Qwen3.6-35B-A3B-NVFP4

Qwen3.6-35B-A3B-NVFP4

For the fastest local setup of this model, Docker is the best choice.

Refer to the instructions below to proceed.

The loader auto-caches the model archive (several GBs included).

The installer will automatically analyze your hardware and select the optimal configuration for your system.

🛠 Hash code: cfc616c4c5ee60489f7469f2368b6cac — Last modification: 2026-06-24
  • Processor: next-gen chip for heavy context processing
  • RAM: 32 GB highly recommended for 26B+ GGUF models
  • Disk Space: at least 100 GB for multiple local LLM variants
  • Graphics: TensorRT-LLM / vLLM inference engine compatible chip

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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