Qwen3.6-35B-A3B-NVFP4 Locally via Ollama 2 with Native FP4

Qwen3.6-35B-A3B-NVFP4 Locally via Ollama 2 with Native FP4

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

Check out the detailed setup guide below to begin.

The engine will automatically fetch large dependencies in the background.

Your resources are automatically evaluated to lock in the premium configuration.

đź”— SHA sum: 415091e812225c0aa97a668b573b9192 | Updated: 2026-06-27



  • Processor: Intel i7 / Ryzen 7 for heavy Quantized models
  • RAM: at least 32 GB in dual-channel mode for bandwidth
  • Disk Space: required: fast PCIe 4.0 drive for instant boots
  • Graphics: stable 30+ tk/s at 4-bit quantization on medium setup

The **Qwen3.6-35B-A3B-NVFP4** model represents a major leap in large language capabilities, combining **35B parameters** with the innovative A3B architecture. Built on the cutting‑edge **NVFP4** precision format, it achieves unprecedented inference efficiency while maintaining high fidelity in generated text. Evaluations across benchmark suites show *state‑of‑the‑art* performance in reasoning, coding, and multilingual tasks, often surpassing models of comparable size. Its training pipeline leverages a distributed strategy that balances compute utilization, resulting in a model that is both *scalable* and cost‑effective for production deployments. With extensive safety refinements and a transparent licensing model, the Qwen3.6-35B-A3B-NVFP4 is positioned as a versatile solution for enterprises and researchers alike.

Parameters 35 B
Architecture A3B
Precision NVFP4
Max Context Length 8K tokens
FLOPs per Token ~12 TFLOPs
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