Google Releases Gemini 3.6 Flash, 3.5 Flash-Lite, and 3.5 Flash Cyber: A Cheaper, More Token-Efficient Flash Tier Built for Agentic Workloads

Developers building production agents need higher token efficiency, lower latency, and more reliable performance. Today, Google has released three new Gemini models . The lineup is Gemini 3.6 Flash, Gemini 3.5 Flash-Lite, and Gemini 3.5 Flash Cyber. All three sit in the Flash tier, which Google tunes for speed, cost, and high-volume agentic work rather than maximum reasoning depth.

Gemini 3.6 Flash is the new default workhorse. It builds on 3.5 Flash and targets coding, knowledge work, and multimodal tasks. The main point is efficiency. On the Artificial Analysis Index , 3.6 Flash uses 17% fewer output tokens than 3.5 Flash. On the DeepSWE benchmark by Datacurve , Google reports up to a 65% reduction. The model also takes fewer reasoning steps and tool calls per multi-step workflow.

Pricing moves down alongside efficiency. Gemini 3.6 Flash is priced at $1.50 per 1M input tokens and $7.50 per 1M output tokens. The output rate drops from the previous $9.00 on 3.5 Flash. Lower verbosity and a lower output price reduces the total cost per agentic task.

Quality gains accompany the efficiency gains. On DeepSWE, 3.6 Flash scores 49% versus 37% for 3.5 Flash. On MLE Bench, it reaches 63.9% versus 49.7%. On OSWorld-Verified, it hits 83.0% versus 78.4%. On GDPval-AA v2, a knowledge-work benchmark, it scores 1421 versus 1349. Computer use is now a built-in client-side tool through the Gemini API and Gemini Enterprise. Early customers including Hebbia and Harvey cite gains in document parsing, chart and data analysis, and report drafting.

Google is shipping 3.6 Flash with enhanced Frontier Safety safeguards. These cover Chemical, Biological, Radiological, and Nuclear (CBRN) and cyber-offense misuse. Full details are in the 3.6 Flash model card .

The interactive explainer below lets you compare each model against its predecessor and estimate token cost at your own volume.

Gemini 3.5 Flash-Lite is highlighted for low-latency and high-throughput jobs. Target use cases include agentic search and document processing. As measured by Artificial Analysis , it runs at 350 output tokens per second. Pricing is $0.30 per 1M input tokens and $2.50 per 1M output tokens.

The model clears the prior 3.1 Flash-Lite by wide margins. On Terminal-Bench 2.1, it scores 54% versus 31%. On GDM-MRCR v2, a long-context benchmark, it reaches 72.2% versus 60.1%. On GDPval-AA v2, it scores 1140 versus 642. Notably, Flash-Lite also beats the older 3 Flash on some evals. It leads on SWE-Bench Pro at 54.2% versus 49.6% and on OSWorld-Verified at 74.0% versus 65.1%.

Flash-Lite exposes configurable thinking levels: minimal, low, and higher. Developers can prioritize low-cost, low-latency execution for high-volume tasks. They can also engage higher thinking levels for multi-step subagent workloads. Computer use is a built-in tool here too.