TextImage + textCode

Gemma

Compact Google models that run well on a single computer; larger versions understand images. Includes CodeGemma for code, FunctionGemma 270M for function calling and the fast DiffusionGemma.

Developer
Google, USA
First release
Feb 2024
Latest release
Jun 2026
Sizes
270M – 31B
License
Commercial use allowedGemma 4 and DiffusionGemma: Apache 2.0; earlier versions, CodeGemma and FunctionGemma: Gemma Terms of Use
Russian
Not stated
Ready-made builds
GGUF, AWQ, GPTQ, MLX (Apple)
Running
Available in OllamaAlso runs without a GPU
Industries
Customer support, Documents and accounting, Retail and marketplaces
Deploy on your server Hugging Face GitHub

What it does

  • Offline assistant on a laptop
  • Reading photos of documents and receipts
  • Customer request classification

Where it is used

Small businessLow-end hardwareMobile devices

Hardware requirements

LaptopLaptop or regular PC, up to 8 GB of VRAM — smaller versions
fits
1 GPUOne GPU with 16–80 GB — mid-size versions
fits
ClusterServer with several GPUs — flagship versions
no versions

Versions

  1. DiffusionGemma 26B-A4B
  2. Gemma 4
  3. FunctionGemma 270M
  4. Gemma 3n
  5. Gemma 3
  6. Gemma 2
  7. CodeGemma
  8. Gemma

How to run it

With Ollama — the fastest wayInstall Ollama on your computer or server and find the model in its library by name. Good enough to try the model on your own tasks in one evening.Find it in the Ollama library
On your own serverWeights are downloaded from Hugging Face and served with vLLM (load and API) or llama.cpp (modest hardware). The model then runs in a closed network with no per-request fees.Hugging Face
How much hardware you needCalculate the VRAM for the model size, context length and number of concurrent requests.Open the hardware calculator

I can set this up end to end: pick the model size, deploy it on your server and connect it to your systems. Quantization compresses a model so it takes less video memory and runs on more modest hardware. Answers change slightly, so quality is checked on your own examples.

Frequently asked questions

Can Gemma be used in a commercial project?

Yes. License: Gemma 4 and DiffusionGemma: Apache 2.0; earlier versions, CodeGemma and FunctionGemma: Gemma Terms of Use. It allows commercial use, but it is still worth having a lawyer review the license before launch.

What hardware does Gemma need?

At minimum: Laptop or regular PC, up to 8 GB of VRAM — smaller versions. Some versions also run on an ordinary CPU, without a GPU. You can calculate the exact VRAM for your model size and context in the hardware calculator.

Does Gemma support Russian?

The model card does not list languages, so Russian support cannot be promised — it has to be tested on your own examples.

Where can I download Gemma and what does it cost?

The Gemma weights are open and free to download. You only pay for the hardware it runs on and for the setup. Source links are at the bottom of this page.

How I deploy it for clients

  1. SelectionI pick the model size for your task and hardware and test it on your examples.
  2. DeploymentI deploy it on your server or in a closed network and provide an API.
  3. Fine-tuningI fine-tune it on your data (LoRA) or connect a knowledge base — whichever is cheaper for the task.
  4. IntegrationI connect it to your CRM, ERP, bot, website or team chat and set up monitoring.

Comparisons

Similar models

TextQwenAlibaba · ChinaCommercial use with conditions

A family of language models with strong Russian language support, from small versions for a laptop to a flagship on par with commercial APIs.

DetailsTextLlamaMeta · USACommercial use with conditions

The models that started mass open source in AI. A huge ecosystem of fine-tuned versions and tools.

Details

Source: huggingface.co/google. Data checked against the model card on 22 Sep 2026. Have a lawyer review the license before commercial launch.