Introducing SWE-2 Flash, our new fast & efficient coding model. On leading evals, it outperforms all American open-weight models, even ones 3x larger. To balance transparency and cyber risks, we are building a program to securely share the weights with partners & researchers.

We've evaluated Gemini 4 Carbon and Gemini 4 Argon on FrontierCode 2.0, our coding benchmark that measure's a model's ability to go beyond the spec. Gemini 4 Carbon scores near SOTA with a score of 40% and a cost of $4.04 per task, behind Claude Opus 5.5, GPT-6 Astra, and Claude Sonnet 5.5. Gemini 4 Argon scores 26.3% with a cost of $6.41 per task, ahead of Muse Wonder 1.0, but behind Claude Haiku 5.5 and Grok 4.7. See the leaderboard with full scores:

On our price vs performance evaluation, models cluster into several groups. ▪️ Opus 5.5 and GPT-6 Astra lead in intelligence, at average costs of $12.8 and $6.67, respectively. ▪️ GPT-6.1 Sol leads in cost efficiency, scoring 39% at $1.03 per task. ▪️ GPT-6 Luna and Haiku 5.5 lead on overall cost, scoring above 20% at less than $0.50 per task. Chinese OSS models lag far behind, with Kimi K3 and GLM 5.3 scoring at 17%. American OSS models like Beam and Inkling are even further behind with a score of 3%.

Introducing FrontierCode 2.0: our new coding benchmark that measures a model’s ability to go beyond the spec. Most coding evals measure a model’s ability to write code that meets a spec. With FrontierCode 1.0, we asked a new question: would you actually merge the PR? FrontierCode 2.0 is comprised of more diverse tasks, featuring larger scopes and higher mergeability standards. We are now asking: not only would you merge this PR, but should you? One key feature of FrontierCode 2.0 is underspecified prompts. Rather than including every engineering decision, prompts are deliberately ambiguous, giving the models room to demonstrate their judgment. The result is a benchmark that is far from saturated, with the top model scoring just 45%.

Devin Fusion has claimed a top score of 68 on the @ArtificialAnlys Coding Agent Index with an Opus 5.5 lead and GPT-6 Luna sidekick. Devin Fusion outperforms Claude Code with Opus 5.5 on both performance and price – earning a score of 68 at a 31% lower cost per task.

Devin can now build and test iPhone Duo apps in macOS cloud VMs Unfold the phone, fold it, close it, check every screen, and get video verification of everything. Here are some examples: 1. Devin takes someone's portrait while they watch themselves on the outside screen, it sends posing cues, half-folds the phone so it stands on a table, takes timer shots, and closes the phone mid-countdown to make sure no photo gets lost

We’ve partnered with @ndstudio to launch American Forge. It’s a six-month residency for exceptional engineers to embed inside the government and build software that affects hundreds of millions of people. Right now, a small team can do more than ever - including in public service! Applications are now open.

Introducing Devin Oncall: Devin automatically investigates alerts and bugs, helping your team diagnose and resolve production incidents. Devin Oncall already handles thousands of alerts every day for some of the world’s largest companies. Let it become your SRE today.

Pylon tickets now get fixed automatically by Devin New Devin customers on @usepylon also get $15,000 in credits to get started Join our webinar to see it in action

Dynamic workflows let Devin split a big job into pieces, hand each one to its own Devin, and bring the results back together. The plan for a Dynamic Workflow lives in code instead of an agent’s head, so you always know which Devins will run, in what order, and what each one is told.

Devins can start managed Devins of their own, so one task can branch into a tree of Devins several levels deep. Work done in sequence takes as long as all its parts added together, while work split this way takes roughly as long as its slowest part. So size stops being the reason a task gets postponed, since a larger task simply produces a larger tree.

Cloud agents get much more useful when they can run the real toolchain: xcodebuild, the iOS Simulator, Computer Use tapping through the UI. Every Devin session gets its own cloud Mac so mobile work can be delegated like any other ticket. Here's how it works:

Introducing Dreaming: Across sessions, Devin builds a memory graph of how you like to work At night Devin self-improves its memory to remove stale records and discover latent information We are creating an OSS standard called Agent Memory Repo: