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> Composer 2.5 is built on the same open-source checkpoint as Composer 2, Moonshot's Kimi K2.5.

Really nice to see they're giving credit to the company and I am optimistic Kimi K open models soon will outperform Opus models



Sounds like it's the last Kimi-line model at Cursor? As expected they say they'll be training a larger model on the SpaceX infrastructure, or have already started most likely.

I'm very curious to read about the Composer 3 architecture when it comes out. More frontier coding models are a good thing, especially if they diversify into different strengths/weaknesses.


That only seems plausible if whatever corpse of xAI is around is giving them engineering time. I don't know if they hired a bunch of ex frontier lab staff but its unlikely they have the technical capability to train their own frontier models especially the pretraining. Because the thing is if its not competitive with claude/codex it will be panned.


Hmm, I read the situation a little differently. Grok is not a slouchy model. It’s not the best, but it’s not the worst. X currently has one source of proprietary data, Twitter, and grok is by far the best at all the things you might imagine there - today’s zeitgeist, who’s saying what, current news, etc.

Cursor adds in a large corpus of proprietary coding data — I think this is actually fairly hard to acquire right now, because claude and codex are so good.

I bet there’s enough talent at the Grok team to work with the cursor team and data to get something good out the door.

That said, I don’t track Grok’s engineering leads — I’m not sure who’s currently around, and who is not.


Unlikely, given that large swathes of talent have already left xAI, ostensibly due to poor leadership management. Simply throwing money in to build the biggest datacenters in the world doesn't do much good without bright minds to back it up. https://www.fastcompany.com/91531084/inside-the-xai-exodus


Be careful taking the headlines at face value - that list of people leaving was mostly product and redundant senior execs to my eyes, post spacex merger. You’d expect those folks to be asked to leave as part of a re-org in any event. I don’t think it’s dispositive one way or the other on the tech org.


You are wrong, they were not redundant execs.

They were world-class senior developers and AI engineers most renowned in the AI research communities (e.g. Jimmy Ba the legend, Christian Szegedy, Igor Babuschkin, Greg Yang), poached from other companies to join xAI and they were getting very high salaries.

The mass exodus has been happening way before spacex merger though.


Interesting. Agreed that’s a significant list.

Post model 3 launch, Tesla had a number of senior folks leave almost immediately. My read at that time was they had hit or exceeded pareto-optimal on the suffering:wealth scale —- Tesla was clearly going to make it, and they had already vested 90% of the value they’d receive from Tesla ownership: why go suffer through the massive build out?

And in fact, in that era, Tesla did bring in a bunch of auto industry types to help scale, who as it happens also certainly did very well, but order of magnitude less well than the early peeps.

There might be some similar economics here: change of control will often fully vest early founders. Combined with incoming SX IPO, these guys are done financially — as in, already multibillionaires pre-IPO. You’d have to want to stay and the company would have to really want you to stay as well before it made economic sense to re-up.

People say a lot of things about working for Elon; things like “hardest work I ever did,” and “he made me extremely rich”, but you don’t read “that was easy” very often.

I have no idea if there’s enough talent right now at xAI to go build a foundation model, but in the immortal worlds of Carl Icahn: “don’t bet against Elon”


There's been also a lot of good talent joining xAI lately.


> I am optimistic Kimi K open models soon will outperform Opus models

Hard to outperform the model you distill...


Most of the performance on coding comes from RL, not distillation.

Distillation helps with world knowledge and things like that.


They're not distilled. Stop spreading anthropics misuse of the term.

They do use it for synthetic data/judging though, so yes, hard to outperform.

Not that they need to. If they can basically match it for a fifth of the price.


Is that true? If the distillation is not lossy and the model runs much faster due to less resource consumption, then it may outperform.


One of those conditionals is a pretty huge assumption.


It's an assumption and it can be tested


Only because last time they tried to hide it lol


Yes and if I remember the drama correctly - Kimi's license or terms of use says that for commercial use cases (or was it user count?) - you must declare credit to Moonshot and Kimi.


It's important to mention: they were compliant, because they trained the model at an AI hosting provider that had a partnership with Moonshot AI, but Moonshot didn't know Cursor was a customer.


This was misinformed Twitter and Reddit drama.

They had properly licensed it and were complying with the terms of the license.


Note that something that helped the misinformation was that, on Twitter, there were Kimi employees expressing their surprise that the base model was Kimi K2.5, and their indignation that Cursor didn't credit Kimi. They later deleted their tweets (what I infer from that is that some employees were not aware of some pre-existing agreement or understanding between Cursor and Kimi until the drama happened).


How can distilled opus become better than original? There are numbers of reports including anthropic that kimi team was participating in fraudulent activities


Do we know the "fraudulent " requests really came from moonshot engineers and was not QA team running a ton of benchmarks against other models?

I feel distilling something as big as Opus would require many many more samples, but I dont really know much about this subject


sure, sounds like QA lol

Scale: Over 3.4 million exchanges

The operation targeted:

Agentic reasoning and tool use Coding and data analysis Computer-use agent development Computer vision Moonshot (Kimi models) employed hundreds of fraudulent accounts spanning multiple access pathways. Varied account types made the campaign harder to detect as a coordinated operation. We attributed the campaign through request metadata, which matched the public profiles of senior Moonshot staff. In a later phase, Moonshot used a more targeted approach, attempting to extract and reconstruct Claude’s reasoning traces.


And when you here unsubstantiated rumours* that ­say Anthropic has been sending exchanges to say Alibaba's Qwen, will you als oconclude the same about the entire US AI industry?

I doubt it.

* publish the logs.


Even if it's true, it's not like US AI companies can complain, given their entire business is based on ripping off text without attribution


chinese ai is not doing the same? or they don't parse?

they do except they also send thousands of sex-spies to do espionage of this kind on the scale.


Of course they’re also doing this, my point is this is a grubby business where ethics went out of the window a long time ago.

If you’re playing this game in 2026 you know the rules - anything goes


"they also send thousands of sex-spies"

Could they send one (or two) my way?




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