The race to build more capable AI models is shifting towards coding and AI agents and Google has rolled out its most intelligent workhorse model yet for the same. On August 13, the tech giant released a new version of its widely used Flash series, Gemini 3.7 Flash, designed to handle complex software engineering multi-step planning and enterprise workflows while keeping the cost of running AI agents low.
This release comes three weeks after the arrival of Gemini 3.6 Flash, and is a direct result of developer feedback and algorithmic innovations that the company aims to bring in future models.
While AI models are designed primarily to generate text or answer queries, Gemini 3.7 Flash leans heavily towards software engineering, coding, knowledge work, web development and agentic workflows. According to Google, the model is better at understanding instructions, planning multiple steps, using tools and adapting when it encounters problems.
How is Gemini 3.7 Flash different?
Perhaps the most noticeable change is the model's focus on complex workflows. Google said that Gemini 3.7 Flash improves on its predecessor when it comes to tasks like debugging, resolving software issues, and generating production-ready code. On the software-engineering benchmarks cited by Google, Gemini 3.7 Flash scored 43.6 per cent on FrontierCode 1.1 Main, compared with 34.4 per cent for Gemini 3.6 Flash. On DeepSWE v1.1, it scored 65.3 per cent, compared with 49 per cent for the previous model.
The improvements seem to extend to web development too. Google said that Gemini 3.7 Flash can generate more functional layouts and feature-complete apps with fewer prompts.
The model also shows high design adherence and parity, closely reproducing the design of a reference image, screenshot or design system.
For knowledge-dense fields like finance, law, and biosciences, 3.7 Flash delivers improved reasoning and accuracy. On the GDP.pdf benchmark, which tests the ability to understand complex documents, Gemini 3.7 Flash scored 34 per cent, compared with 22 per cent for Gemini 3.6 Flash.
It also surpasses 3.6 Flash in AutomationBench, demonstrating it can more effectively complete real-world business workflows, scoring 30.4 per cent compared with 17 per cent for its predecessor.
Why the focus on AI agents?
AI agents are finding increasing use across a range of domains. Google said that the new Gemini 3.7 Flash has been designed to ‘think more diligently' when dealing with tasks that require multi-step planning and tool calls.
The model is claimed to be better at adapting roadblocks and also asks for clarifications when needed, following instructions with precision.
These features make it particularly relevant for coding agents, enterprise automation and other applications where an AI system needs to complete a task rather than simply respond to a prompt.
The search giant added that it is also using the model to power Gemini Spark, its personal AI agent that can work continuously under a user's direction. Further, the company said that the updated model improves Spark's ability to use Google Workspace tools, consolidate files, draft emails and update status documents.
Cost and availability
Gemini 3.7 Flash comes with half the original 3.6 Flash cost per million tokens. It is available at an introductory price of $0.75 per million input tokens and $3.75 per million output tokens through December 31, 2026.
From January 1, 2027, those prices will increase to $1.50 per million input tokens and $7.50 per million output tokens.
Developers can access the model through Google's Gemini API, Google AI Studio, Android Studio and Google Antigravity. Enterprises can access it through Google's enterprise AI platforms, while individual users can use it through Gemini Spark with eligible Google AI Pro and Ultra subscriptions in supported markets.
The company has also updated the model's safeguards, including protections against misuse in the domains of chemical, biological, radiological and nuclear risks and cyber-related threats.
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