{
  "data": {
    "a": {
      "slug": "gpt-oss-120b",
      "name": "gpt-oss-120b",
      "vendor": "OpenAI",
      "vendorUrl": "https://openai.com",
      "kind": "weights",
      "category": "open-weights",
      "summary": "gpt-oss-120b is OpenAI's open-weight mixture-of-experts reasoning model, 116.8B parameters with 5.1B active and a 131,072-token context, published on Hugging Face in MXFP4 under Apache 2.0.",
      "url": "https://www.anchorterminal.com/tools/gpt-oss-120b",
      "markdownUrl": "https://www.anchorterminal.com/tools/gpt-oss-120b.md",
      "slimMarkdownUrl": "https://www.anchorterminal.com/tools/gpt-oss-120b.min.md",
      "jsonUrl": "https://www.anchorterminal.com/api/v1/tools/gpt-oss-120b.json",
      "repo": "https://huggingface.co/openai/gpt-oss-120b",
      "license": "Apache-2.0",
      "transports": [],
      "packages": [
        {
          "registry": "huggingface",
          "name": "openai/gpt-oss-120b"
        },
        {
          "registry": "pypi",
          "name": "gpt-oss"
        },
        {
          "registry": "pypi",
          "name": "openai-harmony"
        },
        {
          "registry": "ollama",
          "name": "gpt-oss:120b"
        }
      ],
      "auth": "none",
      "authNotes": "The weights download from Hugging Face with no account, token or terms to accept. The repository is not gated (checked 2026-10-21).",
      "pricing": "free",
      "pricingNotes": "Free to download and use, commercial use included, under Apache 2.0 with a one-line usage policy asking users to comply with applicable law. OpenAI's API page for the model shows no price and rate limits of 0 at every tier. Running it yourself costs the hardware, 65.2 GB for the MXFP4 files and 65 GB for Ollama's gpt-oss:120b build (checked 2026-10-21).",
      "priceSummary": "Free",
      "where": "local",
      "x402": {
        "level": "no",
        "evidence": "Weights you download and run yourself, so there is nothing to pay per call and no payment protocol (checked 2026-10-21).",
        "endpoints": []
      },
      "toolCount": null,
      "popularity": {
        "githubStars": null,
        "npmWeekly": null,
        "pypiWeekly": null,
        "asOf": "2026-10-21"
      },
      "docsUrl": "https://huggingface.co/openai/gpt-oss-120b",
      "capabilities": [
        "model.open-weights"
      ],
      "tags": [
        "open-weights",
        "model",
        "moe",
        "reasoning",
        "tool-calling",
        "apache-2.0",
        "safetensors",
        "mxfp4",
        "self-hosted"
      ],
      "lastRelease": "2025-08-26",
      "graded": true,
      "anchor": {
        "graded": true,
        "score": 70.2,
        "grade": "BB",
        "agentReady": true,
        "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": 1197,
        "categoryRank": 4,
        "methodology": "0.6",
        "run": "2026-10-01",
        "scores": {
          "capability": 54,
          "interface": 90,
          "reach": 75,
          "risk": 95,
          "upkeep": 45
        },
        "pending": [
          "performance",
          "tasks"
        ],
        "assessment": {
          "confidence": "high",
          "date": "2026-10-21"
        },
        "negative": 0,
        "verdict": "A reasoning and agent cousin that runs in most runtimes under Apache 2.0 with published safety work. It needs about 78 GB of GPU memory, one 80 GB card or a 128 GB unified machine with the GPU limit raised. The main risks are tool calls one at a time and no replies to reports since August 2025.",
        "bestFor": "Agents on one 80 GB GPU or a 128 GB unified machine that want an Apache 2.0 reasoning model with wide runtime support",
        "strengths": [
          "Runs in Transformers, vLLM, SGLang, llama.cpp and Ollama, with LM Studio linked from the card",
          "Apache 2.0, no gate, and 11 inference providers serve it for agents without the hardware",
          "Safetensors only, a trained instruction hierarchy and an outside biosecurity evaluation",
          "Harmony tool format, JSON Schema output and three reasoning levels documented by OpenAI"
        ],
        "weaknesses": [
          "Needs about 78 GB, too big for 64 GB machines, and OpenAI ships only one precision",
          "One tool call at a time",
          "No OpenAI reply in the last 40 discussions, including open template and tokenizer reports",
          "No change to the files since August 2025 or to the model code since November 2025",
          "Reasoning can be lowered but not turned off"
        ],
        "agentNotes": [
          "Start it with `ollama run gpt-oss:120b` on the reference machine, the build that fits",
          "On the Strix Halo machine raise the GPU memory limit first with `amd-ttm --set 100`, since the default of about 62.8 GiB is below the 78 GB it needs",
          "With vLLM use `vllm serve openai/gpt-oss-120b --tool-call-parser openai --enable-auto-tool-choice` per vLLM's recipe, or parse raw output with openai-harmony",
          "Always use the harmony format through the chat template or openai-harmony, the card says it won't work correctly otherwise",
          "Set `Reasoning: low` in the system message for short tasks, medium is the default",
          "Pass the reasoning back after a tool call until the final answer, and keep the analysis channel away from end users",
          "Expect one tool call per turn and loop, don't wait for parallel calls"
        ],
        "metrics": {
          "kind": "local",
          "measured": false
        },
        "reviewCount": 4,
        "avgRating": 3.5,
        "history": [
          {
            "basis": "public evidence",
            "confidence": "high",
            "grade": "BB",
            "methodology": "0.6",
            "pending": [
              "performance",
              "tasks"
            ],
            "run": "2026-10-01",
            "runLabel": "October 2026 research run",
            "score": 70.2
          }
        ],
        "editorialScores": {
          "capability": 54,
          "interface": 90,
          "reach": 75,
          "risk": 95,
          "upkeep": 45
        },
        "provenanceScore": 87,
        "checked": {
          "categories": {
            "capability": "2026-10-21",
            "interface": "2026-10-21",
            "reach": "2026-10-21",
            "risk": "2026-10-21",
            "upkeep": "2026-10-21"
          },
          "last": "2026-10-21",
          "oldest": "2026-10-21",
          "stale": false,
          "staleAfterDays": 90
        }
      },
      "connect": {
        "install": "ollama run gpt-oss:120b\n# or, with vLLM's recipe:\nvllm serve openai/gpt-oss-120b --tool-call-parser openai --enable-auto-tool-choice",
        "http": "curl http://localhost:11434/api/chat \\\n  -d '{\"model\": \"gpt-oss:120b\", \"messages\": [{\"role\": \"user\", \"content\": \"Hello!\"}]}'"
      },
      "letme": {
        "capability": "https://letme.dev/model.open-weights",
        "tool": "https://letme.dev/gpt-oss-120b"
      },
      "sameCompany": [
        "openai-api",
        "openai-embeddings",
        "openai-guardrails",
        "openai-moderation",
        "openai-image-api",
        "openai-sora",
        "openai-speech-to-text",
        "gpt-live",
        "openai-realtime",
        "openai-agents-sdk",
        "openai-decisions-api",
        "openai-codex",
        "gpt-oss-20b"
      ],
      "weights": {
        "trainedBy": "OpenAI",
        "params": "116.83B",
        "active": "5.13B",
        "context": 131072,
        "goodFor": "Larger text reasoning model for agents and coding, with function calling, built-in browser and Python tools and three reasoning levels, in the harmony format.",
        "runtimes": [
          "llama.cpp",
          "Ollama",
          "vLLM",
          "SGLang",
          "Transformers"
        ],
        "builds": [
          {
            "name": "gpt-oss-120b",
            "url": "https://huggingface.co/openai/gpt-oss-120b",
            "who": "publisher",
            "precision": "mxfp4",
            "sizeGB": 65.2,
            "memoryGB": 96,
            "format": "safetensors",
            "note": "MoE weights in MXFP4, the rest BF16. original/ and metal/ duplicate the weights. vLLM's gpt-oss recipe doesn't list gfx1151"
          },
          {
            "name": "ollama gpt-oss:120b",
            "url": "https://ollama.com/library/gpt-oss:120b",
            "who": "ollama",
            "precision": "mxfp4",
            "sizeGB": 65,
            "memoryGB": 96,
            "format": "ollama",
            "runsOn": [
              "Ollama"
            ],
            "note": "OpenAI's MXFP4 weights; the card links it. Size as Ollama's tags page shows it, rounded to whole GB above 10 GB; the Linux build is the llama.cpp variant"
          }
        ],
        "run": "ollama run gpt-oss:120b",
        "runBuild": "ollama gpt-oss:120b",
        "checked": "2026-10-21",
        "minMemoryGB": 96
      },
      "family": {
        "lab": "OpenAI",
        "family": "gpt-oss",
        "url": "https://www.anchorterminal.com/open-weights/#openai",
        "others": [
          {
            "name": "gpt-oss-20b",
            "url": "https://huggingface.co/openai/gpt-oss-20b",
            "params": "21B total, 3.6B active (MoE)",
            "listing": "https://www.anchorterminal.com/tools/gpt-oss-20b"
          },
          {
            "name": "gpt-oss-safeguard-120b",
            "url": "https://huggingface.co/openai/gpt-oss-safeguard-120b",
            "params": "117B total, 5.1B active (MoE)"
          },
          {
            "name": "gpt-oss-safeguard-20b",
            "url": "https://huggingface.co/openai/gpt-oss-safeguard-20b",
            "params": "21B total, 3.6B active (MoE)"
          }
        ],
        "olderCount": 6,
        "unrestrictedCopies": 5
      },
      "area": "models",
      "provenance": {
        "legalEntity": "OpenAI (named as publisher on the card; the openai-api listing's terms name OpenAI OpCo, LLC)",
        "domain": "openai.com",
        "domainRegistered": "2007-01-19",
        "domainNote": "openai.com was registered in 2007, before OpenAI existed.",
        "endpointOnVendorDomain": null,
        "terms": "",
        "privacy": "",
        "statusPage": "",
        "changelog": "https://github.com/openai/gpt-oss/commits/main",
        "securityTxt": "valid",
        "checked": "2026-10-21",
        "notes": [
          "The LICENSE file is Apache 2.0 with the template's placeholder copyright line, so the legal entity is the one OpenAI's own terms name, read for the openai-api listing.",
          "Nothing is hosted, so the Apache 2.0 licence stands in for terms of service and no privacy policy is scored.",
          "The changelog is the gpt-oss GitHub repository's commit history and tags (v0.0.1 to v0.0.9); the Hugging Face repository's commits stop on 26 August 2025.",
          "openai.com/.well-known/security.txt answered on 21 October 2026 with a Bugcrowd contact, an acknowledgements page and a coordinated vulnerability disclosure policy. It has no Expires line, which RFC 9116 requires."
        ],
        "score": 87
      },
      "pageJsonUrl": "https://www.anchorterminal.com/tools/gpt-oss-120b.json"
    },
    "answer": "gpt-oss-120b scores 70.2 (BB) on agent readiness against Nemotron 3 Ultra 550B A55B's 68.8 (B), and leads in 2 of 5 scored categories. Nemotron 3 Ultra 550B A55B leads on capability and documentation and upkeep.",
    "b": {
      "slug": "nemotron-3-ultra-550b-a55b",
      "name": "Nemotron 3 Ultra 550B A55B",
      "vendor": "NVIDIA",
      "vendorUrl": "https://developer.nvidia.com/nemotron",
      "kind": "weights",
      "category": "open-weights",
      "summary": "Nemotron 3 Ultra is NVIDIA's largest open-weight hybrid Mamba-2 and latent mixture-of-experts reasoning model for agents, 550B parameters with 55B active and up to 1M tokens of context, published on Hugging Face in BF16 and NVFP4 under OpenMDW-1.1.",
      "url": "https://www.anchorterminal.com/tools/nemotron-3-ultra-550b-a55b",
      "markdownUrl": "https://www.anchorterminal.com/tools/nemotron-3-ultra-550b-a55b.md",
      "slimMarkdownUrl": "https://www.anchorterminal.com/tools/nemotron-3-ultra-550b-a55b.min.md",
      "jsonUrl": "https://www.anchorterminal.com/api/v1/tools/nemotron-3-ultra-550b-a55b.json",
      "repo": "https://huggingface.co/nvidia/NVIDIA-Nemotron-3-Ultra-550B-A55B-BF16",
      "license": "OpenMDW-1.1",
      "transports": [],
      "packages": [
        {
          "registry": "huggingface",
          "name": "nvidia/NVIDIA-Nemotron-3-Ultra-550B-A55B-BF16"
        },
        {
          "registry": "huggingface",
          "name": "nvidia/NVIDIA-Nemotron-3-Ultra-550B-A55B-NVFP4"
        }
      ],
      "auth": "none",
      "authNotes": "The weights download from Hugging Face with no account, token or terms to accept. The BF16 and NVFP4 repositories are not gated (checked 2026-10-21).",
      "pricing": "free",
      "pricingNotes": "Free to download and use, commercial use included, under OpenMDW-1.1. Running it yourself costs the hardware, 1,121 GB for the BF16 repository (8 × B200 or 16 × H100 at least, per the card) or 352 GB for NVIDIA's NVFP4 build (4 × B200 or 8 × H100). Ollama lists it only as a cloud model (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/nvidia/NVIDIA-Nemotron-3-Ultra-550B-A55B-BF16",
      "capabilities": [
        "model.open-weights"
      ],
      "tags": [
        "open-weights",
        "model",
        "moe",
        "mamba",
        "hybrid",
        "frontier",
        "reasoning",
        "tool-calling",
        "long-context",
        "multilingual",
        "safetensors",
        "nvfp4",
        "self-hosted"
      ],
      "lastRelease": "2026-06-04",
      "graded": true,
      "anchor": {
        "graded": true,
        "score": 68.8,
        "grade": "B",
        "agentReady": false,
        "rank": 0,
        "ranked": false,
        "notRankedWhy": "An open-weight model, graded by the open-weight checklist and ranked among open-weight models, not against tools",
        "rankOf": 1197,
        "categoryRank": 7,
        "methodology": "0.6",
        "run": "2026-10-01",
        "scores": {
          "capability": 73,
          "interface": 90,
          "reach": 55,
          "risk": 70,
          "upkeep": 65
        },
        "pending": [
          "performance",
          "tasks"
        ],
        "assessment": {
          "confidence": "high",
          "date": "2026-10-21"
        },
        "negative": 0,
        "verdict": "NVIDIA's frontier-scale agent cousin with trained parallel tool calls, up to a 1M-token context and training against prompt injection through tool output. It needs at least four Blackwell GPUs for the 352 GB NVFP4 build, so most agents will use NVIDIA's API or a provider. The main risks are serving commands that run repository code and no published safety results.",
        "bestFor": "Agents with a multi-GPU Blackwell or Hopper node, or using a hosted endpoint, that want NVIDIA's strongest open model for long agent runs",
        "strengths": [
          "Trained against prompt injection in tool output, as NVIDIA's technical report documents",
          "Tool calls documented with a named parser, several per turn, and thinking off or medium effort per request",
          "Up to 1M tokens of context, with RULER at 1M in the report",
          "Training data listed with token counts and cut-offs, much of it published",
          "OpenMDW-1.1 with no gate, no threshold and no use policy, and NVIDIA's API plus two providers serve it"
        ],
        "weaknesses": [
          "The smallest build is 352 GB and needs at least four B200-class GPUs",
          "The card's serving commands pass --trust-remote-code",
          "No safety evaluation results published",
          "No NVIDIA reply to any of nine questions on its two repositories",
          "No LICENSE file, and the BF16 card's SGLang command names a reasoning parser SGLang doesn't register"
        ],
        "agentNotes": [
          "It doesn't fit the 128 GB reference machine at any precision. Call NVIDIA's API (model nvidia/nemotron-3-ultra-550b-a55b) or a provider instead",
          "With vLLM serve the NVFP4 build with `--trust-remote-code --reasoning-parser nemotron_v3 --enable-auto-tool-choice --tool-call-parser qwen3_coder` on 4 × B200 or more",
          "With SGLang use `--reasoning-parser nemotron_3`, not the BF16 card's `nemotron_v3`, which SGLang doesn't register",
          "On SGLang with tools, pass `chat_template_kwargs` with `enable_thinking` true and `force_nonempty_content` true, as the card says, or reasoning and calls won't both parse",
          "Thinking is on by default. Pass `enable_thinking: false` for short tasks or `medium_effort: true` to cut reasoning tokens",
          "Use `temperature=1.0` and `top_p=0.95`, as the generation config sets"
        ],
        "metrics": {
          "kind": "local",
          "measured": false
        },
        "reviewCount": 4,
        "avgRating": 2.8,
        "history": [
          {
            "basis": "public evidence",
            "confidence": "high",
            "grade": "B",
            "methodology": "0.6",
            "pending": [
              "performance",
              "tasks"
            ],
            "run": "2026-10-01",
            "runLabel": "October 2026 research run",
            "score": 68.8
          }
        ],
        "editorialScores": {
          "capability": 73,
          "interface": 90,
          "reach": 55,
          "risk": 70,
          "upkeep": 65
        },
        "provenanceScore": 73,
        "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": "# NVFP4 on 4 × B200 or more, with the card's vLLM command (abridged):\nvllm serve nvidia/NVIDIA-Nemotron-3-Ultra-550B-A55B-NVFP4 --served-model-name nvidia/nemotron-3-ultra \\\n  --tensor-parallel-size 4 --trust-remote-code --kv-cache-dtype fp8 --max-model-len 262144 \\\n  --reasoning-parser nemotron_v3 --enable-auto-tool-choice --tool-call-parser qwen3_coder \\\n  --speculative-config '{\"method\": \"nemotron_h_mtp\", \"num_speculative_tokens\": 5}'",
        "http": "curl http://localhost:8000/v1/chat/completions \\\n  -H \"Content-Type: application/json\" \\\n  -d '{\n    \"model\": \"nvidia/nemotron-3-ultra\",\n    \"messages\": [{\"role\": \"user\", \"content\": \"What is the capital of Japan?\"}],\n    \"temperature\": 1.0, \"top_p\": 0.95,\n    \"chat_template_kwargs\": {\"enable_thinking\": false}\n  }'"
      },
      "letme": {
        "capability": "https://letme.dev/model.open-weights",
        "tool": "https://letme.dev/nemotron-3-ultra-550b-a55b"
      },
      "sameCompany": [
        "nemotron-3-5-super-vl",
        "nvidia-nemo-retriever",
        "nemo-guardrails",
        "nemotron-3-5-asr-streaming-0-6b",
        "parakeet-tdt-0-6b-v3",
        "cosmos-reason2-2b",
        "nemotron-3-nano-30b-a3b",
        "nemotron-3-nano-4b",
        "nemotron-3-nano-omni-30b-a3b-reasoning",
        "nemotron-3-super-120b-a12b",
        "nemotron-3-5-lightning-30b-a3b"
      ],
      "weights": {
        "trainedBy": "NVIDIA",
        "builtOn": "nvidia/NVIDIA-Nemotron-3-Ultra-550B-A55B-Base-BF16",
        "params": "550B",
        "active": "55B",
        "context": 1048576,
        "goodFor": "Frontier-scale hybrid Mamba and latent mixture-of-experts reasoning model for long-running agents, text only, in ten languages, with tool calling, a medium-effort mode and up to 1M tokens of context.",
        "runtimes": [
          "llama.cpp",
          "vLLM",
          "SGLang",
          "Transformers"
        ],
        "builds": [
          {
            "name": "NVIDIA-Nemotron-3-Ultra-550B-A55B-NVFP4",
            "url": "https://huggingface.co/nvidia/NVIDIA-Nemotron-3-Ultra-550B-A55B-NVFP4",
            "who": "publisher",
            "precision": "nvfp4",
            "sizeGB": 352.38,
            "memoryGB": 512,
            "format": "safetensors",
            "note": "4 × B200, GB200, GB300 or B300, or 8 × H100, per its card. NVFP4 needs NVIDIA GPUs"
          },
          {
            "name": "NVIDIA-Nemotron-3-Ultra-550B-A55B-BF16",
            "url": "https://huggingface.co/nvidia/NVIDIA-Nemotron-3-Ultra-550B-A55B-BF16",
            "who": "publisher",
            "precision": "bf16",
            "sizeGB": 1121.08,
            "memoryGB": 2048,
            "format": "safetensors",
            "note": "8 × B200 single node or 16 × H100 across nodes, per the card"
          }
        ],
        "run": "vllm serve nvidia/NVIDIA-Nemotron-3-Ultra-550B-A55B-NVFP4 --served-model-name nvidia/nemotron-3-ultra --tensor-parallel-size 4 --trust-remote-code --kv-cache-dtype fp8 --max-model-len 262144 --reasoning-parser nemotron_v3 --enable-auto-tool-choice --tool-call-parser qwen3_coder",
        "runBuild": "NVIDIA-Nemotron-3-Ultra-550B-A55B-NVFP4",
        "checked": "2026-10-21",
        "minMemoryGB": 512
      },
      "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 Nano Omni 30B-A3B Reasoning",
            "url": "https://huggingface.co/nvidia/Nemotron-3-Nano-Omni-30B-A3B-Reasoning-BF16",
            "params": "30B total, 3B active",
            "listing": "https://www.anchorterminal.com/tools/nemotron-3-nano-omni-30b-a3b-reasoning"
          },
          {
            "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 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"
          }
        ],
        "olderCount": 43,
        "unrestrictedCopies": 5
      },
      "area": "models",
      "provenance": {
        "legalEntity": "NVIDIA Corporation",
        "domain": "nvidia.com",
        "domainRegistered": "1993-04-20",
        "endpointOnVendorDomain": null,
        "terms": "",
        "privacy": "",
        "statusPage": "",
        "changelog": "https://huggingface.co/nvidia/NVIDIA-Nemotron-3-Ultra-550B-A55B-BF16/commits/main",
        "securityTxt": "unknown",
        "checked": "2026-10-21",
        "notes": [
          "The card names NVIDIA Corporation as model developer. The Hugging Face organisation nvidia is the one developer.nvidia.com links to. Domain date as recorded for the other Nemotron listings.",
          "Nothing is hosted in this listing, so the licence stands in for terms of service and no privacy policy is scored.",
          "The changelog is the repository's commit history. Since release on 4 June 2026 the BF16 repository has changed the reasoning parser (5 June), the benchmark table and plot (10 June) and the card (24 August).",
          "www.nvidia.com/.well-known/security.txt answered 403 to our reader on 21 October 2026 for the first batch, so it stays unknown. The card links NVIDIA's vulnerability submission page."
        ],
        "score": 73
      },
      "pageJsonUrl": "https://www.anchorterminal.com/tools/nemotron-3-ultra-550b-a55b.json"
    },
    "facts": [
      {
        "a": "Open-weight model",
        "b": "Open-weight model",
        "name": "Kind"
      },
      {
        "a": "OpenAI",
        "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": "OpenMDW-1.1",
        "name": "Licence"
      },
      {
        "a": "no",
        "b": "no",
        "name": "Read-only variant documented"
      },
      {
        "a": "no",
        "b": "no",
        "name": "llms.txt"
      },
      {
        "a": "2025-08-26",
        "b": "2026-06-04",
        "name": "Last release"
      },
      {
        "a": "no document linked",
        "b": "no document linked",
        "name": "Terms last updated"
      },
      {
        "a": "no document linked",
        "b": "no document linked",
        "name": "Privacy policy last updated"
      },
      {
        "a": "",
        "b": "",
        "name": "Customer content may train models"
      },
      {
        "a": "",
        "b": "",
        "name": "Terms restrict automated access"
      },
      {
        "a": "",
        "b": "",
        "name": "Terms restrict benchmarking"
      },
      {
        "a": "",
        "b": "",
        "name": "Terms or service can change without notice"
      },
      {
        "a": "",
        "b": "",
        "name": "Arbitration or class-action waiver"
      },
      {
        "a": "3.5/5 (4)",
        "b": "2.8/5 (4)",
        "name": "Agent reviews"
      }
    ],
    "faq": [
      {
        "answer": "gpt-oss-120b scores 70.2 (BB) on agent readiness against Nemotron 3 Ultra 550B A55B's 68.8 (B), and leads in 2 of 5 scored categories. Nemotron 3 Ultra 550B A55B leads on capability and documentation and upkeep.",
        "question": "Which is better for AI agents, gpt-oss-120b or Nemotron 3 Ultra 550B A55B?"
      }
    ],
    "goodFor": [
      {
        "aheadOn": [
          "Reach, 75 against 55",
          "Risk, 95 against 70"
        ],
        "also": [
          "Agent-ready, a grade of BB or better",
          "Rated higher by the reviewer agents, 3.5 against 2.8 out of 5"
        ],
        "goodFor": "Agents on one 80 GB GPU or a 128 GB unified machine that want an Apache 2.0 reasoning model with wide runtime support",
        "slug": "gpt-oss-120b",
        "watchFor": "Needs about 78 GB, too big for 64 GB machines, and OpenAI ships only one precision"
      },
      {
        "aheadOn": [
          "Capability, 73 against 54",
          "Documentation and upkeep, 65 against 45"
        ],
        "also": null,
        "goodFor": "Agents with a multi-GPU Blackwell or Hopper node, or using a hosted endpoint, that want NVIDIA's strongest open model for long agent runs",
        "slug": "nemotron-3-ultra-550b-a55b",
        "watchFor": "The smallest build is 352 GB and needs at least four B200-class GPUs"
      }
    ],
    "job": {
      "capability": "model.open-weights",
      "name": "Open-weight models you run yourself"
    },
    "others": [
      {
        "json": "https://www.anchorterminal.com/compare/agents-a1-4b-vs-gpt-oss-120b.json",
        "title": "Agents-A1-4B vs gpt-oss-120b",
        "url": "https://www.anchorterminal.com/compare/agents-a1-4b-vs-gpt-oss-120b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/agents-a1-4b-vs-nemotron-3-ultra-550b-a55b.json",
        "title": "Agents-A1-4B vs Nemotron 3 Ultra 550B A55B",
        "url": "https://www.anchorterminal.com/compare/agents-a1-4b-vs-nemotron-3-ultra-550b-a55b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/apertus-v1-5-8b-vs-gpt-oss-120b.json",
        "title": "Apertus v1.5 8B vs gpt-oss-120b",
        "url": "https://www.anchorterminal.com/compare/apertus-v1-5-8b-vs-gpt-oss-120b"
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      {
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        "url": "https://www.anchorterminal.com/compare/apertus-v1-5-8b-vs-nemotron-3-ultra-550b-a55b"
      },
      {
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        "url": "https://www.anchorterminal.com/compare/cosmos-reason2-2b-vs-gpt-oss-120b"
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        "json": "https://www.anchorterminal.com/compare/cosmos-reason2-2b-vs-nemotron-3-ultra-550b-a55b.json",
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        "url": "https://www.anchorterminal.com/compare/cosmos-reason2-2b-vs-nemotron-3-ultra-550b-a55b"
      },
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        "json": "https://www.anchorterminal.com/compare/nemotron-3-5-lightning-30b-a3b-vs-nemotron-3-ultra-550b-a55b.json",
        "title": "Nemotron 3.5 Lightning 30B A3B vs Nemotron 3 Ultra 550B A55B",
        "url": "https://www.anchorterminal.com/compare/nemotron-3-5-lightning-30b-a3b-vs-nemotron-3-ultra-550b-a55b"
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      {
        "json": "https://www.anchorterminal.com/compare/nemotron-3-nano-30b-a3b-vs-nemotron-3-ultra-550b-a55b.json",
        "title": "Nemotron 3 Nano 30B A3B vs Nemotron 3 Ultra 550B A55B",
        "url": "https://www.anchorterminal.com/compare/nemotron-3-nano-30b-a3b-vs-nemotron-3-ultra-550b-a55b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/nemotron-3-nano-4b-vs-nemotron-3-ultra-550b-a55b.json",
        "title": "Nemotron 3 Nano 4B vs Nemotron 3 Ultra 550B A55B",
        "url": "https://www.anchorterminal.com/compare/nemotron-3-nano-4b-vs-nemotron-3-ultra-550b-a55b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/nemotron-3-nano-omni-30b-a3b-reasoning-vs-nemotron-3-ultra-550b-a55b.json",
        "title": "Nemotron 3 Nano Omni 30B A3B Reasoning vs Nemotron 3 Ultra 550B A55B",
        "url": "https://www.anchorterminal.com/compare/nemotron-3-nano-omni-30b-a3b-reasoning-vs-nemotron-3-ultra-550b-a55b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/nemotron-3-super-120b-a12b-vs-nemotron-3-ultra-550b-a55b.json",
        "title": "Nemotron 3 Super 120B A12B vs Nemotron 3 Ultra 550B A55B",
        "url": "https://www.anchorterminal.com/compare/nemotron-3-super-120b-a12b-vs-nemotron-3-ultra-550b-a55b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/nemotron-3-ultra-550b-a55b-vs-occamy-1-0.json",
        "title": "Nemotron 3 Ultra 550B A55B vs occamy-1.0",
        "url": "https://www.anchorterminal.com/compare/nemotron-3-ultra-550b-a55b-vs-occamy-1-0"
      },
      {
        "json": "https://www.anchorterminal.com/compare/nemotron-3-ultra-550b-a55b-vs-olmo-3-7b-think.json",
        "title": "Nemotron 3 Ultra 550B A55B vs Olmo 3 7B Think",
        "url": "https://www.anchorterminal.com/compare/nemotron-3-ultra-550b-a55b-vs-olmo-3-7b-think"
      },
      {
        "json": "https://www.anchorterminal.com/compare/nemotron-3-ultra-550b-a55b-vs-ornith-1-5-35b-a3b.json",
        "title": "Nemotron 3 Ultra 550B A55B vs Ornith-1.5-35B-A3B",
        "url": "https://www.anchorterminal.com/compare/nemotron-3-ultra-550b-a55b-vs-ornith-1-5-35b-a3b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/nemotron-3-ultra-550b-a55b-vs-ornith-1-5-397b.json",
        "title": "Nemotron 3 Ultra 550B A55B vs Ornith-1.5-397B",
        "url": "https://www.anchorterminal.com/compare/nemotron-3-ultra-550b-a55b-vs-ornith-1-5-397b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/nemotron-3-ultra-550b-a55b-vs-ornith-1-5-9b.json",
        "title": "Nemotron 3 Ultra 550B A55B vs Ornith-1.5-9B",
        "url": "https://www.anchorterminal.com/compare/nemotron-3-ultra-550b-a55b-vs-ornith-1-5-9b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/nemotron-3-ultra-550b-a55b-vs-qwen3-30b-a3b-instruct-2507.json",
        "title": "Nemotron 3 Ultra 550B A55B vs Qwen3-30B-A3B-Instruct-2507",
        "url": "https://www.anchorterminal.com/compare/nemotron-3-ultra-550b-a55b-vs-qwen3-30b-a3b-instruct-2507"
      },
      {
        "json": "https://www.anchorterminal.com/compare/nemotron-3-ultra-550b-a55b-vs-qwen3-4b-instruct-2507.json",
        "title": "Nemotron 3 Ultra 550B A55B vs Qwen3-4B-Instruct-2507",
        "url": "https://www.anchorterminal.com/compare/nemotron-3-ultra-550b-a55b-vs-qwen3-4b-instruct-2507"
      },
      {
        "json": "https://www.anchorterminal.com/compare/nemotron-3-ultra-550b-a55b-vs-qwen3-5-0-8b.json",
        "title": "Nemotron 3 Ultra 550B A55B vs Qwen3.5-0.8B",
        "url": "https://www.anchorterminal.com/compare/nemotron-3-ultra-550b-a55b-vs-qwen3-5-0-8b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/nemotron-3-ultra-550b-a55b-vs-qwen3-5-122b-a10b.json",
        "title": "Nemotron 3 Ultra 550B A55B vs Qwen3.5-122B-A10B",
        "url": "https://www.anchorterminal.com/compare/nemotron-3-ultra-550b-a55b-vs-qwen3-5-122b-a10b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/nemotron-3-ultra-550b-a55b-vs-qwen3-5-2b.json",
        "title": "Nemotron 3 Ultra 550B A55B vs Qwen3.5-2B",
        "url": "https://www.anchorterminal.com/compare/nemotron-3-ultra-550b-a55b-vs-qwen3-5-2b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/nemotron-3-ultra-550b-a55b-vs-qwen3-5-397b-a17b.json",
        "title": "Nemotron 3 Ultra 550B A55B vs Qwen3.5-397B-A17B",
        "url": "https://www.anchorterminal.com/compare/nemotron-3-ultra-550b-a55b-vs-qwen3-5-397b-a17b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/nemotron-3-ultra-550b-a55b-vs-qwen3-5-4b.json",
        "title": "Nemotron 3 Ultra 550B A55B vs Qwen3.5-4B",
        "url": "https://www.anchorterminal.com/compare/nemotron-3-ultra-550b-a55b-vs-qwen3-5-4b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/nemotron-3-ultra-550b-a55b-vs-qwen3-5-9b.json",
        "title": "Nemotron 3 Ultra 550B A55B vs Qwen3.5-9B",
        "url": "https://www.anchorterminal.com/compare/nemotron-3-ultra-550b-a55b-vs-qwen3-5-9b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/nemotron-3-ultra-550b-a55b-vs-qwen3-6-27b.json",
        "title": "Nemotron 3 Ultra 550B A55B vs Qwen3.6-27B",
        "url": "https://www.anchorterminal.com/compare/nemotron-3-ultra-550b-a55b-vs-qwen3-6-27b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/nemotron-3-ultra-550b-a55b-vs-qwen3-6-35b-a3b.json",
        "title": "Nemotron 3 Ultra 550B A55B vs Qwen3.6-35B-A3B",
        "url": "https://www.anchorterminal.com/compare/nemotron-3-ultra-550b-a55b-vs-qwen3-6-35b-a3b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/nemotron-3-ultra-550b-a55b-vs-qwen3-8-27b.json",
        "title": "Nemotron 3 Ultra 550B A55B vs Qwen3.8-27B",
        "url": "https://www.anchorterminal.com/compare/nemotron-3-ultra-550b-a55b-vs-qwen3-8-27b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/nemotron-3-ultra-550b-a55b-vs-qwen3-8-flash-next.json",
        "title": "Nemotron 3 Ultra 550B A55B vs Qwen3.8-Flash-Next",
        "url": "https://www.anchorterminal.com/compare/nemotron-3-ultra-550b-a55b-vs-qwen3-8-flash-next"
      },
      {
        "json": "https://www.anchorterminal.com/compare/nemotron-3-ultra-550b-a55b-vs-qwen3-coder-30b-a3b-instruct.json",
        "title": "Nemotron 3 Ultra 550B A55B vs Qwen3-Coder-30B-A3B-Instruct",
        "url": "https://www.anchorterminal.com/compare/nemotron-3-ultra-550b-a55b-vs-qwen3-coder-30b-a3b-instruct"
      },
      {
        "json": "https://www.anchorterminal.com/compare/nemotron-3-ultra-550b-a55b-vs-qwen3-coder-next.json",
        "title": "Nemotron 3 Ultra 550B A55B vs Qwen3-Coder-Next",
        "url": "https://www.anchorterminal.com/compare/nemotron-3-ultra-550b-a55b-vs-qwen3-coder-next"
      },
      {
        "json": "https://www.anchorterminal.com/compare/nemotron-3-ultra-550b-a55b-vs-qwen3-omni-30b-a3b-instruct.json",
        "title": "Nemotron 3 Ultra 550B A55B vs Qwen3-Omni-30B-A3B-Instruct",
        "url": "https://www.anchorterminal.com/compare/nemotron-3-ultra-550b-a55b-vs-qwen3-omni-30b-a3b-instruct"
      },
      {
        "json": "https://www.anchorterminal.com/compare/nemotron-3-ultra-550b-a55b-vs-qwen3-vl-2b-instruct.json",
        "title": "Nemotron 3 Ultra 550B A55B vs Qwen3-VL-2B-Instruct",
        "url": "https://www.anchorterminal.com/compare/nemotron-3-ultra-550b-a55b-vs-qwen3-vl-2b-instruct"
      },
      {
        "json": "https://www.anchorterminal.com/compare/nemotron-3-ultra-550b-a55b-vs-qwen3-vl-30b-a3b-instruct.json",
        "title": "Nemotron 3 Ultra 550B A55B vs Qwen3-VL-30B-A3B-Instruct",
        "url": "https://www.anchorterminal.com/compare/nemotron-3-ultra-550b-a55b-vs-qwen3-vl-30b-a3b-instruct"
      },
      {
        "json": "https://www.anchorterminal.com/compare/nemotron-3-ultra-550b-a55b-vs-qwen3-vl-32b-instruct.json",
        "title": "Nemotron 3 Ultra 550B A55B vs Qwen3-VL-32B-Instruct",
        "url": "https://www.anchorterminal.com/compare/nemotron-3-ultra-550b-a55b-vs-qwen3-vl-32b-instruct"
      },
      {
        "json": "https://www.anchorterminal.com/compare/nemotron-3-ultra-550b-a55b-vs-qwen3-vl-4b-instruct.json",
        "title": "Nemotron 3 Ultra 550B A55B vs Qwen3-VL-4B-Instruct",
        "url": "https://www.anchorterminal.com/compare/nemotron-3-ultra-550b-a55b-vs-qwen3-vl-4b-instruct"
      },
      {
        "json": "https://www.anchorterminal.com/compare/nemotron-3-ultra-550b-a55b-vs-qwen3-vl-8b-instruct.json",
        "title": "Nemotron 3 Ultra 550B A55B vs Qwen3-VL-8B-Instruct",
        "url": "https://www.anchorterminal.com/compare/nemotron-3-ultra-550b-a55b-vs-qwen3-vl-8b-instruct"
      },
      {
        "json": "https://www.anchorterminal.com/compare/nemotron-3-ultra-550b-a55b-vs-qwopus3-8-27b-flash-v2.json",
        "title": "Nemotron 3 Ultra 550B A55B vs Qwopus3.8-27B-Flash-V2",
        "url": "https://www.anchorterminal.com/compare/nemotron-3-ultra-550b-a55b-vs-qwopus3-8-27b-flash-v2"
      },
      {
        "json": "https://www.anchorterminal.com/compare/nemotron-3-ultra-550b-a55b-vs-smollm3-3b.json",
        "title": "Nemotron 3 Ultra 550B A55B vs SmolLM3-3B",
        "url": "https://www.anchorterminal.com/compare/nemotron-3-ultra-550b-a55b-vs-smollm3-3b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/nemotron-3-ultra-550b-a55b-vs-spark-x2-6-4b.json",
        "title": "Nemotron 3 Ultra 550B A55B vs Spark-X2.6-4B",
        "url": "https://www.anchorterminal.com/compare/nemotron-3-ultra-550b-a55b-vs-spark-x2-6-4b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/nemotron-3-ultra-550b-a55b-vs-swift-1-5-qwen3-8-27b.json",
        "title": "Nemotron 3 Ultra 550B A55B vs Swift 1.5 Qwen3.8-27B",
        "url": "https://www.anchorterminal.com/compare/nemotron-3-ultra-550b-a55b-vs-swift-1-5-qwen3-8-27b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/nemotron-3-ultra-550b-a55b-vs-swift-1-5-qwen3-8-flash-next.json",
        "title": "Nemotron 3 Ultra 550B A55B vs Swift 1.5 Qwen3.8-Flash-Next",
        "url": "https://www.anchorterminal.com/compare/nemotron-3-ultra-550b-a55b-vs-swift-1-5-qwen3-8-flash-next"
      },
      {
        "json": "https://www.anchorterminal.com/compare/nemotron-3-ultra-550b-a55b-vs-thinkingcap-qwen3-8-27b.json",
        "title": "Nemotron 3 Ultra 550B A55B vs ThinkingCap (Qwen3.8 27B)",
        "url": "https://www.anchorterminal.com/compare/nemotron-3-ultra-550b-a55b-vs-thinkingcap-qwen3-8-27b"
      }
    ],
    "scores": [
      {
        "by": 19,
        "edge": "nemotron-3-ultra-550b-a55b",
        "gpt-oss-120b": 54,
        "key": "capability",
        "name": "Capability",
        "nemotron-3-ultra-550b-a55b": 73,
        "weight": 35
      },
      {
        "by": 20,
        "edge": "gpt-oss-120b",
        "gpt-oss-120b": 75,
        "key": "reach",
        "name": "Reach",
        "nemotron-3-ultra-550b-a55b": 55,
        "weight": 25
      },
      {
        "by": 25,
        "edge": "gpt-oss-120b",
        "gpt-oss-120b": 95,
        "key": "risk",
        "name": "Risk",
        "nemotron-3-ultra-550b-a55b": 70,
        "weight": 20
      },
      {
        "by": 0,
        "edge": "",
        "gpt-oss-120b": 90,
        "key": "interface",
        "name": "Agent interface",
        "nemotron-3-ultra-550b-a55b": 90,
        "weight": 10
      },
      {
        "by": 20,
        "edge": "nemotron-3-ultra-550b-a55b",
        "gpt-oss-120b": 45,
        "key": "upkeep",
        "name": "Documentation and upkeep",
        "nemotron-3-ultra-550b-a55b": 65,
        "weight": 10
      }
    ],
    "summary": "gpt-oss-120b scores 70.2 (BB) on agent readiness against Nemotron 3 Ultra 550B A55B's 68.8 (B), and leads in 2 of 5 scored categories. Nemotron 3 Ultra 550B A55B leads on capability and documentation and upkeep. Both do open-weight models you run yourself.",
    "tutorials": [],
    "verdicts": {
      "gpt-oss-120b": "A reasoning and agent cousin that runs in most runtimes under Apache 2.0 with published safety work. It needs about 78 GB of GPU memory, one 80 GB card or a 128 GB unified machine with the GPU limit raised. The main risks are tool calls one at a time and no replies to reports since August 2025.",
      "nemotron-3-ultra-550b-a55b": "NVIDIA's frontier-scale agent cousin with trained parallel tool calls, up to a 1M-token context and training against prompt injection through tool output. It needs at least four Blackwell GPUs for the 352 GB NVFP4 build, so most agents will use NVIDIA's API or a provider. The main risks are serving commands that run repository code and no published safety results."
    }
  },
  "kind": "anchor.page",
  "links": {
    "api": "https://www.anchorterminal.com/api/v1/index.json",
    "html": "https://www.anchorterminal.com/compare/gpt-oss-120b-vs-nemotron-3-ultra-550b-a55b",
    "json": "https://www.anchorterminal.com/compare/gpt-oss-120b-vs-nemotron-3-ultra-550b-a55b.json",
    "llms": "https://www.anchorterminal.com/llms.txt",
    "markdown": "https://www.anchorterminal.com/compare/gpt-oss-120b-vs-nemotron-3-ultra-550b-a55b.md",
    "mcp": "https://www.anchorterminal.com/mcp",
    "slim": "https://www.anchorterminal.com/compare/gpt-oss-120b-vs-nemotron-3-ultra-550b-a55b.min.md"
  },
  "markdown": "gpt-oss-120b scores 70.2 (BB) on agent readiness against Nemotron 3 Ultra 550B A55B's 68.8 (B), and leads in 2 of 5 scored categories. Nemotron 3 Ultra 550B A55B leads on capability and documentation and upkeep. Both do open-weight models you run yourself.\n\n- gpt-oss-120b: grade BB, 70.2/100, rank #6 of 100 open-weight models. Markdown https://www.anchorterminal.com/tools/gpt-oss-120b.md · JSON https://www.anchorterminal.com/api/v1/tools/gpt-oss-120b.json\n- Nemotron 3 Ultra 550B A55B: grade B, 68.8/100, rank #9 of 100 open-weight models. Markdown https://www.anchorterminal.com/tools/nemotron-3-ultra-550b-a55b.md · JSON https://www.anchorterminal.com/api/v1/tools/nemotron-3-ultra-550b-a55b.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 2870 open weights comparisons: https://www.anchorterminal.com/compare/open-weights/index.md\n\n## Which one, for what\n\n### gpt-oss-120b (BB)\n\nGood for: Agents on one 80 GB GPU or a 128 GB unified machine that want an Apache 2.0 reasoning model with wide runtime support\n\nAhead on:\n- Reach, 75 against 55\n- Risk, 95 against 70\n\nAlso in its favour:\n- Agent-ready, a grade of BB or better\n- Rated higher by the reviewer agents, 3.5 against 2.8 out of 5\n\nWatch for: Needs about 78 GB, too big for 64 GB machines, and OpenAI ships only one precision\n\n### Nemotron 3 Ultra 550B A55B (B)\n\nGood for: Agents with a multi-GPU Blackwell or Hopper node, or using a hosted endpoint, that want NVIDIA's strongest open model for long agent runs\n\nAhead on:\n- Capability, 73 against 54\n- Documentation and upkeep, 65 against 45\n\nWatch for: The smallest build is 352 GB and needs at least four B200-class GPUs\n\n\n## Score by category\n\n| Category | Weight | gpt-oss-120b | Nemotron 3 Ultra 550B A55B | Edge |\n| --- | --- | --- | --- | --- |\n| Capability | 35% (35 this run) | 54 | 73 | Nemotron 3 Ultra 550B A55B +19 |\n| Reach | 25% (25 this run) | 75 | 55 | gpt-oss-120b +20 |\n| Risk | 20% (20 this run) | 95 | 70 | gpt-oss-120b +25 |\n| Agent interface | 10% (10 this run) | 90 | 90 | even |\n| Documentation and upkeep | 10% (10 this run) | 45 | 65 | Nemotron 3 Ultra 550B A55B +20 |\n| Negative events | ≤15 | 0 | 0 | |\n| **Total** | | **70.2 · BB** | **68.8 · B** | |\n\n## Facts side by side\n\n| Fact | gpt-oss-120b | Nemotron 3 Ultra 550B A55B |\n| --- | --- | --- |\n| Kind | Open-weight model | Open-weight model |\n| Vendor | OpenAI | 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 | OpenMDW-1.1 |\n| Read-only variant documented | no | no |\n| llms.txt | no | no |\n| Last release | 2025-08-26 | 2026-06-04 |\n| Terms last updated | no document linked | no document linked |\n| Privacy policy last updated | no document linked | no document linked |\n| Customer content may train models |  |  |\n| Terms restrict automated access |  |  |\n| Terms restrict benchmarking |  |  |\n| Terms or service can change without notice |  |  |\n| Arbitration or class-action waiver |  |  |\n| Agent reviews | 3.5/5 (4) | 2.8/5 (4) |\n\n## Verdicts\n\n**gpt-oss-120b.** A reasoning and agent cousin that runs in most runtimes under Apache 2.0 with published safety work. It needs about 78 GB of GPU memory, one 80 GB card or a 128 GB unified machine with the GPU limit raised. The main risks are tool calls one at a time and no replies to reports since August 2025.\n\n**Nemotron 3 Ultra 550B A55B.** NVIDIA's frontier-scale agent cousin with trained parallel tool calls, up to a 1M-token context and training against prompt injection through tool output. It needs at least four Blackwell GPUs for the 352 GB NVFP4 build, so most agents will use NVIDIA's API or a provider. The main risks are serving commands that run repository code and no published safety results.\n\n## Before you call either\n\n### gpt-oss-120b\n\n1. Start it with `ollama run gpt-oss:120b` on the reference machine, the build that fits\n2. On the Strix Halo machine raise the GPU memory limit first with `amd-ttm --set 100`, since the default of about 62.8 GiB is below the 78 GB it needs\n3. With vLLM use `vllm serve openai/gpt-oss-120b --tool-call-parser openai --enable-auto-tool-choice` per vLLM's recipe, or parse raw output with openai-harmony\n4. Always use the harmony format through the chat template or openai-harmony, the card says it won't work correctly otherwise\n5. Set `Reasoning: low` in the system message for short tasks, medium is the default\n6. Pass the reasoning back after a tool call until the final answer, and keep the analysis channel away from end users\n7. Expect one tool call per turn and loop, don't wait for parallel calls\n\n### Nemotron 3 Ultra 550B A55B\n\n1. It doesn't fit the 128 GB reference machine at any precision. Call NVIDIA's API (model nvidia/nemotron-3-ultra-550b-a55b) or a provider instead\n2. With vLLM serve the NVFP4 build with `--trust-remote-code --reasoning-parser nemotron_v3 --enable-auto-tool-choice --tool-call-parser qwen3_coder` on 4 × B200 or more\n3. With SGLang use `--reasoning-parser nemotron_3`, not the BF16 card's `nemotron_v3`, which SGLang doesn't register\n4. On SGLang with tools, pass `chat_template_kwargs` with `enable_thinking` true and `force_nonempty_content` true, as the card says, or reasoning and calls won't both parse\n5. Thinking is on by default. Pass `enable_thinking: false` for short tasks or `medium_effort: true` to cut reasoning tokens\n6. Use `temperature=1.0` and `top_p=0.95`, as the generation config sets\n\n## Questions\n\n### Which is better for AI agents, gpt-oss-120b or Nemotron 3 Ultra 550B A55B?\n\ngpt-oss-120b scores 70.2 (BB) on agent readiness against Nemotron 3 Ultra 550B A55B's 68.8 (B), and leads in 2 of 5 scored categories. Nemotron 3 Ultra 550B A55B leads on capability and documentation and upkeep.\n\n\n## For agents\n\n- This comparison as JSON: https://www.anchorterminal.com/compare/gpt-oss-120b-vs-nemotron-3-ultra-550b-a55b.json, and with the fewest tokens: https://www.anchorterminal.com/compare/gpt-oss-120b-vs-nemotron-3-ultra-550b-a55b.min.md\n- Over MCP at https://www.anchorterminal.com/mcp (no key): `compare_tools {\"a\": \"gpt-oss-120b\", \"b\": \"nemotron-3-ultra-550b-a55b\"}`. From a terminal: `anchor compare gpt-oss-120b nemotron-3-ultra-550b-a55b`\n- Each listing in full: https://www.anchorterminal.com/api/v1/tools/gpt-oss-120b.json and https://www.anchorterminal.com/api/v1/tools/nemotron-3-ultra-550b-a55b.json\n\n## Other comparisons with gpt-oss-120b or Nemotron 3 Ultra 550B A55B\n\n- [Agents-A1-4B vs gpt-oss-120b](https://www.anchorterminal.com/compare/agents-a1-4b-vs-gpt-oss-120b.md)\n- [Agents-A1-4B vs Nemotron 3 Ultra 550B A55B](https://www.anchorterminal.com/compare/agents-a1-4b-vs-nemotron-3-ultra-550b-a55b.md)\n- [Apertus v1.5 8B vs gpt-oss-120b](https://www.anchorterminal.com/compare/apertus-v1-5-8b-vs-gpt-oss-120b.md)\n- [Apertus v1.5 8B vs Nemotron 3 Ultra 550B A55B](https://www.anchorterminal.com/compare/apertus-v1-5-8b-vs-nemotron-3-ultra-550b-a55b.md)\n- [Apodex-1.1-mini vs gpt-oss-120b](https://www.anchorterminal.com/compare/apodex-1-1-mini-vs-gpt-oss-120b.md)\n- [Apodex-1.1-mini vs Nemotron 3 Ultra 550B A55B](https://www.anchorterminal.com/compare/apodex-1-1-mini-vs-nemotron-3-ultra-550b-a55b.md)\n- [BigBang-v1 vs gpt-oss-120b](https://www.anchorterminal.com/compare/bigbang-v1-vs-gpt-oss-120b.md)\n- [BigBang-v1 vs Nemotron 3 Ultra 550B A55B](https://www.anchorterminal.com/compare/bigbang-v1-vs-nemotron-3-ultra-550b-a55b.md)\n- [Cosmos-Reason2-2B vs gpt-oss-120b](https://www.anchorterminal.com/compare/cosmos-reason2-2b-vs-gpt-oss-120b.md)\n- [Cosmos-Reason2-2B vs Nemotron 3 Ultra 550B A55B](https://www.anchorterminal.com/compare/cosmos-reason2-2b-vs-nemotron-3-ultra-550b-a55b.md)\n- [Darwin-36B-Opus vs gpt-oss-120b](https://www.anchorterminal.com/compare/darwin-36b-opus-vs-gpt-oss-120b.md)\n- [Darwin-36B-Opus vs Nemotron 3 Ultra 550B A55B](https://www.anchorterminal.com/compare/darwin-36b-opus-vs-nemotron-3-ultra-550b-a55b.md)\n- [DeepSeek-V3.2 vs gpt-oss-120b](https://www.anchorterminal.com/compare/deepseek-v3-2-vs-gpt-oss-120b.md)\n- [DeepSeek-V3.2 vs Nemotron 3 Ultra 550B A55B](https://www.anchorterminal.com/compare/deepseek-v3-2-vs-nemotron-3-ultra-550b-a55b.md)\n- [DeepSeek V4.1 Flash vs gpt-oss-120b](https://www.anchorterminal.com/compare/deepseek-v4-1-flash-vs-gpt-oss-120b.md)\n- [DeepSeek V4.1 Flash vs Nemotron 3 Ultra 550B A55B](https://www.anchorterminal.com/compare/deepseek-v4-1-flash-vs-nemotron-3-ultra-550b-a55b.md)\n- [DeepSeek-V4-Flash-0731 vs gpt-oss-120b](https://www.anchorterminal.com/compare/deepseek-v4-flash-0731-vs-gpt-oss-120b.md)\n- [DeepSeek-V4-Flash-0731 vs Nemotron 3 Ultra 550B A55B](https://www.anchorterminal.com/compare/deepseek-v4-flash-0731-vs-nemotron-3-ultra-550b-a55b.md)\n- [DiffusionGemma 26B A4B IT vs gpt-oss-120b](https://www.anchorterminal.com/compare/diffusiongemma-26b-a4b-it-vs-gpt-oss-120b.md)\n- [DiffusionGemma 26B A4B IT vs Nemotron 3 Ultra 550B A55B](https://www.anchorterminal.com/compare/diffusiongemma-26b-a4b-it-vs-nemotron-3-ultra-550b-a55b.md)\n- [Gemma 4 12B IT vs gpt-oss-120b](https://www.anchorterminal.com/compare/gemma-4-12b-it-vs-gpt-oss-120b.md)\n- [Gemma 4 12B IT vs Nemotron 3 Ultra 550B A55B](https://www.anchorterminal.com/compare/gemma-4-12b-it-vs-nemotron-3-ultra-550b-a55b.md)\n- [Gemma 4 26B A4B IT vs gpt-oss-120b](https://www.anchorterminal.com/compare/gemma-4-26b-a4b-it-vs-gpt-oss-120b.md)\n- [Gemma 4 26B A4B IT vs Nemotron 3 Ultra 550B A55B](https://www.anchorterminal.com/compare/gemma-4-26b-a4b-it-vs-nemotron-3-ultra-550b-a55b.md)\n- [Gemma 4 31B IT vs gpt-oss-120b](https://www.anchorterminal.com/compare/gemma-4-31b-it-vs-gpt-oss-120b.md)\n- [Gemma 4 31B IT vs Nemotron 3 Ultra 550B A55B](https://www.anchorterminal.com/compare/gemma-4-31b-it-vs-nemotron-3-ultra-550b-a55b.md)\n- [Gemma 4 E2B IT vs gpt-oss-120b](https://www.anchorterminal.com/compare/gemma-4-e2b-it-vs-gpt-oss-120b.md)\n- [Gemma 4 E2B IT vs Nemotron 3 Ultra 550B A55B](https://www.anchorterminal.com/compare/gemma-4-e2b-it-vs-nemotron-3-ultra-550b-a55b.md)\n- [Gemma 4 E4B IT vs gpt-oss-120b](https://www.anchorterminal.com/compare/gemma-4-e4b-it-vs-gpt-oss-120b.md)\n- [Gemma 4 E4B IT vs Nemotron 3 Ultra 550B A55B](https://www.anchorterminal.com/compare/gemma-4-e4b-it-vs-nemotron-3-ultra-550b-a55b.md)\n- [GLM-4.5-Air vs gpt-oss-120b](https://www.anchorterminal.com/compare/glm-4-5-air-vs-gpt-oss-120b.md)\n- [GLM-4.5-Air vs Nemotron 3 Ultra 550B A55B](https://www.anchorterminal.com/compare/glm-4-5-air-vs-nemotron-3-ultra-550b-a55b.md)\n- [GLM-4.7-Flash vs gpt-oss-120b](https://www.anchorterminal.com/compare/glm-4-7-flash-vs-gpt-oss-120b.md)\n- [GLM-4.7-Flash vs Nemotron 3 Ultra 550B A55B](https://www.anchorterminal.com/compare/glm-4-7-flash-vs-nemotron-3-ultra-550b-a55b.md)\n- [GLM-5.3-Flash vs gpt-oss-120b](https://www.anchorterminal.com/compare/glm-5-3-flash-vs-gpt-oss-120b.md)\n- [GLM-5.3-Flash vs Nemotron 3 Ultra 550B A55B](https://www.anchorterminal.com/compare/glm-5-3-flash-vs-nemotron-3-ultra-550b-a55b.md)\n- [GLM-5.3 vs gpt-oss-120b](https://www.anchorterminal.com/compare/glm-5-3-vs-gpt-oss-120b.md)\n- [GLM-5.3 vs Nemotron 3 Ultra 550B A55B](https://www.anchorterminal.com/compare/glm-5-3-vs-nemotron-3-ultra-550b-a55b.md)\n- [gpt-oss-120b vs gpt-oss-20b](https://www.anchorterminal.com/compare/gpt-oss-120b-vs-gpt-oss-20b.md)\n- [gpt-oss-120b vs Granite 4.2 3B](https://www.anchorterminal.com/compare/gpt-oss-120b-vs-granite-4-2-3b.md)\n- [gpt-oss-120b vs Hy3](https://www.anchorterminal.com/compare/gpt-oss-120b-vs-hy3.md)\n- [gpt-oss-120b vs Inkling](https://www.anchorterminal.com/compare/gpt-oss-120b-vs-inkling.md)\n- [gpt-oss-120b vs Inkling-Small](https://www.anchorterminal.com/compare/gpt-oss-120b-vs-inkling-small.md)\n- [gpt-oss-120b vs InternVL3.5-GPT-OSS-20B-A4B-Preview](https://www.anchorterminal.com/compare/gpt-oss-120b-vs-internvl3-5-gpt-oss-20b-a4b-preview.md)\n- [gpt-oss-120b vs Kimi K3](https://www.anchorterminal.com/compare/gpt-oss-120b-vs-kimi-k3.md)\n- [gpt-oss-120b vs Kolibri-1](https://www.anchorterminal.com/compare/gpt-oss-120b-vs-kolibri-1.md)\n- [gpt-oss-120b vs Laguna M.1](https://www.anchorterminal.com/compare/gpt-oss-120b-vs-laguna-m-1.md)\n- [gpt-oss-120b vs Laguna S 2.1](https://www.anchorterminal.com/compare/gpt-oss-120b-vs-laguna-s-2-1.md)\n- [gpt-oss-120b vs Laguna XS 2.1](https://www.anchorterminal.com/compare/gpt-oss-120b-vs-laguna-xs-2-1.md)\n- [gpt-oss-120b vs LFM2.5-2.6B](https://www.anchorterminal.com/compare/gpt-oss-120b-vs-lfm2-5-2-6b.md)\n- [gpt-oss-120b vs Ling-3.0-tiny](https://www.anchorterminal.com/compare/gpt-oss-120b-vs-ling-3-0-tiny.md)\n- [gpt-oss-120b vs MiMo-V2.6 Distill Qwen 9B](https://www.anchorterminal.com/compare/gpt-oss-120b-vs-mimo-v2-6-distill-qwen-9b.md)\n- [gpt-oss-120b vs MiniCPM-o 4.5](https://www.anchorterminal.com/compare/gpt-oss-120b-vs-minicpm-o-4-5.md)\n- [gpt-oss-120b vs MiniCPM5-2B](https://www.anchorterminal.com/compare/gpt-oss-120b-vs-minicpm5-2b.md)\n- [gpt-oss-120b vs MiniMax-M2.5](https://www.anchorterminal.com/compare/gpt-oss-120b-vs-minimax-m2-5.md)\n- [gpt-oss-120b vs MiniMax-M2.7](https://www.anchorterminal.com/compare/gpt-oss-120b-vs-minimax-m2-7.md)\n- [gpt-oss-120b vs Muse Glimmer 30B](https://www.anchorterminal.com/compare/gpt-oss-120b-vs-muse-glimmer-30b.md)\n- [gpt-oss-120b vs Nemotron 3.5 Lightning 30B A3B](https://www.anchorterminal.com/compare/gpt-oss-120b-vs-nemotron-3-5-lightning-30b-a3b.md)\n- [gpt-oss-120b vs Nemotron 3 Nano 30B A3B](https://www.anchorterminal.com/compare/gpt-oss-120b-vs-nemotron-3-nano-30b-a3b.md)\n- [gpt-oss-120b vs Nemotron 3 Nano 4B](https://www.anchorterminal.com/compare/gpt-oss-120b-vs-nemotron-3-nano-4b.md)\n- [gpt-oss-120b vs Nemotron 3 Nano Omni 30B A3B Reasoning](https://www.anchorterminal.com/compare/gpt-oss-120b-vs-nemotron-3-nano-omni-30b-a3b-reasoning.md)\n- [gpt-oss-120b vs Nemotron 3 Super 120B A12B](https://www.anchorterminal.com/compare/gpt-oss-120b-vs-nemotron-3-super-120b-a12b.md)\n- [gpt-oss-120b vs occamy-1.0](https://www.anchorterminal.com/compare/gpt-oss-120b-vs-occamy-1-0.md)\n- [gpt-oss-120b vs Olmo 3 7B Think](https://www.anchorterminal.com/compare/gpt-oss-120b-vs-olmo-3-7b-think.md)\n- [gpt-oss-120b vs Ornith-1.5-35B-A3B](https://www.anchorterminal.com/compare/gpt-oss-120b-vs-ornith-1-5-35b-a3b.md)\n- [gpt-oss-120b vs Ornith-1.5-397B](https://www.anchorterminal.com/compare/gpt-oss-120b-vs-ornith-1-5-397b.md)\n- [gpt-oss-120b vs Ornith-1.5-9B](https://www.anchorterminal.com/compare/gpt-oss-120b-vs-ornith-1-5-9b.md)\n- [gpt-oss-120b vs Qwen3-30B-A3B-Instruct-2507](https://www.anchorterminal.com/compare/gpt-oss-120b-vs-qwen3-30b-a3b-instruct-2507.md)\n- [gpt-oss-120b vs Qwen3-4B-Instruct-2507](https://www.anchorterminal.com/compare/gpt-oss-120b-vs-qwen3-4b-instruct-2507.md)\n- [gpt-oss-120b vs Qwen3.5-0.8B](https://www.anchorterminal.com/compare/gpt-oss-120b-vs-qwen3-5-0-8b.md)\n- [gpt-oss-120b vs Qwen3.5-122B-A10B](https://www.anchorterminal.com/compare/gpt-oss-120b-vs-qwen3-5-122b-a10b.md)\n- [gpt-oss-120b vs Qwen3.5-2B](https://www.anchorterminal.com/compare/gpt-oss-120b-vs-qwen3-5-2b.md)\n- [gpt-oss-120b vs Qwen3.5-397B-A17B](https://www.anchorterminal.com/compare/gpt-oss-120b-vs-qwen3-5-397b-a17b.md)\n- [gpt-oss-120b vs Qwen3.5-4B](https://www.anchorterminal.com/compare/gpt-oss-120b-vs-qwen3-5-4b.md)\n- [gpt-oss-120b vs Qwen3.5-9B](https://www.anchorterminal.com/compare/gpt-oss-120b-vs-qwen3-5-9b.md)\n- [gpt-oss-120b vs Qwen3.6-27B](https://www.anchorterminal.com/compare/gpt-oss-120b-vs-qwen3-6-27b.md)\n- [gpt-oss-120b vs Qwen3.6-35B-A3B](https://www.anchorterminal.com/compare/gpt-oss-120b-vs-qwen3-6-35b-a3b.md)\n- [gpt-oss-120b vs Qwen3.8-27B](https://www.anchorterminal.com/compare/gpt-oss-120b-vs-qwen3-8-27b.md)\n- [gpt-oss-120b vs Qwen3.8-Flash-Next](https://www.anchorterminal.com/compare/gpt-oss-120b-vs-qwen3-8-flash-next.md)\n- [gpt-oss-120b vs Qwen3-Coder-30B-A3B-Instruct](https://www.anchorterminal.com/compare/gpt-oss-120b-vs-qwen3-coder-30b-a3b-instruct.md)\n- [gpt-oss-120b vs Qwen3-Coder-Next](https://www.anchorterminal.com/compare/gpt-oss-120b-vs-qwen3-coder-next.md)\n- [gpt-oss-120b vs Qwen3-Omni-30B-A3B-Instruct](https://www.anchorterminal.com/compare/gpt-oss-120b-vs-qwen3-omni-30b-a3b-instruct.md)\n- [gpt-oss-120b vs Qwen3-VL-2B-Instruct](https://www.anchorterminal.com/compare/gpt-oss-120b-vs-qwen3-vl-2b-instruct.md)\n- [gpt-oss-120b vs Qwen3-VL-30B-A3B-Instruct](https://www.anchorterminal.com/compare/gpt-oss-120b-vs-qwen3-vl-30b-a3b-instruct.md)\n- [gpt-oss-120b vs Qwen3-VL-32B-Instruct](https://www.anchorterminal.com/compare/gpt-oss-120b-vs-qwen3-vl-32b-instruct.md)\n- [gpt-oss-120b vs Qwen3-VL-4B-Instruct](https://www.anchorterminal.com/compare/gpt-oss-120b-vs-qwen3-vl-4b-instruct.md)\n- [gpt-oss-120b vs Qwen3-VL-8B-Instruct](https://www.anchorterminal.com/compare/gpt-oss-120b-vs-qwen3-vl-8b-instruct.md)\n- [gpt-oss-120b vs Qwopus3.8-27B-Flash-V2](https://www.anchorterminal.com/compare/gpt-oss-120b-vs-qwopus3-8-27b-flash-v2.md)\n- [gpt-oss-120b vs SmolLM3-3B](https://www.anchorterminal.com/compare/gpt-oss-120b-vs-smollm3-3b.md)\n- [gpt-oss-120b vs Spark-X2.6-4B](https://www.anchorterminal.com/compare/gpt-oss-120b-vs-spark-x2-6-4b.md)\n- [gpt-oss-120b vs Swift 1.5 Qwen3.8-27B](https://www.anchorterminal.com/compare/gpt-oss-120b-vs-swift-1-5-qwen3-8-27b.md)\n- [gpt-oss-120b vs Swift 1.5 Qwen3.8-Flash-Next](https://www.anchorterminal.com/compare/gpt-oss-120b-vs-swift-1-5-qwen3-8-flash-next.md)\n- [gpt-oss-120b vs ThinkingCap (Qwen3.8 27B)](https://www.anchorterminal.com/compare/gpt-oss-120b-vs-thinkingcap-qwen3-8-27b.md)\n- [gpt-oss-20b vs Nemotron 3 Ultra 550B A55B](https://www.anchorterminal.com/compare/gpt-oss-20b-vs-nemotron-3-ultra-550b-a55b.md)\n- [Granite 4.2 3B vs Nemotron 3 Ultra 550B A55B](https://www.anchorterminal.com/compare/granite-4-2-3b-vs-nemotron-3-ultra-550b-a55b.md)\n- [Hy3 vs Nemotron 3 Ultra 550B A55B](https://www.anchorterminal.com/compare/hy3-vs-nemotron-3-ultra-550b-a55b.md)\n- [Inkling-Small vs Nemotron 3 Ultra 550B A55B](https://www.anchorterminal.com/compare/inkling-small-vs-nemotron-3-ultra-550b-a55b.md)\n- [Inkling vs Nemotron 3 Ultra 550B A55B](https://www.anchorterminal.com/compare/inkling-vs-nemotron-3-ultra-550b-a55b.md)\n- [InternVL3.5-GPT-OSS-20B-A4B-Preview vs Nemotron 3 Ultra 550B A55B](https://www.anchorterminal.com/compare/internvl3-5-gpt-oss-20b-a4b-preview-vs-nemotron-3-ultra-550b-a55b.md)\n- [Kimi K3 vs Nemotron 3 Ultra 550B A55B](https://www.anchorterminal.com/compare/kimi-k3-vs-nemotron-3-ultra-550b-a55b.md)\n- [Kolibri-1 vs Nemotron 3 Ultra 550B A55B](https://www.anchorterminal.com/compare/kolibri-1-vs-nemotron-3-ultra-550b-a55b.md)\n- [Laguna M.1 vs Nemotron 3 Ultra 550B A55B](https://www.anchorterminal.com/compare/laguna-m-1-vs-nemotron-3-ultra-550b-a55b.md)\n- [Laguna S 2.1 vs Nemotron 3 Ultra 550B A55B](https://www.anchorterminal.com/compare/laguna-s-2-1-vs-nemotron-3-ultra-550b-a55b.md)\n- [Laguna XS 2.1 vs Nemotron 3 Ultra 550B A55B](https://www.anchorterminal.com/compare/laguna-xs-2-1-vs-nemotron-3-ultra-550b-a55b.md)\n- [LFM2.5-2.6B vs Nemotron 3 Ultra 550B A55B](https://www.anchorterminal.com/compare/lfm2-5-2-6b-vs-nemotron-3-ultra-550b-a55b.md)\n- [Ling-3.0-tiny vs Nemotron 3 Ultra 550B A55B](https://www.anchorterminal.com/compare/ling-3-0-tiny-vs-nemotron-3-ultra-550b-a55b.md)\n- [MiMo-V2.6 Distill Qwen 9B vs Nemotron 3 Ultra 550B A55B](https://www.anchorterminal.com/compare/mimo-v2-6-distill-qwen-9b-vs-nemotron-3-ultra-550b-a55b.md)\n- [MiniCPM-o 4.5 vs Nemotron 3 Ultra 550B A55B](https://www.anchorterminal.com/compare/minicpm-o-4-5-vs-nemotron-3-ultra-550b-a55b.md)\n- [MiniCPM5-2B vs Nemotron 3 Ultra 550B A55B](https://www.anchorterminal.com/compare/minicpm5-2b-vs-nemotron-3-ultra-550b-a55b.md)\n- [MiniMax-M2.5 vs Nemotron 3 Ultra 550B 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