In addition to their excellent and unique training data, the Cursor team is also making major engineering contributions to v9 SFT & RL. It’s an honor and a pleasure to work with them.
For this 1.5T run, Cursor data was added in supplemental training, which is not quite as good as having it in initial training.
The 2T run that started a few weeks ago has greatly improved data in scope & scale in almost every arena, and many upgrades/fixes to the training recipe. That will finish in late July for August release.
Introducing Cursor for iOS.
Build from anywhere by launching always-on cloud agents. Or remotely control agents running on your computer from the app.
Composer 2.5 is 75% off in the app now through July 5.
To anyone saying Cursor is back.
I don’t think you’ve used Cursor lately, try it, I think you’ll see, it never left, it is the best it has ever been.
And try Composer 2.5, it is a very good model.
But holy moly are things going parabolic from here.
Massive win for software engineers around the world, and non-engineers that are going to become engineers.
This slide says a lot, no words needed.
SpaceX has exercised the option to acquire @cursor_ai in an all-stock transaction with the goal of building the world’s most useful AI models.
For the past few months, SpaceXAI has been jointly training a model with Cursor, which will be released in Cursor and Grok Build soon.
We look forward to working closely with the Cursor team to advance our frontier AI capabilities
We're launching code storage and git hosting.
Origin gives teams and agents a place to host, review, and collaborate on code.
Available this fall. Join the waitlist.
https://t.co/uamaIarJXY
Michael Truell says we're still early in automating software:
"It's really easy at an executive level to underestimate just how far away we are from the limit of automating software."
"I think that there's a really, really long way to go. There's a really long, messy middle."
"We are in a market that's had an iPod moment, and it's going to have an iPhone moment and another iPhone moment. And I think that there have been a couple of those so far. I think that there are definitely more in the future."
@mntruell with @martin_casado
Cursor’s code review agent is now over 3x faster, 22% cheaper, and finds 10% more bugs.
You can also use /review to run Bugbot locally to catch and fix issues before pushing code.
This is a great way to think about model selection and eval interpretation.
At enterprises, users will often set and forget the most expensive model and blow through CFO’s budgets in days.
Composer 2.5 has been a massive help for my customers dealing with these issues, but there there is still a place for the most expensive, most intelligent models like Fable.
It’s increasingly important to use the right model for a given task.
Composer 2.5 @cursor_ai just changed everything. In the last two weeks it completely took over my workflow. I used to switch between multiple models daily. Now? I barely touch anything else. Just look at my usage this billing period.
the economics of intelligence
> Cost per agent request varies by nearly 9x across model families, showing that the same workflow can have very different cost profiles depending on the model behind it.
some higher cost models are cheaper in the long run due to increased intelligence, but for p50 requests a model like composer 2.5 will do the job both faster and cheaper
a lot of interesting data in this report, recommend a read
We're hosting an event on June 16th in San Francisco.
Compile is a one-day event that brings together engineers, researchers, designers, and builders of all kinds to discuss the future of software.
https://t.co/8YERlPFooL
Cursor Composer 2.5's is 3–18x cheaper than Opus 4.7 in Claude Code (medium reasoning), and 5–32x cheaper than GPT-5.5 in Codex (medium) based on API pricing
This low Cost per Task isn't just driven by relatively low token pricing, it's also driven by low relatively low token usage compared to other leading models. @cursor_ai Composer 2.5 only used 1.6M token to complete our Coding Agent Index benchmarks, while other models used up to 5.7M.
This lower token usage also contributes to a low Time per Task. Across the Coding Agent Index configurations shown, average Time per Task was ~12 minutes. Composer 2.5 completed tasks in ~9 minutes on average, making it ~1.3x faster than average, while Composer 2.5 Fast completed tasks in ~7 minutes, making it ~1.8x faster than the average across agents.
Link to full benchmark results below