🔥 Gate Square Event: #PostToWinNIGHT 🔥
Post anything related to NIGHT to join!
Market outlook, project thoughts, research takeaways, user experience — all count.
📅 Event Duration: Dec 10 08:00 - Dec 21 16:00 UTC
📌 How to Participate
1️⃣ Post on Gate Square (text, analysis, opinions, or image posts are all valid)
2️⃣ Add the hashtag #PostToWinNIGHT or #发帖赢代币NIGHT
🏆 Rewards (Total: 1,000 NIGHT)
🥇 Top 1: 200 NIGHT
🥈 Top 4: 100 NIGHT each
🥉 Top 10: 40 NIGHT each
📄 Notes
Content must be original (no plagiarism or repetitive spam)
Winners must complete Gate Square identity verification
Gat
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