Google Launches Three Gemini Models, Begins Gemini 4 Pre-training

Google DeepMind Releases Three Gemini Models

Google DeepMind announced three new Gemini models in a single release, targeting production AI agents with improved speed, cost, and specialized capabilities.

Gemini 3.6 Flash: Token Efficiency and Performance Gains

The flagship Gemini 3.6 Flash focuses on reducing token consumption. According to Artificial Analysis Index, it uses 17% fewer output tokens than 3.5 Flash overall, and up to 65% fewer tokens on the DeepSWE coding benchmark . It also requires fewer reasoning steps and tool calls for multi-step tasks, making it both faster and cheaper.

Pricing is lowered to $1.50 per million input tokens and $7.50 per million output tokens , cheaper than 3.5 Flash.

Benchmark improvements over 3.5 Flash:

DeepSWE (coding): 37% → 49%

MLE Bench (ML research): 49.7% → 63.9%

OSWorld-Verified (computer control): 78.4% → 83%

GDPVal-AA v2 (knowledge work): 1,421 tasks completed, 70+ more than previous generation

Demos show 3.6 Flash orchestrating multiple agents for complex code migration, generating 3D workflows via Gemini Canvas (e.g., a photography-grade texture extraction tool), and acting as an AI interaction designer for immersive theme studios.

Gemini 3.5 Flash-Lite: Speed and Cost for High-Volume Workloads

Gemini 3.5 Flash-Lite prioritizes throughput and cost. It outputs at 350 tokens per second , the fastest in the 3.5 series, with pricing at $0.30 per million input tokens and $2.50 per million output tokens . It is designed for high-frequency, high-volume scenarios like massive document processing and agent search.

Despite being a lighter model, it outperforms the larger Gemini 3 Flash on several benchmarks:

SWE-Bench Pro: 54.2% vs 49.6%

OSWorld-Verified: 74.0% vs 65.1%

The article suggests a dual-model architecture : 3.6 Flash as the "planner" decomposing tasks, and multiple Flash-Lite instances as "workers" executing in parallel, demonstrating the generation of 25 production-ready web designs in rapid succession. Flash-Lite is already available in the Gemini App and will roll into Google Search.

Gemini 3.5 Flash Cyber: Specialized Vulnerability Detection and Remediation

Gemini 3.5 Flash Cyber is a dedicated cybersecurity model for finding and fixing vulnerabilities. Integrated into the CodeMender security agent, multiple Cyber agents collaborate to achieve state-of-the-art on the CyberGym benchmark at lower cost than larger models. The model addresses the growing gap where AI discovers vulnerabilities faster than existing systems can patch them. This model is not yet publicly accessible.

Gemini 4 Pre-training Underway: "Most Aggressive Ever"

Alongside the three releases, Google confirmed that pre-training for Gemini 4 has begun , described as the "most aggressive pre-training in Google's history." Following Google's typical six-month training cycle, Gemini 4 could appear by year-end. The article notes that while the flagship 3.5 Pro is still pending, the immediate practical value for developers lies in the reduced costs and token usage of the newly released models.

Reference: https://blog.google/innovation-and-ai/models-and-research/gemini-models/gemini-3-6-flash-3-5-flash-lite-3-5-flash-cyber/?utm_source=tw&utm_medium=social&utm_campaign=og