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Qwen3.5-35B-A3B

Qwen3.5-35B-A3B

Qwen3.5-35B-A3B

Deploying this model locally is quickest when done via a simple curl command.

Carefully read and apply the steps described below.

The engine will automatically fetch large dependencies in the background.

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

📡 Hash Check: f0a667fa86c1068b78194b3f23618d4d | 📅 Last Update: 2026-06-29



  • CPU: AVX2/AVX-512 instruction set required for llama.cpp
  • RAM: at least 32 GB in dual-channel mode for bandwidth
  • Disk: high-speed SSD 120 GB to cache model layers
  • 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.

Specification Value
Parameter Count 35 billion
Context Length 128 k tokens
Training Data Scientific, technical, creative corpora
Attention Mechanism A3B (optimized)
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Author Info

mike