PaliGemma Models by Google DeepMind
Details
Capabilities
About
PaliGemma is a family of open-source vision-language models (VLMs) developed by Google, emphasizing lightweight design and efficiency compared to other large language models. Built using open components, including the SigLIP vision model and the Gemma language model, PaliGemma models seamlessly process both images and text to deliver text outputs. This capability makes them well-suited for tasks such as image captioning, visual question answering, and object detection. Available in resolutions ranging from 224x224 to 896x896, these models are offered in various forms including pre-trained, mix, and fine-tuned versions to meet diverse research and practical needs. While useful for direct inference, they excel when fine-tuned for specific applications 13578.
Current Variants
Use-when guidance is derived from seed capabilities, context, release, and replacement fields.
Use when the workload needs 512 context, 3B parameters, and multimodal inputs.
Use when the workload needs 512 context and 3B parameters.
Use when the workload needs 128 context and 3B parameters.
| Model | Use when | Released | Signals | Status |
|---|---|---|---|---|
| PaliGemma 3B 896 | Use when the workload needs 512 context, 3B parameters, and multimodal inputs. | 2024-05 | 512 context3B parametersmultimodal inputs | Current |
| PaliGemma 3B 448 | Use when the workload needs 512 context and 3B parameters. | 2024-05 | 512 context3B parameters | Current |
| PaliGemma 3B 224 | Use when the workload needs 128 context and 3B parameters. | 2024-05 | 128 context3B parameters | Current |
Release Timeline
1 release groupSpecifications(3 models)
| Model | Released | Context | Parameters | Vision | Multimodal |
|---|---|---|---|---|---|
| PaliGemma 3B 896 | 2024-05 | 512 | 3B | Yes | Yes |
| PaliGemma 3B 448 | 2024-05 | 512 | 3B | No | No |
| PaliGemma 3B 224 | 2024-05 | 128 | 3B | No | No |
Available From(1 provider)
Frequently Asked Questions
- What is PaliGemma used for?
- PaliGemma is used for vision and multimodal work. The family description and listed model capabilities point to those workloads as the best fit.
- How does PaliGemma compare to Gemma 4?
- PaliGemma by Google DeepMind is strongest where you need vision and multimodal work, while Gemma 4 by Google DeepMind is the closest related family to check for multimodal. PaliGemma has 3 listed variants and reaches up to 512 context, while Gemma 4 reaches up to 256k context, so compare the specs and pricing tables before choosing a production model.
- Which PaliGemma model should I use?
- If price is the main constraint, use the pricing table first because PaliGemma does not have complete provider pricing in the local data. For the most capable/latest local choice, evaluate PaliGemma 3B 896 with 512 context and multimodal inputs.
