Compare Ostia Portus vs. SWE-2

In numerous modern organizations, the process of launching a new product concept or enhancing an existing one can span several months or even years. This delays stem from intricate IT ecosystems and infrastructures, as well as factors such as change control procedures, the necessity for stability and reliability in production, and various security concerns—creating a lengthy list of hurdles. Imagine the possibilities if we could roll out a new product idea within just a few weeks! Portus offers a solution with its innovative technology designed for on-demand creation of intelligent testing systems. By generating simulations that replicate the necessary connections to back-office IT frameworks, Portus addresses the challenge of quickly providing complex IT testing environments. This capability significantly shortens the testing timeline, allowing for completion in weeks or even days instead of months, based on feedback from our reference clients. Consequently, this leads to faster launches of new or improved applications, minimizing risk and lowering costs. Furthermore, Portus test systems are developed in just a few days using affordable, standard hardware and software solutions, making it a practical choice for organizations looking to enhance their agility in product development.

SWE-2 is a software engineering model from Cognition built for agentic coding tasks that require strong performance at lower computational and monetary cost. It is post-trained from the Kimi K3 base model and extends Cognition’s earlier SWE-1.7 training approach with a new reinforcement learning method for jointly optimizing multiple reasoning-effort settings. Medium, high, and maximum effort modes provide different tradeoffs between speed, cost, exploration, and verification depending on task complexity. The model is trained to inspect only the parts of a codebase that are likely to matter, helping it reach implementation faster and reduce unnecessary exploration. SWE-2 can generate and modify code, run tests, analyze repositories, work through terminal tasks, and verify whether implementations satisfy user requirements. Cognition also reports improvements in end-to-end test creation, regression detection, instruction following, and re-deriving conclusions when challenged. Its training process incorporates cost-aware rewards, length-weighted reward baselines, expanded reinforcement learning environments, and hardened verifiers intended to improve both efficiency and reliability. SWE-2 is positioned as a cost-efficient alternative to larger frontier coding models while remaining competitive on software engineering benchmarks such as FrontierCode, DeepSWE, and Terminal-Bench. The model is available in Devin Desktop and Devin CLI and is being introduced to additional Cognition products including Devin Web and Fusion.