gemma-4-31B-it

gemma-4-31B-it

Deploying this model locally is quickest when done via Docker.

Refer to the instructions below to proceed.

After that, launch the environment using docker-compose.

🔗 SHA sum: c22d507ca8b6e3ac327dff13213dbfc6 | Updated: 2026-06-21



  • CPU: 8-core / 16-thread recommended for orchestration
  • RAM: at least 32 GB in dual-channel mode for bandwidth
  • Disk Space: 80 GB NVMe SSD required for fast model weights loading
  • GPU: modern architecture (Ada Lovelace / Ampere minimum)

The Gemma-4-31B-it model represents a significant advancement in open‑source language models, combining a 31 billion parameter architecture with sophisticated instruction tuning. It leverages a mixture‑of‑experts design to achieve both high performance and computational efficiency, making it suitable for a wide range of commercial and research applications. The model supports multimodal inputs, allowing users to process text, images, and audio within a unified framework. Benchmark evaluations place it among the top‑tier models in reasoning, coding, and factual knowledge tasks, often matching or surpassing proprietary alternatives. An accompanying

provides detailed technical specifications and a comparative performance snapshot against earlier Gemma releases.

Specification Value
Parameters 31 B
Context Length 8 K tokens
Training Data Web‑scale multilingual corpus
Inference Speed ~120 MFLOPS
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