AIThis post was created with the assistance of artificial intelligence (AI).

TL;DR

Google’s Gemini 3.5 Pro AI model remains unreleased past multiple deadlines, causing a $425 billion market value decline. The delay underscores risks in AI race leadership.

Google has not yet released its Gemini 3.5 Pro AI model, despite multiple announced deadlines in July 2026, leading to a market cap loss of approximately $425 billion. This delay is significant because it impacts Google’s position in the AI race and investor confidence.

On May 19, 2026, Google announced at I/O that Gemini 3.5 Pro would be available in June. However, as of this week, the model remains unreleased, with internal sources and third-party reports indicating the project is months behind schedule. Bloomberg reported on July 16 that the delay is due to efforts to improve coding capabilities, a key area where competitors like OpenAI and Anthropic have gained an edge. Google declined to comment on the specific reasons for the delay.

The market reacted strongly: Alphabet’s stock fell 4.4% the day after Bloomberg’s report, equating to roughly $200 billion in lost market capitalization. Combined with an earlier $225 billion selloff in June following departures of DeepMind researchers, the total decline exceeds $425 billion within a month. Despite these losses, Google’s Q1 2026 financials remained strong, with revenues of $109.9 billion and cloud growth of 63%, indicating the market’s concern is primarily about leadership and future potential rather than current financial health.

At a glance
reportWhen: ongoing; delays announced in July 2026…
The developmentGoogle’s Gemini 3.5 Pro AI model has been delayed multiple times, resulting in a significant market cap loss and raising questions about its development timeline.

Impact of AI Development Delays on Market Leadership

The delay of Gemini 3.5 Pro illustrates the high stakes of AI development for tech giants. Market capitalization is being repriced based on the perceived leadership gap, with investors fearing that falling behind in flagship AI models could diminish Google’s competitive edge and revenue potential. The $425 billion loss demonstrates how market confidence is tightly linked to timely innovation in this sector.

Amazon

AI development kit

As an affiliate, we earn on qualifying purchases.

As an affiliate, we earn on qualifying purchases.

Recent AI Development and Market Reactions

Google announced Gemini 3.5 Pro at I/O in May, aiming for a July release. Multiple reports suggest the project is facing technical challenges, including issues with reliability and hallucination rates, leading to repeated delays. Meanwhile, competitors like GPT-5.6 Sol and Grok 4.5 launched publicly in early July, capturing market attention. Google’s internal efforts to rebuild and improve Gemini 3.5 have not met deadlines, and the company has not officially confirmed the specifics of the delays or the technical setbacks.

The market’s response underscores the importance of flagship AI models in maintaining leadership. As other models ship and gain traction, Google’s absence in the flagship space during this critical period has contributed to the steep valuation decline, despite stable financials in other areas.

“Google’s Gemini 3.5 Pro is months behind schedule, primarily over efforts to improve coding capabilities, with disappointing results from recent training data updates.”

— Bloomberg, Julia Love and Davey Alba

Amazon

AI coding training software

As an affiliate, we earn on qualifying purchases.

As an affiliate, we earn on qualifying purchases.

Unconfirmed Technical Details and Future Timelines

It remains unclear when Gemini 3.5 Pro will finally be released, as multiple deadlines have passed without confirmation or official updates. The specifics of the technical issues, such as reliability problems or hallucination rates, are based on third-party reports and are not officially confirmed by Google. The impact of these delays on Google’s long-term AI leadership is also uncertain, as competitors continue to release models and capture market share.

AI Systems Performance Engineering: Optimizing Model Training and Inference Workloads with GPUs, CUDA, and PyTorch

AI Systems Performance Engineering: Optimizing Model Training and Inference Workloads with GPUs, CUDA, and PyTorch

As an affiliate, we earn on qualifying purchases.

As an affiliate, we earn on qualifying purchases.

Next Steps for Google’s AI Strategy and Market Recovery

Google is expected to provide an official update on Gemini 3.5 Pro’s development timeline soon. Market analysts will monitor whether the company can meet revised deadlines and restore investor confidence. Meanwhile, competitors’ models continue to ship, increasing pressure on Google to accelerate its AI roadmap. The coming months will be critical in determining if Google can regain its leadership position or face further valuation impacts.

AI Engineering: Building Applications with Foundation Models

AI Engineering: Building Applications with Foundation Models

As an affiliate, we earn on qualifying purchases.

As an affiliate, we earn on qualifying purchases.

Key Questions

Why has Google delayed the Gemini 3.5 Pro release?

According to reports, the delay is due to technical challenges related to improving coding capabilities and reliability issues, which have required significant rebuilding efforts. Google has not officially confirmed these reasons.

How does this delay affect Google’s market position?

The delay has led to a $425 billion decline in market capitalization, reflecting investor concern that Google is falling behind competitors in flagship AI models, which are crucial for maintaining industry leadership.

Are competitors’ models available now?

Yes, models like GPT-5.6 Sol and Grok 4.5 have been publicly launched in early July, capturing market attention and demonstrating the rapid pace of AI development outside of Google.

Will Google’s financial performance be affected long-term?

While current financials remain strong, the long-term impact depends on whether Google can successfully launch Gemini 3.5 Pro and maintain its leadership in AI innovation. Market confidence is closely tied to timely releases.

Source: ThorstenMeyerAI.com

You May Also Like

Capital: The Lever Beneath the Levers

Analysis of how capital funding shapes AI infrastructure and markets, highlighting risks and circular financial flows in 2026.

AI in Financial Services Work: Analysts and Advisors Augmented

Boost your financial expertise with AI-augmented tools that revolutionize analysis and advisory work—discover how to stay ahead in a competitive market.

Unlocking AI Potential With Meta’s Muse Glimmer: Local, Agentic, And Open Source

Meta has launched Muse Glimmer, a 30-billion-parameter open-source multimodal model for local AI agents, supported immediately by Hugging Face frameworks.

Exelon Positioned For Capturing Consequential Growth And AI Tailwinds

Exelon is positioned to benefit from significant growth opportunities and AI advancements, according to recent analysis. Key details and implications explained.