Running this model locally is fastest when deployed through Docker.
Follow the step-by-step instructions below.
The setup auto-downloads all needed files (several GBs).
The setup file includes an intelligent feature that instantly optimizes all configurations for your hardware profile.
🛡️ Checksum: dcd98fed50f915b1aeee1f1f190ccbc2 — ⏰ Updated on: 2026-06-23
- CPU: multi-threading optimized for fast prompt processing
- RAM: required: 16 GB absolute minimum for small models
- Disk: high-speed SSD 120 GB to cache model layers
- GPU: high memory bandwidth GPU for next-gen local AI pipeline
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The Qwen3.6-35B-A3B-NVFP4 model represents a significant leap in large language model efficiency, combining 35 billion parameters with an innovative A3B architecture that optimizes both performance and computational cost. By leveraging NVFP4 quantization, the model achieves unprecedented memory savings while maintaining high accuracy across a wide range of NLP tasks. It supports an extended context window of up to 128 K tokens, enabling deeper understanding of long documents and complex reasoning chains. Benchmarks show that the model delivers state‑of‑the‑art results in multilingual generation, code synthesis, and reasoning, all with significantly lower inference latency compared to previous 35 B‑parameter models. The accompanying
provides a quick technical comparison with competing models, highlighting its superior parameter efficiency and hardware utilization.
| Parameters |
35 B |
| Context Length |
128 K tokens |
| Quantization |
NVFP4 |
| Architecture |
A3B |
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