Category: EXL2

Running this model locally is fastest when deployed through Docker.

Make sure to follow the instructions below.

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

There is no manual tuning required; the builder will automatically deploy the best matching configuration.

🗂 Hash: 4418e401535ac43f96c092eb1f83a292 • Last Updated: 2026-06-25 Verify Processor: 4.0 GHz+ boost clock recommended for CPU inference RAM: 32 GB or higher for smooth 32k context lengths Disk Space:70 GB free space for full FP16 weights storage Graphics: TensorRT-LLM / vLLM inference engine compatible chip

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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