The most efficient approach for a local installation is leveraging Docker containers.
Carefully read and apply the steps described below.
1-click setup: the app automatically fetches the large weight files.
The deployment tool scans your environment and chooses the ideal parameters.
The Qwen3.5-397B-A17B-FP8 is a state‑of‑the‑art large language model designed for high‑performance inference on modern hardware. It leverages a 397‑billion parameter architecture built on the A17B design, delivering superior reasoning and multilingual capabilities. The model employs FP8 quantization, which reduces memory footprint while preserving accuracy and enabling faster computations. Its extensive training on diverse datasets allows it to generate coherent text, code, and creative content across multiple domains. A concise overview of its key specifications is provided below, highlighting parameter count, context window, and precision for easy reference.
| Spec | Value |
|---|---|
| Parameters | 397B |
| Architecture | A17B |
| Precision | FP8 |
| Context Length | 8K tokens |
| Training Data | Web‑scale corpora |
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