Gemma 3 12B Instruct — VRAM, Speed & Local Setup

Autor: Jakub Rusinowski · Ostatnia aktualizacja: 12 marca 2025

Model library → Gemma 3 → Gemma 3 12B Instruct

The sweet spot of the Gemma 3 family. Rivals Llama 3.3 70B in many tasks while fitting comfortably in 8GB VRAM. Exceptional for creative writing and coding.

Gemma 3 12B Instruct needs about 8 GB of VRAM at Q4_K_M — quantized weights plus framework overhead, before any KV cache. On Apple Silicon that figure comes out of unified memory.

Specifications

Parameters12 Billion
Context window128,000
ArchitectureDense
ProviderGoogle
LicenceGemma Terms
Specified atQ4_K_M
System RAM16 GB
Record updated2025-03-12

Licence

Gemma Terms — commercial use permitted. Weights are downloadable and commercial use is permitted, subject to the licence’s acceptable-use terms.

VRAM and Speed by Quantization

Modelled on a reference NVIDIA RTX 4090 (24 GB), at 8K context. Speed figures are ESTIMATES from the memory-bandwidth roofline described on the methodology page, not benchmarks we ran — rows marked measured come from published or reader-submitted runs. VRAM here includes the KV cache, so it reads higher than the headline figure above, which does not.

QuantWeightsVRAM neededEst. speedFit on 24 GB
Q2_K3.9 GB7.8 GB~105 tok/s (est.)Fits comfortably
Q3_K_M5.1 GB9.0 GB~90 tok/s (est.)Fits comfortably
Q4_K_M7.2 GB11.1 GB~72 tok/s (est.)Fits comfortably
Q5_K_M8.5 GB12.4 GB~64 tok/s (est.)Fits comfortably
Q6_K9.8 GB13.7 GB~58 tok/s (est.)Fits comfortably
Q8_012.8 GB16.6 GB~47 tok/s (est.)Fits comfortably
F1624.0 GB27.9 GB~4 tok/s (est.)Offloads to system RAM (slow)

Want the memory numbers alone, at every quantization level and your own context length? Use the Gemma 3 12B Instruct VRAM calculator.

Buy This HardwareIntel Arc B570 10GB — 10 GB VRAM · 150 W board powerDeploy in the Cloud NowRTX 4090 on RunPod — from $0.34/hr · rate checked 2026-07

or compare on Vast.ai from $0.35/hr (typical low · varies)

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Recommended GPU

The cheapest catalogued GPU that runs Gemma 3 12B Instruct is the Intel Arc B570 (10 GB).

Ujawnienie afiliacyjne: Niektóre odnośniki na tej stronie to linki afiliacyjne — jeśli dokonasz zakupu za ich pośrednictwem, LLM Configurator może otrzymać prowizję bez dodatkowych kosztów dla Ciebie. Jako uczestnik programu Amazon Associates, LLM Configurator zarabia na kwalifikujących się zakupach.
Intel Arc B570 10GB
10 GB VRAM · 150 W board power
Ceny w 2026 są niestabilne — sprawdź aktualną ofertę.
Sprawdź cenę na Amazon

How to Run Gemma 3 12B Instruct

Install Ollama, then run:

ollama run gemma3:12b

Weights on Hugging Face: google/gemma-3-12b-it.

Best for: chat, creative, coding, balanced.

Can I Run Gemma 3 12B Instruct on My GPU?

Other Gemma 3 Sizes

Gemma 3 12B Instruct — Frequently Asked Questions

How much VRAM does Gemma 3 12B Instruct need?
About 8 GB at Q4_K_M — quantized weights plus framework overhead, before any KV cache. The cache grows with context length and is added on top; the table above folds it in. Apple Silicon counts unified memory toward the same figure.
Does Gemma 3 12B Instruct run on an RTX 4090 (24 GB)?
Yes. Gemma 3 12B Instruct needs about 8 GB at Q4_K_M, inside a 24 GB card, at an estimated 72 tokens/sec.
How do I run Gemma 3 12B Instruct locally?
Install Ollama and run `ollama run gemma3:12b`. That pulls the weights and starts a local OpenAI-compatible endpoint; after the download nothing leaves the machine.
What other sizes does Gemma 3 come in?
Gemma 3 1B Instruct (1 GB), Gemma 3 4B Instruct (3 GB), Gemma 3 12B Instruct (8 GB), Gemma 3 27B Instruct (17 GB). Every size shares the family's training and licence; the larger ones score higher and need proportionally more memory.

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