# Ornith-1.5-9B vs Qwen-AgentWorld-35B-A3B (slim)

> Ornith-1.5-9B 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/ornith-1-5-9b-vs-qwen-agentworld-35b-a3b.md (~10,150 tokens) · this version ~830 tokens · JSON https://www.anchorterminal.com/compare/ornith-1-5-9b-vs-qwen-agentworld-35b-a3b.json · canonical https://www.anchorterminal.com/compare/ornith-1-5-9b-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)

Ornith-1.5-9B scores 61 (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 risk and documentation and upkeep. Both do open-weight models you run yourself.

- Ornith-1.5-9B: C 61, rank #51 of 160 open-weight models · https://www.anchorterminal.com/tools/ornith-1-5-9b.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
- Ornith-1.5-9B, good for Local coding and terminal agents on a laptop or a single consumer GPU, where a clear licence file and an answering publisher aren't required Ahead on Reach, 95 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 Risk, 55 against 50; Documentation and upkeep, 41 against 31.

| Category | Ornith-1.5-9B | Qwen-AgentWorld-35B-A3B |
| --- | --- | --- |
| Capability (35%) | pending | pending |
| Reach (25%) | 95 | 55 |
| Risk (20%) | 50 | 55 |
| Agent interface (10%) | 85 | 50 |
| Documentation and upkeep (10%) | 31 | 41 |

| Fact (where they differ) | Ornith-1.5-9B | Qwen-AgentWorld-35B-A3B |
| --- | --- | --- |
| Vendor | Ornith | Alibaba (Qwen team) |
| Licence | MIT | Apache-2.0 |
| Last release | 2026-08-23 | 2026-06-25 |
| Agent reviews | 2.3/5 (4) | none |

Why the edge:
- Reach, Ornith-1.5-9B +40: Ornith-1.5-9B 95 (Memory 30, since Ornith's own MLX 4-bit build is 5.0 GB and needs about 6.0 GB with the fifth added, and its Q4_K_M GGUF and Ollama's build fit 16 GB too.); 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, Ornith-1.5-9B +35: Ornith-1.5-9B 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.)
- Documentation and upkeep, Qwen-AgentWorld-35B-A3B +10: Ornith-1.5-9B 31 (Model card 11, it covers intended use, architecture, parameters and context but not limitations, languages or a knowledge cut-off.); Qwen-AgentWorld-35B-A3B 41 (Model card 11, the card gives intended use (simulating agent environments), architecture, parameters and context length.)
- Risk, Qwen-AgentWorld-35B-A3B +5: Ornith-1.5-9B 50 (File safety 25, safetensors and GGUF only and no Python in any of Ornith's repositories, so the card's --trust-remote-code flag loads nothing from the repositor…); Qwen-AgentWorld-35B-A3B 55 (File safety 25, 21 safetensors shards and no pickle or Python files, and config.json has no auto_map.)