AI crypto market cap drops 13% to $6.42B amid investor sell-off
AI crypto market plunges 13%
The primary cause of the sector’s struggles is investor exits following the launch of DeepSeek AI and the ongoing market correction.
According to SpazioCrypto estimates, the AI-related crypto sector lost 13% of its market capitalization in the past 24 hours, dropping to $6.42 billion. Tokens like FARTCOIN, AI16Z, and VIRTUAL have been experiencing losses since last week, with no signs of recovery yet.
Top 10 AI Agents: Source CoinGecko
At the start of the year, VIRTUAL became a key player in the AI crypto sector, surpassing major projects like RENDER, FET, and TAO, reaching a market cap of $4.6 billion. However, it is now facing a sharp decline, with its valuation falling to $811 million.
Currently, only five AI agents have maintained a market cap above $300 million, while another 15 projects remain above the $100 million threshold, highlighting the scale of the correction affecting the entire crypto market.
Apathy and declining interest amid temporary setbacks
After a surge in early January, AI crypto agents' growth has slowed. Between January 7 and 24, their number increased from 1,250 to 1,387, an 11% rise. However, since then, only 13 new tokens have been launched, underscoring a gradual decline in interest in creating new AI agents. Additionally, activity in the sector has plummeted by 60%.
Among blockchains, Solana continues to dominate the AI agents market, with a total participant capitalization of $3.23 billion. Base Chain ranks second ($2.54 billion), driven by projects like TOSHI, AIXBT, VIRTUAL, and FAI. Ethereum is absent from the list of leading networks in this segment. Meanwhile, all other networks combined account for only $1.33 billion in market capitalization.
As we wrote, AI agents in crypto are autonomous systems that leverage artificial intelligence to analyze market data, execute trades, manage portfolios, and optimize strategies in the crypto market. These agents use machine learning, natural language processing, and predictive analytics to identify patterns, forecast trends, and make data-driven decisions in real-time. Common applications include algorithmic trading, risk management, fraud detection, and market sentiment analysis.
