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The fastest way to get this model running locally is via Docker.

Please follow the instructions listed below to get started.

The setup auto-downloads all needed files (several GBs).

The smart installation system will instantly find the perfect configuration for your specific hardware.

🧩 Hash sum → 3bb18419a4f20bb19fa271d2baa0162f — Update date: 2026-06-24 Verify CPU: 8-core / 16-thread recommended for orchestration RAM: enough space for background apps and OS overhead Disk Space: 100 GB for multi-modal model vision components Graphics: CUDA Compute Capability 8.0+ required for flash-attention

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.

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