The fastest method for installing this model locally is by using Docker.
Make sure to follow the instructions below.
The loader auto-caches the model archive (several GBs included).
The installer will automatically analyze your hardware and select the optimal configuration for your system.
GLM-5-FP8 is a next-generation language model that leverages *FP8* quantization to deliver high performance on modern hardware. It maintains accuracy and speed while significantly reducing memory usage. The model sets new benchmarks in tasks such as MMLU and Commonsense Reasoning, achieving state-of-the-art results. Its refined transformer block incorporates sparse attention mechanisms for efficient processing of long sequences. A concise overview of its technical specifications is provided below.
| Parameter Count | 176 B |
| Context Length | 8 K tokens |
| Quantization | FP8 |
| Training FLOPs | ≈1.5×10^18 |
| Peak Throughput | ≈2 T tokens/s on GPU clusters |
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