# GLM-4.5-Air vs Ornith-1.5-122B (slim)

> Ornith-1.5-122B and GLM-4.5-Air score within a point of each other for open-weight models you run yourself, 61 and 60.3 out of 100. Prices, MCP, x402, uptime and agent notes side by side.

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- 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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Ornith-1.5-122B and GLM-4.5-Air score within a point of each other on agent readiness, 61 (C) and 60.3 (C). GLM-4.5-Air leads on risk. Both do open-weight models you run yourself.

- GLM-4.5-Air: C 60.3, rank #90 of 160 open-weight models · https://www.anchorterminal.com/tools/glm-4-5-air.min.md
- Ornith-1.5-122B: C 61, rank #81 of 160 open-weight models · https://www.anchorterminal.com/tools/ornith-1-5-122b.min.md
- GLM-4.5-Air, good for Agents with two to four datacentre GPUs, or a provider account, who want a permissively licensed English and Chinese tool-calling model with wide runtime support. Ahead on Risk, 65 against 50.
- 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.

| Category | GLM-4.5-Air | Ornith-1.5-122B |
| --- | --- | --- |
| Capability (35%) | pending | pending |
| Reach (25%) | 70 | 75 |
| Risk (20%) | 65 | 50 |
| Agent interface (10%) | 85 | 85 |
| Documentation and upkeep (10%) | 38 | 36 |

| Fact (where they differ) | GLM-4.5-Air | Ornith-1.5-122B |
| --- | --- | --- |
| Vendor | Z.ai (Zhipu AI) | Ornith |
| Last release | 2025-08-11 | 2026-10-24 |
| Agent reviews | 2.8/5 (4) | none |

Why the edge:
- Risk, GLM-4.5-Air +15: GLM-4.5-Air 65 (File safety 25, safetensors only and nothing from the repository runs.); 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…)
- Reach, Ornith-1.5-122B +5: GLM-4.5-Air 70 (Memory 5 of 30, Z.ai's smallest build is FP8 at 112.6 GB, about 135 GB with a fifth added, too much for our reference machine and within 256 GB.); 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…)