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PaliGemma

Google's vision model built on Gemma, designed as a base for fine-tuning on a narrow task: captions, object detection, reading text.

Developer
Google, USA
First release
May 2024
Latest release
Nov 2024
Sizes
3B – 28B
License
Commercial use with conditionsGemma Terms of Use (commercial use allowed under usage rules)
Russian
Not stated
Ready-made builds
GGUF
Running
On your own serverAlso runs without a GPU
Industries
Science and research, Manufacturing and logistics
Deploy on your server Hugging Face

What it does

  • Fine-tuning for your own recognition task
  • Finding objects in photos
  • Reading text in images
  • Photo captions

Where it is used

ManufacturingRetailResearch teams

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. PaliGemma 2 (3B, 10B, 28B)
  2. PaliGemma 3B

How to run it

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 PaliGemma be used in a commercial project?

With conditions. License: Gemma Terms of Use (commercial use allowed under usage rules). Restrictions vary — region, company revenue, attribution requirements. Have a lawyer check the terms before a commercial launch.

What hardware does PaliGemma 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 PaliGemma 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 PaliGemma and what does it cost?

The PaliGemma 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.

Similar models

TextGemmaGoogle · USACommercial use allowed

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.

DetailsImage + textFlorence-2Microsoft · USACommercial use allowed

A very small vision model: captions, object detection, segmentation and text reading from a single prompt. Runs even on a CPU.

DetailsImage + textQwen-VLAlibaba (Qwen team) · ChinaCommercial use allowed

One of the strongest open vision models: reads documents, tables, charts and video, and works with user interfaces. Since Qwen3.5, vision is built directly into the main Qwen model.

Details

Source: huggingface.co/google/paligemma2-28b-pt-896. Data checked against the model card on 22 Sep 2026. Have a lawyer review the license before commercial launch.