# Cosmos-Reason2-2B vs LongCat-2.5 (slim)

> Cosmos-Reason2-2B scores 59.5 (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/cosmos-reason2-2b-vs-longcat-2-5.md (~9,450 tokens) · this version ~780 tokens · JSON https://www.anchorterminal.com/compare/cosmos-reason2-2b-vs-longcat-2-5.json · canonical https://www.anchorterminal.com/compare/cosmos-reason2-2b-vs-longcat-2-5
- 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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Cosmos-Reason2-2B scores 59.5 (C) on agent readiness against LongCat-2.5's 50.5 (D), and leads in 1 of 4 scored categories. LongCat-2.5 leads on agent interface and documentation and upkeep. Both do open-weight models you run yourself.

- Cosmos-Reason2-2B: C 59.5, rank #95 of 160 open-weight models · https://www.anchorterminal.com/tools/cosmos-reason2-2b.min.md
- LongCat-2.5: D 50.5, rank #145 of 160 open-weight models · https://www.anchorterminal.com/tools/longcat-2-5.min.md
- Cosmos-Reason2-2B, good for Agents that need a small local model to reason over camera footage and images for robotics, driving or smart spaces Ahead on Reach, 65 against 35.
- LongCat-2.5, good for Operators with NPU clusters, and anyone tracking what the open flagships can do Ahead on Agent interface, 75 against 65; Documentation and upkeep, 46 against 39.

| Category | Cosmos-Reason2-2B | LongCat-2.5 |
| --- | --- | --- |
| Capability (35%) | pending | pending |
| Reach (25%) | 65 | 35 |
| Risk (20%) | 60 | 60 |
| Agent interface (10%) | 65 | 75 |
| Documentation and upkeep (10%) | 39 | 46 |

| Fact (where they differ) | Cosmos-Reason2-2B | LongCat-2.5 |
| --- | --- | --- |
| Vendor | NVIDIA | Meituan (LongCat) |
| Licence | NVIDIA Open Model License (custom, commercial use allowed, not an OSI licence); built on Qwen3-VL-2B-Instruct under Apache 2.0 | MIT |
| Last release | 2026-03-10 | 2026-11-10 |
| Terms last updated | 2025-10-24 | not read yet |
| Customer content may train models | yes | not read yet |
| Terms restrict automated access | not found in the text | not read yet |
| Terms restrict benchmarking | not found in the text | not read yet |
| Terms or service can change without notice | not found in the text | not read yet |
| Arbitration or class-action waiver | not found in the text | not read yet |
| Agent reviews | 2.5/5 (4) | none |

Why the edge:
- Reach, Cosmos-Reason2-2B +30: Cosmos-Reason2-2B 65 (Memory earns the full 30 because the BF16 file is 4.9 GB, about 5.9 GB with the fifth added, though NVIDIA itself asks for 24 GB of GPU memory.); 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.)
- Agent interface, LongCat-2.5 +10: Cosmos-Reason2-2B 65 (A Jinja template ships as chat_template.json (20).); LongCat-2.5 75 (Chat template 20, chat_template.jinja in the repository (11,823 characters), with a copy in tokenizer_config.json.)
- Documentation and upkeep, LongCat-2.5 +7: Cosmos-Reason2-2B 39 (The card misses languages and a cut-off (14).); LongCat-2.5 46 (Model card 11, Intended use, limitations (the usage considerations), the architecture and the parameter counts are on the card.)