If you need a near-instant local setup, just fetch files via a basic curl request.
Review and follow the instructions below.
The framework seamlessly downloads the massive neural network binaries.
To save you time, the system will automatically determine efficient resource allocation.
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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