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

> GLM-5.3-Flash scores 65.1 (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.

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GLM-5.3-Flash scores 65.1 (B) on agent readiness against Ornith-1.5-122B's 61 (C), and leads in 2 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-Flash: B 65.1, rank #18 of 160 open-weight models · https://www.anchorterminal.com/tools/glm-5-3-flash.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-Flash, good for Teams with a multi-GPU server who want an MIT-licensed multimodal agent model with a 1M-token context, or agents that call it through a hosted provider Ahead on Risk, 55 against 50; 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 60; Agent interface, 85 against 70.

| Category | GLM-5.3-Flash | Ornith-1.5-122B |
| --- | --- | --- |
| Capability (35%) | pending | pending |
| Reach (25%) | 60 | 75 |
| Risk (20%) | 55 | 50 |
| Agent interface (10%) | 70 | 85 |
| Documentation and upkeep (10%) | 58 | 36 |

| Fact (where they differ) | GLM-5.3-Flash | Ornith-1.5-122B |
| --- | --- | --- |
| Vendor | Z.ai | Ornith |
| Last release | 2026-08-26 | 2026-10-24 |
| Agent reviews | 2.8/5 (4) | none |

Why the edge:
- Documentation and upkeep, GLM-5.3-Flash +22: GLM-5.3-Flash 58 (The card covers architecture, parameters and languages and misses four of the seven items, for 8. Training data is 5, a 30T-token corpus described with no sourc…); 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 +15: GLM-5.3-Flash 60 (Memory earns nothing, since Z.ai's smallest build is the 328.4 GB FP8 one, about 394 GB with the fifth added, and neither Ollama nor LM Studio has a local build…); 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-Flash 70 (A Jinja chat template sits in both repositories, for 20. The tool-calling format is 10, because it is defined only by the template and the glm47 parser is named…); Ornith-1.5-122B 85 (Chat template 20, a Jinja file in the repository.)
- Risk, GLM-5.3-Flash +5: GLM-5.3-Flash 55 (File safety is full, with safetensors only, no Python and no remote code needed in Transformers 5.16.1 or later.); 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…)