If you want the fastest local installation for this model, use Docker.
Review and follow the instructions below.
The client handles the setup, pulling gigabytes of data automatically.
You don’t need to tweak anything, as the installer will automatically pick the highest performing setup for you.
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 |
- Installer configuring distributed tensor calculation grids across multiple local computers
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- Script downloading IP-Adapter-FaceID models for local consistent character creation
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- Downloader pulling specialized textual inversion files for photographic facial alignment texture adjustments
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- Script downloading precision depth-mapping files for 3D volumetric world building routines
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- Script downloading modern cross-encoder weights for refining local RAG pipeline loops and arrays
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- Setup utility configuring private RAG engines using modern BGE embeddings
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