# Agents-A1-4B vs Qwen-AgentWorld-35B-A3B (slim)

> Agents-A1-4B scores 61 (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/agents-a1-4b-vs-qwen-agentworld-35b-a3b.md (~9,150 tokens) · this version ~580 tokens · JSON https://www.anchorterminal.com/compare/agents-a1-4b-vs-qwen-agentworld-35b-a3b.json · canonical https://www.anchorterminal.com/compare/agents-a1-4b-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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Agents-A1-4B scores 61 (C) on agent readiness against Qwen-AgentWorld-35B-A3B's 52.1 (D), and leads in 3 of 4 scored categories. 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
- 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
- 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 55; Agent interface, 70 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

| Category | Agents-A1-4B | Qwen-AgentWorld-35B-A3B |
| --- | --- | --- |
| Capability (35%) | pending | pending |
| Reach (25%) | 90 | 55 |
| Risk (20%) | 55 | 55 |
| Agent interface (10%) | 70 | 50 |
| Documentation and upkeep (10%) | 43 | 41 |

| Fact (where they differ) | Agents-A1-4B | Qwen-AgentWorld-35B-A3B |
| --- | --- | --- |
| Vendor | InternScience (Shanghai AI Laboratory) | Alibaba (Qwen team) |
| Last release | 2026-07-14 | 2026-06-25 |
| Agent reviews | 3/5 (4) | none |

Why the edge:
- Reach, Agents-A1-4B +35: 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.); 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.)
- Agent interface, Agents-A1-4B +20: Agents-A1-4B 70 (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.)