Running this model locally is fastest when deployed through Docker.
Make sure to follow the instructions below.
The client handles the setup, pulling gigabytes of data automatically.
The installer will automatically analyze your hardware and select the optimal configuration for your system.
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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