I been using MiMo-V2.5 to do most of my work as software engineer, on a variety of projects I'm working on, and I been VERY happy with ROI. The model is very powerful! Not perfect – I've run in hallucination loops once or twice, but nothing a stop-then-continue wouldn't solve.
The cost is unbelievably low, and the quality of intelligence I get is equivalent to when I was working mostly with Anthropic models (late last year/early this year). I'm fully invested in MiMo and I'm very happy with it.
--
PS: I also check almost daily to see if other models are capable of doing such great work. And they do – DS4F is powerful and DS41 is impressive, GLM 5.3 Flash gets a job done well, etc. – but when I add cost of M-token in the ROI math, Jeez! MiMo is an order of magnitude better.
ehsankia 2 hours ago [-]
> late last year/early this year
That's an eternity when it comes to coding models.
In my personal experience, we've had almost a step change every ~3 months this year, at least for bigger one-shot tasks. For example looking at Gemini Flash 3.0 vs 3.5 vs 3.8, it went 5% -> 30% -> 75% on DeepSWE, all since the start of the year.
pelagicAustral 22 minutes ago [-]
tbf, I the happiest I've been working with claude is late last year/early this year (before March)...
miyuru 5 hours ago [-]
Same here. It’s the first AI provider I actually gave money to, since they offered the model for free with a Mimo code for the first month or so, and it was great.
These days, there are more intelligent models like DS4.1, but Mimo is very obedient, so I plan things with another model and give the implementation to Mimo.
rapind 9 hours ago [-]
I’ve been very pleased with DS 4.1 flash. Not so much the 4.0 models, but for coding (Rust) it’s been great so far (3 solid days of work).
I’ll give Mimo a try.
trollbridge 9 hours ago [-]
MiMo is my backup whenever DeepSeek is down, had the price bump, is slow, etc.
UltraSpeed was absolutely awesome. I miss it.
DS 4.1 Flash is amazing. Well worth the extra cost.
alwinaugustin 12 hours ago [-]
I am also using 2.5 and it is giving me solid results. Its available free on Openrouter
baxtr 4 hours ago [-]
Could you elaborate on how you check daily? Do you swap models for certain tasks?
walrus01 14 hours ago [-]
I've found that mimo v2.5 works for very basic things like a python script to do one thing, but it also is very 'dumb' compared to qwen 3.8-flash-next (I think the benchmark scores for terminal and coding specific benches back this up). And definitely not in the same class as like a GLM5.2 or 5.3. It's fast but makes basic mistakes that only get caught later.
girvo 9 hours ago [-]
The fact I can run Qwen 3.8 Flash Next locally, forever (on my DGX Spark-alike) is genuinely shocking to me. It’s crazy good for how small it is. Fast, too.
And I am not a web developer! It's an extraordinary model.
(Mouse and keyboard required)
walrus01 8 hours ago [-]
Yeah, I'm guessing you have a variant that fits in <128GB with 262k context? I have the unsloth Q8 GGUF of it here in a setup that with full context and ton of extra llama-server "--cache-ram" sits around 200GB RAM usage on a 256GB system, it's probably the best thing I've found for a 256GB class machine. Enough headroom for a rope/yarn extension to 524288 context if I need it.
girvo 7 hours ago [-]
Yep, the engrams are on NVMe (the speed penalty was lower than I expected) and it is quantised to fit.
It’s good enough that I’m considering a second spark, or selling this and buying an M5 Ultra with 256GB for it
12 hours ago [-]
jwpapi 13 hours ago [-]
May I ask why you ended up there instead of just using the heavy subsidized subscription. I’m actually curious.
eli 12 hours ago [-]
Mimo has subsidized subscriptions too
flexagoon 11 hours ago [-]
How does it compare with DS 4.1 Flash in your experience, if you ignore the cost?
james2doyle 14 hours ago [-]
2.5 Pro or the regular 2.5?
I always found that those Mimo models to be really good at tool calling and following instructions
ignoramous 4 hours ago [-]
> GLM 5.3 Flash gets a job done well, etc. – but when I add cost of M-token in the ROI math, Jeez! MiMo is an order of magnitude better.
API may be expensive, but I do 900m tokens (95% cached, ~0.4% output) on Z.ai's $18/mo coding plan with GLM 5.3 Flash.
miroljub 4 hours ago [-]
I wouldn't call that inexpensive.
For comparison, I am currently at 6.6B tokens, 95% of monthly quota on a 10$ command code plan, mostly using DeepSeek flash 4.1, or some of the free models for easier tasks.
esafak 13 hours ago [-]
How fast is it compared with the other Chinese models?
ricardobeat 12 hours ago [-]
They both are in the 50-100 tok/s range. The Mimo v2.5 Pro Ultraspeed beta could reach 1000 tok/s, hoping they can do something similar for the new model, it was amazing.
wangxili1997 3 hours ago [-]
[flagged]
electroglyph 11 hours ago [-]
[flagged]
NuclearPM 11 hours ago [-]
Real?
electroglyph 8 hours ago [-]
mimo 2.5 has been a big underperformer since shortly after it's release imo. i cancelled my sub after the first month. purposefully using 2.5 right now is just handicapping yourself for no reason.
NuclearPM 7 hours ago [-]
I understand now. You used the wrong word.
yeeeloit 13 hours ago [-]
[flagged]
senordevnyc 13 hours ago [-]
Yeah, this Brazilian dude who has been a contributor here on HN longer than your anonymous account is shilling for a Chinese model company. Makes sense.
platinumrad 13 hours ago [-]
Are you accusing them of astroturfing? Why is it strange for someone to say something topical?
dr_dshiv 12 hours ago [-]
Well, if open source AI is dangerous (for OpenAI/Anthropic IPOs?), this is like watching a time bomb.
dzonga 11 hours ago [-]
the open burial started when zAI served their latest model on all Chinese chips.
now we r just noticing the grave getting dug deeper.
skybrian 10 hours ago [-]
For my own usage, Luna is cheap enough that I don't care if other models are cheaper. I'm interested if another model is in some way better and not too expensive.
rapind 9 hours ago [-]
Luna is great but makes a lot of mistakes at high and lower in my experience (large rust codebase). I use Luna Max for asynchronous subagent reviews and am very happy with its work, but it’s slow af.
ijidak 8 hours ago [-]
What plan are you on?
Trying to understand why users are using Luna when Sol seems essentially unlimited on the pro plan. Unless you have jobs running 24/7.
teki_one 8 hours ago [-]
Sol is useless atm on the Plus plan, 1-2 questions 5-10m to get through the 5h allowance. (used to be good, can change any day)
Neat! I've been trying out their next model for the last week, which I assume is a version of this, and it's been a good experience so far.
I had used 2.5-pro for a hefty chunk of development, and found it to work like a somewhat forgetful senior engineer who was new to my project. Very capable, would almost always choose a reasonable option, if not always the best one for the project, and not great at multi-tasking. Generally, made me comfortable not scrutinizing the code line-by-line, but still needed a bit of steering once projects got to a reasonable size.
The next model is a clear step up in the multi-tasking capability at least, with me very rarely having to steer the implementation of a well-defined issue. In terms of code, I found MiMo-V.2.5-pro to be extremely conservative, implementing minimal solutions. The next model seems a little bit more ambitious, in positive ways, making good guesses about gaps/next steps. It also seems to be a fair bit better at design, at least for the little bit I've done, it was good at translating my concepts to practical elements on screen, and cleaned things up nicely as I made suggestions.
ricardobeat 12 hours ago [-]
For reference, Mimo-v2.5-Pro scored 19% on DeepSWE 1.1. This is looking great.
Fable scores 70%, Kimi K3 69%, Astra 74% (all on max effort).
gemini 3.8 flash is also 74% and google just started letting all their engineers use claude...go figure
ehsankia 1 hours ago [-]
> and google just started letting all their engineers use claude
That's misleading.
1. Having different models available is useful for A/B testing and helping improve Gemini itself.
2. They have an enterprise offering for Antigravity (their agentic coding platform), and they need to test that it works well with non-Gemini models too.
Cookingboy 11 hours ago [-]
2.6-pro just reached 63.7% by step 10, it's on step 11 right now.
Even flash reached 60.7% by step 12, and it's on step 16 now.
This is so exciting lmao.
arcanemachiner 49 minutes ago [-]
DeepSWE is saturated now IMO, and is basically worthless. Lots of new models get around 74%. Shame too, because it was a pretty decent benchmark for a few months there.
krm01 14 hours ago [-]
This is pretty neat. What would be a good reason for the other Model providers to not do this?
kibae 14 hours ago [-]
Speculating here, but I assume researchers can make a reasonable estimate of the size of closed models based on factors like training time, training speed, and the number of tokens processed.
Also, Anthropic and OpenAI probably want to keep each other on their toes so they don’t end up on the wrong side of another Opus 4.6 / GPT-5.3-Codex situation, where one lab releases a model only for the other to drop a better one hours later.
Bolwin 5 hours ago [-]
I don't really remember a situation, which of those models supposedly beat the other?
I still opus 4.6 though not for code
jwpapi 13 hours ago [-]
I think first of all it’s not an obvious idea, also the marketing surplus for other providers is not as big for openai/anthropic as for xiaomi and last but not least I’m pretty sure you can withdraw methodology from here.
I’m saying who has a million dollars for me, so I can make my own model?
nikcub 7 hours ago [-]
this is remarkable transparency in an otherwise hyper competitive and secretive industry
liuliu 14 hours ago [-]
When you run benchmarks while training, isn't that the definition of contamination? Asking because I am not sure if this is normal in big labs now.
jampekka 14 hours ago [-]
Kinda yes. The benchmarks become part of the validation set, which means the models get slightly overfit to them if they are used as criteria for stopping the training. But a lot less compared to using them in the training data.
I'd guess everybody uses at least some benchmarks as stopping criteria, which is kinda sensible, but it also does induce some benchmaxxing, and explains partly why the newest models always tend to eke out in benchmarks.
Correct. If just stopping criteria, that is less contaminated. The question gets muddier once you also use it to determine hyperparameters during small-scale runs.
lucrbvi 14 hours ago [-]
They are using it to evaluate checkpoints during the training, they are probably not using the benchmarks for training the models. It's a common practice for big reinforcement learning runs.
nodja 13 hours ago [-]
They exist to detect degradation. Datasets are not perfect and if a batch contains too much bad data it can ruin a run, also an opportunity to find bad data and improve the dataset filtering.
SwellJoe 14 hours ago [-]
You gotta have something to aim at. And, presumably, the benchmark is not part of the training data, it is the test against which the model is tested at each stage; is behavior moving in the right direction?
esafak 13 hours ago [-]
Not if you don't train against them.
kingstnap 12 hours ago [-]
It's implicitly trained against. There is like information leakage with researchers messing with the training parameters and checkpoints used.
It's not the direct feedback loop of RL but its not far.
fzysingularity 13 hours ago [-]
Very cool to see the openness here, and likely more like this will come from smaller startups where they win users on transparency.
ProfessorLayton 14 hours ago [-]
2.6 Pro: >started 2026-09-15 10:32 UTC
For some reason I thought training took much, much longer than what the progress bar suggests.
This is really neat, I'm currently using mimo 2.5 pro, and it's decent (or great given the price). Hopefully their next one is multimodal.
GaggiX 14 hours ago [-]
These are post-training reinforcement learning steps.
krackers 14 hours ago [-]
Yes, updated the submission title to say "post-training" to hopefully prevent further confusion
ttul 9 hours ago [-]
$5 per second if my eyes don’t fool me. That’s ~$432K per day. Enough to rent 3,000 B300 nodes on Modal.
stymaar 2 hours ago [-]
Which isn't that much when you compare to the kind of DC that US actors are using.
thehamkercat 14 hours ago [-]
This is crazy, but sadly anthropic/openai will never do this, what has happened to this world, where chinese companies are more open than US or even EU companies
b3lvedere 2 hours ago [-]
Is that a bad thing?
medlazik 14 hours ago [-]
Neoliberalism, that famously open and transparent economic ideology
atemerev 6 hours ago [-]
Ah, one Donald Trump, a famous neoliberal.
stymaar 2 hours ago [-]
Were Sam Altman and Dario Amodei different men before Trump was in charge?
ssn2000 6 hours ago [-]
Total run cost is $1.2M until now, what resources are they using to train their model? Wish they shared more details on that and what the MFU metrics are.
speedgoose 14 hours ago [-]
I didn't know 2 thirds of the training data would be source code.
jerrygenser 14 hours ago [-]
that is the the "data used to improve the model" when signing up for the subscription plans
leothetechguy 14 hours ago [-]
this is the rl run, not the pretraining run
ahmadyan 13 hours ago [-]
even in pre-training, usually 30%-50% is code these days.
leothetechguy 2 hours ago [-]
That would be far too high in my opinion. But happy if anybody can give insights from their own experience with pretraining runs.
kkotak 7 hours ago [-]
Wouldn't us observing this break down the model superposition and make it dumber? :)
brcmthrowaway 7 hours ago [-]
Found the Dark Matter (2024) watcher
rao-v 9 hours ago [-]
I absolutely love that someone is doing this! Why isn’t IBM for Granite or Google for Gemini?
If you are going to develop a near frontier model, and you don’t think you have special sauce up your sleeve, why not making training runs and RL environment scores etc. visible to the world?
I’m genuinely learning quite a bit just from the dashboard
gtirloni 8 hours ago [-]
They think they have the special sauce. Even if they do, what would they get in return for doing that?
jstummbillig 5 hours ago [-]
Wow, spending money on training an almost-frontier-model is much more time intensive than I thought it was.
singularity2001 46 minutes ago [-]
"Claude Distill Requests":'hidden'
rozab 14 hours ago [-]
Why are they doing this? To try head off accusations about distillation?
bayindirh 14 hours ago [-]
Sometimes you're confident about what you're doing and show how you work to the world.
Keeping the garage door open, or at least making the door translucent. It's always cool.
jampekka 14 hours ago [-]
That China's official policy is now to prefer open models and open model development may be a part of it.
culi 13 hours ago [-]
BRICS just had a New Delhi meeting where Xi pushed a 5-point plan on AI cooperation that centered on open source models
Aboutplants 14 hours ago [-]
With that policy in place, labs might be incentivized to be creative in their openness. This being fun/free PR
anemic 13 hours ago [-]
Bottom of the page says "Open is what we value."
wolttam 14 hours ago [-]
Hah, it would be great to see more labs pick this up.
ernsheong 12 hours ago [-]
Mino 2.5 has been my workhorse for coder and tester agents (the ones planner agents delegate tasks to)
monneyboi 2 hours ago [-]
Refreshing, now let's make this a default feature. I imagine a "Upcoming models" list with links to these kind of dashboards.
wg0 4 hours ago [-]
"Slow down this much openness in AI or we won't get our trillion dollars valuations!"
Google had this GPT long go and a wise man within Google noted:
"We don't have any maot neither does anyone else."
The AI bubble burst is guaranteed and is only delayed by IPOs.
user43928 2 hours ago [-]
Nothing is guaranteed.
Open models have not yet caught up with February's Mythos checkpoint.
Meanwhile OpenAI is solving millennium problems, and their compute is still fully utilized.
wg0 59 minutes ago [-]
"Stealing millennium problems" would be more complete if not accurate description. And that 99.99% of the market is not interested in solving millennium problems is the other fact.
b3lvedere 2 hours ago [-]
I wonder what we will do with the discarded data centers and its hardware..
Ylpertnodi 11 minutes ago [-]
Copper can be stole, but that's already in progress.
thenews 8 hours ago [-]
been using the 2.5 mimo for side projects, works amazing
dr_kiszonka 10 hours ago [-]
Very curious that everyone here (so far) seems to assume this dashboard presents real data.
hsbalanxvxjsmab 8 hours ago [-]
Haha yeah pretty wild how easily you can see the data is fake by the repeating numbers (refresh the page the progress goes back in time constantly) + watch for restarts. They say they happen but 0 data correlates the log messages. Just a replay of old data or being fed by an llm so they convince people they are open
Bolwin 5 hours ago [-]
The intermediate tickers are fake but real data comes in and resets it. Its like a progress bar essentially. We don't call progress and bars fake
The Chinese labs are just making fun of the US labs at this point.
Where is the cool shit from the US labs?
culi 13 hours ago [-]
With other software, devs convince their managers of the importance of using open source stuff in their stack. With AI, it's usually managers choosing what models to use for the devs. The US labs don't need to give a damn how much devs like open source
impulser_ 12 hours ago [-]
This isn't about liking open source. This is about the labs just being cool and doing cool shit instead of the opposite which is Anthropic where all they talking about is killing everyone and taking everyone's job.
dlisboa 9 hours ago [-]
These labs are still (for the time being) made of people, who reflect their lives onto the work.
The US population is much more pessimistic and doomsday driven these days, whereas the Chinese are more optimistic and future driven.
noir_lord 13 hours ago [-]
> The US labs don't need to give a damn how much devs like open source
In the short term, true.
In the long term, unknown but typically when you hold progress that way while other countries don't you at best end up becoming siloed while the rest of the world continues on without you.
hsbalanxvxjsmab 8 hours ago [-]
You mean all of the frontier models that the Chinese distillation clones are copying? Yeah kinda cool imo. If a dashboard showing training for a model that doesn't even come close to anything us labs have released in 6 months is "cool", then you're a loser
bicepjai 8 hours ago [-]
Hahaha. Is that Sam or Dario with throwaway account. This sounds like calling social security, a free handout. Who distills the distillaters? Get it?
impulser_ 6 hours ago [-]
Why the fuck would you or I care about that?
Anthropic and OpenAI literally stole from every human in history and youre out here complaining that the Chinese are distilling models and releasing them to the public?
Why do you care?
atemerev 6 hours ago [-]
No crying in the copyright casino.
dude250711 11 hours ago [-]
Distillation in real-time? Very interesting!
Cookingboy 10 hours ago [-]
That "training cost" is just live revenue count for Anthropic/OpenAI API calls!
/s
hsbalanxvxjsmab 8 hours ago [-]
This is so very clearly fake? See the message stating the flash 2.6 flash run was restarted and 0 graphs correlate that restart
Retro_Dev 7 hours ago [-]
A restart of the process does not necessarily mean reverting the model state. I don't know why you would even do that, because you'd lose all the progress you made.
levocardia 14 hours ago [-]
You'd think they would make it less obvious that they are running their whole operation with Claude
ricardobeat 12 hours ago [-]
If you're thinking of the UI style, definitely not Claude. It is incapable of writing a clear sentence like "what each step's samples are made of", would have used all-caps for everything, more padding and gradients.
conception 8 hours ago [-]
I hope this is /s because it’s very easy to get Claude to write sensibly. That’s why AI slop writing is so annoying because it’s so easy to avoid with any amount of effort at all.
ricardobeat 56 minutes ago [-]
In my experience Opus and Sonnet 5 subtly ignore most instructions related to writing style, and continue to sound the same half of the time. Do you have a successful skill/prompt to share?
jambutters 11 hours ago [-]
They'd be running in the red then cause they charge way less than Claude. Sorry but it just doesn't make logical sense. They have open source, papers, and self hosting too
SwellJoe 14 hours ago [-]
It's not obvious to me. What's the tell?
iammrpayments 4 hours ago [-]
Did you come here to astroturf or are you a big fan of Claude
cpcabbge 4 hours ago [-]
Do tell cause I can't
Rendered at 10:51:24 GMT+0000 (Coordinated Universal Time) with Vercel.
The cost is unbelievably low, and the quality of intelligence I get is equivalent to when I was working mostly with Anthropic models (late last year/early this year). I'm fully invested in MiMo and I'm very happy with it.
-- PS: I also check almost daily to see if other models are capable of doing such great work. And they do – DS4F is powerful and DS41 is impressive, GLM 5.3 Flash gets a job done well, etc. – but when I add cost of M-token in the ROI math, Jeez! MiMo is an order of magnitude better.
That's an eternity when it comes to coding models.
In my personal experience, we've had almost a step change every ~3 months this year, at least for bigger one-shot tasks. For example looking at Gemini Flash 3.0 vs 3.5 vs 3.8, it went 5% -> 30% -> 75% on DeepSWE, all since the start of the year.
These days, there are more intelligent models like DS4.1, but Mimo is very obedient, so I plan things with another model and give the implementation to Mimo.
I’ll give Mimo a try.
UltraSpeed was absolutely awesome. I miss it.
DS 4.1 Flash is amazing. Well worth the extra cost.
And I am not a web developer! It's an extraordinary model.
(Mouse and keyboard required)
It’s good enough that I’m considering a second spark, or selling this and buying an M5 Ultra with 256GB for it
I always found that those Mimo models to be really good at tool calling and following instructions
API may be expensive, but I do 900m tokens (95% cached, ~0.4% output) on Z.ai's $18/mo coding plan with GLM 5.3 Flash.
For comparison, I am currently at 6.6B tokens, 95% of monthly quota on a 10$ command code plan, mostly using DeepSeek flash 4.1, or some of the free models for easier tasks.
now we r just noticing the grave getting dug deeper.
Trying to understand why users are using Luna when Sol seems essentially unlimited on the pro plan. Unless you have jobs running 24/7.
https://www.debtdefaultclock.us/
I had used 2.5-pro for a hefty chunk of development, and found it to work like a somewhat forgetful senior engineer who was new to my project. Very capable, would almost always choose a reasonable option, if not always the best one for the project, and not great at multi-tasking. Generally, made me comfortable not scrutinizing the code line-by-line, but still needed a bit of steering once projects got to a reasonable size.
The next model is a clear step up in the multi-tasking capability at least, with me very rarely having to steer the implementation of a well-defined issue. In terms of code, I found MiMo-V.2.5-pro to be extremely conservative, implementing minimal solutions. The next model seems a little bit more ambitious, in positive ways, making good guesses about gaps/next steps. It also seems to be a fair bit better at design, at least for the little bit I've done, it was good at translating my concepts to practical elements on screen, and cleaned things up nicely as I made suggestions.
Fable scores 70%, Kimi K3 69%, Astra 74% (all on max effort).
https://deepswe.datacurve.ai/blog/deepswe-v1-1
That's misleading.
1. Having different models available is useful for A/B testing and helping improve Gemini itself.
2. They have an enterprise offering for Antigravity (their agentic coding platform), and they need to test that it works well with non-Gemini models too.
Even flash reached 60.7% by step 12, and it's on step 16 now.
This is so exciting lmao.
Also, Anthropic and OpenAI probably want to keep each other on their toes so they don’t end up on the wrong side of another Opus 4.6 / GPT-5.3-Codex situation, where one lab releases a model only for the other to drop a better one hours later.
I still opus 4.6 though not for code
I’m saying who has a million dollars for me, so I can make my own model?
I'd guess everybody uses at least some benchmarks as stopping criteria, which is kinda sensible, but it also does induce some benchmaxxing, and explains partly why the newest models always tend to eke out in benchmarks.
https://en.wikipedia.org/wiki/Training,_validation,_and_test...
It's not the direct feedback loop of RL but its not far.
For some reason I thought training took much, much longer than what the progress bar suggests.
This is really neat, I'm currently using mimo 2.5 pro, and it's decent (or great given the price). Hopefully their next one is multimodal.
If you are going to develop a near frontier model, and you don’t think you have special sauce up your sleeve, why not making training runs and RL environment scores etc. visible to the world?
I’m genuinely learning quite a bit just from the dashboard
Keeping the garage door open, or at least making the door translucent. It's always cool.
Google had this GPT long go and a wise man within Google noted:
"We don't have any maot neither does anyone else."
The AI bubble burst is guaranteed and is only delayed by IPOs.
Open models have not yet caught up with February's Mythos checkpoint.
Meanwhile OpenAI is solving millennium problems, and their compute is still fully utilized.
Where is the cool shit from the US labs?
The US population is much more pessimistic and doomsday driven these days, whereas the Chinese are more optimistic and future driven.
In the short term, true.
In the long term, unknown but typically when you hold progress that way while other countries don't you at best end up becoming siloed while the rest of the world continues on without you.
Anthropic and OpenAI literally stole from every human in history and youre out here complaining that the Chinese are distilling models and releasing them to the public?
Why do you care?
/s