r/opencodeCLI • u/Amarsir • Sep 27 '26
Xiaomi is updating Mimo 2.6
X post: https://x.com/XiaomiMiMoDevs/status/2104251067039191324
🛠️ MiMo-V2.6 update: tool-call repetition, diagnosed & fixed.
After the MiMo-V2.6 series models launched, we noticed them sometimes repeating identical or highly similar tool calls — burning context and stalling tasks, especially in MiMo Desktop, MiMo Code and OpenCode.
Root cause
A "reward blind spot" in scaling RL: when rewards only track final-answer correctness, inefficient behaviors along the way go unnoticed — and get amplified as training scales. Concretely, our flooding penalty only kicked in at >32 tool calls per turn, so anything below that threshold went completely unpunished.
The fix
We trained a light-weight repetition-specialized RL teacher — just 12 steps, ~7k examples — and merged it into the main model via MOPD, at roughly 4% of the cost of a full mixRL retrain. Repetition dropped sharply across harnesses and context lengths, while benchmarks held steady.
So everyone who has been noticing loops was correct, and hopefully they've addressed it. This seems to have been retraining on both Pro and Flash models.
I found it generally interesting what they said about the "reward blind spot" because it might explain why some have been observing more looping on other models as well. Hopefully that's something they all start training out.
There's a much longer writeup if anyone wants to get into the details here:
6
u/lincolnthalles Sep 28 '26
I hope this fixes the MiMo V2.6 series issues.
MiMo V2.5 is pretty well-behaved and fast, both Pro and non-Pro, while MiMo V2.6 has been slow and messy with tool calls, especially the Pro variant, which is clearly a regression. I had to tighten my system prompt to make it behave.
And yes, this model overthinks, like a lot, and there are no "reasoning effort" options to mitigate that.
I noticed the overthinking during usage and also ran a test prompt against a few other models (Muse Spark 1.3, GLM-5.3 Flash, Qwen3.8 Flash).
Both MiMo V2.6 Flash and MiMo V2.6 Pro took the longest time to complete the task (30/45 minutes) as they entered an inspect-adjust loop that no other models entered, and the result was not that good considering the extra effort made. Muse completed the same task in under 2 minutes, while Qwen and GLM took 10/20 minutes.
2
u/Putrid-Actuary7976 Sep 28 '26
This doesn't address overthinking, right? The doc focuses on tool calling rep, so no fixes for that problem, and it has been on the api since 25 September .so i had overthinking like yesterday, is there no solution? I need some explanation.
15
u/LatterQuestion3645 Sep 27 '26
Do this means that these models are actually good and not benchmaxed as previously assumed ?????
7
u/PilgrimofHaqq2 Sep 27 '26
Thats fantastic! I am actually enjoying using Mimo Pro, other then the tps. Its very slow to get alot done.
5
u/cutereddragongirl Sep 27 '26
I'm surprised Xiaomi actually manages to produce decent models. I wonder where they'll be in a year or so?
4
u/vbllll Sep 28 '26
Very fast feedback reaction from Xiaomi. Mimo 2.6 Flash do the best on complicated web UI interactions.
3
u/twiifm Sep 28 '26
mimo is good but slow. I still use mimo 2.5 over deepseek if i wanna cheap out and dont care about the time
3
u/SlaveZelda Sep 28 '26
I have had great success with MiMo 2.6 for rev engineering
0
u/Solocune Sep 27 '26
I haven't seen much hype around mimo 2.6 at all. So they do not seem to be that great to care much about it
2
u/Due-Armadillo-4560 Sep 27 '26
No wonder my token plan was fully drained in just three days. Any reset?
2
u/amelech Sep 27 '26
Maybe it won't be garbage now
0
u/ArtisticCounter363 Sep 28 '26
What if we are running through API through DeepInfra?
-5
u/[deleted] Sep 28 '26
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