Google’s AI Breakthrough with Gemini 3 Shakes Up Tech Industry

Google’s latest AI model, Gemini 3, has surged to the top of performance benchmarks, drawing public acknowledgments from rivals Nvidia and OpenAI while sparking significant market movements.

Industry Recognition Signals Shift

In a notable development, both Nvidia and OpenAI’s CEO Sam Altman publicly congratulated Google on its Gemini 3 achievement. Nvidia stated they “continue to supply to Google” while emphasizing their chips offer “greater performance, versatility, and fungibility than ASICs” like Google’s Tensor processors.

“Congrats to Google on Gemini 3! Looks like a great model,” OpenAI CEO Sam Altman also wrote on X.

Salesforce CEO Marc Benioff declared he’s “not going back to ChatGPT” after trying Gemini 3, calling the leap “insane” with everything “sharper and faster.”

Market Impact and Strategic Moves

The AI advancements translated directly to market performance, with Google shares climbing nearly 8% last week as Nvidia’s declined over 2%. The competition extends beyond stock prices, as Meta is reportedly in talks to purchase Google’s Tensor chips, following Anthropic’s October announcement to expand Google technology use.

“They’re in the lead for now, let’s call it, until somebody else comes up with the next model,” Angelo Zino, senior vice president and technology lead at CFRA, told CNN.

Google’s AI Resurgence

Despite Google’s long AI history dating to the early 2000s, the company was caught off-guard by ChatGPT’s 2022 debut, prompting a “code red” response. While ChatGPT maintains 800 million weekly users versus Gemini’s 650 million monthly users, Gemini 3’s benchmark dominance marks a significant turnaround.

Gemini 3, launched November 18, now leads in text generation, image editing, and text-to-image capabilities, outperforming ChatGPT, Grok, and Claude in these categories.

The Chip Battle Intensifies

The competition extends to hardware, where Nvidia currently dominates with 62% sales growth and 65% profit increases. However, Google’s Tensor chips represent a different approach—ASICs designed for specific tasks versus Nvidia’s versatile GPUs.

Experts note that while ASICs like Google’s serve “narrower workloads,” Nvidia’s comprehensive packages including software and networking chips create significant competitive advantages.

“If you look at the magnitude of Nvidia’s offerings, nobody really can touch them,” said Ted Mortonson, technology desk sector strategist at Baird.

While Google’s chips won’t replace Nvidia soon, increased ASIC adoption suggests companies are seeking to diversify beyond Nvidia dependence in the rapidly expanding .