Say what you want about Cursor but they don’t lack for ambition.
Forking VS Code, going big on bleeding edge features like cloud agents, and now they’ve thrown down the gauntlet directly challenging frontier labs by training their own model (“much larger” than Kimi 2.5’s 1T parameters) from scratch.
They’ve been highly successful so far. Raised $50B, $2B in revenue, forecast to end 2026 above $6B. But even at these heights, they’re just not in the same league as OpenAI/Anthropic/Google.
And if building a state of the art multitrillion parameter model is not challenging enough, it’s a mountain you don’t climb just once. Every few months you need to push it farther with a new release. Fall off for a couple cycles and like Facebook you may never catch up again.
It is most likely AI generated with a nice "Raised $50B" hallucination and filled with cliches ("thrown down the gauntlet", "mountain you don’t climb just once", "not for the faint of heart").
EDIT: As others have pointed out, the comment above contains hallucinations (Like the $50 billion number) and a lot of AI tells. The account doesn’t have a history of AI-like comments but the hallucinations and structure in this one are suspicious. If anything, don’t trust the numbers it cites because they’re made up.
Cursor is a team that I want to see succeed. They have stacked their company with very smart people and they’re going hard at a highly competitive market. We all win when there is more competition and more innovation.
My problem is that every few months I look at Cursor’s product offerings and maybe retry it, but it never feels like something I want to use. Part is personal preference, the other part is the fact that my combination of other tools and services just does a better job. Their biggest advantage felt like first-mover advantage when they came out early and captured market share, but at in person meetups I hear stories about companies switching away from Cursor or trying to convince their management to let them switch away. They need to come up with a compelling advantage fast, which is a hard thing to do against the other companies with their virtually unlimited budgets by comparison.
1. Evidently you’re no longer able to distinguish AI from people as the whole comment was written by a human off the cuff.
2. The numbers are not hallucinations. It’s word on the street reporting, so yes it’s speculative, but a model did not make up it up unless that’s where TechCrunch got it which is not on me.
Same, I kick the tires on Cursor every several weeks wanting to find they've finally crossed some chasm I can't quite explain. But every time, I bounce off the ground-truth that they're forked off vscode, which just isn't for me. I think moving agents to the center of their experience and developing a model that focuses on speed/efficiency over maximum depth is a promising step away from being a spicy vscode fork.
My company is heavy on Cursor and I still ask them to provide me GitHub Copilot, for the sole reason that Cursor is probably the reason Microsoft had to implement technical enforcement of their TOS on proprietary plugins. Previously, you could use PyLance on VSCodium but now those plugins do not work outside VSCode anymore.
If Cursor (and every other commercial VSCode forks) didn't use MS extension store in the beginning and violate the TOS these might not have happened.
Yeah I want them to do well. I find Cursor to be a much better tool for actually working with the code the agent writes than whatever the big vendors provide.
> now they’ve thrown down the gauntlet directly challenging frontier labs by training their own model (“much larger” than Kimi 2.5’s 1T parameters) from scratch.
To clarify, the model Composer 2.5 announced in this post is not that; it uses Kimi 2.5 as a strong starting point. This is not to discount Cursor's work or future ambitions, but one of the most striking things about the last 6 months is that multiple open-source models/labs are now within striking distance of the frontier closed-sourced labs.
They have no choice but to train their own model to try and survive. They're paying API pricing for the top tier models but competing against subsidized subscriptions.
Them raising this much money doesn't mean they're successful, it only means they know how to fool the investors well. A project that is basically an extension to VSCode only adding a chat interface, isn't really worth this much money. Obviously, it's the users, but people think it's something genius and revolutionary, but no.
Less hot air and more substance please. It’s easy to deconstruct a company as an arm chair quarterback. It’s much harder to build a viable one. Until you have something constructive, kick rocks. Hot air is boring.
I realize you’re a troll account but at least be a fun troll.
I think that the product is easy to build, that's what I think because in my gathered experience it's easy. What more do you want?
This is the last time I'm responding. Good luck on whatever journey you're on. I'm sure it's an interesting journey since you've realizations over troll accounts, very interesting.
As a heavy user, I don't think the model is their product. Cursor is primarily a harness and lately, a specialized agent dashboard.
Composer, their in house model, is dispatched by other models like Claude Opus for individual items on a task list. No one is suggesting you write your main prompt to Composer 2.
they aren't "throwing down the gauntlet", they're trying to find ways to eke margin out of their product by owning a commodity-level coding model. it's an impressive engineering task but it's not particularly ambitious.
Forking VS Code, going big on bleeding edge features like cloud agents, and now they’ve thrown down the gauntlet directly challenging frontier labs by training their own model (“much larger” than Kimi 2.5’s 1T parameters) from scratch.
They’ve been highly successful so far. Raised $50B, $2B in revenue, forecast to end 2026 above $6B. But even at these heights, they’re just not in the same league as OpenAI/Anthropic/Google.
And if building a state of the art multitrillion parameter model is not challenging enough, it’s a mountain you don’t climb just once. Every few months you need to push it farther with a new release. Fall off for a couple cycles and like Facebook you may never catch up again.
Not for the faint of heart.