Introducing Gemini 3.7 Flash
Google introduced Gemini 3.7 Flash, an enhanced AI model for coding and agents, priced at half the cost of its predecessor with improved performance across multiple workflows.
Google has released Gemini 3.7 Flash, positioning it as its most capable model in the Flash series for coding and agent-based tasks. The update arrives three weeks after the launch of Gemini 3.6 Flash and incorporates developer feedback alongside algorithmic improvements. The model is offered at an introductory rate of $0.75 per million input tokens and $3.75 per million output tokens, half the original price of 3.6 Flash, making it more accessible for scaling production workflows.
Gemini 3.7 Flash demonstrates measurable gains over its predecessor in software engineering, web development, and knowledge-intensive fields. In coding benchmarks, it achieved a 43.6% success rate in FrontierCode 1.1 Main and 65.3% in DeepSWE v1.1, compared to 34.4% and 49.0% for 3.6 Flash, respectively. For web development, it generated more functional layouts and feature-complete applications with fewer prompts, outperforming 3.6 Flash on Arena.ai’s WebDev Arena with an Elo score of 1588 versus 1538.
The model also shows improved performance in processing complex documents, scoring 34.0% on the GDP.pdf benchmark compared to 22.0% for 3.6 Flash, and excels in real-world business workflows, achieving 30.4% on AutomationBench versus 17.0%. Developers report better adaptability to roadblocks, clearer intent clarification, and higher fidelity in following instructions, reducing the need for manual oversight and retries in engineering tasks.
Gemini 3.7 Flash is now available through December 31, 2026, at the introductory pricing, with standard rates increasing to $1.50 per million input tokens and $7.50 per million output tokens on January 1, 2027. It powers Google’s Gemini Spark agent, enhancing its efficiency in knowledge work and multi-step tasks within Google Workspace apps. The model includes updated safeguards against misuse in chemical, biological, radiological, nuclear, and cyber domains while supporting beneficial use cases.