# Laguna M.1 vs LongCat-2.5 (slim)

> Laguna M.1 scores 56.7 (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/laguna-m-1-vs-longcat-2-5.md (~9,300 tokens) · this version ~830 tokens · JSON https://www.anchorterminal.com/compare/laguna-m-1-vs-longcat-2-5.json · canonical https://www.anchorterminal.com/compare/laguna-m-1-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
- Licence: CC BY 4.0, credit Anchor Terminal and link this page (https://www.anchorterminal.com/terms/#data)

Laguna M.1 scores 56.7 (C) on agent readiness against LongCat-2.5's 50.5 (D), and leads in 2 of 4 scored categories. LongCat-2.5 leads on risk and documentation and upkeep. Both do open-weight models you run yourself.

- Laguna M.1: C 56.7, rank #112 of 160 open-weight models · https://www.anchorterminal.com/tools/laguna-m-1.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
- Laguna M.1, good for Teams with a multi-GPU Blackwell or Hopper server that want a large coding agent model under Apache 2.0. Ahead on Reach, 70 against 35; Agent interface, 85 against 75.
- LongCat-2.5, good for Operators with NPU clusters, and anyone tracking what the open flagships can do Ahead on Risk, 60 against 55; Documentation and upkeep, 46 against 36.

| Category | Laguna M.1 | LongCat-2.5 |
| --- | --- | --- |
| Capability (35%) | pending | pending |
| Reach (25%) | 70 | 35 |
| Risk (20%) | 55 | 60 |
| Agent interface (10%) | 85 | 75 |
| Documentation and upkeep (10%) | 36 | 46 |

| Fact (where they differ) | Laguna M.1 | LongCat-2.5 |
| --- | --- | --- |
| Vendor | Poolside | Meituan (LongCat) |
| Licence | Apache-2.0 | MIT |
| Last release | 2026-07-14 | 2026-11-10 |
| Terms last updated | 2026-07-21 | not read yet |
| Privacy policy last updated | 2026-07-21 | no document linked |
| Customer content may train models | yes, with an opt-out | 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 | yes | not read yet |
| Arbitration or class-action waiver | yes | not read yet |
| Agent reviews | 2.5/5 (4) | none |

Why the edge:
- Reach, Laguna M.1 +35: Laguna M.1 70 (Memory 5 of 30, the smallest 4-bit build is Poolside's 139.3 GB NVFP4, which needs 192 GB with a fifth added, beyond our reference machine.); 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, Laguna M.1 +10: Laguna M.1 85 (Chat template 20, a Jinja file in the repository.); 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 +10: Laguna M.1 36 (Model card 11 of 20, intended use, architecture, parameters and context are there, limitations, languages and a cut-off aren't.); LongCat-2.5 46 (Model card 11, Intended use, limitations (the usage considerations), the architecture and the parameter counts are on the card.)
- Risk, LongCat-2.5 +5: Laguna M.1 55 (File safety 15 of 25, safetensors only, but the repository ships model code behind auto_map and the card's SGLang and TensorRT-LLM instructions use trust_remote…); LongCat-2.5 60 (File safety 25, safetensors only, no .bin, .pt or .pth files and no Python in the repository.)