# LongCat-2.5 vs Qwen-AgentWorld-35B-A3B (slim)

> Qwen-AgentWorld-35B-A3B scores 52.1 (D) 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-qwen-agentworld-35b-a3b.md (~10,100 tokens) · this version ~780 tokens · JSON https://www.anchorterminal.com/compare/longcat-2-5-vs-qwen-agentworld-35b-a3b.json · canonical https://www.anchorterminal.com/compare/longcat-2-5-vs-qwen-agentworld-35b-a3b
- 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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Qwen-AgentWorld-35B-A3B scores 52.1 (D) 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, agent interface and documentation and upkeep. 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
- Qwen-AgentWorld-35B-A3B: D 52.1, rank #141 of 160 open-weight models · https://www.anchorterminal.com/tools/qwen-agentworld-35b-a3b.min.md
- 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 50; Documentation and upkeep, 46 against 41.
- Qwen-AgentWorld-35B-A3B, good for Agent builders who want to train or test an agent against simulated tools, terminals, browsers and phones on a 128 GB machine Ahead on Reach, 55 against 35.

| Category | LongCat-2.5 | Qwen-AgentWorld-35B-A3B |
| --- | --- | --- |
| Capability (35%) | pending | pending |
| Reach (25%) | 35 | 55 |
| Risk (20%) | 60 | 55 |
| Agent interface (10%) | 75 | 50 |
| Documentation and upkeep (10%) | 46 | 41 |

| Fact (where they differ) | LongCat-2.5 | Qwen-AgentWorld-35B-A3B |
| --- | --- | --- |
| Vendor | Meituan (LongCat) | Alibaba (Qwen team) |
| Licence | MIT | Apache-2.0 |
| Last release | 2026-11-10 | 2026-06-25 |
| Terms last updated | not read yet | no document linked |

Why the edge:
- Agent interface, LongCat-2.5 +25: LongCat-2.5 75 (Chat template 20, chat_template.jinja in the repository (11,823 characters), with a copy in tokenizer_config.json.); Qwen-AgentWorld-35B-A3B 50 (Chat template 20, chat_template.jinja in the repository, the same as the template in tokenizer_config.json.)
- Reach, Qwen-AgentWorld-35B-A3B +20: 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.); Qwen-AgentWorld-35B-A3B 55 (Memory 10, Alibaba's only build is the BF16 safetensors, 69.32 GB, and 69.32 GB × 1.2 = 83.2 GB, above 64 GB and inside the reference machine's GPU share.)
- Risk, LongCat-2.5 +5: LongCat-2.5 60 (File safety 25, safetensors only, no .bin, .pt or .pth files and no Python in the repository.); Qwen-AgentWorld-35B-A3B 55 (File safety 25, 21 safetensors shards and no pickle or Python files, and config.json has no auto_map.)
- Documentation and upkeep, LongCat-2.5 +5: LongCat-2.5 46 (Model card 11, Intended use, limitations (the usage considerations), the architecture and the parameter counts are on the card.); Qwen-AgentWorld-35B-A3B 41 (Model card 11, the card gives intended use (simulating agent environments), architecture, parameters and context length.)