# LongCat-2.5 vs Mistral Large 4 (slim)

> Mistral Large 4 scores 54.6 (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-mistral-large-4.md (~9,650 tokens) · this version ~730 tokens · JSON https://www.anchorterminal.com/compare/longcat-2-5-vs-mistral-large-4.json · canonical https://www.anchorterminal.com/compare/longcat-2-5-vs-mistral-large-4
- 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)

Mistral Large 4 scores 54.6 (C) on agent readiness against LongCat-2.5's 50.5 (D), and leads in every scored category. 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
- Mistral Large 4: C 54.6, rank #128 of 160 open-weight models · https://www.anchorterminal.com/tools/mistral-large-4.min.md
- LongCat-2.5, good for Operators with NPU clusters, and anyone tracking what the open flagships can do
- Mistral Large 4, good for Operators with an 8-GPU Blackwell or H200 node who want a frontier-sized open model for coding agents and defensive security, with a hosted twin on Mistral's API. Ahead on Reach, 50 against 35; Risk, 75 against 60; Agent interface, 95 against 75; Documentation and upkeep, 64 against 46.

| Category | LongCat-2.5 | Mistral Large 4 |
| --- | --- | --- |
| Capability (35%) | pending | pending |
| Reach (25%) | 35 | 50 |
| Risk (20%) | 60 | 75 |
| Agent interface (10%) | 75 | 95 |
| Documentation and upkeep (10%) | 46 | 64 |

| Fact (where they differ) | LongCat-2.5 | Mistral Large 4 |
| --- | --- | --- |
| Vendor | Meituan (LongCat) | Mistral AI |
| Licence | MIT | Mistral Ecosystem Open-Weight License (modified MIT) |
| Last release | 2026-11-10 | 2026-10-29 |
| Terms last updated | not read yet | no document linked |

Why the edge:
- Agent interface, Mistral Large 4 +20: LongCat-2.5 75 (Chat template 20, chat_template.jinja in the repository (11,823 characters), with a copy in tokenizer_config.json.); Mistral Large 4 95 (The chat template is in the repository (20).)
- Documentation and upkeep, Mistral Large 4 +18: LongCat-2.5 46 (Model card 11, Intended use, limitations (the usage considerations), the architecture and the parameter counts are on the card.); Mistral Large 4 64 (The card covers intended use, architecture, parameters, context and languages, and misses limitations and a cut-off (14).)
- Reach, Mistral Large 4 +15: 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.); Mistral Large 4 50 (Memory scores 0, since the smallest 4-bit build, Mistral's NVFP4, is 610 GB, about 732 GB with a fifth added, far above 256 GB.)
- Risk, Mistral Large 4 +15: LongCat-2.5 60 (File safety 25, safetensors only, no .bin, .pt or .pth files and no Python in the repository.); Mistral Large 4 75 (File safety scores 25, safetensors only and loaded by Transformers' own code with a Jinja template.)