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Google replaces Gemini 3.5 Flash with 3.6 Flash

Google has launched Gemini 3.6 Flash, cut output token pricing, and added 3.5 Flash Lite and its first cybersecurity-focused model.

Image: Ars Technica

Google has already moved on from Gemini 3.5 Flash. Just weeks after making it the centerpiece of I/O in May, the company has deprecated the model and replaced it with Gemini 3.6 Flash, alongside Gemini 3.5 Flash Lite and Gemini 3.5 Flash Cyber, its first Gemini variant aimed at cybersecurity.

The delayed Gemini 3.5 Pro, which had been expected in June, is still missing.

Google chart showing Gemini 3.6 Flash evaluations
Google chart showing Gemini 3.6 Flash evaluations

Google says Gemini 3.6 Flash improves on 3.5 based on user feedback, especially around coding and multimodal use. In the DeepSWE coding test, it scored 49 percent, up from 37 percent for 3.5 Flash. In OSWorld, which measures computer-use performance, it reached 83 percent versus 78.4 percent for 3.5.

Efficiency remains the main pitch. Google says Gemini 3.6 Flash uses about 17 percent fewer tokens, and now supports computer use as a standard feature in the Gemini API. The company says that should let agentic workflows complete tasks more accurately, in fewer steps, and with fewer tokens.

Pricing has shifted slightly in developers' favor. Gemini 3.6 Flash costs $1.50/1M input tokens and $7.50/1M output tokens, compared with $1.50 and $9 for 3.5 Flash.

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Google also introduced Gemini 3.5 Flash Lite, which it calls its most efficient modern AI model, reaching 350 tokens per second. The company says it is suited to scaling agentic systems at lower cost. Pricing is $0.30/1M input tokens and $2.50/1M output tokens, up slightly from 3.1 Flash Lite at $0.25 and $1.50.

Ava Chen

AI Editor

Ava covers the rapidly evolving world of artificial intelligence, from foundational models and research labs to the real-world economics of intelligence. With a background in computational linguistics, she cuts through the hype to find out what actually works. She firmly believes that benchmarks are just marketing until reproduced in the wild.

via Ars Technica

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