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TL;DR
Google’s Gemini 3.5 Pro AI model remains unreleased past multiple deadlines, causing a $425 billion drop in market value. The delay underscores the economic impact of AI development setbacks.
Google’s Gemini 3.5 Pro AI model has not been released as scheduled, despite multiple public promises, resulting in a $425 billion loss in market value for Alphabet.
This delay highlights the financial risks associated with AI development setbacks and the market’s sensitivity to project progress.
On May 19, 2026, Google announced that Gemini 3.5 Pro would launch in June, but the model remains unreleased as of mid-July. Bloomberg reported on July 16 that the project is months behind schedule, primarily due to challenges in improving coding capabilities, an area where competitors like OpenAI and Anthropic have made advances.
Following the Bloomberg report, Alphabet’s stock dropped 4.4%, erasing approximately $200 billion in market capitalization. Combined with a prior $225 billion selloff in late June linked to departures from DeepMind, the total market value lost exceeds $425 billion within a month, despite the company’s strong Q1 financials, including $109.9 billion in revenue and a 63% increase in Google Cloud revenue.
Google has not officially confirmed the delays or the reasons behind them. Reports suggest that the company may be discarding a near-ready model and restarting pre-training on a native Gemini 3 foundation, citing issues like hallucination rates and reliability problems. All specific technical details, such as the model’s token window or release dates, remain unconfirmed.
The cost of absence
now has a number: ~$425B.
Gemini 3.5 Pro has missed three deadlines since Google I/O. Bloomberg (Jul 16, ten sources): months behind, coding the sticking point. The market’s verdict came in two selloffs — with zero change to reported fundamentals.
Two selloffs, one story
That’s what absence costs when a market prices it: not countable lost deals — a repricing of whether the company still sets the pace.
Three deadlines, zero launches
Rebuild, hallucination, and stopgap-Flash details rest on third-party reporting Google has not confirmed — labeled accordingly.
Contracts sign on schedules, not roadmaps. Pressure from above (shipped flagships) and below (monthly open-weight cadence): the floor rises whether or not the ceiling does.
- Holding may be right: if the reliability reporting is even directionally true, shipping broken costs more than shipping late. Restarting a failed model is judgment, not weakness.
- Narrative cuts both ways: $425B evaporated on story; Google’s distribution didn’t shrink. A strong launch restores on story too.
- Watch what shipped: Gemini Flash-class models are out — and topping at least one independent document-parsing leaderboard. Small-and-available beating large-and-promised is this week’s thesis wearing a Google badge.
Economic Impact of AI Development Delays
The $425 billion market cap decline illustrates how investor confidence is highly sensitive to AI project progress, especially for major players like Google. The delay not only affects Google’s valuation but also signals to the industry the risks of ambitious AI development timelines. The market’s reaction underscores the importance of timely delivery and reliable performance in maintaining corporate valuation and competitive positioning in the rapidly evolving AI landscape.
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Google’s AI Development Timeline and Market Expectations
Google announced Gemini 3.5 Pro at Google I/O on May 19, 2026, with a scheduled launch for June. However, the model has not shipped as of mid-July, with reports indicating that the project is months behind schedule due to difficulties in enhancing coding capabilities—an area where competitors like OpenAI’s GPT-5.6 and Grok 4.5 have already launched.
Historically, Google has led in AI research, but delays in flagship models can significantly impact its market perception. The absence of a 2026 flagship model in general production, despite strong financials in other divisions, shows how delays in core AI projects can influence overall valuation and competitive standing.
Market reactions reflect a broader trend: shipping available, tested models can sometimes be more profitable than delayed, unreliable ones. The recent launches of GPT-5.6 and Grok 4.5 demonstrate that competitors are actively shipping advanced models, putting pressure on Google’s timeline and market positioning.
“The model is months behind schedule, primarily over efforts to improve its coding capabilities, with disappointing results from recent training updates.”
— Bloomberg, Julia Love and Davey Alba
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Unconfirmed Technical Details and Future Timeline
Specific technical details, such as the model’s token window size, exact release date, and whether the project has been restarted from scratch, remain unconfirmed. It is also unclear when Google will finally release Gemini 3.5 Pro or whether the delays will extend further.
Market analysts are uncertain about the full impact of these delays on Google’s competitive positioning in AI, especially as other companies continue to ship advanced models.
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Next Steps in Google’s AI Development and Market Impact
Google is expected to provide an official update on Gemini 3.5 Pro’s status in upcoming earnings or product announcements. The company may also accelerate testing or consider alternative approaches to meet market expectations. Meanwhile, the industry will closely watch how delays affect Google’s market share and investor confidence, especially as competitors like OpenAI and Anthropic continue to ship new models.
Investors and industry observers will likely assess whether Google’s delayed AI flagship will eventually meet its promised capabilities or if further setbacks are imminent.
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Key Questions
Why has Google delayed Gemini 3.5 Pro?
According to reports, the delay is primarily due to challenges in improving the model’s coding capabilities and reliability issues such as hallucination rates. Google has not officially confirmed these reasons.
How much market value has Google lost due to the delays?
Google’s market capitalization has decreased by approximately $425 billion within a month, combining a $200 billion drop after the Bloomberg report and a prior $225 billion selloff related to DeepMind departures.
What does this delay mean for Google’s competitive position?
The delay puts Google behind competitors who have already shipped advanced AI models, potentially impacting its leadership in AI innovation and investor confidence.
Will Google still release Gemini 3.5 Pro?
It remains unconfirmed when or if Google will release Gemini 3.5 Pro. The company has not provided an updated timeline, and technical challenges continue to be reported.
What are the broader industry implications of this delay?
The delay underscores the risks of ambitious AI development timelines and highlights how market perception can be heavily influenced by project progress, regardless of current financial performance.
Source: ThorstenMeyerAI.com
