# swe-bench

> Analysis by Optimly for Optimly AI Visibility, in the Optimly AI Brand Index. Last analyzed August 16, 2026.

> swe-bench is a benchmark for evaluating the performance of AI agents and models on real-world software engineering tasks. It provides a dataset of GitHub issues from open-source projects, including a human-filtered 'Verified' subset, to measure how well AI agents can resolve these issues. The platform serves as a leaderboard to compare various AI models and agents based on their resolution rates and associated costs.

- Business Profile: https://optimly.ai/brand/swe-bench
- Publisher: Optimly (https://optimly.ai)
- Dataset: Optimly AI Brand Index (https://optimly.ai/brand)
- Official website: https://swebench.com/
- Logo: https://logo.clearbit.com/swebench.com
- Slug: swe-bench
- Category: AI Development
- Last Analyzed: August 16, 2026

## Buyer Intent Signals
Problems: Manual Code Review and Testing: Human software engineers manually review code, identify bugs, and write tests, which is the traditional method for ensuring code quality without AI agents or automated  | Software Quality Assurance Consulting: Hiring a specialized agency or consultancy to perform extensive code audits, bug detection, and software testing using human expertise and established QA methodo | No Formal AI Agent Evaluation: Opting not to rigorously evaluate the performance of AI agents on software engineering tasks, relying instead on anecdotal evidence, internal testing, or simply deployin
Solutions: swe-bench benchmark | AI agent evaluation software engineering | compare AI coding agents | swe-agent leaderboard | AI software bug fixing benchmark | Static Code Analyzers & Linters: Using tools like SonarQube, ESLint, or Pylint to automatically identify potential bugs, code smells, and style violations in source code, but without autonomously fixi