Qwen3.5-122B-A10B on AMD/Nvidia GPU

Qwen3.5-122B-A10B on AMD/Nvidia GPU

The fastest method for installing this model locally is by using Docker.

Make sure to follow the instructions below.

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

The automated installation script takes care of everything by tailoring the setup perfectly to your system specs.

📎 HASH: 713462d9d236dc0206dd0f3cf559decc | Updated: 2026-06-23



  • Processor: next-gen chip for heavy context processing
  • RAM: 32 GB or higher for smooth 32k context lengths
  • Storage: extra room for future model updates and datasets
  • GPU: RTX 4080 / RTX 4090 recommended for 26B-A4B fast inference

Qwen3.5-122B-A10B is a state‑of‑the‑art language model featuring 122 billion parameters and an A10B architecture. It leverages a massive web‑scale training corpus to achieve exceptional performance across a wide range of NLP tasks. The model incorporates advanced attention mechanisms and multi‑layer decoder stacks that enable deep contextual understanding and fluent generation. Benchmark evaluations place it among the top performers, delivering record‑breaking scores in reasoning, comprehension, and code synthesis. Its efficient A10B design balances computational demands with high‑quality output, making it suitable for both research and production environments. Ongoing fine‑tuning initiatives allow developers to customize the model for specialized domains while preserving its core capabilities.

Parameter Value
Model Name Qwen3.5-122B-A10B
Parameters 122 B
Architecture A10B
Training Data Web‑scale corpus
Key Features Advanced attention, multi‑layer decoder
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