How to Setup GLM-5.2-FP8 Locally via Ollama 2 with Native FP4 Offline Setup

Using Docker is the absolute quickest way to install this model on your local machine.

Simply follow the directions outlined below.

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1-click setup: the app automatically fetches the large weight files.

The deployment tool scans your environment and automatically chooses the ideal parameters for your OS.

🔗 SHA sum: 0d33c37be0b852d89d0c9f8a3aa9f0f9 | Updated: 2026-06-22



  • Processor: Intel i7 / Ryzen 7 for heavy Quantized models
  • RAM: fast 5600MHz+ required to avoid memory bottlenecks
  • Disk Space: required: fast PCIe 4.0 drive for instant boots
  • Graphics: stable 30+ tk/s at 4-bit quantization on medium setup

GLM-5.2-FP8 is a next‑generation language model that combines massive scale with FP8 quantization to deliver unprecedented efficiency.

It features a parameter count of 180 billion weights, enabling it to handle complex reasoning tasks with high fidelity.

The model achieves inference speeds of up to 200 tokens per second on standard hardware, making it suitable for real‑time applications.

Its multimodal architecture supports text, code, and image inputs, allowing developers to build versatile solutions without deploying multiple models.

By leveraging advanced quantization techniques, GLM-5.2-FP8 reduces memory footprint while preserving state‑of‑the‑art performance across benchmarks.

Spec Value
Parameters 180 B
Precision FP8
Throughput 200 tokens/s
Modalities Text, Code, Image
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