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How to Run GLM-5-FP8 No-Internet Version No-Code Guide

July 1, 2026 · betiang

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

Please follow the instructions listed below to get started.

No manual effort needed; the setup auto-ingests the large data.

You don’t need to tweak anything; the installer picks the highest performing setup.

📦 Hash-sum → 59f824fbf07c6720b3835c8bd104bd6e | 📌 Updated on 2026-06-30

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Processor: 6-core 3.5 GHz minimum required
RAM: minimum 16 GB for stable 8B model loading
Disk Space: free: 80 GB on system drive for scratch space
GPU: high memory bandwidth GPU for next-gen local AI pipeline

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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