# Beating Models 20x Its Size — Gemma 4 31B Lands on SageMaker JumpStart!

Hi everyone, I'm Shiichan! Today's news is about Google DeepMind's newest model, Gemma 4, arriving on SageMaker JumpStart — in both a full-power version and a lightweight one.

## What was announced?

AWS What's New announced that two models are now available on Amazon SageMaker JumpStart: Google DeepMind's `Gemma-4-31B-it-assistant`, and NVIDIA's quantized version, `Gemma-4-31B-IT-NVFP4`. Both are built on the same Gemma 4 31B (31 billion parameter) dense model — one at full precision, one optimized and quantized.

## Why it matters

Bigger models tend to perform better, but they also cost more to run in memory and compute. Here, the same base model comes in both a "use it as-is" version and a "lightened" version, so you can choose based on whether your workload prioritizes accuracy or cost and speed.

## What changes

Here's what each model brings:

- **Gemma-4-31B-it-assistant**: An assistant-tuned model built for multimodal reasoning, coding, and agentic workflows. It handles text and image input (with video treated as frame sequences), supports a 256K-token context window, and covers over 140 languages. It combines local sliding-window attention with global attention in a hybrid mechanism, plus native function calling for building autonomous agents. On the Arena AI text leaderboard, it ranked #3 — beating models 20 times its size.
- **Gemma-4-31B-IT-NVFP4**: The same Gemma 4 31B capabilities, at a much smaller memory footprint. NVIDIA's ModelOpt framework quantizes it to 4-bit FP4 precision, cutting memory usage to about 18.5 GB (68% smaller than the base model) and delivering roughly 2.5x faster inference, while retaining 97-99% of the original model's quality.

## Dive Deep

Gemma-4-31B-IT-NVFP4 is optimized for NVIDIA RTX, DGX Spark, and data center GPUs. If your team's GPU resources are limited, this quantized version lets you get close to Gemma 4 31B-class performance with a much smaller memory budget. Deploy either model from the SageMaker JumpStart model catalog in a few clicks, or via the SageMaker Python SDK.

## Wrap-up

- Gemma-4-31B-it-assistant (full precision) and Gemma-4-31B-IT-NVFP4 (quantized) are now on SageMaker JumpStart
- The full-precision version supports 256K tokens, 140+ languages, and beats models 20x its size on the Arena AI leaderboard
- The quantized version cuts memory by 68% and runs 2.5x faster, while keeping 97-99% of the quality
- Pick the full-precision version for accuracy, or the quantized version for cost and speed, depending on your workload