# Hy-Memory-30B-A3B vs Qwen-AgentWorld-35B-A3B (slim)

> Hy-Memory-30B-A3B 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/hy-memory-30b-a3b-vs-qwen-agentworld-35b-a3b.md (~10,350 tokens) · this version ~730 tokens · JSON https://www.anchorterminal.com/compare/hy-memory-30b-a3b-vs-qwen-agentworld-35b-a3b.json · canonical https://www.anchorterminal.com/compare/hy-memory-30b-a3b-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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Hy-Memory-30B-A3B scores 61 (C) on agent readiness against Qwen-AgentWorld-35B-A3B's 52.1 (D), and leads in every scored category. Both do open-weight models you run yourself.

- Hy-Memory-30B-A3B: C 61, rank #68 of 160 open-weight models · https://www.anchorterminal.com/tools/hy-memory-30b-a3b.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
- Hy-Memory-30B-A3B, good for Agents with an external memory framework that want a local model for the write path on a 24 GB card Ahead on Reach, 85 against 55; Risk, 60 against 55; Agent interface, 65 against 50; Documentation and upkeep, 68 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

| Category | Hy-Memory-30B-A3B | Qwen-AgentWorld-35B-A3B |
| --- | --- | --- |
| Capability (35%) | pending | pending |
| Reach (25%) | 85 | 55 |
| Risk (20%) | 60 | 55 |
| Agent interface (10%) | 65 | 50 |
| Documentation and upkeep (10%) | 68 | 41 |

| Fact (where they differ) | Hy-Memory-30B-A3B | Qwen-AgentWorld-35B-A3B |
| --- | --- | --- |
| Vendor | Tencent (Hy team) | Alibaba (Qwen team) |
| Last release | 2026-10-16 | 2026-06-25 |

Why the edge:
- Reach, Hy-Memory-30B-A3B +30: Hy-Memory-30B-A3B 85 (Memory 25, Tencent's own Q4_K_M GGUF is 18.24 GB, and 18.24 GB × 1.2 = 21.9 GB, which fits 24 GB but not 16 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.)
- Documentation and upkeep, Hy-Memory-30B-A3B +27: Hy-Memory-30B-A3B 68 (Model card 8, Intended use (the write path of Mem0, MemOS and Hy-Memory), parameters (30B, about 3B active) and languages (English and Chinese, in the metadata)…); Qwen-AgentWorld-35B-A3B 41 (Model card 11, the card gives intended use (simulating agent environments), architecture, parameters and context length.)
- Agent interface, Hy-Memory-30B-A3B +15: Hy-Memory-30B-A3B 65 (Chat template 20, chat_template.jinja 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.)
- Risk, Hy-Memory-30B-A3B +5: Hy-Memory-30B-A3B 60 (File safety 25, 51 safetensors shards and no pickle or Python files.); Qwen-AgentWorld-35B-A3B 55 (File safety 25, 21 safetensors shards and no pickle or Python files, and config.json has no auto_map.)