Gemini 3.5 Flash-Lite

Gemini 3.5 Flash-Lite is a current AI model verified from first-party Google sources.

Gemini 3.5 Flash-Lite verified specifications

Gemini 3.5 Flash-Lite is Google’s low-latency, cost-efficient GA model for high-volume agents, parsing, translation and simple data processing. Its verified context or usage limit is 1048576 tokens, with 65536 tokens maximum output.

Gemini 3.5 Flash-Lite pricing and access

Gemini 3.5 Flash-Lite costs $0.30 per 1M multimodal input tokens and $2.50 per 1M output tokens, with a free tier available.

Gemini 3.5 Flash-Lite best uses

High-volume agents, Data extraction, Document parsing, Translation, Classification.

Gemini 3.5 Flash-Lite limitations

Not designed for maximum reasoning quality, Tool costs can add up, No image generation.

Gemini 3.5 Flash-Lite capabilities and use cases

In addition, its main capabilities include 1M context, 65K output, Multimodality, Function calling, Structured outputs and Code execution. For example, common use cases include Automation, Extraction, Translation, Classification and Subagents.

Who should consider Gemini 3.5 Flash-Lite?

In practice, this model may suit High-volume agents, Data extraction, Document parsing, Translation and Classification. Also, notable strengths include Low price, GA status, Large context and Broad inputs. However, review trade-offs such as Not designed for maximum reasoning quality, Tool costs can add up and No image generation before adopting it.

Gemini 3.5 Flash-Lite pricing and access

Meanwhile, Gemini 3.5 Flash-Lite costs $0.30 per 1M multimodal input tokens and $2.50 per 1M output tokens, with a free tier available. Low standard pricing of $0.30/M input and $2.50/M output makes it suitable for high-volume automation.

Official resources and verification

Use the official model website, official documentation, pricing or release source and additional primary source to confirm current availability, limits and pricing. Product details can change after publication, so rely on primary documentation for final decisions.

Compare with other AI models

Next, continue your research in the AI models directory, Google models and Multimodal Language Model models. Compare providers, pricing, modalities and practical limitations side by side to choose the right model for your workflow.

How to evaluate Gemini 3.5 Flash-Lite responsibly

First, test the model with a small set of realistic tasks before relying on it for production work. Also, check response quality, consistency, latency, supported file types, context limits and the effort required to review its output. For sensitive or regulated work, examine the provider’s privacy, data-retention, regional-processing and security documentation before submitting private information.

However, AI systems sometimes return incomplete, outdated or confidently incorrect information. Therefore, check important claims against trusted sources and test generated code before deployment. Pricing, quotas and model availability can also change without notice. Finally, revisit the official documentation before you plan a long-term integration or a large-volume workload.