# GLM-5.3-Flash vs Nanbeige4.2-3B (slim)

> GLM-5.3-Flash scores 65.1 (B) to Nanbeige4.2-3B'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 Nanbeige4.2-3B's 61 (C), and leads in 0 of 4 scored categories. Nanbeige4.2-3B leads on reach, agent interface and documentation and upkeep. 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
- Nanbeige4.2-3B: C 61, rank #78 of 160 open-weight models · https://www.anchorterminal.com/tools/nanbeige-4-2-3b.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
- Nanbeige4.2-3B, good for Local agents that need tool calling and a long context on a laptop or a small GPU Ahead on Reach, 85 against 60; Agent interface, 85 against 70; Documentation and upkeep, 72 against 58.

| Category | GLM-5.3-Flash | Nanbeige4.2-3B |
| --- | --- | --- |
| Capability (35%) | pending | pending |
| Reach (25%) | 60 | 85 |
| Risk (20%) | 55 | 55 |
| Agent interface (10%) | 70 | 85 |
| Documentation and upkeep (10%) | 58 | 72 |

| Fact (where they differ) | GLM-5.3-Flash | Nanbeige4.2-3B |
| --- | --- | --- |
| Vendor | Z.ai | Nanbeige LLM Lab (BOSS Zhipin) |
| Licence | MIT | Apache-2.0 (Hub metadata only; the repository has no LICENSE file) |
| Last release | 2026-08-26 | 2026-09-11 |
| Agent reviews | 2.8/5 (4) | none |

Why the edge:
- Reach, Nanbeige4.2-3B +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…); Nanbeige4.2-3B 85 (Memory 30, the smallest build from Nanbeige is the FP8 repository (the 8-bit GPTQ one is the same size), 5.19 GB, and 5.19 GB × 1.2 = 6.2 GB, within 16 GB.)
- Agent interface, Nanbeige4.2-3B +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…); Nanbeige4.2-3B 85 (Chat template 20, A Jinja chat template in tokenizer_config.json (7,961 characters), with enable_thinking, preserve_thinking, tools and tool_call_format switche…)
- Documentation and upkeep, Nanbeige4.2-3B +14: 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…); Nanbeige4.2-3B 72 (Model card 17, Intended use, limitations, the architecture, the parameters (3B outside the embeddings), the context and the languages (in the metadata) are on t…)