Alphabet shares fall on report its most powerful AI model Gemini 3.5 Pro is delayed
π Alphabet shares fell 4% following reports that the Gemini 3.5 Pro AI model release has been delayed by several months.
π» The delay is driven by coding capabilities falling short of internal expectations, a key area where rivals currently lead.
π Competitors like OpenAI and Meta recently debuted new models that outpace Google's current offerings in generating software code.
ποΈ The model was previously announced at the May Google I/O conference but will not be ready for broader rollout until later than expected.
π° An Alphabet spokesperson confirmed the company is testing upgraded Flash models while keeping them cost-effective for customers.
π€ Google stated it is productively engaged with the U.S. government regarding its AI initiatives despite the technical delays.
βοΈ Meta's Muse Spark 1.1 and OpenAI's GPT-5.6 Sol are cited as examples of rivals offering superior agentic and coding performance.
π The report highlights that code generation has become a primary use case for major AI model providers in the open-source ecosystem.
- Alphabet maintains engagement with the U.S. government on AI initiatives, indicating continued strategic alignment with public sector needs.
- The company is actively testing upgraded Flash models alongside the delayed 3.5 Pro, suggesting a diversified portfolio of available AI tools.
- A spokesperson affirmed the commitment to keeping AI models highly cost-effective for customers, addressing a key competitive metric.
- Alphabet shares sank 4% immediately following the news of the Gemini 3.5 Pro delay, indicating negative market reaction to the setback.
- The flagship model's coding capabilities were reported as short of internal expectations, exposing a weakness in a critical high-value use case.
- Google is now months behind schedule on its most powerful AI model while rivals like OpenAI and Meta have already debuted superior coding models.
- Competitors are successfully pitching their AI models as more cost-effective relative to performance, potentially eroding Google's value proposition in the enterprise market.