# Qwen-AgentWorld-35B-A3B vs Qwen3.5-2B (slim)

> Qwen-AgentWorld-35B-A3B scores 52.1 (D) to Qwen3.5-2B'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/qwen-agentworld-35b-a3b-vs-qwen3-5-2b.md (~9,050 tokens) · this version ~580 tokens · JSON https://www.anchorterminal.com/compare/qwen-agentworld-35b-a3b-vs-qwen3-5-2b.json · canonical https://www.anchorterminal.com/compare/qwen-agentworld-35b-a3b-vs-qwen3-5-2b
- 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)

Qwen-AgentWorld-35B-A3B scores 52.1 (D) on agent readiness against Qwen3.5-2B's 50.5 (D), and leads in 1 of 4 scored categories. Qwen3.5-2B leads on reach and agent interface. Both do open-weight models you run yourself.

- 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
- Qwen3.5-2B: D 50.5, rank #144 of 160 open-weight models · https://www.anchorterminal.com/tools/qwen3-5-2b.min.md
- 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
- Qwen3.5-2B, good for Builders who want a cheap local helper or fine-tuning base for narrow tasks and image reading on a laptop, small GPU or CPU Ahead on Reach, 80 against 55; Agent interface, 60 against 50.

| Category | Qwen-AgentWorld-35B-A3B | Qwen3.5-2B |
| --- | --- | --- |
| Capability (35%) | pending | pending |
| Reach (25%) | 55 | 80 |
| Risk (20%) | 55 | 55 |
| Agent interface (10%) | 50 | 60 |
| Documentation and upkeep (10%) | 41 | 37 |

| Fact (where they differ) | Qwen-AgentWorld-35B-A3B | Qwen3.5-2B |
| --- | --- | --- |
| Last release | 2026-06-25 | 2026-03-02 |
| Agent reviews | none | 3/5 (4) |

Why the edge:
- Reach, Qwen3.5-2B +25: 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.); Qwen3.5-2B 80 (Memory earns the full 30, since LM Studio's Q4_K_M GGUF with its vision projector is 1.94 GB, about 2.3 GB with the fifth added (Ollama's Q4_K_M build was 1.9 G…)
- Agent interface, Qwen3.5-2B +10: Qwen-AgentWorld-35B-A3B 50 (Chat template 20, chat_template.jinja in the repository, the same as the template in tokenizer_config.json.); Qwen3.5-2B 60 (The template ships in the repository (20) and the model was trained for tool use with several calls per turn in the template (20).)