Google Gemini 3.5 Pro Delayed as Coding Performance Falls Short
Google has delayed Gemini 3.5 Pro, its most powerful flagship AI model, after the system fell short of internal coding benchmarks following a late-June training data refresh. The model was scheduled to ship in June 2026 after its announcement at Google I/O in mid-May, but that deadline passed with no firm release date. Alphabet’s stock dropped approximately 4% in intraday trading after the news broke.
Why It Matters
Google had spent the past year in an unusually strong position. Gemini 3 turned skeptics around, the Gemini app passed 750 million monthly active users, and Alphabet broke through a $4 trillion valuation on the strength of that momentum. At I/O 2026 in May, the company arrived with aggressive pricing and a full roadmap, and Gemini 3.5 Pro was the headline item on that roadmap. CEO Sundar Pichai said on stage that the more powerful Pro model would land in June. Gemini 3.5 Flash went live the same day. Pro did not follow.
The delay lands at a moment when competitive pressure is relentless. OpenAI shipped GPT-5.6 last week, its most advanced model yet. Anthropic continues releasing models that push the frontier. Chinese labs are shipping frontier-adjacent models at a fraction of the cost, including Zhipu’s GLM 5.2, which matches Opus 4.8 on coding benchmarks at a fifth of the price. The ground keeps shifting, and a missed launch window is expensive in that context.
What Went Wrong
Coding is the sticking point. According to reporting that cited 10 current and former employees, Google updated the data used to train Gemini late last month specifically to improve coding skills. The results fell short of expectations, and internal frustration is running high. The problems extend beyond code generation: token efficiency, AI agentic features, and the model’s ability to handle long-horizon tasks have all been flagged as structural challenges. There have even been discussions about scrapping previous base models entirely and rebuilding from scratch, which suggests the issues run deeper than typical fine-tuning adjustments.
The coding focus is no accident. As of April, 75% of all new code at Google is now AI-generated and approved by engineers, up from 50% last fall. The company is deeply invested in AI coding tools across multiple divisions. Google DeepMind runs AI Studio, Cloud operates Vertex, and the Android team has its own effort inside Android Studio. An effort to unite the company’s internal AI coding tools is currently underway, and Pichai himself has acknowledged that Google runs “a bit behind” on agentic coding. A dedicated DeepMind coding team has been formed to close that gap.
Some engineers inside Google have taken a more purist stance, arguing that all important code should be human-written to adhere to Google standards, according to former employees. That internal tension, combined with AI capacity restraints on internal tools, adds another layer of complexity to an already difficult engineering challenge.
Google’s next flagship AI model missed its launch window because it could not meet internal coding benchmarks, showing even trillion-dollar AI leaders face real engineering limits.
The Numbers
- June 2026: The original launch window for Gemini 3.5 Pro, announced on stage at Google I/O in mid-May. The deadline passed with no update.
- Approximately 4%: Alphabet’s intraday stock drop after news of the delay broke.
- 75%: Share of all new code at Google that is now AI-generated and approved by engineers, up from 50% last fall.
- 10: Current and former employees who described internal frustration to reporters.
- 750 million: Monthly active users on the Gemini app, a milestone that signaled strong consumer adoption.
- $4 trillion: Alphabet’s valuation breakthrough earlier this year, driven by positive AI sentiment.
“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. We’re shipping quickly across a wide range of models while keeping them highly cost-effective for customers.”
Google spokesperson, in a statement to Reuters
What Comes Next
Google has not provided a new launch date, but some sources have pointed to a potential mid-July window, possibly around July 17, though that depends entirely on whether current improvement efforts succeed. The company says it is testing 3.5 Pro with partners alongside an upgraded Flash model and other unreleased systems. A new variable in the release calculus is the U.S. government. OpenAI’s GPT-5.6 launch was delayed by government requests over national security concerns about misuse of powerful AI. Anthropic disabled its most advanced models, Mythos 5 and Fable 5, for all users following a June 12 export control order, and those curbs were only lifted in late June after the company added safeguards. Google’s statement explicitly mentions being “productively engaged with the U.S. government,” signaling that frontier model launches now clear two sets of gates, and only one of them is technical.
Internally, the push to unify coding tools and build a dedicated DeepMind coding team will likely accelerate. The fact that Gemini 3.1 Pro dates back to February means the gap between Google’s last major Pro-tier release and whatever ships next is already stretching past five months, an eternity in the current AI release cycle.
What This Means for You
The AI tools you use every day, whether a coding assistant, a writing companion, or a search summarizer, are shaped by these development cycles at the major labs. When a flagship model misses its launch window, the downstream effect is that the next generation of consumer-facing AI features gets pushed back too. Google’s delay is a reminder that the AI industry is still working through real engineering constraints. Progress is fast but uneven, and not every roadmap item lands on time.
For anyone following the broader AI race, the delay also highlights how competitive the coding domain has become. When a company with Google’s resources and internal AI adoption rate struggles to hit its own coding benchmarks, it underscores just how difficult it is to build models that write production-quality code reliably. The models that do ship, like Moonshot’s Kimi K3 with 2.8 trillion parameters, are setting a high bar. Meanwhile, Google’s own guidance on how AI search will reshape content signals that the company is still thinking strategically about the AI landscape even as it works through technical setbacks on the model side.
The Bigger Picture
The Gemini 3.The 5 Pro delay is a product slip. It also signals that frontier AI development is entering a phase where engineering quality and real-world reliability matter more than announcement schedules. Google has the talent, the infrastructure, and the internal demand to get this right. The question is whether it can do so before its competitors widen the gap, and before investors lose patience with AI spending that does not produce shipped product. For now, the model is still in testing, the government is watching, and the entire industry is waiting to see what ships next.
Sources
- Reuters: Google Gemini launch delayed as tech falls short of internal goals
- Bloomberg: Google Gemini Launch Delayed as Tech Falls Short of Internal Goals
- CNBC: Alphabet stock drops on Gemini 3.5 Pro delay report
FAQ
Why was Gemini 3.5 Pro delayed?
Gemini 3.5 Pro was delayed because it fell short of Google’s internal coding benchmarks after a late-June training data refresh meant to sharpen coding skills produced disappointing results. Reported issues also include token efficiency, AI agentic features, and the model’s ability to handle long-horizon tasks.
When was Gemini 3.5 Pro originally supposed to launch?
Gemini 3.5 Pro was scheduled to launch in June 2026, a timeline announced by CEO Sundar Pichai on stage at Google I/O in mid-May. As of mid-July 2026, no firm new release date has been set, though some sources have pointed to a potential mid-July window around July 17.
How did the market react to the Gemini 3.5 Pro delay?
Alphabet’s stock dropped approximately 4% in intraday trading after news of the delay broke, reflecting investor sensitivity to AI roadmap execution at a company trading at a $4 trillion valuation.