Zero-Click Run gemma-4-26B-A4B-it-NVFP4

Zero-Click Run gemma-4-26B-A4B-it-NVFP4

Using Docker is the absolute quickest way to install this model on your local machine.

Follow the guidelines below to continue.

The installer auto-downloads and deploys the entire model pack.

Once launched, the setup wizard will detect your specs to configure the model for maximum efficiency.

🧾 Hash-sum — 8c5f1dbad0ec7f1affaa0e67eb240ec6 • 🗓 Updated on: 2026-06-28



  • CPU: AVX2/AVX-512 instruction set required for llama.cpp
  • RAM: enough space for background apps and OS overhead
  • Disk Space: 100 GB for multi-modal model vision components
  • GPU: modern architecture (Ada Lovelace / Ampere minimum)

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.

SpecificationValue
Parameter Count26 B
Context Length128 K tokens
Training Tokens1.5 T
ArchitectureA4B
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