Grok vs ChatGPT: How AI Became the Day Trader’s Secret Weapon for Maximum Profits
Wall Street's latest obsession isn't a hot stock tip—it's two AI models battling for trading supremacy.
Grok's edge? Real-time X data streams give traders nano-second advantages. ChatGPT counters with uncanny pattern recognition—spotting breakout opportunities before human analysts blink.
Both platforms now dominate trading desks, with users reporting 30% faster decision cycles. (Though let's be honest—half these 'genius trades' still rely on caffeine and hope.)
The real winner? Retail traders finally have tools that level the playing field against institutional algos. Until the next market crash, at least.
Python framework prompt converted to live trades
Clevar told followers that he began by instructing Grok to “generate a basic Python trading bot framework” with support for token fetching, config management, and placeholders for trading logic. The resulting script was modular and could accommodate future upgrades.
Before any tokens could be traded, they were verified using the Rugcheckxyz API. A prompt told Grok to “check each token and continue only if the rating is ‘GOOD,’” with failed tokens logged or skipped. This helps the bot avoid scams and honeypots on Solana.
After the verification, Clevar configured the bot to automatically sell portions of holdings at price multipliers of 2x and 3x, while managing exposure through customizable settings. Using a prompt, Grok was asked to “implement a trade strategy module” with configurable sell percentages and a cap on trade allocation.
The bot was connected to the GMGN trading platform using either wallet or Telegram login. Grok was told to support “live buy and sell orders through the GMGN API endpoints.” More metrics including token liquidity, holder count, and trend direction, up, down, or flat were added later on.
ChatGPT wallet tracking automation
While Grok was used for modular bot architecture, ChatGPT seemed more useful for wallet-tracking. Another trader named Bard shared how they built a system that identifies elite wallets, those with at least 20 trades in a week.
The tracker also listed wallets with a 50% win rate and a 7-day PnL of 200% or more, filtered using GMGN’s CopyTrade panel.
8/ Legal & Ethical Note
This thread is educational, not financial advice.
Crypto is volatile; never risk capital you can’t lose.
Respect front-running laws in your jurisdiction. pic.twitter.com/tWtEQMpG0p
The trader prompted ChatGPT to “write Python that monitors wallet transactions on Solana, parses token contracts, scrapes social links, and stores everything in an array.”
To protect a user against scams, ChatGPT was asked to integrate two separate verification APIs, Rugcheckxyz and TweetScout_io, into the bot. A single prompt was used to “add verification for coins through Rugcheckxyz and TweetScout_io services to prevent scams and honeypots.”
When a tracked wallet executed a buy, the bot responded almost immediately. The logic prioritized Raydium for trades, falling back to Pump.fun only if it had better liquidity.
The final script combined all modules into one deployable file, resolving import and dependency issues along the way.
Trades were capped using micro-bankrolls, and any position that dropped 30% from entry was automatically sold. Daily profit sweeps were built in to avoid losses during congestion on the Solana network. The trader also diversified wallet sources to avoid single signals. “Even whales whiff,” the user cautioned his followers.
Grok has also been providing financial commentary and the effects of geopolitical events on X. In one instance on Friday, it responded to a question “if TRUMP is serving Russian interest by extending the tariff implementation deadline for Russia,” with references to sources such as Reuters, the New York Times, and the Institute for the Study of War.
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