Author: Wu Talks Blockchain
What are the top three questions users will ask about cryptocurrency in 2025? We conducted a user survey using AI large models, asking the same question to different models: 'What are the three most frequently asked questions about cryptocurrency in the year 2025?'
To minimize homogenized answers due to models retrieving information from the internet, and considering that large models typically cannot and are not allowed to provide verifiable statistics and disclosures about their training data, we added a note to the question: 'Please do not perform real-time searches and do not cite specific articles, only respond based on your understanding of long-term discussion patterns.'
ChatGPT
1. How far can this bull market go? Is Bitcoin already close to its peak?
2. Is there still real Alpha in this round of the market, and how can ordinary users make money?
3. Do current popular projects or tracks have long-term survival capability, and is there structural harvesting?
X Grok
1. Is the market in a bull or bear phase after Bitcoin halving?
2. What are the most worthwhile crypto assets or tracks to invest in 2025?
3. How is the performance of Ethereum spot ETFs and the inflow of institutional funds?
Perplexity AI
1. How might Bitcoin's price evolve in 2025?
2. How to identify and avoid cryptocurrency-related scams?
3. How will ETF and regulatory progress affect the crypto market?
Claude
1. Is now the right time to buy or sell Bitcoin or Ethereum?
2. Is a certain crypto project a scam, and can it be trusted?
3. How should new users start investing in cryptocurrency and manage risk?
Gemini 3
1. Which crypto projects have real-world application value (RWA)?
2. How will current and future regulatory policies affect personal asset security?
3. Among Ethereum L2, Solana, and AI + Crypto, which technical route might become the final winner?
DeepSeek
1. Is the current market in a bull or bear phase?
2. Which crypto sectors or assets will have the most potential in 2025?
3. How will changes in regulatory policies affect asset security and investment decisions?
Bean Bag
1. Has a new round of the cryptocurrency bull market arrived?
2. How will changes in regulatory policies in various countries affect ordinary investors?
3. What does the Bitcoin halving market mean for retail investment strategies?
Qianwen
1. How will the price trend evolve after Bitcoin halving?
2. Have Ethereum and mainstream public chains made substantial breakthroughs in practical applications?
3. How will regulatory policies in various countries affect the legal use of cryptocurrencies?
Wenxin Yiyan
1. How will global cryptocurrency regulatory policies change?
2. Do Bitcoin and mainstream crypto assets have long-term investment value?
3. Can the application scenarios of cryptocurrency in the real world really be realized?
Kimi
1. Can retail investors stabilize profits through high-frequency trading in the crypto market?
2. How should private keys and wallet assets be stored for maximum security?
3. In on-chain trading, how to set slippage to avoid MEV losses?
Summary
The reason why the 'top three questions' given by these models are not completely the same may relate to their respective positioning and context. ChatGPT is more like standing from the trader's perspective, organizing the discussion into a 'how far can the cycle go - is Alpha still there - is there structural harvesting' type of semi-structured anxiety chain; Grok is closer to social platform hotspots, focusing on market narrative centers around halving, bull-bear, and ETF funds; Perplexity's style resembles a retrieval-type summary, concentrating on price trends, anti-fraud, and ETF/regulatory progress; Claude is more cautious, emphasizing trading timing, project credibility, and risk control for newcomers; Gemini leans more towards industry and technology routes, focusing on RWA, the impact of regulation on asset security, and the 'endgame choices' of L2/Solana/AI. The Chinese models are generally more concentrated on the three 'hardcore certainty variables' of cycles, halving, and regulation, while Kimi is relatively an exception, sinking the questions down to on-chain execution details (wallet security, slippage/MEV, HFT), resembling real friction from high-frequency on-chain users.
Another more secondary but worth noting possibility is that model capability differences may also affect the output's 'sharpness'. Stronger models often ask the same topic in a more specific and systematic way; conversely, weaker models are more likely to fall back to the 'price/regulation/scam' type of maximum common divisor expression, making the answers look more alike, with less information increment. This factor may not be the main cause, but in macro-open questions, it can indeed amplify the perception of homogenization.
In summary, these questions are highly focused on three main themes: cycle position, paths to profit, and risk boundaries. A significant characteristic of the crypto market is high volatility and strong narrative drive, so 'which phase the market is in' almost determines all subsequent actions of users (hold, sell, switch positions, leverage, or exit). As the market enters a more mature and crowded phase, users will quickly shift from 'is there an opportunity' to 'where is the opportunity, can I still benefit', so Alpha, track selection, and institutional funds (ETFs) naturally become high-frequency topics. Meanwhile, scams, project credibility, asset security, and regulatory compliance reflect that crypto users are long-term in a 'high return/high uncertainty' environment: chasing returns on one hand and worrying about pitfalls on the other, ultimately forming a typical behavioral structure—first judging the trend, then looking for opportunities, and finally controlling risk.
