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

https://openrouter.ai/deepseek/deepseek-v4-pro?sort=throughp...

It's also pretty funny sometimes how it gives weird future roadmap estimates ("part 2 - 3 weeks, part 3 - 2 months", etc.) and when you tell it to actually do those changes it's pretty much done in half an hour

Basically I never have to wait - yes I have to tell it little corrections occasionally (but I know the domain really well so that's not an issue), but it's so much faster than anything else it's kinda crazy. I love the super fast speeds with high involvement development cycle.

I actually enjoy using agentic development flows for the first time now - whereas with Claude I absolutely hated it. That 5 to 20 min wait after every prompt absolutely killed my desire to even want to work at all.

the way software engineering works these days reminds me a lot of factory workers on production lines that just sit in front of a production line all day and take out faulty items and/or perform a single step in the production of goods.

You were likely thinking of AI accelerator startup Taalas.

Previous HN discussion: https://news.ycombinator.com/item?id=47086181

It's a cute toy right now, but you can tell an LLM that it's an http server, and have it respond directly to a web browser hitting it. It generates headers in response, as well as page contents. As 1000 tok/sec becomes three new normal, we will come up with newer ways to use it outside of toy fiction encyclopedias.

Build and test would move back into the critical path, though, and for some projects that will take effort to bring down.

I am on Dutch subreddits a lot, to get a local pulse and not to be too HN minded.

A lot of them would have vilified you by now. Some even would have even questioned your morality.

Again, I agree with you. But clearly not everyone has this view.

It also makes me think about the temptation to stop thinking with these tools, i.e. "cognitive surrender". Addy Osmani wrote a nice blog post about this: https://addyosmani.com/blog/cognitive-surrender

The thing I really love about working with computers is when I achieve something. That's the thing that makes me figuratively, and sometimes literally, throw my fists into the air and go "Yeaaah!"

With the AI tooling, I'm getting those more like a couple times a week.

Plus, I'm using AI to attack the things in my day that are "a drag", and getting them done too.

The highs are more frequent and the lows are not so low.

Or Google. I'm working with multiple customers right now that are very pissed at Google for deprecating Gemini 2.5 Flash, canning the GA release of 3.0 Flash and now have to decide whether to bite the bullet of the 5x price increase for 3.5 Flash or switching providers. Quite a few of them will likely fully pivot to open models.

For non subsidized plans? Pretty sure they'd need to put this in ToS, or law suites would have followed by now.

On HN China is seen as a cheap labor copycat. This used to be a fair approximation at some point in the past. In my opinion China is getting ahead of everyone else much more than US used to be.

SF is a beautiful thing in the US, vast power and wealth comes from there. Smart people collaborating communicating and building fast and with excitement. China did SF kind of thing for many different sectors in many different places.

The $0.87/M tokens price for Mimo Pro is probably subsidized.

Mimo models aren't widely available on western providers, but Kimi and Deepseek are similar sizes and cost about the same to run. They are priced $3-$4/M tokens (which is right were Google's very confused range of Flash models are priced at: between $0.40/M tokens and $9/M tokens depending on exactly which model - and you don't want the $9 one!).

Anthropic overprices Sonnet (probably because of their capacity issues). GPT 5.4 mini is $4.50/M tokens.

https://docs.fireworks.ai/serverless/pricing

https://www.together.ai/pricing

It was pretty clear the USA won World War 2 because it out produced and out innovated everyone else. Probably with that in mind, after World War 2 the USA adopted the "Vannevar Bush" model, summarised in this picture: https://www.researchgate.net/figure/annevar-Bushs-Science-th... The idea is to jump start R&D through public funding. The hoped for outcome was that R&D feed private enterprise, leading to a productivity boom.

The boom happened, and the USA did seem to out-compete everybody else in R&D, science, and the products they delivered for decades after that.

That way of doing things seems to have faded over time in the USA. The decline seemed to coincide with the rise of Neo-econmics, and now of course it's been obliterated by Trump. He's very keen to fund Intel to produce chips in a year or two's time (which is something the stock market and banks do perfectly well), but funding basic science is getting drastic cuts.

Still other countries noticed the rise of the USA, and some adopted similar funding models for basic R&D. China seems to have picked it up with gusto, both subsidising R&D and STEM training, leading to huge numbers of engineers and scientists. Whether it will lead to an economic boom remains unknown, but acceleration of ideas and innovations coming out of China seems undeniable. More recently, Ukraine showered its local engineering garages with funds in the hopes of getting a similar outcome to the USA in WW2. It looks like it worked. If the Iran war continues, it's entirely possible arms trade will reverse: the USA could well start buying drones off Ukraine.

It is another thing the BigLabs accuse open weight models of benefiting from distillation & other techniques & essentially avoid higher training costs (which typically bleed into bills end users pay for inference).

Ex A: https://www.anthropic.com/research/2028-ai-leadership

Ex B: https://www.reuters.com/world/china/openai-accuses-deepseek-...

MiMo v2.5 is on there, as well as the pro version.

We found a few anomalies in our evaluations, which makes sense -- if every new sub-release is better across the board in every area of the model card, that should raise alarms about benchmaxxing. But the main thing we found is that hype != performance, and I trust our benchmark methodology significantly more than the model cards the labs add to their press releases.

This strategy will seem to work really well until the economy that enabled that foundation to form is hollowed out. Then, there will be a reckoning (but we will have no choice but to march forth from there).

Especially as teams invest in proper agentic harnessing.

We have had a champion in our team that has invested a lot of time into it over the last 4 months, and if anything, quality has improved, not decreased. Architecture is more coherent, codebase has been cleaned up, agents find information quickly, code produced is very solid and my role is more and more checking that the output meets the requirements. But I cannot confidently say that I would've done a better job than AI more often than not I have to admit it does a better job than mine.

The mistakes are less and less technical and merely in the domain mapping. And AI is still not creative as I am for finding solutions quickly to unlock stakeholders' issues. Also, AI is still not creative as I am for finding the proper solutions for advanced technical problems. But it does a better job than me, even on that front, one shotting few solutions in a fraction of a time it would've taken me to test one idea myself.

Mind you, I don't like AI and I think it ruined the job, I don't like working this way, it's exhausting, way more work on one side, way less fun and fiddling with technical parts.

And yet, I have the genuine belief that few years from now we'll be cloning open source repositories that are already optimized/harnessed and tested for agentic loops and best practices left and right with software engineers mostly overseeing the domain translation and putting their 2 cents on the non-boilerplatey parts of the product (which, in general, are a small part of the surface).

I think that the next years of my career will be mostly spent in setting up and writing the harnessing and domain mapping part. Then I will move to another sector, not because I necessarily believe I won't have a job, but because I want to vomit thinking that's going to be my job.

> No one cares anymore.

I never cared about this.

I think this captures something that I've been searching for the words for. (Maybe I should have gotten an LLM to write the words for me.) Some of the biggest AI boosters are the kind of dev that would have cared about the new frameworks of the last 3 months. They had a "the framework does all the thinking for me" attitude already, so it is easy for AI to slot into that.

it needs to win marketing landscape, hyper-overcrowded by thousands of competitors, slop-gened over weekend.

But quite a bit more expensive than MiMo 2.5 Pro. Like 5x to 10x more on my little tests, at least by the API rates.

Not nearly as obvious as the ones from 6 months ago, but seems to be more the use of hyperbolic phrasing in a particularly unnatural way.

The assess/explain, then hyperbole at the end kind of structure.

Top comment looks suspicious from this perspective, but it's kind of a losing battle to be able to differentiate them with sufficient accuracy anyway

But it may well do. They mention TileRT in the announcement, so this speed comes from low level optimization for some specific GPU target.

With availability of SOTA western GPUs being scarce in China, they may well have a mishmash of different GPUs.

Understand the spirit of this, but probably not true. I don't think Xiaomi, or any big tech company, needs to break even on their new model releases.

From that point of view, they have as much money as they need. That's why there is no "VC", because Chinese government assumes that role.

so there is alwasy a maximum limit for how well MTP can do.

128 sounds really tiny, I wonder if they mean some kind of blocks?

[0] https://huggingface.co/XiaomiMiMo/MiMo-V2.5-Pro-FP4-DFlash#4...

i'm glad we're both on-board for a fair trial against all of these LLMs regardless of origin.

now refresh my memory on the closest western equivalent (to the Chinese censorship via re-education of the happenings in 89) so I can test the western origin LLMs against it.

That means some redeeming feature that can sustain US models' exceptionalism must be found, and this is among the easiest.

Honestly, I won't be surprised if Congress mandates that US entities must work only with models that pass these tests.

We are not assuming anything; it is illegal, and you will get prison time just for talking about it. Yeah, sure, everyone distorts reality, but there is a huge gap between hiding and enforcing. So yeah, having models respond accordingly is unexpected. There are probably multiple variants tuned differently.

Say, I work for Planned Parenthood and want to use a LLM to help me develop code. Will it refuse to run because there are mentions of abortion? Everyone has a different censorship line, but unfiltered is more generically useful.

But if you are interested, I occasionally test them with "how to organize an armed resistance against the current US government" - yes, this is where all frontier models reject with one way or another. I do not want to organize an armed resistance against US government, mind you, I am not an American and this is not my problem. But still, it is interesting to check such things.

So far I haven't seen any refusals to report historical facts. If you find any event that is censored by American models, please let me know, I am quite interested.

Curiously, MiniMax M3 answers correctly.