Qwen3.5-397B-A17B-FP8 Zero Config

Docker offers the quickest path to setting up this model locally.

Please follow the instructions listed below to get started.

Finishing these instructions ensures you instantly get all the exact results you wanted to receive.

🔐 Hash sum: 2f7ef0466e7e2a7ed8422749a6a573a6 | 📅 Last update: 2026-06-25 Verify CPU: 8-core / 16-thread recommended for orchestration RAM: enough space for background apps and OS overhead Disk Space: required: fast PCIe 4.0 drive for instant boots Graphics: 12 GB VRAM minimum required for basic quantization

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.

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