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- 📢 #Gate Square Writing Contest Phase 3# is officially kicks off!
🎮 This round focuses on: Yooldo Games (ESPORTS)
✍️ Share your unique insights and join promotional interactions. To be eligible for any reward, you must also participate in Gate’s Phase 286 Launchpool, CandyDrop, or Alpha activities!
💡 Content creation + airdrop participation = double points. You could be the grand prize winner!
💰Total prize pool: 4,464 $ESPORTS
🏆 First Prize (1 winner): 964 tokens
🥈 Second Prize (5 winners): 400 tokens each
🥉 Third Prize (10 winners): 150 tokens each
🚀 How to participate:
1️⃣ Publish an
- 📢 Gate Square #TopContentChallenge# is coming! Post high-quality content and win exclusive rewards!
🌟 We will select outstanding posts for exposure, and help elevate your influence!
💡 How to Participate?
1.Add the #TopContentChallenge# tag to your post.
2.Posts must be over 60 characters and receive at least 3 interactions (Likes/Comment/Share).
3.Post may include only the #TopContentChallenge# tag.
🎁 We’ll select 1 top post to win $50 Futures Voucher every Tuesday and Thursday!
📃 High-quality posts will be shared on Gate Square and labeled as [Featured Posts]!
📌 Rewards will be distribu
- 🎉 [Gate 30 Million Milestone] Share Your Gate Moment & Win Exclusive Gifts!
Gate has surpassed 30M users worldwide — not just a number, but a journey we've built together.
Remember the thrill of opening your first account, or the Gate merch that’s been part of your daily life?
📸 Join the #MyGateMoment# campaign!
Share your story on Gate Square, and embrace the next 30 million together!
✅ How to Participate:
1️⃣ Post a photo or video with Gate elements
2️⃣ Add #MyGateMoment# and share your story, wishes, or thoughts
3️⃣ Share your post on Twitter (X) — top 10 views will get extra rewards!
👉
MiniMax Open Source's first inference model: Competing with DeepSeek, the Computing Power cost is only about $530,000.
Gate News bot message, MiniMax announced on June 17 that it will release important updates for five consecutive days. Today's first release is the Open Source first inference model MiniMax-M1.
According to the official report, the MiniMax-M1 has benchmarked alongside open source models such as DeepSeek-R1 and Qwen3, approaching the most advanced models overseas.
The official blog also mentioned that based on two major technological innovations, the MiniMax-M1 training process was efficient "beyond expectations," completing the reinforcement learning training phase in just 3 weeks using 512 H800 GPUs, with a computing power rental cost of only $534,700. This is an order of magnitude less than the initial expectations.
Source: Jinshi