Stock Markets July 16, 2026 03:12 PM

Google's Gemini 3.5 Pro Release Slips as Internal Benchmarks Miss the Mark

Delay on flagship AI model comes amid intense competition and recent regulator-driven pauses at rival firms

By Avery Klein
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Google has pushed back the public launch of Gemini 3.5 Pro after internal testing showed the model did not meet performance targets, particularly in coding tasks. The postponement, disclosed in a recent report, has raised concerns inside the company while competitors continue to roll out new advanced models and navigate regulatory reviews.

Google's Gemini 3.5 Pro Release Slips as Internal Benchmarks Miss the Mark
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Key Points

  • Gemini 3.5 Pro, Google’s most advanced flagship AI model, is delayed by months after failing to meet internal performance benchmarks.
  • The model was expected in June following an announcement by the CEO at the I/O developer event in May.
  • The delay and competitive pressure are affecting Alphabet’s stock price and have implications for AI development, cloud services and enterprise AI adoption.

Google is running behind on the planned release of Gemini 3.5 Pro, its most capable flagship artificial intelligence model, after internal evaluations found the system fell short of expectations, according to a recent report.

The model had been slated for a June release, a timeline the company’s chief executive announced at its annual I/O developer conference in May. The delay has stretched into months as Google works to address shortcomings highlighted during testing.

Within the company, the setback has prompted concern among engineers, researchers and managers who worry about competing models from other developers that have demonstrated stronger performance, the report said, citing the views of 10 current and former employees.

Google undertook a data refresh late last month intended to improve Gemini’s capabilities, with particular emphasis on coding proficiency. Those updated training data and subsequent results did not deliver the improvements engineering teams had expected, the report added.

  • The model was announced for a June release by the CEO at the I/O conference in May.
  • Internal unease stems from rival models released by competitors that are considered to outperform Gemini.
  • Google updated the model’s training data late last month, but the outcomes remained below internal targets.

Market reaction was swift: shares of Alphabet fell nearly 3% after the information was reported.

"We’re currently testing 3.5 Pro, an upgraded Flash model, and other models with partners, and we’re productively engaged with the U.S. government," a company spokesperson said in a statement.

"We’re shipping quickly across a wide range of models while keeping them highly cost-effective for customers," the spokesperson added.

The broader AI landscape remains active. OpenAI introduced GPT-5.6 last week following a delay that was prompted by requests from the U.S. government about potential national security risks associated with powerful AI technology.

Separately, Anthropic temporarily disabled its most advanced offerings, Mythos 5 and Fable 5, after a June 12 U.S. export control order cited national security concerns. Those restrictions were removed in late June after Anthropic implemented additional safeguards.


These developments underscore an industrywide push to boost model performance, reduce operational costs and expand capabilities for enterprise customers while also responding to heightened regulatory scrutiny. Google says it continues product testing and partner collaborations as it works toward meeting its internal performance goals for Gemini 3.5 Pro.

Risks

  • Product development risk: Continued underperformance in model testing could postpone release timelines and affect Google’s competitiveness in AI - impacts technology and cloud sectors.
  • Market reaction risk: Share-price volatility can follow reports of setbacks, as evidenced by Alphabet shares slipping nearly 3% after the report - impacts capital markets and investor sentiment.
  • Regulatory and national-security risk: Government scrutiny of advanced models can delay launches and force capability restrictions, as seen with OpenAI and Anthropic - impacts AI developers and enterprise customers dependent on cutting-edge models.

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