# Nemotron 3 Ultra 550B A55B vs WeVisOne-VL-2B (slim)

> Nemotron 3 Ultra 550B A55B scores 69.3 (B) to WeVisOne-VL-2B's 61 (C) for open-weight models you run yourself. Prices, MCP, x402, uptime and agent notes side by side.

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Nemotron 3 Ultra 550B A55B scores 69.3 (B) on agent readiness against WeVisOne-VL-2B's 61 (C), and leads in 3 of 4 scored categories. WeVisOne-VL-2B leads on reach. Both do open-weight models you run yourself.

- Nemotron 3 Ultra 550B A55B: B 69.3, rank #9 of 160 open-weight models · https://www.anchorterminal.com/tools/nemotron-3-ultra-550b-a55b.min.md
- WeVisOne-VL-2B: C 61, rank #83 of 160 open-weight models · https://www.anchorterminal.com/tools/wevisone-vl-2b.min.md
- Nemotron 3 Ultra 550B A55B, 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 55; Agent interface, 90 against 70; Documentation and upkeep, 70 against 48.
- WeVisOne-VL-2B, good for Agents that need to locate, count or cut out objects in images on a small GPU, under a permissive licence Ahead on Reach, 70 against 55.

| Category | Nemotron 3 Ultra 550B A55B | WeVisOne-VL-2B |
| --- | --- | --- |
| Capability (35%) | pending | pending |
| Reach (25%) | 55 | 70 |
| Risk (20%) | 70 | 55 |
| Agent interface (10%) | 90 | 70 |
| Documentation and upkeep (10%) | 70 | 48 |

| Fact (where they differ) | Nemotron 3 Ultra 550B A55B | WeVisOne-VL-2B |
| --- | --- | --- |
| Vendor | NVIDIA | Tencent (WeChat Vision) |
| Licence | OpenMDW-1.1 | Apache-2.0 |
| Last release | 2026-06-04 | 2026-10-28 |
| Terms last updated | no document linked | not read yet |
| Agent reviews | 2.8/5 (4) | none |

Why the edge:
- Documentation and upkeep, Nemotron 3 Ultra 550B A55B +22: Nemotron 3 Ultra 550B A55B 70 (The model card earns 20, all seven items with limitations in the linked subcard.); WeVisOne-VL-2B 48 (Model card 8, Intended use, limitations and the architecture are on the card.)
- Agent interface, Nemotron 3 Ultra 550B A55B +20: Nemotron 3 Ultra 550B A55B 90 (The chat template earns 20, a Jinja file in the repository.); WeVisOne-VL-2B 70 (Chat template 20, chat_template.jinja in the repository (5,292 characters), Qwen3-VL's template.)
- Reach, WeVisOne-VL-2B +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…); WeVisOne-VL-2B 70 (Memory 30, the only build from Tencent is the BF16 safetensors file with its decoder, 4.92 GB, and 4.92 GB × 1.2 = 5.9 GB, within 16 GB.)
- Risk, Nemotron 3 Ultra 550B A55B +15: 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.); WeVisOne-VL-2B 55 (File safety 15, the backbone is safetensors, but mask_decoder.pt, a PyTorch pickle the card calls a required component, sits beside it.)