# GLM-5.3 vs Ornith-1.5-122B (slim)

> GLM-5.3 scores 64.6 (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.

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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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GLM-5.3 scores 64.6 (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.

- GLM-5.3: B 64.6, rank #21 of 160 open-weight models · https://www.anchorterminal.com/tools/glm-5-3.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-5.3, good for Teams with an 8-GPU server who want an open coding and long-horizon agent model with a 1M-token context, or agents that call it through Z.ai or a hosted provider Ahead on Documentation and upkeep, 58 against 36.
- 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 70.

| Category | GLM-5.3 | Ornith-1.5-122B |
| --- | --- | --- |
| Capability (35%) | pending | pending |
| Reach (25%) | 55 | 75 |
| Risk (20%) | 50 | 50 |
| Agent interface (10%) | 70 | 85 |
| Documentation and upkeep (10%) | 58 | 36 |

| Fact (where they differ) | GLM-5.3 | Ornith-1.5-122B |
| --- | --- | --- |
| Vendor | Z.ai (Zhipu AI) | Ornith |
| Licence | GLM-5.3 License (MIT-style, with a security review for the largest model-as-a-service operators) | MIT |
| Last release | 2026-10-15 | 2026-10-24 |
| Agent reviews | 2.8/5 (4) | none |

Why the edge:
- Documentation and upkeep, GLM-5.3 +22: GLM-5.3 58 (The card covers intended use, languages and context and misses limitations, architecture, parameters and cut-off, for 8. Training data is 5, a description of th…); 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.)
- Reach, Ornith-1.5-122B +20: GLM-5.3 55 (Memory earns nothing, since Z.ai's smallest build is the 755.6 GB FP8 one, about 907 GB with the fifth added, and Ollama only lists a cloud entry.); 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…)
- Agent interface, Ornith-1.5-122B +15: GLM-5.3 70 (A Jinja chat template sits in the repository, for 20. The tool-calling format is 10, since it is defined only by the template and the glm47 parser is named by v…); Ornith-1.5-122B 85 (Chat template 20, a Jinja file in the repository.)