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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.

Hi everyone,

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.

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.

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.

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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?

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)

I used the new system tonight and it felt like a definite downgrade. Generated a few non-working basic apps, couldn’t handle CSS in a NextJS environment. Terminal context didn’t work. And it went back to not reasoning through the problem until resolution. And kept slowing down.

I’m assuming major release vs stable, but this is pretty lackluster so far. Switched back to Sonnet reasoning. Here’s to improving!

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!

[0]: https://cognition.ai/blog/swe-grep [1]: https://github.com/aperoc/op-grep

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?

What I can't stand about cursor is the constantly changing and confusing billing and usage.

I think competition in the space is a good thing, but I'm very skeptical their model will outperform Claude.

Insane velocity from the Cursor team. I wonder how they move so fast?

This looks like a model RLed on top of Qwen3-Coder or GLM 4.6 as per their graph and foot note.

Cursor 2.0 keeps crashing on me while having an agent running and opening the IDE part of the application. I might have to rollback.

Where is the comparison with Sonnet 4.5? That would be the only thing that matters, really.

I wish it was easy to find out how much it costs relative to Claude :)

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.

see also https://cursor.com/changelog/2-0 and https://cursor.com/blog/2-0

other links across the web:

https://x.com/amanrsanger/status/1983581288755032320?s=46

https://x.com/cursor_ai/status/1983567619946147967?s=46

is Cursor Bench open? Would like to see an open benchmark for agentic coding

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 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).

One thing no competitor is serious on is average response completion time. Cursor lapped everyone there

Here's the Composer 1 pelican riding a bicycle: https://static.simonwillison.net/static/2025/cursor-1-pelica...

Feels like the comments are fighting of prepaid influencers.

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.

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.

Very cool, congrats!

Same price as GPT-5

The metrics in the post seem quite abstract. Does anyone know the detailed metrics of this mysterious model? Was it fine-tuned from open models or trained from scratch?

I just gave it a try and it's reaally fast. Didn't expect this from you Cursor, good job.