# GLM-5.3 vs LongCat-2.5 (slim)

> GLM-5.3 scores 64.6 (B) to LongCat-2.5's 50.5 (D) for open-weight models you run yourself. Prices, MCP, x402, uptime and agent notes side by side.

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GLM-5.3 scores 64.6 (B) on agent readiness against LongCat-2.5's 50.5 (D), and leads in 2 of 4 scored categories. LongCat-2.5 leads on risk 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
- LongCat-2.5: D 50.5, rank #145 of 160 open-weight models · https://www.anchorterminal.com/tools/longcat-2-5.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 Reach, 55 against 35; Documentation and upkeep, 58 against 46.
- LongCat-2.5, good for Operators with NPU clusters, and anyone tracking what the open flagships can do Ahead on Risk, 60 against 50; Agent interface, 75 against 70.

| Category | GLM-5.3 | LongCat-2.5 |
| --- | --- | --- |
| Capability (35%) | pending | pending |
| Reach (25%) | 55 | 35 |
| Risk (20%) | 50 | 60 |
| Agent interface (10%) | 70 | 75 |
| Documentation and upkeep (10%) | 58 | 46 |

| Fact (where they differ) | GLM-5.3 | LongCat-2.5 |
| --- | --- | --- |
| Vendor | Z.ai (Zhipu AI) | Meituan (LongCat) |
| 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 | 2026-11-10 |
| Terms last updated | no document linked | not read yet |
| Agent reviews | 2.8/5 (4) | none |

Why the edge:
- Reach, GLM-5.3 +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.); LongCat-2.5 35 (Memory 0, the smallest build is Meituan's W4A4 repository, 1,336 GB, and 1,336 GB × 1.2 = 1,603 GB, far above 256 GB.)
- Documentation and upkeep, GLM-5.3 +12: 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…); LongCat-2.5 46 (Model card 11, Intended use, limitations (the usage considerations), the architecture and the parameter counts are on the card.)
- Risk, LongCat-2.5 +10: GLM-5.3 50 (File safety is full, with safetensors only, no Python in the repository and no remote code needed in Transformers 5.12.0 or later.); LongCat-2.5 60 (File safety 25, safetensors only, no .bin, .pt or .pth files and no Python in the repository.)
- Agent interface, LongCat-2.5 +5: 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…); LongCat-2.5 75 (Chat template 20, chat_template.jinja in the repository (11,823 characters), with a copy in tokenizer_config.json.)