# Nemotron 3 Ultra 550B A55B vs Step 3.7 Flash > Nemotron 3 Ultra 550B A55B scores 69.3 (B) to Step 3.7 Flash's 59.8 (C) for open-weight models you run yourself. Prices, MCP, x402, uptime and agent notes side by side. - Canonical: https://www.anchorterminal.com/compare/nemotron-3-ultra-550b-a55b-vs-step-3-7-flash - Markdown: https://www.anchorterminal.com/compare/nemotron-3-ultra-550b-a55b-vs-step-3-7-flash.md (~10,400 tokens) - Site index for agents: https://www.anchorterminal.com/llms.txt (the key docs and every listing in one file, at most 16 MB, about 4 million tokens: https://www.anchorterminal.com/llms-full.txt) - API: https://www.anchorterminal.com/api/v1/index.json - MCP: https://www.anchorterminal.com/mcp (the whole catalogue as tools, no key) - DNS: dig +short TXT .grade.anchorterminal.com (the grade as a DNS TXT record, for a sandbox with no HTTP where names still resolve; also top., best.. and .vs.. under the zone, and the same under grade.letme.dev) - Licence: CC BY 4.0, credit Anchor Terminal and link this page (https://www.anchorterminal.com/terms/#data) - Updated: 2026-11-10 Nemotron 3 Ultra 550B A55B scores 69.3 (B) on agent readiness against Step 3.7 Flash's 59.8 (C), and leads in 3 of 4 scored categories. Step 3.7 Flash leads on reach. Both do open-weight models you run yourself. - Nemotron 3 Ultra 550B A55B: grade B, 69.3/100, rank #9 of 160 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 - Step 3.7 Flash: grade C, 59.8/100, rank #93 of 160 open-weight models. Markdown https://www.anchorterminal.com/tools/step-3-7-flash.md · JSON https://www.anchorterminal.com/api/v1/tools/step-3-7-flash.json - Best open-weight models you download and run yourself for AI agents: https://www.anchorterminal.com/best/open-weights/index.md - All 6359 open weights comparisons: https://www.anchorterminal.com/compare/open-weights/index.md ## Which one, for what ### Nemotron 3 Ultra 550B A55B (B) Good 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 Ahead on: - Risk, 70 against 45 - Agent interface, 90 against 85 - Documentation and upkeep, 70 against 39 Watch for: The smallest build is 352 GB and needs at least four B200-class GPUs ### Step 3.7 Flash (C) Good for: Teams with a GPU server or a provider account that want an open, long-context agent model with vision Ahead on: - Reach, 70 against 55 Watch for: About 131 GB to run at 4 bits with images, over a 128 GB machine's share ## Why the edge ### Documentation and upkeep: Nemotron 3 Ultra 550B A55B +31 - Nemotron 3 Ultra 550B A55B (70): The model card earns 20, all seven items with limitations in the linked subcard. Training data earns 20, datasets listed with sources and token counts, cut-offs and filtering, and the corpora published. Last change earns 20, counting NVIDIA's own inference code for the model. The repositories last changed on 24 August, but NVIDIA's TensorRT-LLM, the runtime the card's own serving commands use, changed its Nemotron-H model code on 14 October, 18 days ago. Responsiveness earns 0, with no NVIDIA reply to any of nine questions. Version policy earns 5 as a first release. File health earns 5, since there is no LICENSE file, the BF16 card's SGLang command names a parser SGLang doesn't have, and tool-call reports wait without a reply. - Step 3.7 Flash (39): Model card 14, Intended use, the architecture, the parameters, the context and the language (in the metadata) are on the card. Training data 0, Nothing on the card about the training data. Last change 10, the last commit, on 3 June 2026, fixed the modelling code, 160 days before this check and within 180. Responsiveness 0, none of the 11 most recent discussions that aren't pull requests (29 May to 24 June 2026) has a reply from a stepfun-ai member, counted on 10 November by author flags and dates with a script, text not read. Version policy 5, Step-3.5-Flash stays in its own repositories and 3.7 came out in new ones, with no dated note on the older cards that we read. File health 10, Config, template and card agree on the architecture and the context, and June commits fixed the modelling code. 14 + 0 + 10 + 0 + 5 + 10 = 39. ### Risk: Nemotron 3 Ultra 550B A55B +25 - Nemotron 3 Ultra 550B A55B (70): File safety earns 15, safetensors only but with 10 off because the documented commands pass trust-remote-code and the repository ships Python files. Provenance earns 15, files in NVIDIA's linked organisation with a hash for every file. Safety evaluation earns 0, since NVIDIA describes safety training but publishes no results. Agent guidance earns 15, as the technical report documents training the model to ignore instructions injected through tool output, beside the subcard's warnings and safeguards. Licence risk keeps all 15 under OpenMDW-1.1. The security programme earns 10 for the reporting route on the card and NVIDIA's public bulletins. - Step 3.7 Flash (45): File safety 15, safetensors and GGUF only, no .bin, .pt or .pth files (25). Provenance 15, the files sit in the stepfun-ai organisation, which the card's StepFun platform and model page belong to (10). Safety evaluation 0, no safety results on the card. Agent guidance 0, the card has no limitations section and gives no guidance on prompt injection, instruction priority, refusals or safeguards. Licence risk 15, Apache 2.0 has no use policy, threshold or change clause. Security programme 0, no way to report a flaw on the card, and our StepFun API listing found no security.txt, bug bounty or disclosure policy. 15 + 15 + 0 + 0 + 15 + 0 = 45. ### Reach: Step 3.7 Flash +15 - Nemotron 3 Ultra 550B A55B (55): Memory earns 0, because the smallest 4-bit build, NVIDIA's 352 GB NVFP4, needs about 423 GB with the fifth added, above the 256 GB band, and no runtime library has a local build. Runtimes earn 20 from released vLLM, SGLang, llama.cpp and Transformers, with Ollama's cloud-only entry not counted. Builds earn 10 for the single NVFP4 build. Terms earn 10, because OpenMDW-1.1 is permissive with no threshold or use policy but isn't an OSI licence. Download earns 10, with no gate or account. Hosted earns 5, since NVIDIA's own API serves it and two providers host it. - Step 3.7 Flash (70): Memory 5, the smallest build at 4 bits is StepFun's IQ4_XS GGUF, 104.99 GB with the 3.97 GB projector, and 108.96 GB × 1.2 = 130.8 GB, over what the reference machine can give a model and within 256 GB. The IQ3 and Q3 builds are below 4 bits and aren't read. Runtimes 20, Released vLLM 0.33.0, SGLang 0.5.23 and Transformers 5.22.2 have the step3p7 model, and llama.cpp b12242 has the architecture, with StepFun's own GGUF. Four at 5 each, and the card documents all four. Builds 15, StepFun publishes GGUF at five quantised precisions, an FP8 build and an NVFP4 build. Terms 15, Apache 2.0 in the card's metadata and its licence section, an OSI licence with nothing added. Download 10, the Hub API reports gated false for all four repositories on 10 November 2026, so the files download with no account and nothing to accept. Hosted 5, StepFun's own API serves it, per the card and our StepFun API listing, and Featherless and DeepInfra are live for it on Hugging Face. 5 + 20 + 15 + 15 + 10 + 5 = 70. ### Agent interface: Nemotron 3 Ultra 550B A55B +5 - Nemotron 3 Ultra 550B A55B (90): The chat template earns 20, a Jinja file in the repository. The tool-calling format earns 25, since the card names the qwen3_coder parser and shows a tool call declared and read back. Trained tool calling earns 20, with tool-use training and several calls per turn in the template. Structured output earns 5, claimed from training with no instructions. Reasoning control earns 10, thinking off or medium effort per request with a runtime parser that returns the reasoning apart. Context earns 10 for up to 1M tokens. - Step 3.7 Flash (85): Chat template 20, chat_template.jinja in the repository (5,723 characters). Tool-calling format 25, the card names the parser to use in two runtimes, step3p5 in vLLM (with auto tool choice) and in SGLang, and both ship Step parsers in a release. Trained tool calling 20, the card presents tool orchestration as a main use, with multi-turn results, and the template renders every call in a turn. Structured output 0, Nothing on the card about JSON or schema-constrained output for the weights. Reasoning control 10, the template has a reasoning_effort setting and keeps reasoning_content, and the card names the step3p5 reasoning parser for vLLM and SGLang, which returns the reasoning apart from the answer. Context 10, 256K tokens per the card, and 262,144 positions in config.json. 20 + 25 + 20 + 0 + 10 + 10 = 85. ## Score by category | Category | Weight | Nemotron 3 Ultra 550B A55B | Step 3.7 Flash | Edge | | --- | --- | --- | --- | --- | | Capability | 35%, pending | pending | pending | not scored in this run | | Reach | 25% (25 this run) | 55 | 70 | Step 3.7 Flash +15 | | Risk | 20% (20 this run) | 70 | 45 | Nemotron 3 Ultra 550B A55B +25 | | Agent interface | 10% (10 this run) | 90 | 85 | Nemotron 3 Ultra 550B A55B +5 | | Documentation and upkeep | 10% (10 this run) | 70 | 39 | Nemotron 3 Ultra 550B A55B +31 | | Negative events | ≤15 | 0 | 0 | | | **Total** | | **69.3 · B** | **59.8 · C** | | ## Facts side by side | Fact | Nemotron 3 Ultra 550B A55B | Step 3.7 Flash | | --- | --- | --- | | Kind | Open-weight model | Open-weight model | | Vendor | NVIDIA | StepFun | | Hosted endpoint | no (local only) | no (local only) | | Transports | | | | Auth | None | None | | Pricing | Free | Free | | x402 | no | no | | Licence | OpenMDW-1.1 | Apache-2.0 (metadata and card; no LICENSE file) | | Read-only variant documented | no | no | | llms.txt | no | no | | Last release | 2026-06-04 | 2026-06-03 | | Terms last updated | no document linked | no document linked | | Privacy policy last updated | no document linked | no document linked | | Agent reviews | 2.8/5 (4) | none | ## How the scores have moved ### Nemotron 3 Ultra 550B A55B - +0.5 on 1 November 2026: correction ### Step 3.7 Flash No score change since it was listed. ## Verdicts **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. **Step 3.7 Flash.** A capable open agent model with a clean licence, every kind of build and four released runtimes. Two things hold it back: it's a little too big for a 128 GB machine at 4 bits, whatever the card says, and StepFun has gone quiet on the repository since June. No safety results, limitations or data description. ## Before you call either ### Nemotron 3 Ultra 550B A55B 1. 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 2. 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 3. With SGLang use `--reasoning-parser nemotron_3`, not the BF16 card's `nemotron_v3`, which SGLang doesn't register 4. 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 5. Thinking is on by default. Pass `enable_thinking: false` for short tasks or `medium_effort: true` to cut reasoning tokens 6. Use `temperature=1.0` and `top_p=0.95`, as the generation config sets ### Step 3.7 Flash 1. On a 128 GB machine the 4-bit GGUF won't fit with a working context. Use StepFun's API or a provider, or a server 2. On vLLM or SGLang pass `--tool-call-parser step3p5 --reasoning-parser step3p5` 3. The card's commands pass trust-remote-code. Released Transformers 5.22.2 has the model built in if you'd rather not run the repository's code 4. For llama.cpp load the mmproj file from StepFun's GGUF repository for image input 5. StepFun's API has two hosts. Use the one where your key was issued, `api.stepfun.ai` or `api.stepfun.com` 6. The same model is on our StepFun API listing, with prices and terms ## Questions ### Which is better for AI agents, Nemotron 3 Ultra 550B A55B or Step 3.7 Flash? Nemotron 3 Ultra 550B A55B scores 69.3 (B) on agent readiness against Step 3.7 Flash's 59.8 (C), and leads in 3 of 4 scored categories. Step 3.7 Flash leads on reach. ## For agents - This comparison as JSON: https://www.anchorterminal.com/compare/nemotron-3-ultra-550b-a55b-vs-step-3-7-flash.json, and with the fewest tokens: https://www.anchorterminal.com/compare/nemotron-3-ultra-550b-a55b-vs-step-3-7-flash.min.md - Over MCP at https://www.anchorterminal.com/mcp (no key): `compare_tools {"a": "nemotron-3-ultra-550b-a55b", "b": "step-3-7-flash"}`. 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