Qwen3.5-35B-A3B Locally via Ollama 2 Offline Setup

Qwen3.5-35B-A3B Locally via Ollama 2 Offline Setup



For an instant local deployment, running a pre-configured shell script is ideal.




Just follow the guidelines provided below.



The engine will automatically fetch large dependencies in the background.




The automated script takes care of everything, tailoring the setup to your specs.



🖹 HASH-SUM: 72ac5272fa05be278d6486d6111f4b92 | 📅 Updated on: 2026-07-07


  • Processor: 6-core 3.5 GHz minimum required
  • RAM: required: 16 GB absolute minimum for small models
  • Disk Space: 80 GB NVMe SSD required for fast model weights loading
  • GPU: 16 GB+ video memory highly recommended for exl2 / AWQ formats

The Qwen3.5-35B-A3B is a next‑generation language model that combines massive scale with advanced reasoning capabilities. It features 35 billion parameters and a context window of up to 128 k tokens, enabling it to understand and generate long, complex texts with remarkable coherence. Trained on a diverse corpus that includes scientific papers, technical documentation, and creative writing, the model demonstrates exceptional versatility across domains such as code generation, data analysis, and natural language understanding. Its architecture introduces an optimized A3B attention mechanism that reduces computational overhead while preserving high fidelity in output, making it suitable for both cloud‑based and edge deployments. In benchmark evaluations, the model consistently outperforms prior models in reasoning tasks, achieving state‑of‑the‑art results without sacrificing latency or memory usage.

SpecificationValue
Parameter Count35 billion
Context Length128 k tokens
Training DataScientific, technical, creative corpora
Attention MechanismA3B (optimized)
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