I wonder if this custom model is trained on cursor users. There’s a lot of potential on how much better a custom model could be the closer it is integrated with the product. Having the model learn to adapt to different user preferences would make it stand out compared to memoryless frontier models.
I love Cursor. I've tried Copilot/Claude/etc. but keep coming back to Cursor. I just want to work, and Cursor tab complete is dang accurate, esp. for refactoring tasks.
While I am excited to see a new model, I am skeptical when there is so much vagueness - charts with "frontier models" without actually spelling out which ones, charts with no numbers (time axis, or in one chart - entirely).
People on here love to be contrarian about Cursor, but I’ve tried all the popular alternatives (Copilot, Claude Code, Codex, Gemini CLI, Cline) and found Cursor’s overall experience to just be unmatched. A big part of that is its speed, another its reliability.
It’s the only coding agent I’m actually really motivated to use out of the box because it really does make me feel more productive while the others keep messing up the project, from way too large changes I didn’t ask for all the way to constant syntax and request errors.
It’s the only coding agent I’ve used that feels serious about being a product rather than a prototype. Their effort in improving their stack is totally paying off.
I used Cursor for the total of one day (paid for a year subscription), discovered Claude Code later that day and havent opened Cursor since.
Note, later I started using Codex and now Codex is my daily driver, Claude Code for problems where Codex fails (not many), and again Cursor is never used.
They were the first mover but Codex (in my opinion) blows Cursor up into 1000 tiny pieces. It's just so, so much better.
Maybe I'm an outlier but Sonnet 4.5 quality is about as low as I'm willing to go.
It's generation speed is not the problem or the time sink.
It's wrestling with it to get the right output.
---
And just to clarify as maybe I misunderstood again but people are comparing cursor to Claude Code and codex etc here- isn't this whole article all cursor just using different models?
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.
Cursor has the best Tab model, and I feel like their lead there has kept growing - they're doing some really cool things there. https://cursor.com/blog/tab-rl
I wonder how much the methods/systems/data transfer, if they can pull off the same with their agentic coding model that would be exciting.
I agree, I tried to switch to Zed this week, and I prefer it in all respects, but the tab model is much worse, and it made me switch back. I never imagined I would care so much about a feature I felt was secondary.
I actually find myself using the agent mode less now, I like keeping code lean by hand and avoid technical debt. But I do use the tab completions constantly and they are fantastic now ever since they can jump around the file.
I am an ML researcher at Cursor, and worked on this project. Would love to hear any feedback you may have on the model, and can answer question about the blog post.
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.
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.
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.
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
Please keep the naming of your models sane, I'd like to know that composer 1 is the first model and composer 2 is second but composer 1o is not yet another 1 variant that's actually newer and better than 2, that's just dumb. Not that you're doing that, some other companies do that.
Could anyone explain how to use multiple agents and subagents in Cursor, Claude Code, or others? It is already challenging to me taming one model doing work, let alone synchronizing multiple parallel workers.
Do you have to split the plan in parallelizable tasks that could be worked in parallel in one codebase without breaking and confusing the other agents?
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
For anyone else who was wondering, it looks like the within-Cursor model pricing for Cursor Composer is identical to gemini-2.5-pro, gpt-5, and gpt-5-codex: https://cursor.com/docs/models#model-pricing
($1.25 input, $1.25 cache write, $0.13 cache read, and $10 output per million tokens)
The lack of transparency here is wild. They aggregate the scores of the models they test against, which obscures the performance. They only release results on their own internal benchmark that they won't release. They talk about RL training but they don't discuss anything else about how the model was trained, including if they did their own pre-training or fine-tuned an existing model. I'm skeptical of basically everything claimed here until either they share more details or someone is able to interpedently benchmark this.
I love cursor, the tab completion and agent mode. But I really dislike vscode after using intellij for so many years. I really wish the underlying editor was better, or I could get cursor features in intellij instead. The editing of the files is mostly fine, but its everything else around it that a full IDE provides thats just so much better. Right now its intellij + claude code for me, and its fine, but I wish I could get the AI power of cursor in a better package.
I think both Cursor and Cognition and going in the same direction of SWE-grep[0].
SWE-grep was able to hit ~700tokens/s and Cursor ~300token/s, hard to compare the precision/recall and cost effectiveness though, considering SWE-grep also adopted a "hack" of running it on Cerebras.
I'm trying to kickstart a RL-based code search project called "op-grep" here[1], still pretty early, but looking for collaborators!
44 comments
[ 3.1 ms ] story [ 59.0 ms ] threadIt’s the only coding agent I’m actually really motivated to use out of the box because it really does make me feel more productive while the others keep messing up the project, from way too large changes I didn’t ask for all the way to constant syntax and request errors.
It’s the only coding agent I’ve used that feels serious about being a product rather than a prototype. Their effort in improving their stack is totally paying off.
Note, later I started using Codex and now Codex is my daily driver, Claude Code for problems where Codex fails (not many), and again Cursor is never used.
They were the first mover but Codex (in my opinion) blows Cursor up into 1000 tiny pieces. It's just so, so much better.
It's generation speed is not the problem or the time sink.
It's wrestling with it to get the right output.
---
And just to clarify as maybe I misunderstood again but people are comparing cursor to Claude Code and codex etc here- isn't this whole article all cursor just using different models?
I wonder how much the methods/systems/data transfer, if they can pull off the same with their agentic coding model that would be exciting.
I actually find myself using the agent mode less now, I like keeping code lean by hand and avoid technical debt. But I do use the tab completions constantly and they are fantastic now ever since they can jump around the file.
I think competition in the space is a good thing, but I'm very skeptical their model will outperform Claude.
I am an ML researcher at Cursor, and worked on this project. Would love to hear any feedback you may have on the model, and can answer question about the blog post.
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?
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
other links across the web:
https://x.com/amanrsanger/status/1983581288755032320?s=46
https://x.com/cursor_ai/status/1983567619946147967?s=46
Do you have to split the plan in parallelizable tasks that could be worked in parallel in one codebase without breaking and confusing the other agents?
($1.25 input, $1.25 cache write, $0.13 cache read, and $10 output per million tokens)
SWE-grep was able to hit ~700tokens/s and Cursor ~300token/s, hard to compare the precision/recall and cost effectiveness though, considering SWE-grep also adopted a "hack" of running it on Cerebras.
I'm trying to kickstart a RL-based code search project called "op-grep" here[1], still pretty early, but looking for collaborators!
[0]: https://cognition.ai/blog/swe-grep [1]: https://github.com/aperoc/op-grep