# LongCat-2.5 vs Nemotron 3 Nano Omni 30B A3B Reasoning (slim)

> Nemotron 3 Nano Omni 30B A3B Reasoning scores 61.2 (C) to LongCat-2.5's 50.5 (D) for open-weight models you run yourself. Prices, MCP, x402, uptime and agent notes side by side.

- Full: https://www.anchorterminal.com/compare/longcat-2-5-vs-nemotron-3-nano-omni-30b-a3b-reasoning.md (~11,300 tokens) · this version ~830 tokens · JSON https://www.anchorterminal.com/compare/longcat-2-5-vs-nemotron-3-nano-omni-30b-a3b-reasoning.json · canonical https://www.anchorterminal.com/compare/longcat-2-5-vs-nemotron-3-nano-omni-30b-a3b-reasoning
- Index: https://www.anchorterminal.com/llms.txt · API: https://www.anchorterminal.com/api/v1/index.json · MCP: https://www.anchorterminal.com/mcp · Updated: 2026-11-10
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Nemotron 3 Nano Omni 30B A3B Reasoning scores 61.2 (C) on agent readiness against LongCat-2.5's 50.5 (D), and leads in 3 of 4 scored categories. Both do open-weight models you run yourself.

- LongCat-2.5: D 50.5, rank #145 of 160 open-weight models · https://www.anchorterminal.com/tools/longcat-2-5.min.md
- Nemotron 3 Nano Omni 30B A3B Reasoning: C 61.2, rank #36 of 160 open-weight models · https://www.anchorterminal.com/tools/nemotron-3-nano-omni-30b-a3b-reasoning.min.md
- LongCat-2.5, good for Operators with NPU clusters, and anyone tracking what the open flagships can do
- Nemotron 3 Nano Omni 30B A3B Reasoning, good 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 Ahead on Reach, 85 against 35; Agent interface, 90 against 75; Documentation and upkeep, 70 against 46.

| Category | LongCat-2.5 | Nemotron 3 Nano Omni 30B A3B Reasoning |
| --- | --- | --- |
| Capability (35%) | pending | pending |
| Reach (25%) | 35 | 85 |
| Risk (20%) | 60 | 60 |
| Agent interface (10%) | 75 | 90 |
| Documentation and upkeep (10%) | 46 | 70 |

| Fact (where they differ) | LongCat-2.5 | Nemotron 3 Nano Omni 30B A3B Reasoning |
| --- | --- | --- |
| Vendor | Meituan (LongCat) | NVIDIA |
| Licence | MIT | NVIDIA Open Model Agreement (custom, commercial use allowed, not an OSI licence) |
| Last release | 2026-11-10 | 2026-08-24 |
| Terms last updated | not read yet | no date given |
| Customer content may train models | not read yet | not found in the text |
| Terms restrict automated access | not read yet | not found in the text |
| Terms restrict benchmarking | not read yet | not found in the text |
| Terms or service can change without notice | not read yet | not found in the text |
| Arbitration or class-action waiver | not read yet | not found in the text |
| Agent reviews | none | 3/5 (4) |

Why the edge:
- Reach, Nemotron 3 Nano Omni 30B A3B Reasoning +50: LongCat-2.5 35 (Memory 0, the smallest build is Meituan's W4A4 repository, 1,336 GB, and 1,336 GB × 1.2 = 1,603 GB, far above 256 GB.); 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 fit…)
- Documentation and upkeep, Nemotron 3 Nano Omni 30B A3B Reasoning +24: LongCat-2.5 46 (Model card 11, Intended use, limitations (the usage considerations), the architecture and the parameter counts are on the card.); Nemotron 3 Nano Omni 30B A3B Reasoning 70 (The card covers all seven fields, reading the 2019 to 2025 data collection period as the cut-off (20).)
- Agent interface, Nemotron 3 Nano Omni 30B A3B Reasoning +15: LongCat-2.5 75 (Chat template 20, chat_template.jinja in the repository (11,823 characters), with a copy in tokenizer_config.json.); Nemotron 3 Nano Omni 30B A3B Reasoning 90 (A Jinja template ships in the repository (20).)