Meta's Alexandr Wang Taunts Google's Gemini After AI Benchmark Win

Meta’s highest paid employee Alexandr Wang recently shared a post on X (formerly Twitter) taunting Google’s Gemini model. Wang was responding to a leaderboard shared by an X user – Tae Kim depicting Meta's Muse Spark 1.1 outperforming the world's biggest internet company’s latest AI model – Gemini 3.6 Flash. “Google getting beaten by @alexandr_wang this early, when Meta's new AI team is tiny in comparison, is absolutely embarrassing for Google,” the post stated. The chart quoted in the post from Artificial Analysis Intelligence Index showed top models like Anthropic’s Claude Fable 5 and OpenAI’s GPT-5.6 (59) leading, with Gemini 3.6 Flash scoring 50 while Meta's entry ranks higher in reasoning, coding, and agentic tasks. Alexandr Wang shared the post on his timeline, writing “gemini who?”, underscoring Meta's rapid AI progress since his high-profile 2025 hire from Scale AI. For those unaware, Mark Zuckerberg hired Alexandr Wang as Meta's Chief AI Officer after a reported $15 billion deal.

What is Meta Muse Spark

Muse Spark is the company’s first model developed by Meta Superintelligence Labs which is led by Alexandr Wang. Earlier this month, Meta launched Muse Spark 1.1 as a new version of Muse Spark – a multimodal AI model designed for agentic coding. Announcing the model then, the company said: “Muse Spark 1.1 delivers exceptional performance in personal agentic tasks that require planning and orchestration across a range of external apps and services”.

Google brings Gemini 3.6 Flash

Alexandr Wang’s comment on Gemini model comes on the same day when Google launched Gemini 3.6 Flash, claimed to be “more efficient and better quality than 3.5 Flash”. “Gemini 3.6 Flash builds directly on developer and customer feedback from 3.5 Flash. 3.6 Flash not only delivers a step up in coding and knowledge work, but it does this while meaningfully improving token efficiency,” Google said in its official announcement. Stating how Gemini 3.6 Flash is better than the previous model – Gemini 3.5 Flash, the company said:

3.6 Flash delivers higher precision with fewer unwanted code edits and reduced execution loops, as seen in DeepSWE (49% vs. 37%), and shows significant improvement in ML Research, as seen in MLE Bench (63.9% vs. 49.7%).

It has improved computer use capabilities as seen in OSWorld-Verified (83.0% vs. 78.4%). Computer use is now a built-in client side tool via the Gemini API and Gemini Enterprise.

It outperforms 3.5 Flash in knowledge work, as shown by benchmarks like GDPval-AA v2 (1421 vs. 1349). Customers like Hebbia and Harvey have found it particularly capable at multimodal tasks like document parsing, chart and data analysis, and report drafting.