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MoreReps Training

Deploy Qwen3.5-397B-A17B-FP8 No Admin Rights 5-Minute Setup

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

Follow the guidelines below to continue.

The loader auto-caches the model archive (several GBs included).

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

📎 HASH: 26ca4681516a22b3001ddeb27eb66d0d | Updated: 2026-06-23



  • CPU: 8-core / 16-thread recommended for orchestration
  • RAM: 32 GB or higher for smooth 32k context lengths
  • Disk Space:70 GB free space for full FP16 weights storage
  • GPU: RTX 4080 / RTX 4090 recommended for 26B-A4B fast inference

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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