Gemma 3 — Local AI Model by Google

Written by Jakub Rusinowski · Last updated March 12, 2025

Gemma 3 delivers exceptional quality-per-VRAM ratio, with the 4B model outperforming many 7B competitors. Features multimodal capabilities and a 128k context window across all sizes. Previous generation — superseded by Gemma 4 (E2B/E4B/26B-A4B/31B and the 12B Unified follow-up), which improves efficiency and multimodal support. Still widely used and supported.

Licence

Licence	What it permits	Applies to
`Gemma Terms`	Commercial use permitted Weights are downloadable and commercial use is permitted, subject to the licence’s acceptable-use terms.	Gemma 3 1B Instruct, Gemma 3 4B Instruct, Gemma 3 12B Instruct, Gemma 3 27B Instruct

Hardware Requirements

Gemma 3 1B Instruct	Min 1 GB VRAM · Q4_K_M · 32,000 ctx · `ollama run gemma3:1b`
Gemma 3 4B Instruct	Min 3 GB VRAM · Q4_K_M · 128,000 ctx · `ollama run gemma3:4b`
Gemma 3 12B Instruct	Min 8 GB VRAM · Q4_K_M · 128,000 ctx · `ollama run gemma3:12b`
Gemma 3 27B Instruct	Min 17 GB VRAM · Q4_K_M · 128,000 ctx · `ollama run gemma3:27b`

Recommended GPU

The cheapest GPU that runs Gemma 3 locally (min 1 GB VRAM) is the Intel Arc B570 (10 GB).

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Intel Arc B570 10GB

10 GB VRAM · 150 W board power

2026 prices are volatile — check the current listing.

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How to Run Locally

Install Ollama then run: ollama run gemma3:1b

Minimum VRAM: 1 GB. For best results use Q4_K_M quantization.

Gemma 3 — Frequently Asked Questions

How much VRAM does Gemma 3 need?

Gemma 3 needs about 1 GB VRAM at Q4_K_M quantization for its smallest variant. Variants: Gemma 3 1B Instruct (1 GB, Q4_K_M); Gemma 3 4B Instruct (3 GB, Q4_K_M); Gemma 3 12B Instruct (8 GB, Q4_K_M); Gemma 3 27B Instruct (17 GB, Q4_K_M). On Apple Silicon, unified memory counts toward this requirement.

Can I run Gemma 3 on an RTX 4090 (24 GB)?

Yes — Gemma 3 runs on an RTX 4090 (24 GB) and other 24 GB cards such as the RTX 3090. Smaller variants also fit comfortably on 8–16 GB GPUs at Q4_K_M.

What quantization should I use for Gemma 3?

Q4_K_M is the best balance of quality and VRAM for Gemma 3 in most cases. Choose Q8_0 for near-lossless quality if you have spare VRAM, or smaller quants (Q3/Q2) only when memory is tight.

How do I run Gemma 3 with Ollama?

Install Ollama, then run: ollama run gemma3:1b. This downloads Gemma 3 and starts a local, OpenAI-compatible endpoint — no internet connection is needed after the initial download.