Gemini 3 Flash is Google's lightweight multimodal model with 1M token context window, supporting text, image, video, and audio inputs for high-speed applications.
| Provider | Input / 1M | Output / 1M | Cached / 1M |
|---|---|---|---|
| $0.250 | $1.50 | - | |
| $0.500 | $3.00 | $0.050 |
Prices updated daily. Last check: Sep 6, 2026
Input, output, and batch rates, plus alternatives, for one provider at a time.
Benchmarks measured Sep 2026. Scores are independent evaluations, not vendor-reported.
Gemini 3 Flash is designed for applications requiring fast multimodal processing without the cost overhead of flagship models. Its large context window and multimodal capabilities make it suitable for content analysis workflows, document processing with mixed media, customer support chatbots that handle images and documents, and real-time applications where response speed is critical. The model works well for high-volume use cases like content moderation, automated social media responses, and educational applications that need to process various media types quickly. Its lightweight nature makes it cost-effective for startups and businesses that need capable multimodal AI without premium pricing.
Gemini 3 Flash pricing varies by provider and usage type (standard vs batch processing). Input and output tokens are typically priced differently for multimodal models. Check the pricing table above for current rates across all providers offering Gemini 3 Flash access.
Gemini 3 Flash excels at high-speed multimodal applications where cost efficiency matters. Its 1M token context window and support for text, image, video, and audio make it ideal for content analysis, document processing, customer support with media attachments, and real-time applications requiring fast responses across multiple content types.
Gemini 3 Flash stands out with its 1 million token context window, which is larger than most lightweight competitors, and native support for four modalities including video and audio. Its 180+ tokens per second output speed is competitive, though the 5+ second time to first token is slower than some alternatives optimized purely for text generation.