Run GLM-5-FP8 Uncensored Edition Direct EXE Setup

The most efficient approach for a local installation is leveraging Docker containers.

Follow the sequence of steps detailed below.

The download manager will automatically pull several gigabytes of data.

The automated script takes care of everything, tailoring the setup to your specs.

🛠 Hash code: 66b09cb852ef7e043d2dd5da876f24ac — Last modification: 2026-06-24



  • CPU: modern architecture (Zen 3 / Alder Lake minimum)
  • RAM: 48 GB needed to prevent memory swapping to disk
  • Storage: extra room for future model updates and datasets
  • Graphic Processor: hardware Tensor Cores support needed for FP16 acceleration

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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