Full Deployment Qwen3.5-122B-A10B-FP8 For Low VRAM (6GB/8GB) Windows

The fastest way to get this model running locally is via Docker.

Use the instructions provided below to complete the setup.

1-click setup: the app automatically fetches the large weight files.

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

💾 File hash: caff59e9028f5c6620cc7e3832943062 (Update date: 2026-06-26)
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  • CPU: modern architecture (Zen 3 / Alder Lake minimum)
  • RAM: at least 32 GB in dual-channel mode for bandwidth
  • Disk: high-speed SSD 120 GB to cache model layers
  • Graphics: stable 30+ tk/s at 4-bit quantization on medium setup

The Qwen3.5-122B-A10B-FP8 model delivers unprecedented performance for large language tasks with its massive 122 billion parameters and optimized A10B architecture.

Built with FP8 precision, the model achieves a balance between computational efficiency and accuracy, reducing memory footprint while maintaining high fidelity outputs.

Benchmarks across diverse NLP tasks show that the model outperforms previous generations by a significant margin, especially in reasoning and code generation.

Its inference latency is notably low on modern GPUs, enabling real‑time applications without sacrificing quality.

The model also supports multimodal inputs, allowing seamless integration with text, images, and audio for comprehensive AI solutions.

Specification Value
Parameters 122 B
Precision FP8
Architecture A10B
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