PaliGemma 3B 896
PaliGemma 3B 896 is worth evaluating for vision when its provider route and context window match the workload.
Use it for
- Teams evaluating vision
- Workloads that can use a 512 context window
- Buyers comparing 1 tracked provider route
Do not use it for
- Strict JSON or tool-calling flows
Cheapest of 1 route · NVIDIA NIM
About
PaliGemma 3B 896 is a versatile and lightweight vision-language model developed by Google, designed to process and integrate both images and text. Inspired by the PaLI-3 model, it employs components like the SigLIP vision model and the Gemma-2B language model, featuring a linear projection layer for seamless integration of visual and textual inputs. Capable of handling tasks such as image captioning, visual question answering, object detection, and segmentation, it supports multilingual text processing. Despite requiring task-specific fine-tuning for optimal performance, PaliGemma highlights strong capabilities across various vision-language applications, although it may encounter challenges with contextual understanding, biases, and computational demands 124.
PaliGemma 3B 896 is an open-weight model in the PaliGemma family. The structured metadata tracks a 512-token context window and multimodal input. This page tracks provider routes through NVIDIA NIM. No headline benchmark score is tracked for PaliGemma 3B 896 yet.
Top use-case fit
Vision
Included by capability and metadata signals in the decision map.
Provider price ladder
Compare API pricing across 1 providers for input and output tokens, batch, and cached reads when available.
| Provider | Input / 1M | Output / 1M | Route |
|---|---|---|---|
| NVIDIA NIM | - | - | ProvisionedPartial |
Available via routers & gateways(1)
Capabilities
Benchmark peer barsfor Vision
No task-mapped benchmark peers are available for this model yet.
Migration checks
No linked migration route is available for this model yet.
Cheapest of 1 route · NVIDIA NIM