AfterQuery vs. SWE-2 Comparison


AfterQuery	SWE-2 Cognition	+	+
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About AfterQuery is an applied research platform designed to create high-quality training data for frontier artificial intelligence models by capturing how real experts think, reason, and solve problems in professional contexts. It focuses on transforming real-world work into structured datasets that go beyond simple outputs, encoding decision-making processes, tradeoffs, and contextual reasoning that traditional internet-sourced data cannot provide. It works directly with domain experts to generate supervised fine-tuning data, including prompt–response pairs and detailed reasoning traces, as well as reinforcement learning datasets with expert-designed prompts and grading frameworks that convert subjective judgment into scalable reward signals. It also builds custom agent environments across APIs and tools, enabling models to be trained and evaluated in realistic workflows, and captures computer-use trajectories that demonstrate how humans interact with software step by step.	About SWE-2 is Cognition’s advanced coding model designed to improve software engineering performance while reducing the cost of agentic coding workflows. The model is post-trained from Kimi K3 and uses reinforcement learning to optimize multiple reasoning-effort levels within a single training run. SWE-2 is designed to explore codebases more selectively, begin implementation sooner, and complete tasks with fewer redundant reads and reasoning steps than earlier Cognition models. Its capabilities include code generation, debugging, test creation, verification, repository analysis, and complex terminal-based software engineering tasks. The model also emphasizes stronger engineering judgment, end-to-end test coverage, instruction following, and evidence-based verification of user assumptions. SWE-2 is available through Devin Desktop and Devin CLI, with broader rollout planned across Devin Web and Fusion.
Platforms Supported Windows Not Supported Mac Not Supported Linux Not Supported Cloud Supported On-Premises Not Supported iPhone Not Supported iPad Not Supported Android Not Supported Chromebook Not Supported	Platforms Supported Windows Not Supported Mac Not Supported Linux Not Supported Cloud Supported On-Premises Not Supported iPhone Not Supported iPad Not Supported Android Not Supported Chromebook Not Supported
Audience AI researchers, developers, and enterprises building advanced models who need high-quality, expert-driven training data to improve reasoning and real-world task performance	Audience Software developers, engineering teams, AI coding agent users, DevOps professionals, and organizations that need capable agentic software engineering with lower execution cost and more efficient reasoning
Support Phone Support Not Supported 24/7 Live Support Not Supported Online Supported	Support Phone Support Not Supported 24/7 Live Support Not Supported Online Supported
API Offers API Supported	API Offers API Not Supported
Screenshots and Videos View more images or videos	Screenshots and Videos View more images or videos
Pricing No information available. Free Version Not Supported Free Trial Not Supported	Pricing $20/month Free Version Supported Free Trial Not Supported
Reviews/Ratings Overall 0.0 / 5 ease 0.0 / 5 features 0.0 / 5 design 0.0 / 5 support 0.0 / 5 This software hasn't been reviewed yet. Be the first to provide a review: Review this Software	Reviews/Ratings Overall 5.0 / 5 ease 5.0 / 5 features 5.0 / 5 design 5.0 / 5 Read all reviews
	Pros & Cons from Real Users Pros The biggest thing that stands out is the cost-performance balance. SWE-2 is not just trying to top one benchmark; it is trying to get very close to frontier coding performance at a much lower cost. For developers, that matters a lot. Coding agents can burn through tokens quickly when they are reading files, making edits, running tests, and iterating. A model that performs near the top while being meaningfully cheaper is much easier to use every day. I also like that SWE-2 seems built for real software engineering workflows, not just isolated code snippets. The strong DeepSWE and Terminal-Bench results make it especially interesting for repo-level tasks, debugging, tool use, and longer agent runs. Cons Benchmarks are useful, but real projects bring messy architecture, flaky tests, undocumented behavior, and weird edge cases.
Training Documentation Supported Webinars Not Supported Live Online Not Supported In Person Not Supported	Training Documentation Supported Webinars Not Supported Live Online Not Supported In Person Not Supported
Company Information AfterQuery Founded: 2025 United States www.afterquery.com	Company Information Cognition Founded: 2023 United States cognition.com
Alternatives Bitext	Alternatives Claude Sonnet 5.5 Anthropic
Phi-4-reasoning Microsoft	Claude Fable 5.1 Anthropic
Dataset Finder	Claude Mythos 5.1 Anthropic
Gramosynth Rightsify	SWE-1.7 Cognition
Step 3.5 Flash StepFun View All	SWE-1.6 Cognition View All
Categories AI Training Data Providers Supported	Categories AI Coding Models Supported AI Models Supported

Integrations .NET Not Supported C Not Supported C++ Not Supported Dart Not Supported Devin Not Supported JSON Not Supported Kubernetes Not Supported Lua Not Supported MATLAB Not Supported Model Context Protocol (MCP) Supported Objective-C Not Supported PHP Not Supported PowerShell Not Supported Python Not Supported Rust Not Supported Scala Not Supported Solidity Not Supported Swift Not Supported Terraform Not Supported YAML Not Supported Show More Integrations View All 1 Integration	Integrations .NET Supported C Supported C++ Supported Dart Supported Devin Supported JSON Supported Kubernetes Supported Lua Supported MATLAB Supported Model Context Protocol (MCP) Not Supported Objective-C Supported PHP Supported PowerShell Supported Python Supported Rust Supported Scala Supported Solidity Supported Swift Supported Terraform Supported YAML Supported Show More Integrations View All 32 Integrations
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