Story
MiMo-v2.5-Pro-UltraSpeed: 1T model with 1000 tokens per second
1 report
1 website
1 discussion
Latest report
Overview
Xiaomi has released the MiMo-V2.5-Pro-UltraSpeed, capable of generating 1 trillion parameter models at a speed of 1000 transactions per second (TPS). This advancement enhances real-time AI reasoning and collaboration, making it more responsive and integrated into human thought processes.
Summary from mimo.xiaomi.com.
Reports
One report so far. Additional coverage will appear here when it is linked to this story.
Community reactions
Each reaction summarizes sampled comments from the linked discussion.
Hacker News · mimo.xiaomi.com
Historical count: 5 · 5 saved in sample · Historical sample
Analysis ready
Read this discussion’s reaction
Based on 5 sampled comments from this thread. Analyzed 2026-06-08.
- Praise: The introduction of MiMo-v2.5-Pro-UltraSpeed, achieving 1000 tokens per second, signifies a major leap in model efficiency, potentially transforming real-time AI applications.
- Praise: The prospect of compute-in-memory technology could lead to models that are not only faster but also significantly smarter, enhancing the capabilities of AI systems.
- Praise: Ultrafast AI could streamline workflows, allowing developers to focus more deeply on complex problems rather than getting bogged down in lengthy processes.
- Praise: The ability to render UIs directly from context data and prompts could revolutionize software development, making it more accessible for small businesses.
- Concern: There are concerns that the rapid pace of AI development may lead to a proliferation of low-quality software, overshadowing genuine advancements.
- Concern: The shift towards ultrafast AI might diminish the enjoyment of the craft for developers, as the focus shifts from deep problem-solving to quick fixes.
- Concern: The increasing costs associated with AI usage, particularly from American providers, could create barriers for many companies, complicating the landscape for developers.
- Concern: The inconsistency in model performance and pricing from AI providers raises concerns about reliability and predictability in AI applications.