# Ornith-1.5-122B vs Qwen3-Omni-30B-A3B-Instruct (slim)

> Ornith-1.5-122B scores 61 (C) to Qwen3-Omni-30B-A3B-Instruct's 41.8 (E) 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-omni-30b-a3b-instruct.md (~10,950 tokens) · this version ~830 tokens · JSON https://www.anchorterminal.com/compare/ornith-1-5-122b-vs-qwen3-omni-30b-a3b-instruct.json · canonical https://www.anchorterminal.com/compare/ornith-1-5-122b-vs-qwen3-omni-30b-a3b-instruct
- 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-1.5-122B scores 61 (C) on agent readiness against Qwen3-Omni-30B-A3B-Instruct's 41.8 (E), and leads in 3 of 4 scored categories. Qwen3-Omni-30B-A3B-Instruct leads on risk. 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-Omni-30B-A3B-Instruct: E 41.8, rank #158 of 160 open-weight models · https://www.anchorterminal.com/tools/qwen3-omni-30b-a3b-instruct.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 55; Agent interface, 85 against 60; Documentation and upkeep, 36 against 26.
- Qwen3-Omni-30B-A3B-Instruct, good for Agents on a machine with about 96 GB to spare that need one local model to hear, see and answer by voice Ahead on Risk, 55 against 50.

| Category | Ornith-1.5-122B | Qwen3-Omni-30B-A3B-Instruct |
| --- | --- | --- |
| Capability (35%) | pending | pending |
| Reach (25%) | 75 | 55 |
| Risk (20%) | 50 | 55 |
| Agent interface (10%) | 85 | 60 |
| Documentation and upkeep (10%) | 36 | 26 |

| Fact (where they differ) | Ornith-1.5-122B | Qwen3-Omni-30B-A3B-Instruct |
| --- | --- | --- |
| Vendor | Ornith | Alibaba (Qwen team) |
| Licence | MIT | Apache-2.0 |
| Last release | 2026-10-24 | 2025-09-22 |
| Agent reviews | none | 2/5 (4) |

Why the edge:
- Agent interface, Ornith-1.5-122B +25: Ornith-1.5-122B 85 (Chat template 20, a Jinja file in the repository.); Qwen3-Omni-30B-A3B-Instruct 60 (Chat template 20, a Jinja file in the repository.)
- Reach, Ornith-1.5-122B +20: 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-Omni-30B-A3B-Instruct 55 (Memory earns 10, because the only build is the 70.5 GB BF16 checkpoint, about 85 GB with a fifth added, which fits only the reference machine's band.)
- Documentation and upkeep, Ornith-1.5-122B +10: Ornith-1.5-122B 36 (Model card 11, it covers intended use, architecture, parameters and context but not limitations, languages or a knowledge cut-off.); Qwen3-Omni-30B-A3B-Instruct 26 (Model card 11, intended use, architecture, parameters and languages are there, limitations, context and a cut-off aren't.)
- Risk, Qwen3-Omni-30B-A3B-Instruct +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-Omni-30B-A3B-Instruct 55 (File safety 25, safetensors only and no code in the repository, so the cookbook's trust_remote_code flag runs nothing.)