The Gemini 3.5 Pro delay has rattled Wall Street and the global developer community, sending Alphabet shares down more than 4% in a single trading session after Bloomberg reported that Google’s most powerful AI model is months behind its original schedule. For Pakistani developers and businesses that have bet their workflows on Google’s AI stack, the news is a reminder that even the world’s biggest tech company can fall behind in a fast-moving race.
What Actually Happened with the Gemini 3.5 Pro Delay
Google first showed off Gemini 3.5 Pro at Google I/O in May 2026 and promised a June launch. That deadline came and went. A July 17 target then circulated widely in tech media, but that date has also passed with no public release. As of the latest information on Google’s Gemini platform, there is still no model card, no pricing page, and no public listing for Gemini 3.5 Pro in the Gemini API documentation.
According to Bloomberg’s reporting, the core problem is coding performance. Google updated the training data for the model in late June in an attempt to fix weak coding skills, but the results were disappointing. That appears to have reset the development timeline entirely.
What makes this especially notable is the number of missed deadlines. This is the third consecutive external deadline the model has missed, not simply a routine slip. First it was June, then July 17, and now there is no confirmed date at all. Google’s official response has been measured: the company says it is currently testing Gemini 3.5 Pro with select partners and is productively engaged with the US government on model testing, but it has not given users or developers a firm launch window.
Why the Gemini 3.5 Pro Delay Hurt Alphabet’s Stock Price
Alphabet shares fell more than 4% on July 16 as investors absorbed the Bloomberg report. The reaction was sharp because Gemini 3.5 Pro is seen as a crucial product for Alphabet to stay competitive in the enterprise AI market. A months-long delay raises concerns that Google is losing ground to its rivals, which could threaten its long-term market share in AI applications.
The timing could hardly be worse. GPT-5.6 from OpenAI reached general availability on July 9, offered in three tiers and described by OpenAI as setting a new benchmark on agentic coding tasks. Anthropic’s Claude Fable 5 launched July 1 after clearing an export-control review. Grok 4.5 from SpaceXAI also went live in early July. That means Google is now the only major frontier AI lab without a 2026 flagship model in general production on a date its own leadership publicly promised.
Adding to the pressure, Alphabet’s Q2 2026 earnings are due on July 22. Any perceived weakness in cloud growth or AI momentum going into that report is making investors especially cautious right now.
The Internal Problem Most Coverage Is Missing
Beyond the headline of a missed launch date, there is a deeper story inside Google that explains why the Gemini 3.5 Pro delay happened. According to 10 current and former employees cited in Bloomberg’s reporting, the delay has been a source of real frustration among Google engineers, AI researchers, and managers. Many are worried the company risks losing its competitive edge as rivals produce models that outperform Gemini on key tasks.
Part of the problem is structural. Google has multiple layers of stakeholders involved in getting a model ready for release, because the AI has to work across a vast product portfolio including Search, Maps, and YouTube. That complexity can slow things down in ways that a more focused AI lab simply does not face.
There is also a cultural dimension that most coverage has skipped over. Some Google engineers hold a strong view that important code should be written by humans, not generated by AI, to meet Google’s internal quality standards. That internal resistance has slowed the push to use AI coding tools aggressively inside the company, even as rivals have moved faster. At the same time, Google’s own figures show that 75% of all new code at the company is now AI-generated and approved by engineers, a figure that has grown sharply. The gap between those two realities created friction at a critical moment in Gemini 3.5 Pro’s development.
Where Google Still Has an Edge
It would be wrong to write Google off. The company’s existing Gemini 3.1 Pro remains a strong model, particularly for multimodal tasks involving images, video, and very large documents. Google also argues it has strengths in AI world models that can mimic physical environments, and its deep integration with Search, YouTube, and Android gives Gemini a distribution advantage that no other AI lab can easily replicate.
Analysts at BMO Capital actually raised their price target on Alphabet stock to $455 even after the delay news broke, suggesting that long-term confidence in the company remains intact. Berkshire Hathaway has also built a position in Alphabet worth over $26 billion, a signal that some of the world’s most careful investors still see long-term value here.
Meanwhile, Google is not standing still. It has released Gemini Omni Flash to developers via the Gemini API, and it continues testing Gemini 3.5 Pro with partners. The company says it is also working on an upgraded Flash model alongside the Pro version.
What This Means for Pakistani Developers and Businesses
Pakistan’s freelance and software development community is one of the biggest users of AI coding tools in South Asia. Many Pakistani developers use Gemini through Google AI Studio, which offers a generous free tier and direct API access. Businesses running on Google Cloud also rely on Vertex AI and the Gemini Enterprise stack.
The practical impact of the Gemini 3.5 Pro delay is straightforward: if you were planning to upgrade your workflows to Gemini 3.5 Pro this summer, you will need to wait longer with no confirmed date. In the meantime, the current Gemini 3.1 Pro remains available and is genuinely strong for multimodal and long-context tasks. If coding is your primary need, it may be worth exploring Anthropic’s Claude Sonnet 5, which independent benchmarks show outperforms GPT-5.5 on professional software engineering tasks at a lower price point.
For developers building products or client projects on a deadline, the lesson here is to avoid building a hard dependency on any single model that has not yet been officially released. The AI model landscape is moving fast enough that even well-funded, world-class engineering teams miss their own launch windows. Plan with what is available today, and treat upcoming releases as a bonus rather than a given.
If you want to stay current on how AI models compare in real use for Pakistani tech businesses, our earlier look at the Kimi K3 open-weight AI model covers another strong alternative that costs far less than frontier models from Google or OpenAI.
Frequently Asked Questions
Why is the Gemini 3.5 Pro delay happening?
Google has confirmed it is still testing the model with partners. Bloomberg’s reporting, citing multiple current and former employees, says the main issue is that the model has not met internal standards for coding performance. A late-June attempt to fix this by updating training data did not produce the hoped-for results, effectively resetting the timeline.
How much did Alphabet shares fall because of the delay?
Alphabet shares fell more than 4% on July 16, 2026, the day Bloomberg published its report on the delay. Shares continued to slide into July 17 as well, extending the two-day loss.
What AI models are available right now instead of Gemini 3.5 Pro?
OpenAI’s GPT-5.6 is live as of July 9 across ChatGPT and the API. Anthropic’s Claude Fable 5 and Claude Sonnet 5 are both available. Grok 4.5 from SpaceXAI launched on July 8. Google’s existing Gemini 3.1 Pro is also still accessible via the Gemini API and AI Studio for developers who need it today.
Should Pakistani developers stop using Gemini because of this delay?
Not necessarily. The Gemini 3.5 Pro delay is about a single upcoming model, not about the existing Gemini ecosystem. Gemini 3.1 Pro, Gemini 3.5 Flash, and Gemini Omni Flash are all still available and useful. The key advice is simply not to build critical product timelines around a model release that has no confirmed launch date yet.
