Trade
Trading Type
Spot
Trade crypto freely
Alpha
Points
Get promising tokens in streamlined on-chain trading
Pre-Market
Trade new tokens before they are officially listed
Margin
Magnify your profit with leverage
Convert & Block Trading
0 Fees
Trade any size with no fees and no slippage
Leveraged Tokens
Get exposure to leveraged positions simply
Futures
Futures
Hundreds of contracts settled in USDT or BTC
Options
HOT
Trade European-style vanilla options
Unified Account
Maximize your capital efficiency
Demo Trading
Futures Kickoff
Get prepared for your futures trading
Futures Events
Participate in events to win generous rewards
Demo Trading
Use virtual funds to experience risk-free trading
Earn
Launch
CandyDrop
Collect candies to earn airdrops
Launchpool
Quick staking, earn potential new tokens
HODLer Airdrop
Hold GT and get massive airdrops for free
Launchpad
Be early to the next big token project
Alpha Points
NEW
Trade on-chain assets and enjoy airdrop rewards!
Futures Points
NEW
Earn futures points and claim airdrop rewards
Investment
Simple Earn
Earn interests with idle tokens
Auto-Invest
Auto-invest on a regular basis
Dual Investment
Buy low and sell high to take profits from price fluctuations
Soft Staking
Earn rewards with flexible staking
Crypto Loan
0 Fees
Pledge one crypto to borrow another
Lending Center
One-stop lending hub
VIP Wealth Hub
Customized wealth management empowers your assets growth
Private Wealth Management
Customized asset management to grow your digital assets
Quant Fund
Top asset management team helps you profit without hassle
Staking
Stake cryptos to earn in PoS products
BTC Staking
HOT
Stake BTC and earn 10% APR
GUSD Minting
Use USDT/USDC to mint GUSD for treasury-level yields
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DeepSeek launched the DeepSeekMath-V2 model
PANews, November 27th news, according to Zhitong Finance reports, DeepSeek has launched a new mathematical reasoning model, DeepSeekMath-V2, which uses a self-verifiable training framework. This model is built on DeepSeek-V3.2-Exp-Base and automatically reviews generated mathematical proofs through an LLM verifier, continuously optimizing performance with high-difficulty samples.