# Agents-A1-4B vs LongCat-2.5 (slim)

> Agents-A1-4B scores 61 (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/agents-a1-4b-vs-longcat-2-5.md (~8,850 tokens) · this version ~630 tokens · JSON https://www.anchorterminal.com/compare/agents-a1-4b-vs-longcat-2-5.json · canonical https://www.anchorterminal.com/compare/agents-a1-4b-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)

Agents-A1-4B scores 61 (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 risk and agent interface. Both do open-weight models you run yourself.

- Agents-A1-4B: C 61, rank #39 of 160 open-weight models · https://www.anchorterminal.com/tools/agents-a1-4b.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
- Agents-A1-4B, good for Local agent loops (search, research, tool calls) on a laptop, a small GPU or a phone-class machine, under a plain licence Ahead on Reach, 90 against 35.
- LongCat-2.5, good for Operators with NPU clusters, and anyone tracking what the open flagships can do Ahead on Risk, 60 against 55; Agent interface, 75 against 70.

| Category | Agents-A1-4B | LongCat-2.5 |
| --- | --- | --- |
| Capability (35%) | pending | pending |
| Reach (25%) | 90 | 35 |
| Risk (20%) | 55 | 60 |
| Agent interface (10%) | 70 | 75 |
| Documentation and upkeep (10%) | 43 | 46 |

| Fact (where they differ) | Agents-A1-4B | LongCat-2.5 |
| --- | --- | --- |
| Vendor | InternScience (Shanghai AI Laboratory) | Meituan (LongCat) |
| Licence | Apache-2.0 | MIT |
| Last release | 2026-07-14 | 2026-11-10 |
| Terms last updated | no document linked | not read yet |
| Agent reviews | 3/5 (4) | none |

Why the edge:
- Reach, Agents-A1-4B +55: Agents-A1-4B 90 (Memory 30, InternScience's Q4_K_M GGUF with its vision projector is 3.4 GB and needs about 4.1 GB with the fifth added.); 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.)
- Risk, LongCat-2.5 +5: Agents-A1-4B 55 (File safety 25, safetensors and GGUF only and nothing from the repository runs.); LongCat-2.5 60 (File safety 25, safetensors only, no .bin, .pt or .pth files and no Python in the repository.)
- Agent interface, LongCat-2.5 +5: Agents-A1-4B 70 (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.)