Qwen3.5-397B-A17B-FP8 Locally via Ollama 2

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Qwen3.5-397B-A17B-FP8 Locally via Ollama 2

To install this model locally in the shortest time, opt for Docker.

Follow the step-by-step instructions below.

Next, execute the setup script or run docker-compose.

🗂 Hash: 787e07888d66fe23db857c5250ca1cf5 • Last Updated: 2026-06-25 Verify CPU: AVX2/AVX-512 instruction set required for llama.cpp RAM: 48 GB needed to prevent memory swapping to disk Disk Space: 100 GB for multi-modal model vision components GPU: 16 GB+ video memory highly recommended for exl2 / AWQ formats

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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