12:00
10:00
09:00
07:48
19:00
13:35
12:00
10:00
09:00
07:48
19:00
13:35
12:00
10:00
09:00
07:48
19:00
13:35
12:00
10:00
09:00
07:48
19:00
13:35
Google has released Gemini 3.6 Flash and Gemini 3.5 Flash-Lite, while also confirming that training has started on Gemini 4, according to the company's blog.
Gemini 3.6 Flash replaces the previous 3.5 Flash model. According to Google's benchmarks, the new version uses 17% fewer output tokens based on Artificial Analysis metrics, with savings reaching 65% on some tests, including DeepSWE. The model is also cheaper, costing $1.50 per million input tokens and $7.50 per million output tokens.

For coding tasks, Gemini 3.6 Flash showed improved results, generating more production-ready code. Its score on DeepSWE increased from 37% to 49%, while performance on MLE Bench, a test focused on machine learning research tasks, grew from 49.7% to 63.9%. On GDPval-AA v2, which evaluates office-related tasks, the model scored 1421 points compared with 1349 for its predecessor. Performance on OSWorld-Verified, a computer-use benchmark, improved from 78.4% to 83%. Computer control is now available as a built-in tool in the Gemini API and Gemini Enterprise.

Google also highlighted improvements in safety. Gemini 3.6 Flash includes stronger protection against jailbreak attempts in sensitive areas, including chemical, biological, radiological, and nuclear (CBRN) risks, as well as cyberattacks. At the same time, the company says the model is less likely to refuse legitimate requests.
Gemini 3.6 Flash and Gemini 3.5 Flash-Lite are already available in the Gemini app, as well as for developers through Google AI Studio, Android Studio, and Gemini Enterprise. Gemini 3.5 Pro remains in testing with partners, with no public release date announced.
Google's AI team has also started what it calls its most ambitious pretraining effort ever for Gemini 4. The company has not yet revealed details about the next-generation model.
Gemini 3.5 Flash was first introduced at Google I/O in May. Read our full coverage on the model on our website:


