// HACKER NEWS — CYBERSECURITY
Gemini 3.7 Flash
Our most intelligent workhorse model yet for coding and agents.
Senior Director, Product Management, on behalf of the Gemini team
Today, we’re building on the progress of our widely used Flash series by introducing Gemini 3.7 Flash, our most intelligent workhorse model yet for coding and agents.
This release comes just three weeks after Gemini 3.6 Flash, and is a direct result of developer feedback and algorithmic innovations that we look forward to bringing to future models. 3.7 Flash delivers substantial improvements across software engineering, knowledge work, and web development workflows — with an introductory price of half the original 3.6 Flash cost per million tokens.
3.7 Flash shows strong gains over 3.6 Flash in coding tasks like debugging and issue resolution. It also achieves higher first-pass code accuracy and has improved performance in generating production-ready code as seen in FrontierCode 1.1 Main (43.6% vs 34.4%) and DeepSWE v1.1 (65.3% vs 49.0%).
In web development, 3.7 Flash generates more functional layouts and feature-complete apps in fewer prompts. For UI generation, the model shows high design adherence and parity based on a reference input, whether it’s a screenshot, an image, or a full design system. It outperforms 3.6 Flash on Arena.ai’s WebDev Arena with an Elo score of 1588 vs 1538.
For knowledge-dense fields like finance, law, and biosciences, 3.7 Flash delivers improved reasoning and accuracy. It significantly outperforms 3.6 Flash on the GDP.pdf benchmark (34.0% vs 22.0%), an eval for testing a model’s ability to process complex documents. It also surpasses 3.6 Flash in AutomationBench, demonstrating it can more effectively complete real-world business workflows (30.4% vs 17.0%).
From a simple text prompt to a fully playable 3D game. We used Gemini 3.7 Flash combined with Nano Banana to dynamically generate characters, items, and textures in real-time.
Stunning, interactive landing pages generated in a single shot. We used Gemini 3.7 Flash to orchestrate sub-agents, using Gemini Omni to create smooth, interactive parallax components.
A robotics model getting trained with Gemini 3.7 Flash using multimodal understanding in a 3 agent graph loop that helps the robot learn faster.