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What is SWE-1.7?

SWE-1.7 is a frontier software engineering model from Cognition built for advanced coding agents and long-horizon development workflows. It is designed to deliver strong coding intelligence at a fraction of the cost of some leading frontier alternatives, improving the cost-performance balance for real software engineering work. The model is trained from a Kimi K2.7 base and further improved through Cognition’s reinforcement learning pipeline, showing that additional post-training can still produce major capability gains. SWE-1.7 is optimized for tasks such as bug fixing, feature implementation, code migrations, terminal-based workflows, multilingual software engineering, large codebase navigation, and end-to-end validation. It performs especially well on longer asynchronous tasks where an AI agent needs to gather context, inspect files, test hypotheses, make changes, and verify results over an extended period. Cognition trained the model with infrastructure improvements that preserve entropy, stabilize training, support multi-cluster reinforcement learning, and improve fault tolerance across large distributed runs. The training process also focused heavily on data quality, using automated execution tests, verifier quality checks, reward-hacking prevention, and task filtering to create stronger learning signals. SWE-1.7 includes self-compaction, allowing it to summarize its working state and continue long projects even when tasks exceed the raw context window. It also uses an alternating length penalty to encourage concise reasoning on easier tasks while maintaining deeper exploration when a problem requires it. In practice, the model tends to explore codebases carefully, read relevant files, search for hidden requirements, test edge cases, and experiment before deciding how to implement a fix. Available in Devin across web, desktop, and CLI via Cerebras, SWE-1.7 gives engineering teams a powerful model for running scalable, cost-efficient coding agents.

What is Composer 2.5?

Composer 2.5 is Cursor’s newest AI-powered coding model, designed to significantly improve software development productivity through stronger reasoning, enhanced collaboration, and better handling of complex engineering tasks. Compared to Composer 2, the new release delivers major gains in sustained coding performance, allowing developers to work on larger and more complicated projects with improved reliability. The model was trained using expanded compute resources, more advanced reinforcement learning environments, and additional optimization techniques focused on both intelligence and usability. Cursor also refined behavioral aspects of the AI, including communication style and effort calibration, to make interactions feel more natural and productive during real-world coding sessions. A major feature of Composer 2.5 is its targeted reinforcement learning system with textual feedback, which provides localized corrections during training when the model makes mistakes such as invalid tool calls or style violations. This approach helps the AI understand exactly where errors occur and improves its decision-making more effectively than broad reward signals alone. The company further strengthened the model by training it on 25 times more synthetic coding tasks than Composer 2, exposing it to a wider range of difficult engineering challenges and edge cases. These synthetic tasks included feature deletion exercises where the model had to reconstruct missing functionality in real codebases using automated tests as validation signals. During large-scale training, Composer 2.5 demonstrated advanced problem-solving capabilities by reverse-engineering cached data and decompiling Java bytecode to recover deleted APIs in synthetic environments. Cursor also implemented sophisticated distributed training systems such as Sharded Muon and dual mesh HSDP, allowing efficient optimization across extremely large AI models and infrastructure clusters.

Media

Media

Integrations Supported

.NET
C
C#
C++
Cerebras
Devin Desktop
JSON
JavaScript
Kotlin
Lua
Objective-C
PHP
Python
SQL
Solidity
Swift
Terraform
TypeScript
XML
YAML

Integrations Supported

.NET
C
C#
C++
Cerebras
Devin Desktop
JSON
JavaScript
Kotlin
Lua
Objective-C
PHP
Python
SQL
Solidity
Swift
Terraform
TypeScript
XML
YAML

API Availability

Has API

API Availability

Has API

Pricing Information

$20/month
Free Trial Offered?
Free Version

Pricing Information

$0.50/M input
Free Trial Offered?
Free Version

Supported Platforms

SaaS
Android
iPhone
iPad
Windows
Mac
On-Prem
Chromebook
Linux

Supported Platforms

SaaS
Android
iPhone
iPad
Windows
Mac
On-Prem
Chromebook
Linux

Customer Service / Support

Standard Support
24 Hour Support
Web-Based Support

Customer Service / Support

Standard Support
24 Hour Support
Web-Based Support

Training Options

Documentation Hub
Webinars
Online Training
On-Site Training

Training Options

Documentation Hub
Webinars
Online Training
On-Site Training

Company Facts

Organization Name

Cognition

Date Founded

2023

Company Location

United States

Company Website

cognition.com

Company Facts

Organization Name

Cursor

Date Founded

2022

Company Location

United States

Company Website

cursor.com

Categories and Features

Categories and Features

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