Full Deployment Qwen3.5-122B-A10B Locally via Ollama 2 No-Internet Version Step-by-Step

Full Deployment Qwen3.5-122B-A10B Locally via Ollama 2 No-Internet Version Step-by-Step

If you want the fastest local installation for this model, use standard pip packages.

Follow the step-by-step instructions below.

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

During setup, the script automatically determines and applies the best settings.

📦 Hash-sum → 7238db5ca6b8eb9bfe0f37dde0cb41a2 | 📌 Updated on 2026-07-01



  • Processor: high single-core performance needed for token latency
  • RAM: enough space for background apps and OS overhead
  • Disk Space: 80 GB NVMe SSD required for fast model weights loading
  • 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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