Launch gemma-4-26B-A4B-it Easy Build

Docker offers the quickest path to setting up this model locally.

Refer to the instructions below to proceed.

Then, simply start the container with the provided Docker command.

🔍 Hash-sum: 6a207585e62d0b9683737cad51af8360 | 🕓 Last update: 2026-06-26



  • CPU: 8-core / 16-thread recommended for orchestration
  • RAM: 48 GB needed to prevent memory swapping to disk
  • Disk Space: required: fast PCIe 4.0 drive for instant boots
  • Graphics: 12 GB VRAM minimum required for basic quantization

The gemma-4-26B-A4B-it model represents a significant advancement in open‑source language models, combining a massive 26‑billion parameter architecture with optimized inference performance. It leverages an attention‑sparse design that reduces computational load while maintaining high fidelity in both factual and creative tasks. The model supports a 2048‑token context window and incorporates a refined instruction‑tuning pipeline that improves alignment with user intent. A comparison with peer models shows superior scores in reasoning, code generation, and multilingual understanding, as summarized below.

MetricValue
Parameters26 B
Context Length2048 tokens
Training DataWeb‑scale multilingual corpus
Inference Speed~120 tokens/s on GPU

Users can integrate the model into production environments via standard APIs, benefiting from its balanced trade‑off between size, speed, and capability.

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