Google is reportedly months behind schedule on the next version of its flagship Gemini Pro AI model, as the system has struggled to meet internal goals for coding.
Bloomberg reported on Thursday, citing 10 current and former employees, that Google has been unable to close the gap with rivals such as Anthropic and OpenAI in AI-assisted code generation. Reuters, citing the Bloomberg report, said Gemini 3.5 Pro is Google’s most powerful flagship AI model and is currently delayed as the company works to improve its capabilities, especially in coding.
Google was widely expected to release the upgraded Gemini Pro model after its May developer conference.
On May 19, Google introduced Gemini 3.5 Flash and said Gemini 3.5 Pro was already being used internally, with a rollout planned for the following month.
However, the Pro model has still not been released publicly. Reuters reported that the model had been due in June, based on comments from Alphabet CEO Sundar Pichai during Google I/O.
The biggest reported issue is coding performance.
Bloomberg reported that Google updated the training data for Gemini late last month to improve coding, but the results still fell short of expectations. The setback has reportedly worried some Google engineers, AI researchers, and managers as competitors continue to release stronger coding models.
OpenAI and Anthropic have both released models that outperform Google’s current offerings in writing code, according to the report.
Alphabet shares fell after the delay report. Reuters said Alphabet shares slipped nearly 3 percent following the report, while MarketWatch reported a drop of more than 4 percent on Thursday as investors reacted to concerns that Google is falling behind in the AI race.
The delay is also reportedly tied to Google’s internal structure.
Google Cloud, DeepMind, Android, and consumer product teams have all been working on AI coding tools, creating overlapping efforts inside the company. According to the report, that internal competition has slowed progress.
Co-founder Sergey Brin has reportedly pushed the company to move faster in AI coding. However, former employees said his efforts have run into competing internal factions and resistance from engineers who believe important code should still be written by humans to meet Google’s standards.
Google has started bringing more of its AI coding work under one structure.
Chief AI Architect Koray Kavukcuoglu is reportedly working to unify the company’s internal AI coding tools. A new DeepMind team led by research engineer Sebastian Borgeaud has also been formed to focus on the problem.
Google has also said that 75 percent of its new code is now generated by AI and reviewed by engineers. The company has consolidated much of its developer tooling under Antigravity, an internal platform that manages data, memory, and safety protocols for AI applications.
The delays have reportedly contributed to senior engineers leaving Google for Anthropic and other AI labs.
Former employees cited frustration with Google’s competitive position as one reason behind the exits. Engineers trying to use AI tools internally also reportedly face capacity limits because teams are competing for compute power.
The report said the compute issue also affects some external customers. Inside Google, only some teams are allowed to use Anthropic’s Claude, and access is limited to groups working on advanced research.
Customers waiting for the Gemini Pro upgrade have had mixed experiences with Google’s current Flash model.
Rodrigo Davies, a product manager at Figma, said the Flash model offers a strong balance of speed and quality for the company’s AI assistant. However, Freddy Vega, CEO of Latin American education platform Platzi, said Flash is slower and more expensive than its predecessor while still being less capable than competing models. His team has shifted to Anthropic instead.
Google said it is still moving quickly. A company spokesperson told Reuters that Google is currently testing 3.5 Pro, an upgraded Flash model, and other models with partners. The spokesperson also said Google is shipping quickly across a wide range of models while keeping them cost-effective for customers.
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