MiMo-v2.5-Pro-UltraSpeed: 1T model with 1000 tokens per second

Post by johndough » Mon, Jun 08, 2026, 10:41 PM UTC

scosman wrote: post #19

Cerebras is trialing Kimi K2.6 at 3000t/s (invite only). I'm excited for when the fast hardware gets more mainstream for frontier models. Models designed for speed on Nvidia are nice addition that could bridge the gap.

Post by erikus » Mon, Jun 08, 2026, 11:01 PM UTC

powerapple wrote: post #275

dakiol wrote: post #136

So, regarding the productivity argument: I don't get it. It doesn't really matter (for regular employees) that you can do now in 2h what before it took 2 days. Why? Because it's not that you have the rest of the day for yourself. You still have to work 8h/day as usual. But now the pattern is different: instead of enjoying the craft digging deeper into problems in the span of 2 days, now you are rushing into some slot…

In my case, I think slower model makes it hard to manage context and tasks in parallel. I would much prefer to work in one task only, and finish it, take a break, and work on another task. Currently I have three tabs for three tasks in parallel, it is much worse than because constantly context switching is painful. I think a faster model would mean that you don't have to start a new task while waiting.

Post by 8note » Mon, Jun 08, 2026, 11:09 PM UTC

Terretta wrote: post #277

ghshephard wrote: post #271

Earlier quoted context omitted.

I think people are continuing to view these systems as pure LLMs - when that ship sailed 6+ months ago. Between being able to review memory, using agent harnesses and sub agents and skills to go out and discover information - modern systems (Codex, Claude Code, Cursor) - use LLMs - but the LLM is only a small component of it. Compare what you get from sending a request to a chatbot like ChatGPT - to what you can from…

You think someone is, or even should, special case things like estimates? What else deserves that level of intervention so they look less dumb? Logistics for getting to the car wash next door? In the mean time, alas, no, we can see from actual prompts sent directly or through sub-agents, and actual replies, estimates remain LLM generated. Though, this discussion here could change that, because indeed there is a lot o…

Post by opsnooperfax » Mon, Jun 08, 2026, 11:11 PM UTC

ttoinou wrote: post #152

dakiol wrote: post #136

So, regarding the productivity argument: I don't get it. It doesn't really matter (for regular employees) that you can do now in 2h what before it took 2 days. Why? Because it's not that you have the rest of the day for yourself. You still have to work 8h/day as usual. But now the pattern is different: instead of enjoying the craft digging deeper into problems in the span of 2 days, now you are rushing into some slot…

In which world do you live where employees work 8 hours per day ? They clock 8 hours per day maybe, but they don't work that time

Post by ayewo » Mon, Jun 08, 2026, 11:18 PM UTC

dkersten wrote: post #317

goyozi wrote: post #58

Fast AI seems genuinely exciting and somewhat unsettling to me. Right now Claude is faster than me on some tasks but we’re at least close. I have a prompt to clean up a PR that’s been running for 1h now and I expect it to take another few. It’s hard to imagine how the workflow would look like if it was near-instant. On the one hand, it might be easier to focus. Some prompts take so long that I start to multitask and…

I’ve been playing around with groq and GPT OSS which they run at 1000 TPS (20B) or 800 TPS (120B) and the speed feels quite magical. I haven’t tried cerebras’ 3000 TPS yet but I did try the demo of that 15,000 TPS model whose name escapes me right now. I’m not sure if it makes a meaningful difference for my actual work, but it sure is amazing to watch it generate a screen full of text in the blink of an eye. I do thi…