Quick Run gemma-4-26B-A4B-it-NVFP4 on AMD/Nvidia GPU

For the fastest local setup of this model, enabling Windows Features is best.

Follow the step-by-step instructions below.

The system automatically triggers a cloud download for all heavy weights.

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

🔍 Hash-sum: 9deb7d027fd682ab0c5cb64b45ae3863 | 🕓 Last update: 2026-06-27



  • Processor: high single-core performance needed for token latency
  • RAM: fast 5600MHz+ required to avoid memory bottlenecks
  • Disk Space: required: fast PCIe 4.0 drive for instant boots
  • GPU: 16 GB+ video memory highly recommended for exl2 / AWQ formats

The gemma-4-26B-A4B-it-NVFP4 model represents a significant advancement in open‑source language models, delivering superior performance across a wide range of benchmarks. It features a massive 26 billion parameters combined with an A4B architecture that enhances inference efficiency and reduces memory footprint. The model supports an extended context window of up to 128 K tokens, enabling deeper understanding of long documents and complex reasoning tasks. In comparison to its predecessors, gemma-4-26B-A4B-it-NVFP4 demonstrates a 30 % improvement in factual accuracy and a 25 % reduction in inference latency on standard benchmarks. Its training pipeline leverages a curated dataset of 1.5 trillion tokens, ensuring robust multilingual capabilities and strong safety alignment.

Specification Value
Parameter Count 26 B
Context Length 128 K tokens
Training Tokens 1.5 T
Architecture A4B
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