How to Install gemma-4-26B-A4B-it-GGUF Locally via Ollama 2 One-Click Setup Windows

How to Install gemma-4-26B-A4B-it-GGUF Locally via Ollama 2 One-Click Setup Windows

For an instant local deployment, running a pre-configured shell script is ideal.

Follow the step-by-step instructions below.

All large files and heavy weights are downloaded automatically by the script.

To guarantee smooth performance, the process auto-selects the best options.

📎 HASH: dfdd926013c2306cb9fc9ad929cde623 | Updated: 2026-06-30



  • Processor: 6-core 3.5 GHz minimum required
  • RAM: 64 GB to avoid OOM crashes on large contexts
  • Disk Space: free: 80 GB on system drive for scratch space
  • GPU: RTX 4080 / RTX 4090 recommended for 26B-A4B fast inference

The gemma-4-26B-A4B-it-GGUF model represents a state-of-the-art addition to the Gemma family, built on a 26‑billion parameter architecture optimized for both reasoning and generation tasks. It leverages an enhanced attention mechanism that allows the model to capture longer-range dependencies, achieving a context window of 128K tokens for complex prompts. The model is quantized in GGUF format, delivering significantly lower memory footprint while preserving near‑original performance across a range of benchmarks. In comparative testing, gemma-4-26B-A4B-it-GGUF outperforms its predecessors on reasoning challenges, scoring 84.3% accuracy on multi‑step problem solving. Its open‑source nature and efficient inference make it suitable for deployment in production environments, research projects, and edge devices where computational resources are constrained.

Parameters 26 billion
Context length 128K tokens
Quantization GGUF
Benchmark accuracy 84.3%
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