Model Cards are intended to provide essential information on Gemini models, including known limitations, mitigation approaches, and safety performance. Model cards may be updated from time to time; for example, to include updated evaluations as the model is improved or revised. See theGoogle DeepMind sitefor a comprehensive list of model cards.
Gemini 3.8 Flash is the next iteration in the Gemini 3 model family, building on Gemini 3.7 Flash, delivering performance advancements across software engineering and agentic knowledge workflows. It continues to support customizable effort levels to control the mix of quality, cost and latency.
Gemini 3.8 Flash is based on Gemini 3.7 Flash.
Text strings (e.g., a question, a prompt, document(s) to be summarized), images, audio, and video files, with a token context window of up to 1M.
Gemini 3.8 Flash is based on Gemini 3.7 Flash. For more information about the model architecture for Gemini 3.8 Flash, see the Gemini 3.7 Flashmodel card.
Gemini 3.8 Flash is based on Gemini 3.7 Flash. For more information about the training dataset for Gemini 3.8 Flash, see the Gemini 3.7 Flashmodel card.
For more information about the training data processing for Gemini 3.8 Flash, see the Gemini 3.7 Flashmodel card.
Gemini 3.8 Flash is based on Gemini 3.7 Flash. For more information about the hardware for Gemini 3.8 Flash and our continuedcommitment to operate sustainably, see the Gemini 3.7 Flashmodel card.
Gemini 3.8 Flash is based on Gemini 3.7 Flash. For more information about the software for Gemini 3.8 Flash, Gemini 3.7 Flashmodel card.
Our models are available to downstream providers via an application program interface (API) and subject to relevant terms of use. There is no required hardware or software to use the model. For AI Studio and Gemini API, see theGemini API Additional Terms of Service; for Gemini Enterprise Agent Platform, seeGoogle Cloud Platform Terms of Service. For more information, seeGemini Model API instructionsandGemini API quickstart.
Gemini 3.8 Flash was evaluated across a range of benchmarks, including coding, knowledge work, multimodal capabilities, long-context, computer use, scientific reasoning. Additional benchmarks and details on approach, results and their methodologies can be found at:deepmind.com/models/evals-methodology/gemini-3-8-flash.
Results as of September, 2026 are listed below: