Gemini 3.8 Flash

Gemini 3.8 Flash is Google’s newest generally available Flash model, released September 2, 2026.

Verified model facts

Google documents a 1,048,576-token input limit, 65,536-token output limit, text/image/video/audio/PDF input, thinking, function calling, structured outputs, code execution and computer-use support.

Current status

It is active in the Gemini API with introductory pricing through the end of 2026.

Best fit

It is best for coding agents, complex enterprise automation and high-volume multimodal workflows.

Limitations

Pricing increases in 2027, computer use remains a preview capability and Google does not state a knowledge-cutoff date on the current model page.

Gemini 3.8 Flash capabilities and use cases

In addition, its main capabilities include 1M context, 65K output, Thinking, Function calling, Structured outputs and Code execution. For example, common use cases include Coding, Agents, Enterprise automation, Research and Multimodal document analysis.

Who should consider Gemini 3.8 Flash?

In practice, this model may suit Coding agents, Autonomous agents, Enterprise workflows, Multimodal analysis and Long-context tasks. Also, notable strengths include Newest GA Flash model, Low introductory price, 1M context and Strong tool suite. However, review trade-offs such as Can still hallucinate or make agent mistakes, Computer use remains preview and Knowledge cutoff is not stated on the model page before adopting it.

Gemini 3.8 Flash pricing and access

Meanwhile, Introductory pricing through December 31, 2026 is $0.75 per 1M input tokens and $3.75 per 1M output tokens. Standard prices rise to $1.50 and $7.50 from January 1, 2027. Through December 2026, standard API pricing is $0.75/M input and $3.75/M output, with lower Batch/Flex rates.

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 General Purpose 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 3.8 Flash 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.