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MiMo Code is now released and open-source

mimo.xiaomi.com

111–120 of 338 posts

Re: MiMo Code is now released and open-source

#111
post #88

Earlier quoted context omitted.

> promote the free-for-a-limited-time use of their new coding AI service Not sure which "free" service you're referring to, but MiMo v2.5 Pro is plenty capable & (after its recent 70%+ price drop) one of the most affordable options in its class ( DeepSeek v4 Pro , MiniMax M3 , & Qwen 3.7 Plus ). I read somewhere that Labs are incentivized to implement custom harnesses because each model has its strengths, quirks, & b…

What I like about MiMo too is that it is multimodal. For example, I can send screenshots of what I'm developing and it understands.

I thought only the MmiMo 2.5 non-pro was multimodal?

Re: MiMo Code is now released and open-source

#113
post #94

What a transformation by Xiaomi to build almost frontier level models. Five years back, when I was in the data science team, they dint really bother about AI models and were using Baidu for NLP and vision under the hood of their APIs

[flagged]

> While Americans Oppose AI Data Centers

I know it's more mixed and complex than this, but i think a big opposition is not to the data centers themselves but to their locations. Too often it feels like the centers are exploiting local resources and community infrastructure rather than paying their share or locating themselves in places that are less likely to cause problems to home owners.

The whole process feels indifferent or even adversarial at times.

Re: MiMo Code is now released and open-source

#114

Xiaomi have been cooking a lot in recent times. Their model, especially the pro series, is underrated in my opinion. It haven't received the attention it deserves while it is pushing higher and higher in benchmark scores (looking at artifical analysis), and this was before Deepseek dropped V4. Furthermore, their pricing plan is insanely cheap, they even upped usage limit for their cheapest plan, lite plan, which is a…

Looks like they have very effective collaboration with DeepSeek and Kimi. Those three models have been bouncing ideas and sharing R&D innovation, which made all of them improve very fast. Based solely on quality and price, OpenAI, Anthropic, and other western models just can't compete with the new generation of Chinese open models.

>Looks like they have very effective collaboration with DeepSeek and Kimi.

The collaboration is informal. People don’t seem to realize this, but the Chinese internet for programmers and developers today feels a lot like StackExchange in its heyday. There’s a huge emphasis on sharing knowledge, because sharing what you know builds your profile, and becoming a rockstar in a subfield is one of the only ways to get ahead.

Competition in China is ruthless. But unlike in North America, where individuals are often bound by agreement to hoard knowledge because it can give them a competitive edge, the competitive advantage in China is building face and peer recognition. And that comes from proving that you are worthy of being a "master/teacher", and that extends to the valuation of your knowledge business. For example, the third wave coffee shops in China, the master roaster is often called "master/teacher" once they win a roasting competition and start sharing new knowledge of roasting in the public sphere, and that's a title of sincere respect.

You can see parallels with those that apply to give talks at conferences and post snazzy technical presentations they give in the US, but the bar for what qualifies as new knowledge is far higher in China because there's a massive ecosystem of people rushing to outcompete what you have to offer, and once the ball gets rolling on knowledge sharing, lots of people will go off and build upon that knowledge or try to build businesses on top of that, which in turn produces more knowledge.

Reading developer forums in China, once you crack the code (I find Gemini will get you a good chunk of the way with good translations), they are really quite far ahead with what they're willing to share. And I suspect in great part, the decision to release open-weights is heavily tied to that concept of building face/peer recognition = building valuations.

Re: MiMo Code is now released and open-source

#115
post #88

Earlier quoted context omitted.

> promote the free-for-a-limited-time use of their new coding AI service Not sure which "free" service you're referring to, but MiMo v2.5 Pro is plenty capable & (after its recent 70%+ price drop) one of the most affordable options in its class ( DeepSeek v4 Pro , MiniMax M3 , & Qwen 3.7 Plus ). I read somewhere that Labs are incentivized to implement custom harnesses because each model has its strengths, quirks, & b…

What I like about MiMo too is that it is multimodal. For example, I can send screenshots of what I'm developing and it understands.

Only non-pro is multimodal I believe

Re: MiMo Code is now released and open-source

#116
post #31

Earlier quoted context omitted.

Sounds like they slapped in a bunch of common plugins and released it as a product to promote the free-for-a-limited-time use of their new coding AI service.

> promote the free-for-a-limited-time use of their new coding AI service Not sure which "free" service you're referring to, but MiMo v2.5 Pro is plenty capable & (after its recent 70%+ price drop) one of the most affordable options in its class ( DeepSeek v4 Pro , MiniMax M3 , & Qwen 3.7 Plus ). I read somewhere that Labs are incentivized to implement custom harnesses because each model has its strengths, quirks, & b…

I'm guessing the greatest reason behind each provider creating and agent harness is that (a) there is not a clear winner still and (b) it is harder to switch models with a competitor, as you also have to switch harness

Re: MiMo Code is now released and open-source

#118
post #114

Earlier quoted context omitted.

Looks like they have very effective collaboration with DeepSeek and Kimi. Those three models have been bouncing ideas and sharing R&D innovation, which made all of them improve very fast. Based solely on quality and price, OpenAI, Anthropic, and other western models just can't compete with the new generation of Chinese open models.

>Looks like they have very effective collaboration with DeepSeek and Kimi. The collaboration is informal. People don’t seem to realize this, but the Chinese internet for programmers and developers today feels a lot like StackExchange in its heyday. There’s a huge emphasis on sharing knowledge, because sharing what you know builds your profile, and becoming a rockstar in a subfield is one of the only ways to get ahead…

Thank you for the insights, this sounds like an environment I want to partake.

> Reading developer forums in China, once you crack the code (I find Gemini will get you a good chunk of the way with good translations), they are really quite far ahead with what they're willing to share.

Are you able to share those forums and other resources? I would love to read what people in these communities are sharing.

Re: MiMo Code is now released and open-source

#119
As much as I absolutely love Mimo V2.5 Pro (it's a genuinely good model), I absolutely hate the way they calculate usage in their token plan.

For example: For a super small task in a small project that should not be consuming more than 500K total tokens after all tool calls included, their shown usage shot up to 152 million tokens.

But, when I scroll down on the same page, a table shows usage as 3 million tokens, out of which 2.5 million were cached.

This is such a huge conflict on the very same page. The bad thing is that the usage progress bar is shown against that 150 million token usage, not against that 3 million one.

This has been in discussions for at least past 3 months on reddit as well, and was precisely the reason I subscribed to their lowest tier, and for a single month only.

Update: their own harness, mimocode, shows total token usage as just 63.1K. We now have 3 entirely different values, differing in 3 orders of magnitude.

Update 2: So, I did the exact same task this time using DS4Pro, and total token usage was just 101K (as shown by opencode).

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