Google launches Gemini 3.6 Flash, 3.5 Flash-Lite, and Flash Cyber

Google launches Gemini 3.6 Flash, 3.5 Flash-Lite, and Flash Cyber

Google's three new Gemini Flash models split the work between higher-quality general tasks, low-cost high-throughput processing, and restricted cybersecurity research.

Google splits the Gemini Flash tier by workload

Google DeepMind announced three Gemini models on July 21: Gemini 3.6 Flash for higher-quality general work, Gemini 3.5 Flash-Lite for low-latency scale, and Gemini 3.5 Flash Cyber for controlled vulnerability research. The announcement also says Gemini 3.5 Pro is still being tested with partners and that Gemini 4 pre-training has begun. 1
ModelIntended jobWhat changesAccess and limits
Gemini 3.6 FlashCoding, knowledge work, multimodal tasks, and computer useGoogle says it uses 17% fewer output tokens than 3.5 Flash, with lower listed pricing of $1.50 per 1M input tokens and $7.50 per 1M output tokens.Available through the Gemini API, Google AI Studio, Android Studio, Antigravity, the Gemini app, and enterprise products. The benchmark figures are vendor-reported.
Gemini 3.5 Flash-LiteAgentic search, document processing, and other high-throughput tasksGoogle cites 350 output tokens per second from Artificial Analysis, plus configurable thinking levels. Pricing is $0.30 per 1M input tokens and $2.50 per 1M output tokens.Available through the Gemini API, Google AI Studio, Android Studio, and the Gemini app; a Google Search rollout is gradual. Its speed and cost focus make it a scaling model, not a universal replacement for a stronger reasoner.
Gemini 3.5 Flash CyberFinding and patching software vulnerabilitiesA 3.5 Flash variant tuned for CodeMender, where multiple agents work together on one security report. Google describes its CyberGym result as frontier-level but does not publish a score in the announcement.A limited-access pilot for governments and trusted partners because the model is dual-use. It is not a general public API model.
The 3.6 Flash story is efficiency with a quality step up. Google reports 49% on DeepSWE versus 37% for 3.5 Flash, 63.9% versus 49.7% on MLE Bench, and 83.0% versus 78.4% on OSWorld-Verified. Those are useful signals for coding, machine-learning work, and computer use, but they remain claims from the launch material rather than independent leaderboard results. The official X announcement summarizes the same positioning: fewer tokens for higher-quality work, a cheaper high-speed option, and a security model for critical vulnerabilities. 2
For developers, the important change is portfolio design. A single Flash label now covers three different operating points: spend more for broader capability, spend less for throughput, or accept restricted access for specialized cyber defense. That gives teams a clearer way to match model choice to workload, but it also makes simple model rankings less useful. The next checks are real-world latency and cost, independent evaluations, and whether CodeMender's security results generalize beyond Google's pilot.
Google's forward-looking notes are deliberately thin: Gemini 3.5 Pro remains in partner testing, while Gemini 4 has entered pre-training with no release date disclosed. 1
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