gemini-3.1-flash-lite-preview β API, Pricing & Context Window | Vivgrid
gemini-3.1-flash-lite-preview on Vivgrid: Google's lightweight multimodal model with a ~1M-token context window at a very low price.
gemini-3.1-flash-lite-preview is Google's lightweight, low-cost Gemini model, tuned for high-volume multimodal workloads. It keeps a ~1.05M-token context window and accepts text, image, video, audio, and PDF inputs.
On Vivgrid it is served as a globally centralized model through the same unified, OpenAI-compatible API used across the catalog.
Specifications
| Provider | |
| Model ID | gemini-3.1-flash-lite-preview |
| Best for | General-purpose |
| Context window | 1,048,576 tokens |
| Max output | 65,536 tokens |
| Modalities | Text, Image, Video, Audio, Pdf |
| Tool / function calling | Yes |
| Knowledge cutoff | 2025-01 |
| Acceleration | π Global (Centralized) |
Pricing
Pricing in USD per 1M tokens, matching the provider's rates.
| Input | Cached input | Output |
|---|---|---|
| $0.25 | β | $1.50 |
Quick start
Call gemini-3.1-flash-lite-preview through Vivgrid's unified, OpenAI-compatible endpoint. Get an API key from the Vivgrid Console.
curl https://api.vivgrid.com/v1/chat/completions \
-H "Authorization: Bearer $VIVGRID_API_KEY" \
-H "Content-Type: application/json" \
-d '{
"model": "gemini-3.1-flash-lite-preview",
"messages": [
{ "role": "user", "content": "Say hello in English, Chinese and Spanish." }
],
"stream": true
}'Ideal use cases
- Very high-volume multimodal classification and extraction
- Cost-sensitive media ingestion pipelines
- Lightweight assistants needing large context
- Bulk PDF, image, and audio triage
Related models
- gemini-3.5-flash β faster, higher-quality flash
- gemini-3.1-pro-preview β the pro-tier model
- gpt-5.4-nano β comparable ultra-low-cost option
gemini-3.1-pro-preview
gemini-3.1-pro-preview on Vivgrid: Google's high-end multimodal coding model with a ~1M-token context window across text, image, video, audio and PDF.
gemini-3-pro-preview
gemini-3-pro-preview on Vivgrid: Google's high-end multimodal model with a 1M-token context window across text, image, video, audio and PDF.