> "Best Frontier" includes GPT-5 and Sonnet 4.5, which both outperform Composer.

The fact that you are wondering this is bad. You definitely should know this. _ALL_ the online ai providers are training on your data. They have more expensive enterprise plans if want to opt out.

I tried going back to VS Code + Copilot a month ago. I only lasted 4 days because it was to bad. It was super slow and gave poor suggestions, but mostly it just flat out did not suggest anything. Cursor feels snappy in comparison and the suggestions are more often than not useful. The most annoying thing about Cursor tab complete, is that it is so fast that when I am doing something unusual then it will keep on jumping in with useless suggestions. They have a snooze function for this though.

There is a footnote that should help with the models. Training is a harder thing to report on, but roughly our finding here is that RL scales.

I dropped cursor for the precise reason you mention: reliability.

Countless times my requests in the AI chat just hang there for 30+ seconds more until I can retry them.

When I decided to give Claude Code a try (I thought I didn't need it because I used Claude in Cursor) I couldn't believe how faster it was, and literally 100% reliable.

EDIT: given today's release, decided to give it a go. The Composer1 model _is_ fast, but right at the second new agent I started I got this:

> Connection failed. If the problem persists, please check your internet connection or VPN

You tried Claude and still prefer cursor?

Yep, it just works seamlessly. Sure, it hangs sometimes, but their UI allows you to retry or undo changes to an earlier point in the conversation easily. The autocompletion is nice as well and pretty satisfying to tab through the small and menial things when refactoring.

> I’ve tried all the popular alternatives (Copilot, Claude Code, Codex, Gemini CLI, Cline)

Can't help but notice you haven't tried Zed!

I too have tried them all and have settled with Cursor being the best. That said I see the current space split between folks like me who know generally what I want built and appreciate a tool that helps me get to goal quicker and on the otherwise of the spectrum, folks who want the tool to orchestrate most of the engineering. I have no opinion on which is better but for me I sit on the first camp. In that camp Cursor is by far the best tool.

Agree that Sonnet 4.5 is an excellent model. Would be curious to hear your experience using Composer though, it's quite good.

> Sonnet 4.5 quality is about as low as I'm willing to go.

literally a 30 day old model and you've moved the "low" goalpost all the way there haha. funny how humans work

The reason I pulled out the comparison is to highlight how serious they are about all the important parts that make or break the AI coding experience - speed being very important to me. I’d rather catch my model doing the wrong thing quickly than having a higher chance of one-shotting it at the cost of having to do a lot of specification upfront.

There’s two different kinds of users, on one side people are more hands off and want the model to autonomously handle longer tasks on its own with minimal guidance, and on the other side is users who want to interactively collaborate with the model to produce desired results. Speed matters much more for the second case, where you know what you want and just want the model to implement whatever you had in mind as quick as possible. Intelligence/ability matters more for the first case when you don’t have full understanding of all the code. I think it’s context dependent for me where more serious work tends to be more interactive. The intelligence of a model doesn’t make up for issues due to lack of context to me.

Same... I've found that using a non-Claude model just ends up being more expensive and not worth it. "Auto" tokens are hardly free, and I've had plenty of experiences putting "Auto" to work on a "simple" seeming task to have it consume like 1 USD of tokens quite quickly while producing nothing of value, when I'd replay with Claude 4.5 Sonnet non-thinking and it would provide a solid solution for 0.5 USD.

gpt-5-high is as low as i can go :]

We also are big Tab users here at Cursor. In the blog we talk about the motivation for this project came from thinking about a Tab-like agent.

It's great. BUT: Wish they had selected another shortcut like shift+tab.

Every time I write code myself I find myself racing the AI to get an indentation in before the AI is done... gets annoying

I feel like that's like having a lead in producing better buggy whips.

I run Claude Code in the background near constantly for a variety of projects, with --dangerously-skip-permissions, and review progress periodically. Tabbing is only relevant when it's totally failing to make progress and I have to manually intervene, and that to me is a failure scenario that is happening less and less often.

Tab model is fantastic but I wish it was somehow aware of the conversation happening in the currently active AI chat session.

Is the new model trained from scratch? What training data went into it?

Is it true that Cheetah is Grok Code Fast 2? Does this mean that the new Cursor model is also based on Grok?

Why did you stop training shy of the frontier models? From the log plot it seems like you would only need ~50% more compute to reach frontier capability

is Composer a fine tune of an existing open source base model?

Which model did you distill it from? Great work! PS getting a few scenarios where it doesn't follow rules as well as sonnet 4.5

There is a youtube livestreamer building with it now, if you are looking for direct feedback: https://www.youtube.com/watch?v=1bDPMVq69ac

How do you work with multiple agents?

How many times have you needed to reset the optimizer during the RL training cycles?

I prefer the approach of focusing on faster models despite their lower intelligence because I want my IDE to fly when I can see the code. I find this useful when I need to manually debug something that any model is able to do, so I know it's going to fail but at least it will fail fast. On the other hand, if I need more intelligence I have my other CLI that doesn't allow me to see the code but gets the planning and difficult code done.

Can you please tell us more about how you used Ray for setting up the RL infrastructure?

Do you have any graphs handy that kind of replicates the one used first in the blog post but a bit less ambiguous, maybe without model grouping? I feel like it would have been a bit more fair to include proper names, and individualize them rather than group everything together by something, and then present your own model on its own.

Impressive systems write-up. A question: if Composer is an RL finetune on an open model, why keep weights closed? The edge from a slightly better checkpoint erodes quickly in this market, it's not a durable advantage. Composer protects Cursor's margins from being squeezed by the big AI labs, but that is true whether the weights are open or closed, and I think Cursor would have more lasting benefit by generating developer goodwill than from a narrow, short-lived advantage. But, that's just my opinion. I personally find it hard to get excited about yet-another proprietary model. GPT-5 and Sonnet 4.5 are around when I need one of those, but I think the future is open.

Amazing work! The UX is great.

GPT-5-codex does more research before tackling a task, that is the biggest weakness for me not using Composer yet.

Could you provide any color on whether ACP (from zed) will be supported?

Congratulations on your work. I spent the day working with a mix of the Composer/Sonnet 4.5/Gemini 2.5 Pro models. In terms of quality, the Composer seems to perform well compared to the others. I have no complaints so far. I'm still using Claude for planning/starting a task, but the Composer performed very well in execution. What I've really enjoyed is the speed. I had already tested other fast models, but with poor quality. Composer is the first one that combines speed and quality, and the experience has been very enjoyable to work with.

It's stunning.

I don't use these tools that much ( I tried and rejected Cursor a while ago, and decided not to use it ) but having played with GPT5 Codex ( as a paying customer) yesterday in regular VSCode , and having had Composer1 do the exact same things just now, it's night and day.

Composer did everything better, didn't stumble where Codex failed, and most importantly, the speed makes a huge difference. It's extremely comfortable to use, congrats.

Edit: I will therefore reconsider my previous rejection

my very small nit is... why is the model called Composer?? of all things?? when there was already a Cursor Composer from 2024.

Cursor Cheetah wouldve been amazing. reusing the Composer name feels like the reverse OpenAI Codex move haha

There are lots of good models we like here. But we agree that getting the right point on the smart+fast graph can make agentic coding feel really good.

(Cursor researcher)

We don't wear shoes [1].

[1] https://www.businessinsider.com/no-shoes-policy-in-office-cu...

We will do our best. Luckily I don't think there are major telecom companies called Composer-2.

you can use git worktrees and just have multiple Claude Code terminal instances working on each worktree. That way they don't clash, just delete the worktree when the task is done.

Unfortunately not, as we used our own internal code for the benchmark. We would also like to see more benchmarks that reflect the day-to-day agentic coding use.

Hey - really sorry to hear this - could you email me andrew@cursor.com? Here are 3 suggestions to try- 1. Reset your settings.json - if shared with vscode, sometimes settings can cause perf regressions 2. Could you try cmd-shift-p -> "capture and send debugging data"? Will send us some profiling data to debug 3. Clear your user data (will delete chats) as a last resort - cmd-shift-p, "reveal user data," close the app, then delete this folder and restart the app

I'm curious if their near-term expectation is that this is be better than these models or is this a model they tend to use in Auto mode, or if the focus is really if you want speed...? I guess my question is why would I actively chose this over Auto?

I understand where you're coming from, and I'd love to have learned about pre-training vs. off-the-shelf base model too. But

> their own internal benchmark that they won't release

If they'd release their internal benchmark suite, it'd make it into the training set of about every LLM, which from a strictly scientific standpoint, invalidates all conclusions drawn from that benchmark from then on. On the other hand, not releasing the benchmark means they could've hand-picked the datapoints to favor them. It's a problem that can't be resolved unfortunately.

Facts. They really need to make pricing more clear across the entire product.

As a stealth model, it was priced as $1.25M in / $10M out

Right now, it seems free when you are a Cursor Pro user, but I'd love more clarity on how much it will cost (I can't believe it'll be unlimited usage for subscribers)

Building off of VSCode was probably Cursors silver bullet and the best decision they could have ever made.

It made migrating for everyone using VSCode (probably the single most popular editor) or another vscode forked editor (but at the time it was basically all VSCode) as simple as install and import settings.

I do not think Cursor would have done nearly as well as it has if it didn't. So even though it can be subpar in some areas due to VSCodes baggage, its probably staying that way for a while.

Intellij's tab-complete is coming along; it's hit and miss if it will work but for similar edits I'm finding it picks up the pattern quickly and I can tab - tab - tab to make them happen.

Still not up to Cursor standards though :)

honestly better than I expected