The most rapid route to a local installation of this model is through WSL2.
Review and follow the instructions below.
1-click setup: the app automatically fetches the large weight files.
The script runs a quick hardware check to dynamically adjust parameters for elite speed.
The GLM-4.7-Flash model delivers exceptionally fast inference while maintaining high accuracy across a broad range of language tasks. Built with a parameter count of 26 billion and a context window of 128 k tokens, it balances size and efficiency for both research and production environments. Its training leverages a diverse corpus of web‑scale text and multimodal data, enabling robust understanding of images, code, and natural language queries. The model incorporates optimized attention mechanisms that reduce latency, making real‑time applications such as chat assistants and content generation seamlessly responsive. Compared to earlier GLM versions, GLM-4.7-Flash shows notable improvements in factual consistency and reasoning speed, as highlighted in the following comparison table.
| Parameter Count | 26 B |
| Context Length | 128 k tokens |
| Inference Speed | >200 tokens/s |
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