Family Gemma · 31B parameters

Gemma 4 31B

Dense 31B multimodal (text+image+audio). 140+ languages, 256k context. #3 open model on Chatbot Arena.

🇺🇸 Google·License Apache 2.0·Context 250k tokens·Output April 2026·Fits within the 128 GB of the GIGABYTE AI TOP ATOM← Catalog

01What it can do

Strengths
  • #3 Chatbot Arena open
  • Native audio
  • 256k ctx
  • 140 languages
  • Apache 2.0
Limitations to know
  • —18 GB of VRAM in Q4: beyond the reach of 12–16 GB GPUs
Architecture
Dense 31B · text+image+audio multimodal · 256k ctx
Training
140+ languages.
Ideal for
Advanced multimodalAudio + visionWriting

04Install

Install Ollama for your OS. Check the model and its quantization before downloading. Start with 4096 tokens of context, then check placement with ollama ps. A command below is not proof that a test was run on your machine.

$ollama run gemma4:31b
⚠
First download: between 2 and 40 GB depending on the selected quantization. Plan for sufficient disk space; a stable connection is recommended. Subsequent launches are instant.

02Required memory

Approximate GPU VRAM required to run this model, including 4k tokens of context overhead. For a longer context, add ~1 GB per 8k-token increment.

Q4_K_M
The lightest, ~5% loss
18 GB
Q5_K_M
Good quality/size compromise
22 GB
Q8_0
Nearly indistinguishable from FP16
33 GB
FP16
Full precision — server use
62 GB
Fallback CPU · If you don't have a GPU, allow 32 GB of RAM minimum to run this model at reduced speed.

What hardware do you need for Gemma 4 31B?

To run Gemma 4 31B locally with Q4 quantization, you need about 18 GB of VRAM. An option to compare: GMKtec EVO-X2 64GB / 1TB (Ryzen AI Max+ 395) — leave some headroom for the system and context; check engine compatibility with the GPU.

Current offer: GMKtec EVO-X2 64GB / 1TB (Ryzen AI Max+ 395)
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Why this choice? Our complete guide on GMKtec EVO-X2 64GB / 1TB (Ryzen AI Max+ 395) →

Affiliate links — commission possible at no extra cost to you; independent recommendations. As an Amazon Associate, BestLLMfor earns from qualifying purchases.

On the go: Gemma 4 31B also runs on a RTX laptop PC (24 GB of VRAM) →

This model in your private ChatGPT, without the cloud

Your private ChatGPT, free, on your own machine in an hour — LM Studio, Ollama, Open WebUI, your documents, no cloud.

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03Expected speed

Tokens generated per second in Q4_K_M, 4k context. Beyond 20 t/s, reading is comfortable. Below 10 t/s, that's just for testing.

Entry-level
~3t/s
GTX 1650, RX 6600, MBA M2 8GB
Mid-range
~12t/s
RTX 4060, 4070, MBP M3 Pro
High-end
~30t/s
RTX 4090, M4 Max, Radeon 7900