Google’s next Gemini Pro is months behind schedule as coding capabilities fall short of internal goals

Google is months behind schedule on delivering the next version of its flagship AI model, Gemini Pro, because the technology has fallen short of internal goals in coding, Bloomberg reported on Thursday citing 10 current and former employees. The company was widely expected to release the upgrade at its May developer conference but has been unable to close the gap with Anthropic and OpenAI, which have both released models that outperform Google’s current offerings in writing code. Alphabet shares slipped more than three percent on the news.

Late last month, Google updated the data used to train Gemini in an attempt to improve its coding abilities, but the results were disappointing, according to one of the people Bloomberg spoke with. Both OpenAI and Meta recently released new models that further outpace Google’s current AI for writing code, intensifying pressure on a team already struggling to ship. A Google spokesperson said the company is “shipping quickly across a wide range of models” and is testing the upgraded Pro, a new Flash model, and other models with partners.

Part of the problem is structural. Google Cloud, DeepMind, and the Android team are all building AI coding tools for developers, with involvement from consumer product teams as well, creating internal competition that has slowed progress. Co-founder Sergey Brin has been pushing for the company to move faster on AI coding, but his efforts have been hampered by competing factions and by engineers who believe important code should still be written by humans to meet Google’s standards, according to former employees.

Google has taken steps to consolidate its fragmented coding efforts. Chief AI Architect Koray Kavukcuoglu is working to unite the company’s internal AI coding tools, and a new team within DeepMind led by research engineer Sebastian Borgeaud has been formed specifically to tackle the problem. The company said at its most recent Cloud conference that 75 percent of code at Google is now AI-generated and that it has consolidated most of its developer tooling under Antigravity, the internal platform that manages data, memory, and safety protocols for AI applications.

The delays have contributed to a wave of senior departures to Anthropic and other labs, with former employees saying frustration with Google’s competitive position is a driving factor. Engineers who try to use AI for their own work often hit capacity constraints due to internal competition for computing power, a problem that extends to external customers as well. Only some teams inside Google are even allowed to use Anthropic’s Claude, with access restricted to groups doing cutting-edge research.

Customers waiting for the Pro upgrade have had mixed experiences with the current Flash model. Rodrigo Davies, a product manager at Figma, said the model hit “a sweet spot of speed and quality” for the design platform’s AI assistant. But Freddy Vega, CEO of Latin American education platform Platzi, said the Flash model is more expensive and slower than its predecessor while remaining far less capable than competitors, and his team has shifted to Anthropic instead.