Google launches Gemini 3.7 Flash – while flagship model stalls
Google has released Gemini 3.7 Flash, featuring significant advancements in coding and a low introductory price. Meanwhile, there is no word on the delayed flagship model, Gemini 3.5 Pro.
What happened?
Google has launched Gemini 3.7 Flash only three weeks after the previous Flash update. The new model shows significant improvements in coding benchmarks and is being released at an introductory price of USD 0.75 per million input tokens. Simultaneously, the flagship model, Gemini 3.5 Pro, remains several months behind schedule, and Google has not indicated whether it will be released at all.
Key facts
| Lanseringsdatum | 13 augusti 2026 |
|---|---|
| Introduktionspris input | 0,75 USD per miljon tokens |
| Modellversion | Gemini 3.7 Flash |
| Försenad modell | Gemini 3.5 Pro |
Why it matters
The event is notable as Google's budget and high-speed model is now two versions ahead of the company's intended flagship. Coding is an area where Google has lost ground to competitors such as OpenAI and Anthropic, making the significant strides in the Flash model crucial for retaining developers within its ecosystem.
Who is affected?
The launch primarily impacts software developers and companies building AI-driven applications who are seeking higher coding performance at lower operational costs. However, product developers awaiting Google's most advanced Pro model are being forced to adjust their roadmaps due to the flagship's delay.
Impact on the EU
The model is being distributed globally via Google Cloud and the Gemini API, making it available to developers and companies within the EU. It remains to be seen how the model's advanced coding capabilities will align with the requirements of the EU AI Act.
What else you should know
Google has chosen to focus heavily on the Flash series to meet the demand for fast and inexpensive models. Industry analysts speculate that the delay of the Pro model may be due to challenges with training scaling or a strategic shift towards more cost-effective AI agent architectures.
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