# GLM-5.3-Flash vs LongCat-2.5 (slim)

> GLM-5.3-Flash scores 65.1 (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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- 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-Flash scores 65.1 (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-Flash: B 65.1, rank #18 of 160 open-weight models · https://www.anchorterminal.com/tools/glm-5-3-flash.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-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 Reach, 60 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 55; Agent interface, 75 against 70.

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

| Fact (where they differ) | GLM-5.3-Flash | LongCat-2.5 |
| --- | --- | --- |
| Vendor | Z.ai | Meituan (LongCat) |
| Last release | 2026-08-26 | 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-Flash +25: 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…); 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-Flash +12: 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…); 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 +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.); 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-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…); LongCat-2.5 75 (Chat template 20, chat_template.jinja in the repository (11,823 characters), with a copy in tokenizer_config.json.)