I think it's also telling that they left out the usual hallmarks of the Pareto distribution: GLM 5.2, Qwen 3.7, Minimax M3, and Mimo 2.5

https://arena.ai/leaderboard/code/webdev/pareto

Good observation.

I actually started typing the same point that the chances are actually high because of train/eval overlap then realised you answered your own question with that same observation.

It is interesting though!

Perhaps in some way this means we should decide which eval set aligns best with our taste?

Back to the blog post. This is an excellent write up of an excellent technical achievement.

I have a lot of respect for the Cognition/Devin (always "Windsurf" to me) and Cursor teams.

I found it interesting - but justified - that they referred to themselves as a foundation lab rather than a dev tools company.

and what is actual intelligence per dollar benchmark ???? its useless comparing token/dollar while some model inherently generate more thinking output and cost more despite lower cost

Likely benchmaxxed. You see it in Qwen and other smaller models all the time.

> This tells me the benchmarks they use are cherry-picked.

Which benchmarks would you have chosen instead, and why?

Defining what "coding" means now, and how quickly we fall off the capability cliff seems increasingly important.

Today my "coding" sessions often enough begin with real life problems, where I discuss domain or inter-domain things, ranging from business, economics, psychology, etc. Being able to do all of that with one model is something I am willing to pay a premium for.

Of course not having to pay the premium, because the routing is smart or whatever, would be great. I just don't want to have to think about it.

Qwen was doing something like this with their coder models. But alas, they seem not to be releasing those anymore. Last one was Qwen3-coder-next.

And make it run locally!

And to do that you’ll need development so until we’re all out of a job they’ll keep pushing. Once automating is automated it’s done.

Like diplomacy? heh

I work with Devin daily (as well as Claude and a few others) and I can attest it's not a cheap product but it's a good one and it saves me a bunch of time.

Open weight models should have GPL-like license where it says if you train model on it, it needs to be open weight as well.

Yes, and not only that but you can't even access it via API, you can only use it in Devin (formerly Windsurf).

I'm an OpenCode user, but I'll fall back to Claude Code if I want to use Opus end to end for something, given my company has a subscription. But I'm not using yet another tool and subscription for a model that isn't even winning.

To be fair it does seem like most AI startups are now like this (particularly when it comes to constantly mentioning how hard they work and ignoring consumer markets).

Link for this?

I highly respect many people at cognition but yeah that's put a sour taste in my mouth.

I want to work in the AI space on actual AI research, at any part of the stack. Even if I'm developing training infra - as long as people are advancing knowledge of what intelligence could be.

But it seems like either it's big labs or grifters, that's it, and even the big labs, at least publicly, seem very grifty at times. Not like I have the technical chops probably, but still.

> "A company whose first demo was completely fraudulent"

Could you expand on this?

Would love to see these companies use benchmarks done by third parties.

What happened ?

Why? I'm personally on the opposite end. Less babysitting/higher quality means more time goes back to me/the user. 1000tps of bad code means you have to keep validating the output and circling back.

Indeed. For me opus 4.8 is good enough. If only it would be 100 times faster. You could run it in self verification loops much much faster. It sometimes takes 15 minutes for me to complete a simple task. For example configuring AWS agentcore and deploying an agent on it. Takes forever with Claude with constant issues it tries to solve.

Because papers are often referred to by the first author’s name, and often the first author is the primary researcher and therefore deserves the extra credit. When two or more primary authors are equally involved, they’ll often do a random ordering but annotate this so that no one thinks one did more than the others.

Harness-wrapper tools that support multiple harnesses and allow sharing workspace features (skills, slash commands, etc.) between them will be meta.

Ugh, that changes everything. If I wanted an arranged marriage I could go back to Claude Code.

Pretty sure most benchmarks are being gamed by people training on the test set deliberately or accidentally anyway.

Is this open source? I can't find a link to download the weights.

Not open source. Also, not available beyond it's own harness.

The reality is most people building their own models and providing that alongside SOTA ones don't really care about how great these models are. They just prove that 'hey we are smart enough to build our own models so you can trust us instead of going with a single provider like Claude via Claude Code', also a cheap alternative for cost sensitive/free users - at least this was the case for Windsurf, not sure if Devin Desktop still has that tier. They just need to hillclimb the benchmarks and show something reasonable enough there.

Benchmarks are just vibes with error bars... wake me up when it survives a week on a real codebase without hallucinating a package that doesn't exist.

Funny, the cheerleading at HN for leading Chinese models, but a non Chinese lab (building on top of a Chinese model) gets dissed here.