More training scale, still aggressive pricing, and a better model for long-running coding work.
That is Composer 2.5 in a nutshell.
It continues from the same base as Composer 2, and this version is trained to be better at sustained work, complex instructions, communication style, and effort calibration inside Cursor.
Targeted textual feedback helps the model improve specific mistakes inside long rollouts, while 25x more synthetic tasks push it into harder coding problems grounded in real codebases.
Looking forward to the next larger model trained from scratch with 10x more compute!
About Composer 2.5 on Product Hunt
“Cursor’s most powerful model yet”
Composer 2.5 launched on Product Hunt on May 19th, 2026 and earned 393 upvotes and 12 comments, earning #3 Product of the Day. A substantial improvement in intelligence and behavior over Composer 2, particularly on long-horizon agentic tasks.
On the analytics side, Composer 2.5 competes within Artificial Intelligence and Development — topics that collectively have 476.3k followers on Product Hunt. The dashboard above tracks how Composer 2.5 performed against the three products that launched closest to it on the same day.
Who hunted Composer 2.5?
Composer 2.5 was hunted by Zac Zuo. A “hunter” on Product Hunt is the community member who submits a product to the platform — uploading the images, the link, and tagging the makers behind it. Hunters typically write the first comment explaining why a product is worth attention, and their followers are notified the moment they post. Around 79% of featured launches on Product Hunt are self-hunted by their makers, but a well-known hunter still acts as a signal of quality to the rest of the community. See the full all-time top hunters leaderboard to discover who is shaping the Product Hunt ecosystem.
Zac Zuo
Hi everyone!
More training scale, still aggressive pricing, and a better model for long-running coding work.
That is Composer 2.5 in a nutshell.
It continues from the same base as Composer 2, and this version is trained to be better at sustained work, complex instructions, communication style, and effort calibration inside Cursor.
Targeted textual feedback helps the model improve specific mistakes inside long rollouts, while 25x more synthetic tasks push it into harder coding problems grounded in real codebases.
Looking forward to the next larger model trained from scratch with 10x more compute!