Bitget Launches 7 AI Trading Avatars to Battle DeepSeek

  • Bitget debuts seven AI trading avatars with distinct real-time strategies in GetAgent.
  • Users can copy trade instantly and track every move through transparent performance data.
  • A 10,000 USDT airdrop and daily vouchers reward participants during the limited event.

Bitget, the world’s largest Universal Exchange (UEX), has launched a full set of AI trading avatars on its GetAgent platform. The update introduces six new AI traders, along with DeepSeek as a benchmark model. All of them trade with real accounts and can be copied with one click.

Seven Avatars, Seven Trading Styles

Instead of testing general AI models like ChatGPT, Gemini, or DeepSeek in simulations, Bitget is putting purpose-built AI agents directly into live trading markets. Each avatar follows its own trading philosophy:

  • Steady Hedge – cautious, risk-controlled trades
  • Majors Momentum – trend-focused trading on major coins
  • Altcoin Turbo – aggressive strategies targeting fast-moving altcoins
  • CTA Force – rule-based, systematic execution
  • Infinite Grid – range trading using grid logic
  • Dip Sniper – buys into market dips with a contrarian approach
  • DeepSeek (base model) – the unmodified benchmark for comparison

All strategies use Bitget’s multi-factor indicators, extensive historical testing, and continuous optimization inside the GetAgent platform..

Copy Trading Window and Airdrop Incentives

From 18:00 on November 24 to 18:00 on December 15 (UTC+8), users can access a limited one-click copy trading channel. Each avatar trades autonomously in real time. Users can monitor entries, exits, drawdowns, and adjustments in the Model Arena via transparent performance curves and strategy documentation.

To encourage participation, Bitget has launched a 10,000 USDT airdrop pool.

  • Any user who successfully copy-trades and sends at least one message to GetAgent qualifies for a share.
  • The first 100 copy-trading users each day will receive contract copy-trading vouchers worth up to 100 USDT.

“Trading Made Personal”: Bitget CEO Gracy Chen

“People want solutions they can actually use to trade,” said Gracy Chen, CEO of Bitget. “These avatars make trading feel more personal and more approachable. Whether someone prefers momentum, hedging, or contrarian plays, there’s now an AI companion that thinks the way they do.”

Unlike traditional copy trading, GetAgent lets users talk directly with the avatar they follow, asking why it opened a trade, how it manages risk, or which signals it relies on. This makes each avatar both a trader and a teacher, helping beginners learn while giving advanced traders a way to test new ideas.

DeepSeek vs. Bitget Avatars: A Real-World AI Trading Study

DeepSeek’s inclusion as an unmodified base model creates a meaningful benchmark. After the trading period, Bitget will release a performance comparison showing how the engineered avatars stack up against a generic model under live market conditions. 

This will be one of the first real-world studies of how multiple AI agents behave when trading side by side.

Bitget’s Push Toward Smarter, More Accessible Trading

Bitget’s new AI trading suite supports its goal of making advanced tools easy for its 120 million users to access. As a Universal Exchange, Bitget brings together millions of crypto tokens, tokenized stocks, ETFs, real-world assets, and real-time prices for major coins like Bitcoin, Ethereum, and XRP.

On the decentralized side, Bitget Wallet serves over 80 million users and offers a single app for buying, trading, earning, and making payments with everyday simplicity.

Bitget is also growing its global reach through major partnerships, including its role as the Official Crypto Partner of LALIGA in the EASTERN, Southeast Asia, and Latin America regions. It also works with UNICEF to support blockchain education for 1.1 million people by 2027, and serves as the exclusive crypto exchange sponsor of MotoGP™.

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Source: https://coinedition.com/bitget-ai-getagent-7-new-trading-avatars-deepseek-benchmark/