🎉 #Gate Alpha 3rd Points Carnival & ES Launchpool# Joint Promotion Task is Now Live!
Total Prize Pool: 1,250 $ES
This campaign aims to promote the Eclipse ($ES) Launchpool and Alpha Phase 11: $ES Special Event.
📄 For details, please refer to:
Launchpool Announcement: https://www.gate.com/zh/announcements/article/46134
Alpha Phase 11 Announcement: https://www.gate.com/zh/announcements/article/46137
🧩 [Task Details]
Create content around the Launchpool and Alpha Phase 11 campaign and include a screenshot of your participation.
📸 [How to Participate]
1️⃣ Post with the hashtag #Gate Alpha 3rd
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