Amid Google's executive shake-up, the company is still trying to keep up with the breakneck pace of AI model development.
On Thursday, the company announced Gemini 3.7 Flash, which it calls its most intelligent "workhorse" model to date for coding and agents. Google said in its announcement that the model offers substantial improvements in software engineering, knowledge work and development workflows.
To start, the model will be priced the same as Gemini 3.6 Flash, its cost-efficient model that it released in late July, at $0.75 per million input tokens and $3.75 per million output tokens. It's still undercut by OpenAI's lowest-cost model, GPT-5.6 Luna, at and $0.20 per million input tokens and $1.20 per million output tokens.
Google noted that the new model is a "direct result" of developer feedback and offers significant improvements over its predecessor in tasks such as debugging and resolving issues.
- The model also offers better first-pass code accuracy and improved generation of production-ready code: Both in the FrontierCode 1.1 Main and the DeepSWE v1.1coding benchmarks, 3.7 Flash saw improvements in score between 10 and 15 percentage points. - For developers, Google noted that the model is better at adapting to roadblocks, clarification and instruction following, as well as puts more effort into multi-step tasks and tool calling.
- The model also shows improvements in "knowledge-dense fields" like finance, law and biosciences, and outperforms 3.6 Flash on the GDP.pdf benchmarkfor processing complex documents by 12 percentage points. - The model also shows better adherence in user interface development, generating more functional layouts and apps from simple prompts than the previous generation.
Notably, Google said it shipped Gemini 3.7 Flash with updated safeguards against misuse for chemical, biological, radiological and nuclear use cases, as well as cyber offenses.
The model is available in Google Antigravity, its agentic software development platform, through the Gemini API via the Google AI Studio and Android Studio, and through its enterprise platforms. Additionally, the model will be integrated into Gemini Spark, Google's personal AI agent, for Google AI Pro and Ultra subscribers.
The model follows a significant executive shift at Google, in which two of the company's most influential figures, Demis Hassabis and Jeff Dean, announced big moves, with Hassabis shifting from CEO to chairman of DeepMind and chief scientist of Alphabet, and Dean leaving the company entirely to launch a new startup called Discovery Loop.
Despite making a big splash with the launch of Gemini 3 last fall, the company has since struggled to keep pace with the other frontier labs, both in terms of the latest models as well as agents and coding tools.
Our Deeper View #
Google has all the ingredients to make a big impact in AI. It has the brand equity laying the foundation for the modern internet, access to capital and compute resources, and a wide market reach among both enterprises and consumers. And there are a few things it can do to differentiate itself, as The Deep View's editor in chief Jason Hiner recently pointed out, including shipping a real rival to Claude Code, clarifying its brands, and using its ubiquity as an enterprise strength. Further, leaning into cost efficiency with Gemini Flash 3.7 could offer another advantage as the industry starts to reckon with massive inference bills. But most importantly, Google can't rest on its laurels. Though the company has critical advantages in compute, user trust, and research, those can't be the only things that it relies on to compete in AI, especially with frontier labs and neolabs alike moving at lightning speed.