# Laguna M.1 vs Qwen-AgentWorld-35B-A3B (slim)

> Laguna M.1 scores 56.7 (C) to Qwen-AgentWorld-35B-A3B's 52.1 (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-qwen-agentworld-35b-a3b.md (~9,550 tokens) · this version ~780 tokens · JSON https://www.anchorterminal.com/compare/laguna-m-1-vs-qwen-agentworld-35b-a3b.json · canonical https://www.anchorterminal.com/compare/laguna-m-1-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
- 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 Qwen-AgentWorld-35B-A3B's 52.1 (D), and leads in 2 of 4 scored categories. Qwen-AgentWorld-35B-A3B leads on 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
- 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
- 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 55; Agent interface, 85 against 50.
- 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 Documentation and upkeep, 41 against 36.

| Category | Laguna M.1 | Qwen-AgentWorld-35B-A3B |
| --- | --- | --- |
| Capability (35%) | pending | pending |
| Reach (25%) | 70 | 55 |
| Risk (20%) | 55 | 55 |
| Agent interface (10%) | 85 | 50 |
| Documentation and upkeep (10%) | 36 | 41 |

| Fact (where they differ) | Laguna M.1 | Qwen-AgentWorld-35B-A3B |
| --- | --- | --- |
| Vendor | Poolside | Alibaba (Qwen team) |
| Last release | 2026-07-14 | 2026-06-25 |
| Terms last updated | 2026-07-21 | no document linked |
| 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:
- Agent interface, Laguna M.1 +35: Laguna M.1 85 (Chat template 20, a Jinja file in the repository.); Qwen-AgentWorld-35B-A3B 50 (Chat template 20, chat_template.jinja in the repository, the same as the template in tokenizer_config.json.)
- Reach, Laguna M.1 +15: 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.); 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.)
- Documentation and upkeep, Qwen-AgentWorld-35B-A3B +5: 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.); Qwen-AgentWorld-35B-A3B 41 (Model card 11, the card gives intended use (simulating agent environments), architecture, parameters and context length.)