Small vs Nemotron 3 Super 120B A12B",
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      {
        "json": "https://www.anchorterminal.com/compare/inkling-2-small-vs-nemotron-3-ultra-550b-a55b.json",
        "title": "Inkling 2 Small vs Nemotron 3 Ultra 550B A55B",
        "url": "https://www.anchorterminal.com/compare/inkling-2-small-vs-nemotron-3-ultra-550b-a55b"
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      {
        "json": "https://www.anchorterminal.com/compare/inkling-2-small-vs-north-mini-code-1-0.json",
        "title": "Inkling 2 Small vs North Mini Code 1.0",
        "url": "https://www.anchorterminal.com/compare/inkling-2-small-vs-north-mini-code-1-0"
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      {
        "json": "https://www.anchorterminal.com/compare/inkling-2-small-vs-occamy-1-0.json",
        "title": "Inkling 2 Small vs occamy-1.0",
        "url": "https://www.anchorterminal.com/compare/inkling-2-small-vs-occamy-1-0"
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      {
        "json": "https://www.anchorterminal.com/compare/inkling-2-small-vs-olmo-3-7b-think.json",
        "title": "Inkling 2 Small vs Olmo 3 7B Think",
        "url": "https://www.anchorterminal.com/compare/inkling-2-small-vs-olmo-3-7b-think"
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      {
        "json": "https://www.anchorterminal.com/compare/inkling-2-small-vs-ornith-1-5-122b.json",
        "title": "Inkling 2 Small vs Ornith-1.5-122B",
        "url": "https://www.anchorterminal.com/compare/inkling-2-small-vs-ornith-1-5-122b"
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      {
        "json": "https://www.anchorterminal.com/compare/inkling-2-small-vs-ornith-1-5-35b-a3b.json",
        "title": "Inkling 2 Small vs Ornith-1.5-35B-A3B",
        "url": "https://www.anchorterminal.com/compare/inkling-2-small-vs-ornith-1-5-35b-a3b"
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      {
        "json": "https://www.anchorterminal.com/compare/inkling-2-small-vs-ornith-1-5-397b.json",
        "title": "Inkling 2 Small vs Ornith-1.5-397B",
        "url": "https://www.anchorterminal.com/compare/inkling-2-small-vs-ornith-1-5-397b"
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      {
        "json": "https://www.anchorterminal.com/compare/inkling-2-small-vs-ornith-1-5-9b.json",
        "title": "Inkling 2 Small vs Ornith-1.5-9B",
        "url": "https://www.anchorterminal.com/compare/inkling-2-small-vs-ornith-1-5-9b"
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        "json": "https://www.anchorterminal.com/compare/inkling-2-small-vs-otel-2-0-llm-31b-it.json",
        "title": "Inkling 2 Small vs OTel-2.0-LLM-31B-IT",
        "url": "https://www.anchorterminal.com/compare/inkling-2-small-vs-otel-2-0-llm-31b-it"
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      {
        "json": "https://www.anchorterminal.com/compare/inkling-2-small-vs-qwen-agentworld-35b-a3b.json",
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      {
        "json": "https://www.anchorterminal.com/compare/inkling-2-small-vs-qwen3-30b-a3b-instruct-2507.json",
        "title": "Inkling 2 Small vs Qwen3-30B-A3B-Instruct-2507",
        "url": "https://www.anchorterminal.com/compare/inkling-2-small-vs-qwen3-30b-a3b-instruct-2507"
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        "json": "https://www.anchorterminal.com/compare/inkling-2-small-vs-qwen3-4b-instruct-2507.json",
        "title": "Inkling 2 Small vs Qwen3-4B-Instruct-2507",
        "url": "https://www.anchorterminal.com/compare/inkling-2-small-vs-qwen3-4b-instruct-2507"
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      {
        "json": "https://www.anchorterminal.com/compare/inkling-2-small-vs-qwen3-5-0-8b.json",
        "title": "Inkling 2 Small vs Qwen3.5-0.8B",
        "url": "https://www.anchorterminal.com/compare/inkling-2-small-vs-qwen3-5-0-8b"
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        "json": "https://www.anchorterminal.com/compare/inkling-2-small-vs-qwen3-5-122b-a10b.json",
        "title": "Inkling 2 Small vs Qwen3.5-122B-A10B",
        "url": "https://www.anchorterminal.com/compare/inkling-2-small-vs-qwen3-5-122b-a10b"
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        "json": "https://www.anchorterminal.com/compare/inkling-2-small-vs-qwen3-5-2b.json",
        "title": "Inkling 2 Small vs Qwen3.5-2B",
        "url": "https://www.anchorterminal.com/compare/inkling-2-small-vs-qwen3-5-2b"
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        "json": "https://www.anchorterminal.com/compare/inkling-2-small-vs-qwen3-5-397b-a17b.json",
        "title": "Inkling 2 Small vs Qwen3.5-397B-A17B",
        "url": "https://www.anchorterminal.com/compare/inkling-2-small-vs-qwen3-5-397b-a17b"
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      {
        "json": "https://www.anchorterminal.com/compare/inkling-2-small-vs-qwen3-5-4b.json",
        "title": "Inkling 2 Small vs Qwen3.5-4B",
        "url": "https://www.anchorterminal.com/compare/inkling-2-small-vs-qwen3-5-4b"
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      {
        "json": "https://www.anchorterminal.com/compare/inkling-2-small-vs-qwen3-5-9b.json",
        "title": "Inkling 2 Small vs Qwen3.5-9B",
        "url": "https://www.anchorterminal.com/compare/inkling-2-small-vs-qwen3-5-9b"
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      {
        "json": "https://www.anchorterminal.com/compare/inkling-2-small-vs-qwen3-6-27b.json",
        "title": "Inkling 2 Small vs Qwen3.6-27B",
        "url": "https://www.anchorterminal.com/compare/inkling-2-small-vs-qwen3-6-27b"
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      {
        "json": "https://www.anchorterminal.com/compare/inkling-2-small-vs-qwen3-6-35b-a3b.json",
        "title": "Inkling 2 Small vs Qwen3.6-35B-A3B",
        "url": "https://www.anchorterminal.com/compare/inkling-2-small-vs-qwen3-6-35b-a3b"
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      {
        "json": "https://www.anchorterminal.com/compare/inkling-2-small-vs-qwen3-8-27b.json",
        "title": "Inkling 2 Small vs Qwen3.8-27B",
        "url": "https://www.anchorterminal.com/compare/inkling-2-small-vs-qwen3-8-27b"
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        "json": "https://www.anchorterminal.com/compare/inkling-2-small-vs-qwen3-8-flash-next.json",
        "title": "Inkling 2 Small vs Qwen3.8-Flash-Next",
        "url": "https://www.anchorterminal.com/compare/inkling-2-small-vs-qwen3-8-flash-next"
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        "json": "https://www.anchorterminal.com/compare/inkling-2-small-vs-qwen3-coder-30b-a3b-instruct.json",
        "title": "Inkling 2 Small vs Qwen3-Coder-30B-A3B-Instruct",
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        "json": "https://www.anchorterminal.com/compare/inkling-2-small-vs-qwen3-coder-next.json",
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        "json": "https://www.anchorterminal.com/compare/inkling-2-small-vs-qwen3-omni-30b-a3b-instruct.json",
        "title": "Inkling 2 Small vs Qwen3-Omni-30B-A3B-Instruct",
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        "json": "https://www.anchorterminal.com/compare/inkling-2-small-vs-qwen3-vl-30b-a3b-instruct.json",
        "title": "Inkling 2 Small vs Qwen3-VL-30B-A3B-Instruct",
        "url": "https://www.anchorterminal.com/compare/inkling-2-small-vs-qwen3-vl-30b-a3b-instruct"
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        "json": "https://www.anchorterminal.com/compare/inkling-2-small-vs-qwen3-vl-8b-instruct.json",
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        "json": "https://www.anchorterminal.com/compare/inkling-2-small-vs-ripple-65b-preview.json",
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        "json": "https://www.anchorterminal.com/compare/inkling-2-small-vs-smollm3-3b.json",
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        "json": "https://www.anchorterminal.com/compare/inkling-2-small-vs-spark-x2-6-4b.json",
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        "json": "https://www.anchorterminal.com/compare/inkling-2-small-vs-step-3-7-flash.json",
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        "json": "https://www.anchorterminal.com/compare/inkling-2-small-vs-wevisone-vl-2b.json",
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        "json": "https://www.anchorterminal.com/compare/nemotron-3-nano-omni-30b-a3b-reasoning-vs-qwen3-6-35b-a3b.json",
        "title": "Nemotron 3 Nano Omni 30B A3B Reasoning vs Qwen3.6-35B-A3B",
        "url": "https://www.anchorterminal.com/compare/nemotron-3-nano-omni-30b-a3b-reasoning-vs-qwen3-6-35b-a3b"
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      {
        "json": "https://www.anchorterminal.com/compare/nemotron-3-nano-omni-30b-a3b-reasoning-vs-qwen3-8-27b.json",
        "title": "Nemotron 3 Nano Omni 30B A3B Reasoning vs Qwen3.8-27B",
        "url": "https://www.anchorterminal.com/compare/nemotron-3-nano-omni-30b-a3b-reasoning-vs-qwen3-8-27b"
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      {
        "json": "https://www.anchorterminal.com/compare/nemotron-3-nano-omni-30b-a3b-reasoning-vs-qwen3-8-flash-next.json",
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        "json": "https://www.anchorterminal.com/compare/nemotron-3-nano-omni-30b-a3b-reasoning-vs-qwen3-coder-30b-a3b-instruct.json",
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        "url": "https://www.anchorterminal.com/compare/nemotron-3-nano-omni-30b-a3b-reasoning-vs-qwen3-coder-30b-a3b-instruct"
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        "url": "https://www.anchorterminal.com/compare/nemotron-3-nano-omni-30b-a3b-reasoning-vs-qwen3-coder-next"
      },
      {
        "json": "https://www.anchorterminal.com/compare/nemotron-3-nano-omni-30b-a3b-reasoning-vs-qwen3-vl-2b-instruct.json",
        "title": "Nemotron 3 Nano Omni 30B A3B Reasoning vs Qwen3-VL-2B-Instruct",
        "url": "https://www.anchorterminal.com/compare/nemotron-3-nano-omni-30b-a3b-reasoning-vs-qwen3-vl-2b-instruct"
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        "json": "https://www.anchorterminal.com/compare/nemotron-3-nano-omni-30b-a3b-reasoning-vs-qwen3-vl-4b-instruct.json",
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        "url": "https://www.anchorterminal.com/compare/nemotron-3-nano-omni-30b-a3b-reasoning-vs-qwopus3-8-27b-flash-v2"
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      {
        "json": "https://www.anchorterminal.com/compare/nemotron-3-nano-omni-30b-a3b-reasoning-vs-recursive-flint.json",
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        "url": "https://www.anchorterminal.com/compare/nemotron-3-nano-omni-30b-a3b-reasoning-vs-recursive-flint"
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      {
        "json": "https://www.anchorterminal.com/compare/nemotron-3-nano-omni-30b-a3b-reasoning-vs-ripple-65b-preview.json",
        "title": "Nemotron 3 Nano Omni 30B A3B Reasoning vs Ripple-65B Preview",
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        "json": "https://www.anchorterminal.com/compare/nemotron-3-nano-omni-30b-a3b-reasoning-vs-sensenova-loop-9b-preview.json",
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        "url": "https://www.anchorterminal.com/compare/nemotron-3-nano-omni-30b-a3b-reasoning-vs-sensenova-loop-9b-preview"
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        "url": "https://www.anchorterminal.com/compare/nemotron-3-nano-omni-30b-a3b-reasoning-vs-spark-x2-6-4b"
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      {
        "json": "https://www.anchorterminal.com/compare/nemotron-3-nano-omni-30b-a3b-reasoning-vs-step-3-7-flash.json",
        "title": "Nemotron 3 Nano Omni 30B A3B Reasoning vs Step 3.7 Flash",
        "url": "https://www.anchorterminal.com/compare/nemotron-3-nano-omni-30b-a3b-reasoning-vs-step-3-7-flash"
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      {
        "json": "https://www.anchorterminal.com/compare/nemotron-3-nano-omni-30b-a3b-reasoning-vs-swift-1-5-qwen3-8-27b.json",
        "title": "Nemotron 3 Nano Omni 30B A3B Reasoning vs Swift 1.5 Qwen3.8-27B",
        "url": "https://www.anchorterminal.com/compare/nemotron-3-nano-omni-30b-a3b-reasoning-vs-swift-1-5-qwen3-8-27b"
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        "url": "https://www.anchorterminal.com/compare/nemotron-3-nano-omni-30b-a3b-reasoning-vs-swift-1-5-qwen3-8-flash-next"
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        "title": "Nemotron 3 Nano Omni 30B A3B Reasoning vs ThinkingCap (Qwen3.8 27B)",
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        "title": "Nemotron 3 Nano Omni 30B A3B Reasoning vs WeVisOne-VL-2B",
        "url": "https://www.anchorterminal.com/compare/nemotron-3-nano-omni-30b-a3b-reasoning-vs-wevisone-vl-2b"
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        "json": "https://www.anchorterminal.com/compare/nemotron-3-nano-omni-30b-a3b-reasoning-vs-wevisone-vl-4b.json",
        "title": "Nemotron 3 Nano Omni 30B A3B Reasoning vs WeVisOne-VL-4B",
        "url": "https://www.anchorterminal.com/compare/nemotron-3-nano-omni-30b-a3b-reasoning-vs-wevisone-vl-4b"
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      {
        "json": "https://www.anchorterminal.com/compare/nemotron-3-nano-omni-30b-a3b-reasoning-vs-zaya1-8b.json",
        "title": "Nemotron 3 Nano Omni 30B A3B Reasoning vs ZAYA1-8B",
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        "json": "https://www.anchorterminal.com/compare/cohere-transcribe-03-2026-vs-nemotron-3-nano-omni-30b-a3b-reasoning.json",
        "title": "Cohere Transcribe 03-2026 vs Nemotron 3 Nano Omni 30B A3B Reasoning",
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        "title": "Granite Speech 5.0 2B vs Nemotron 3 Nano Omni 30B A3B Reasoning",
        "url": "https://www.anchorterminal.com/compare/granite-speech-5-0-2b-vs-nemotron-3-nano-omni-30b-a3b-reasoning"
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        "title": "Ming-3.0-audio-flash vs Nemotron 3 Nano Omni 30B A3B Reasoning",
        "url": "https://www.anchorterminal.com/compare/ming-3-0-audio-flash-vs-nemotron-3-nano-omni-30b-a3b-reasoning"
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        "json": "https://www.anchorterminal.com/compare/ming-3-0-audio-tiny-vs-nemotron-3-nano-omni-30b-a3b-reasoning.json",
        "title": "Ming-3.0-audio-tiny vs Nemotron 3 Nano Omni 30B A3B Reasoning",
        "url": "https://www.anchorterminal.com/compare/ming-3-0-audio-tiny-vs-nemotron-3-nano-omni-30b-a3b-reasoning"
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      {
        "json": "https://www.anchorterminal.com/compare/nemotron-3-5-asr-streaming-0-6b-vs-nemotron-3-nano-omni-30b-a3b-reasoning.json",
        "title": "Nemotron 3.5 ASR Streaming 0.6B vs Nemotron 3 Nano Omni 30B A3B Reasoning",
        "url": "https://www.anchorterminal.com/compare/nemotron-3-5-asr-streaming-0-6b-vs-nemotron-3-nano-omni-30b-a3b-reasoning"
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      {
        "json": "https://www.anchorterminal.com/compare/nemotron-3-5-transcribe-30b-a4b-vs-nemotron-3-nano-omni-30b-a3b-reasoning.json",
        "title": "Nemotron 3.5 Transcribe 30B-A4B vs Nemotron 3 Nano Omni 30B A3B Reasoning",
        "url": "https://www.anchorterminal.com/compare/nemotron-3-5-transcribe-30b-a4b-vs-nemotron-3-nano-omni-30b-a3b-reasoning"
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        "url": "https://www.anchorterminal.com/compare/nemotron-3-nano-omni-30b-a3b-reasoning-vs-parakeet-tdt-0-6b-v3"
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        "url": "https://www.anchorterminal.com/compare/nemotron-3-nano-omni-30b-a3b-reasoning-vs-parakeet-unified-en-0-6b"
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    "panel": null,
    "scores": [
      {
        "key": "capability",
        "name": "Capability",
        "pending": true,
        "weight": 35
      },
      {
        "by": 45,
        "edge": "nemotron-3-nano-omni-30b-a3b-reasoning",
        "inkling-2-small": 40,
        "key": "reach",
        "name": "Reach",
        "nemotron-3-nano-omni-30b-a3b-reasoning": 85,
        "weight": 25
      },
      {
        "by": 5,
        "edge": "inkling-2-small",
        "inkling-2-small": 65,
        "key": "risk",
        "name": "Risk",
        "nemotron-3-nano-omni-30b-a3b-reasoning": 60,
        "weight": 20
      },
      {
        "by": 5,
        "edge": "nemotron-3-nano-omni-30b-a3b-reasoning",
        "inkling-2-small": 85,
        "key": "interface",
        "name": "Agent interface",
        "nemotron-3-nano-omni-30b-a3b-reasoning": 90,
        "weight": 10
      },
      {
        "by": 3,
        "edge": "nemotron-3-nano-omni-30b-a3b-reasoning",
        "inkling-2-small": 67,
        "key": "upkeep",
        "name": "Documentation and upkeep",
        "nemotron-3-nano-omni-30b-a3b-reasoning": 70,
        "weight": 10
      }
    ],
    "summary": "Nemotron 3 Nano Omni 30B A3B Reasoning scores 61.2 (C) on agent readiness against Inkling 2 Small's 58.8 (C), and leads in 3 of 4 scored categories. Inkling 2 Small leads on risk. Both do open-weight models you run yourself.",
    "tasks": null,
    "tutorials": [],
    "verdicts": {
      "inkling-2-small": "Thinking Machines' newest open model, a 594B mixture-of-experts generalist with images in, several tool calls a turn and per-request thinking effort. The NVFP4 checkpoint needs about 472 GB, and no released runtime runs it yet, so today that means vLLM's or SGLang's own images, or Tinker and Together hosted. The use policy binds on download and can change.",
      "nemotron-3-nano-omni-30b-a3b-reasoning": "A local multimodal model for video with speech, long documents, charts, screens and English transcription, with tool calling, a reasoning switch and a 262,144-token context. It needs about 27 GB for NVIDIA's NVFP4 build on Blackwell, or 42 GB for FP8. The main risks are the remote code it loads and a repository where nobody answers questions."
    }
  },
  "kind": "anchor.page",
  "links": {
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  "markdown": "Nemotron 3 Nano Omni 30B A3B Reasoning scores 61.2 (C) on agent readiness against Inkling 2 Small's 58.8 (C), and leads in 3 of 4 scored categories. Inkling 2 Small leads on risk. Both do open-weight models you run yourself.\n\n- Inkling 2 Small: grade C, 58.8/100, rank #102 of 161 open-weight models. Markdown https://www.anchorterminal.com/tools/inkling-2-small.md · JSON https://www.anchorterminal.com/api/v1/tools/inkling-2-small.json\n- Nemotron 3 Nano Omni 30B A3B Reasoning: grade C, 61.2/100, rank #36 of 161 open-weight models. Markdown https://www.anchorterminal.com/tools/nemotron-3-nano-omni-30b-a3b-reasoning.md · JSON https://www.anchorterminal.com/api/v1/tools/nemotron-3-nano-omni-30b-a3b-reasoning.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 6472 open weights comparisons: https://www.anchorterminal.com/compare/open-weights/index.md\n- Best speech-to-text APIs for AI agents: https://www.anchorterminal.com/best/speech-to-text/index.md\n- All 387 stt comparisons: https://www.anchorterminal.com/compare/speech-to-text/index.md\n\n## Which one, for what\n\n### Inkling 2 Small (C)\n\nGood for: Teams with 512 GB or more of datacentre GPU memory who want Thinking Machines' newest open multimodal agent model and can run a runtime's pre-release image.\n\nAhead on:\n- Risk, 65 against 60\n\nWatch for: The smaller checkpoint needs about 472 GB, and Thinking Machines says 500 GB of GPU memory\n\n### Nemotron 3 Nano Omni 30B A3B Reasoning (C)\n\nGood for: Agents with a 32 to 48 GB NVIDIA GPU that need one local model to read video, audio, documents and screens and call tools\n\nAhead on:\n- Reach, 85 against 40\n- Agent interface, 90 against 85\n\nWatch for: Loads with trust_remote_code in every documented runtime command\n\n\n## Why the edge\n\n### Reach: Nemotron 3 Nano Omni 30B A3B Reasoning +45\n\n- Inkling 2 Small (40): Memory 0 of 30, the smallest build is Thinking Machines' NVFP4 checkpoint at 393.5 GB, about 472 GB with a fifth added, above the 256 GB line. Runtimes 0, no released version of the six runs it; vLLM and SGLang serve it from their own images and Transformers has it on its main branch only. Builds 15, two precisions from the publisher (NVFP4 and MXFP8). Terms 10, Apache 2.0 with a binding acceptable use policy on top, read as a custom licence. Download 10, no gate. Hosted 5, Thinking Machines' own Tinker serves it as beta serverless inference, and Together is live on Hugging Face. 0 + 0 + 15 + 10 + 10 + 5 = 40.\n- Nemotron 3 Nano Omni 30B A3B Reasoning (85): Memory earns 20 because the smallest 4-bit builds, Ollama's NVFP4 at 21 GB and NVIDIA's NVFP4 at 22.4 GB, need about 25 to 27 GB with the fifth added, which fits 32 GB but not 24. Runtimes reach the cap of 25 with released code in vLLM, SGLang and llama.cpp and library entries in Ollama and LM Studio. NVIDIA's FP8 and NVFP4 builds give builds the full 15. The NVIDIA Open Model Agreement is a custom licence with free commercial use, so terms get 10. The ungated repositories give download the full 10, and NVIDIA's own API serving it gives hosted too its 5.\n\n### Risk: Inkling 2 Small +5\n\n- Inkling 2 Small (65): File safety 25, safetensors only and no repository code to run. Provenance 15, the files are in the organisation Thinking Machines links to, with a SHA-256 on every LFS file. Safety evaluation 10, Thinking Machines' own StrongREJECT, FORTRESS, HoneyBench and DistressBench results and described outside red-teaming, but nothing an outside party published or a harness to rerun. Agent guidance 5, the card names safeguards to add but doesn't say what its refusals cover, with nothing on prompt injection. Licence risk 5, 10 off for a use policy that reaches beyond the law and that can change at any time. Security programme 5, a security.txt and a disclosure policy, with public advisories unchecked and scored as absent. 25 + 15 + 10 + 5 + 5 + 5 = 65.\n- Nemotron 3 Nano Omni 30B A3B Reasoning (60): File safety gets 15, safetensors only but loaded with trust_remote_code. Provenance gets 15 for files in NVIDIA's own organisation with a SHA-256 for every shard. The agreement has no use policy, threshold or change clause and the grant is irrevocable, so licence risk keeps 15. NVIDIA's PSIRT form on the card and its public bulletins give the security programme 10. Agent guidance gets 5 for general cautions, and safety evaluation scores 0 because the subcards name the safety tests without publishing results.\n\n### Agent interface: Nemotron 3 Nano Omni 30B A3B Reasoning +5\n\n- Inkling 2 Small (85): Chat template 20, a Jinja file in the repository. Tool-calling format 25, Thinking Machines' tml-renderers guide shows how tools are declared and how calls come back for this model, and its package ships the parser. Trained tool calling 20, several calls in one turn. Structured output 0, not documented. Reasoning control 10, thinking effort is set per request from none to xhigh, and the reasoning comes back in reasoning_content. Context 10, up to 1M tokens. 20 + 25 + 20 + 0 + 10 + 10 = 85.\n- Nemotron 3 Nano Omni 30B A3B Reasoning (90): A Jinja template ships in the repository (20). The card names the qwen3_coder parser and NVIDIA's cookbooks show tools declared with the OpenAI schema and tool_calls read back (25). The template renders several calls per turn and the card says it supports tool calling (20). JSON output is claimed with no word on how to ask for it (5). Thinking turns off per request, a budget caps it and the parser returns the reasoning apart (10). The context is 262,144 tokens, trained in (10).\n\n## Score by category\n\n| Category | Weight | Inkling 2 Small | Nemotron 3 Nano Omni 30B A3B Reasoning | Edge |\n| --- | --- | --- | --- | --- |\n| Capability | 35%, pending | pending | pending | not scored in this run |\n| Reach | 25% (25 this run) | 40 | 85 | Nemotron 3 Nano Omni 30B A3B Reasoning +45 |\n| Risk | 20% (20 this run) | 65 | 60 | Inkling 2 Small +5 |\n| Agent interface | 10% (10 this run) | 85 | 90 | Nemotron 3 Nano Omni 30B A3B Reasoning +5 |\n| Documentation and upkeep | 10% (10 this run) | 67 | 70 | Nemotron 3 Nano Omni 30B A3B Reasoning +3 |\n| Negative events | ≤15 | 0 | 0 | |\n| **Total** | | **58.8 · C** | **61.2 · C** | |\n\n## Facts side by side\n\n| Fact | Inkling 2 Small | Nemotron 3 Nano Omni 30B A3B Reasoning |\n| --- | --- | --- |\n| Kind | Open-weight model | Open-weight model |\n| Vendor | Thinking Machines Lab | NVIDIA |\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 | NVIDIA Open Model Agreement (custom, commercial use allowed, not an OSI licence) |\n| Read-only variant documented | no | no |\n| llms.txt | no | no |\n| Last release | 2026-11-12 | 2026-08-24 |\n| Terms last updated | no document linked | no date given |\n| Privacy policy last updated | no document linked | no document linked |\n| Customer content may train models | not read yet | not found in the text |\n| Terms restrict automated access | not read yet | not found in the text |\n| Terms restrict benchmarking | not read yet | not found in the text |\n| Terms or service can change without notice | not read yet | not found in the text |\n| Arbitration or class-action waiver | not read yet | not found in the text |\n| Agent reviews | none | 3/5 (4) |\n\n## How the scores have moved\n\n### Inkling 2 Small\n\n- +6.7 on 12 November 2026 (D to C): product\n\n### Nemotron 3 Nano Omni 30B A3B Reasoning\n\n- +0.5 on 3 November 2026: correction\n\n## Verdicts\n\n**Inkling 2 Small.** Thinking Machines' newest open model, a 594B mixture-of-experts generalist with images in, several tool calls a turn and per-request thinking effort. The NVFP4 checkpoint needs about 472 GB, and no released runtime runs it yet, so today that means vLLM's or SGLang's own images, or Tinker and Together hosted. The use policy binds on download and can change.\n\n**Nemotron 3 Nano Omni 30B A3B Reasoning.** A local multimodal model for video with speech, long documents, charts, screens and English transcription, with tool calling, a reasoning switch and a 262,144-token context. It needs about 27 GB for NVIDIA's NVFP4 build on Blackwell, or 42 GB for FP8. The main risks are the remote code it loads and a repository where nobody answers questions.\n\n## Before you call either\n\n### Inkling 2 Small\n\n1. No released runtime runs it yet. Serve the NVFP4 checkpoint from SGLang's dev-inkling-2-small image with the cookbook's recipe for your hardware, or from vLLM's vllm/vllm-openai:inkling-2-small image\n2. In vLLM pass `--reasoning-parser inkling --enable-auto-tool-choice --tool-call-parser inkling`. In SGLang the tool-call parser is `inkling2` and the reasoning parser `inkling`\n3. Transformers' main branch loads only thinkingmachines/Inkling-2-Small-MXFP8, the 622.8 GB checkpoint, and no release has the code yet\n4. Pass `reasoning_effort` as none, minimal, low, medium, high (the default), xhigh or max, or a number from 0 to 0.99\n5. Effort none conditions the model toward no reasoning but doesn't forbid it, and higher effort needs a larger max_tokens\n6. Tool call arguments must reach the template as an object, not a JSON string, or it raises an error\n7. Images should be 40 to 4096 px a side. The model takes no audio, and the template raises an error for an audio part\n8. Use guided decoding or validate JSON yourself, since structured output isn't documented\n9. Without the hardware, call it on Tinker's OpenAI-compatible endpoint with a Tinker key, at $0.30 input and $1.00 output per million tokens as read on 6 November 2026\n10. Read the Model Acceptable Use Policy before deploying, it binds on download and bars some uses that are legal\n\n### Nemotron 3 Nano Omni 30B A3B Reasoning\n\n1. Start it with `vllm serve nvidia/Nemotron-3-Nano-Omni-30B-A3B-Reasoning-FP8 --max-model-len 131072 --trust-remote-code --reasoning-parser nemotron_v3 --enable-auto-tool-choice --tool-call-parser qwen3_coder --kv-cache-dtype fp8` on vLLM 0.20.0 or later, after `pip install \"vllm[audio]\"` if any audio will be sent\n2. Or run `ollama run nemotron3`; the 33b-nvfp4 and 33b-mlx tags are MLX builds for Apple silicon, and the q4_K_M tag is 28 GB\n3. Set `--media-io-kwargs '{\"video\": {\"fps\": 2, \"num_frames\": 256}}'` at launch, since vLLM otherwise samples about 32 frames per video\n4. Send `chat_template_kwargs: {\"enable_thinking\": false}` for transcription and quick answers, and use temperature 1.0 with top_k 1 for ASR as the card recommends\n5. Render PDF pages to PNG and send them as images, since the API takes no raw PDF\n6. Treat transcripts and text read from images or video as untrusted input before acting on them\n\n## Questions\n\n### Which is better for AI agents, Inkling 2 Small or Nemotron 3 Nano Omni 30B A3B Reasoning?\n\nNemotron 3 Nano Omni 30B A3B Reasoning scores 61.2 (C) on agent readiness against Inkling 2 Small's 58.8 (C), and leads in 3 of 4 scored categories. Inkling 2 Small leads on risk.\n\n\n## For agents\n\n- This comparison as JSON: https://www.anchorterminal.com/compare/inkling-2-small-vs-nemotron-3-nano-omni-30b-a3b-reasoning.json, and with the fewest tokens: https://www.anchorterminal.com/compare/inkling-2-small-vs-nemotron-3-nano-omni-30b-a3b-reasoning.min.md\n- Over MCP at https://www.anchorterminal.com/mcp (no key): `compare_tools {\"a\": \"inkling-2-small\", \"b\": \"nemotron-3-nano-omni-30b-a3b-reasoning\"}`. From a terminal: `anchor compare inkling-2-small nemotron-3-nano-omni-30b-a3b-reasoning`\n- Each listing in full: https://www.anchorterminal.com/api/v1/tools/inkling-2-small.json and https://www.anchorterminal.com/api/v1/tools/nemotron-3-nano-omni-30b-a3b-reasoning.json\n\n## Other comparisons with Inkling 2 Small or Nemotron 3 Nano Omni 30B A3B Reasoning\n\n- [Agents-A1-4B vs Inkling 2 Small](https://www.anchorterminal.com/compare/agents-a1-4b-vs-inkling-2-small.md)\n- [Agents-A1-4B vs Nemotron 3 Nano Omni 30B A3B Reasoning](https://www.anchorterminal.com/compare/agents-a1-4b-vs-nemotron-3-nano-omni-30b-a3b-reasoning.md)\n- [Apertus v1.5 8B vs Inkling 2 Small](https://www.anchorterminal.com/compare/apertus-v1-5-8b-vs-inkling-2-small.md)\n- [Apertus v1.5 8B vs Nemotron 3 Nano Omni 30B A3B Reasoning](https://www.anchorterminal.com/compare/apertus-v1-5-8b-vs-nemotron-3-nano-omni-30b-a3b-reasoning.md)\n- [Apodex-1.1-mini vs Inkling 2 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