# Ornith-1.5-122B vs Qwen3.5-397B-A17B (slim)

> Qwen3.5-397B-A17B scores 64.1 (B) to Ornith-1.5-122B's 61 (C) for open-weight models you run yourself. Prices, MCP, x402, uptime and agent notes side by side.

- Full: https://www.anchorterminal.com/compare/ornith-1-5-122b-vs-qwen3-5-397b-a17b.md (~9,450 tokens) · this version ~730 tokens · JSON https://www.anchorterminal.com/compare/ornith-1-5-122b-vs-qwen3-5-397b-a17b.json · canonical https://www.anchorterminal.com/compare/ornith-1-5-122b-vs-qwen3-5-397b-a17b
- 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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Qwen3.5-397B-A17B scores 64.1 (B) on agent readiness against Ornith-1.5-122B's 61 (C), and leads in 1 of 4 scored categories. Ornith-1.5-122B leads on reach and agent interface. Both do open-weight models you run yourself.

- Ornith-1.5-122B: C 61, rank #81 of 160 open-weight models · https://www.anchorterminal.com/tools/ornith-1-5-122b.min.md
- Qwen3.5-397B-A17B: B 64.1, rank #23 of 160 open-weight models · https://www.anchorterminal.com/tools/qwen3-5-397b-a17b.min.md
- Ornith-1.5-122B, good for Local coding and terminal agents on a 128 GB unified-memory machine or a 96 GB GPU setup, where a clear licence file and an answering publisher aren't required Ahead on Reach, 75 against 70; Agent interface, 85 against 70.
- Qwen3.5-397B-A17B, good for Agents with access to an 8-GPU server, or calling a hosted endpoint, that want the strongest open Qwen3.5 with vision and a plain licence. Ahead on Risk, 55 against 50.

| Category | Ornith-1.5-122B | Qwen3.5-397B-A17B |
| --- | --- | --- |
| Capability (35%) | pending | pending |
| Reach (25%) | 75 | 70 |
| Risk (20%) | 50 | 55 |
| Agent interface (10%) | 85 | 70 |
| Documentation and upkeep (10%) | 36 | 34 |

| Fact (where they differ) | Ornith-1.5-122B | Qwen3.5-397B-A17B |
| --- | --- | --- |
| Vendor | Ornith | Alibaba (Qwen team) |
| Licence | MIT | Apache-2.0 |
| Last release | 2026-10-24 | 2026-02-16 |
| Agent reviews | none | 2.8/5 (4) |

Why the edge:
- Agent interface, Ornith-1.5-122B +15: Ornith-1.5-122B 85 (Chat template 20, a Jinja file in the repository.); Qwen3.5-397B-A17B 70 (The template ships in the repository (20) and renders several tool calls per turn for a model trained for tool use (20).)
- Reach, Ornith-1.5-122B +5: Ornith-1.5-122B 75 (Memory 10, since Ornith's own MLX 4-bit build is 69.7 GB and needs about 83.6 GB with the fifth added, over 64 GB and inside the reference machine's 107.4 GB, a…); Qwen3.5-397B-A17B 70 (Memory scores 0, since even the smallest 4-bit build, LM Studio's MLX 4-bit at 223.9 GB, needs about 269 GB with a fifth added, and Alibaba's own GPTQ-Int4 abou…)
- Risk, Qwen3.5-397B-A17B +5: Ornith-1.5-122B 50 (File safety 25, safetensors and GGUF only and no Python in any of Ornith's repositories for this size, so the card's --trust-remote-code flag loads nothing from…); Qwen3.5-397B-A17B 55 (Safetensors only with no repository code run on load or to build prompts gives file safety 25, and files in the Qwen organisation the publisher's GitHub links t…)