Full Deployment GLM-5-FP8 on AMD/Nvidia GPU Fully Jailbroken

For an instant local deployment, running a pre-configured shell script is ideal.

Follow the guidelines below to continue.

The installer automatically pulls the model (could be multiple GBs).

Once launched, the wizard detects your specs to configure the model for maximum efficiency.

📊 File Hash: 1144da2986e67bee069e0e7c54020814 — Last update: 2026-06-27
  • CPU: multi-threading optimized for fast prompt processing
  • RAM: minimum 16 GB for stable 8B model loading
  • Disk Space: at least 100 GB for multiple local LLM variants
  • Graphics: CUDA Compute Capability 8.0+ required for flash-attention

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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