Gemini 3.5 model releases

A specialized, highly efficient cybersecurity model built on Gemini 3.5 Flash and fine-tuned to find and fix software vulnerabilities at a lower price per token than larger models. Deployed inside Google's CodeMender agent, where multiple 3.5 Flash Cyber agents collaborate to produce a single combined report, reaching competitive frontier performance on the CyberGym benchmark. Given its dual-use nature, it is not generally available: access is limited to governments and trusted partners via CodeMender as part of a limited-access pilot program.

Google DeepMind's fastest and most cost-effective 3.5-class model, released July 21, 2026 for low-latency and high-throughput agentic workloads like agentic search and document processing. Runs at ~350 output tokens/s (Artificial Analysis) with configurable thinking levels and built-in computer use, priced at $0.30 / $2.50 per 1M input/output tokens. Multimodal over a 1M-token context and a large step up on 3.1 Flash-Lite: Terminal-Bench 2.1 54% (vs 31%), GDM-MRCR v2 72.2% (vs 60.1%), GDPval-AA v2 1140 (vs 642); on several agentic and coding evals it even surpasses 3 Flash (SWE-Bench Pro 54.2% vs 49.6%, OSWorld-Verified 74.0% vs 65.1%). Available in the Gemini API (AI Studio, Android Studio), Gemini Enterprise, the Gemini app, and rolling out in Google Search.

Google's fast, cost-efficient Gemini 3.5 tier, unveiled at I/O 2026. Multimodal over a 1M-token context and tuned for agentic and coding workflows; Google says it beats Gemini 3.1 Pro on coding and tool-use while running ~4x faster.