Running this model locally is fastest when deployed through Docker.
Please follow the instructions listed below to get started.
The installer auto-downloads and deploys the entire model pack.
The deployment tool scans your environment and automatically chooses the ideal parameters for your OS.
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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