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Run gemma-4-26B-A4B-it-NVFP4 Offline on PC Complete Walkthrough

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

Make sure to follow the instructions below.

The installer automatically pulls the model (could be multiple GBs).

The automated script takes care of everything, tailoring the setup to your specs.

πŸ“¦ Hash-sum β†’ a0978bcf6cc27e5428e040b14d50037e | πŸ“Œ Updated on 2026-07-03



  • Processor: 4.0 GHz+ boost clock recommended for CPU inference
  • RAM: 32 GB or higher for smooth 32k context lengths
  • Disk Space: 100 GB for multi-modal model vision components
  • GPU: RTX 4080 / RTX 4090 recommended for 26B-A4B fast inference

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 26β€―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 128β€―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 30β€―% improvement in factual accuracy and a 25β€―% reduction in inference latency on standard benchmarks. Its training pipeline leverages a curated dataset of 1.5β€―trillion tokens, ensuring robust multilingual capabilities and strong safety alignment.

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

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