The AI arms race has hit a significant roadblock for Google. The release of Gemini 3.5 Pro, the company's most powerful flagship model, has been delayed by several months. The primary cause is a failure to meet internal performance goals, specifically regarding software coding capabilities.
The Coding Performance Gap
According to Bloomberg reports, Google is struggling to close the gap with OpenAI and Anthropic, both of which have released models that outperform Google's current offerings in code generation. Despite an update to the training data in late June, results remained disappointing. This is a critical failure given that coding proficiency is essential for enterprise adoption and the development of autonomous agents, an area where competitors like Grok 4.5 are aggressively competing.
Google rolls out AI model "Gemini Pro", "Gemini Ultra" to beat GPT-4 — https://the-decoder.com/google-rolls-out-ai-model-gemini-pro-gemini-ultra-to-beat-gpt-4/
Structural Friction and Internal Competition
The delay is as much organizational as it is technical. Alphabet suffers from fragmented efforts, with Google Cloud, DeepMind, and the Android team all building competing AI coding tools. This internal rivalry has slowed overall progress. While co-founder Sergey Brin has pushed for faster development, he faces resistance from engineers who believe critical code must still be written by humans to maintain Google's rigorous standards.
Market Impact and Brand Consolidation
The financial markets reacted sharply, with Alphabet shares slipping and some reports indicating a market cap loss of approximately $225 billion. To stabilize the situation, Google is consolidating its developer tooling under 'Antigravity,' an internal platform for data and safety protocols, while Chief AI Architect Koray Kavukcuoglu works to unite the fragmented coding initiatives.
How Gemini 3 Pro Became 2025’s Top All-Round AI Model | LucasGraphic — https://lucasgraphic.com/posts/how-gemini-3-pro-became-2025s-top-all-round-ai-model
As part of a broader effort to unify its AI identity, Google has also rebranded NotebookLM as Gemini Notebook. This tool now includes code execution for data analysis, providing a functional win while the Pro model remains in testing.
Balancing Power and Safety
The delay of Gemini 3.5 Pro comes at a time when Google is under scrutiny for AI safety, following reports of jailbroken Gemini instances being used for cybercrime. The decision to postpone the launch may therefore be a strategic move to ensure that proprietary code does not leak into training sets and that the model's output is reliable enough for professional software engineering.