Setup gemma-4-26B-A4B-it-NVFP4 on Copilot+ PC No-Internet Version

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

Follow the step-by-step instructions below.

The client handles the setup, pulling gigabytes of data automatically.

The installer diagnoses your environment to deploy the most compatible profile.

📎 HASH: 4b0b8000192594fa82bfd5b4e10bb95e | Updated: 2026-07-05



  • Processor: 4.0 GHz+ boost clock recommended for CPU inference
  • RAM: high-speed DDR5 memory preferred for CPU offloading
  • Disk Space: required: fast PCIe 4.0 drive for instant boots
  • Graphic Processor: hardware Tensor Cores support needed for FP16 acceleration

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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