SWE-2 vs. SWE-2 Flash Comparison


SWE-2 Cognition	SWE-2 Flash Cognition	+	+
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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.	About SWE-2 Flash is an AI coding model developed by Cognition to provide fast, cost-efficient software engineering capabilities for autonomous development agents. Built on Thinking Machines' Inkling-Small foundation model, it uses mid-training and reinforcement learning to improve coding performance, reasoning, and task execution. The model supports software development activities such as code generation, code reviews, feature development, documentation updates, and automated engineering workflows. SWE-2 Flash generates approximately 200 tokens per second, making it three times faster and five times less expensive than the larger SWE-2 model. Its 276-billion-parameter mixture-of-experts architecture activates approximately 12 billion parameters during inference to balance performance and computational efficiency. SWE-2 Flash is available through Devin Desktop and CLI, with Cognition also developing a secure model-weight sharing program for trusted research and enterprise partners.
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 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	Audience Software developers, AI coding assistant users, software engineering teams, DevOps professionals, autonomous agent developers, AI researchers, enterprise development organizations, and cybersecurity researchers seeking fast, cost-efficient AI coding, automated code reviews, feature implementation, software maintenance, technical reasoning, and agentic development workflows
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 Not Supported	API Offers API Not Supported
Screenshots and Videos View more images or videos	Screenshots and Videos View more images or videos
Pricing $20/month Free Version Supported Free Trial Not Supported	Pricing $20/month Free Version Supported Free Trial Not Supported
Reviews/Ratings Overall 5.0 / 5 ease 5.0 / 5 features 5.0 / 5 design 5.0 / 5 Read all reviews	Reviews/Ratings Overall 5.0 / 5 ease 5.0 / 5 features 5.0 / 5 design 5.0 / 5 support 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.	Pros & Cons from Real Users Pros This is the kind of model I would use all day for normal engineering work. It is fast enough that it does not feel like I am waiting on the model, but it is still strong enough for feature work, code review, docs, automations, and debugging. The speed is probably the biggest win. Cognition says it runs at around 200 tokens per second versus about 60 for SWE-2, and that difference matters a lot once an agent starts iterating through files and tools. The cost-performance balance is also really good. It is one-fifth the price of SWE-2, while scoring 45.5 on FrontierCode 1.1 Main, 60.1 on DeepSWE 1.1, and 89.9 on SWE-Bench Pro v2 Hard. Cons My main complaint is that it is not the model I would choose for the hardest repo-wide work. SWE-2 still has a noticeable edge on some tougher benchmarks, so I would move up when the task really needs it.
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 Cognition Founded: 2023 United States cognition.com	Company Information Cognition Founded: 2023 United States cognition.com
Alternatives Gemini 4 Carbon Google	Alternatives Gemini 4 Carbon Google
GPT-6.1 Terra OpenAI	GPT-6.1 Terra OpenAI
GPT-6.1 Sol OpenAI	GPT-6.1 Sol OpenAI
SWE-1.7 Cognition	Inkling Thinking Machines Lab
SWE-2 Flash Cognition View All	Nemotron 3.5 Super VL NVIDIA View All
Categories AI Coding Models Supported AI Models Supported	Categories AI Coding Models Supported AI Models Supported

Integrations .NET Supported C Supported C# Supported C++ Supported CSS Supported Dart Supported Devin Desktop Supported HTML Supported JSON Supported JavaScript Supported Kotlin Supported Kubernetes Supported Lua Supported MATLAB Supported R Supported Rust Supported Scala Supported Terraform Supported TypeScript Supported XML Supported Show More Integrations View All 32 Integrations	Integrations .NET Supported C Supported C# Supported C++ Supported CSS Supported Dart Supported Devin Desktop Supported HTML Supported JSON Supported JavaScript Supported Kotlin Supported Kubernetes Supported Lua Supported MATLAB Supported R Supported Rust Supported Scala Supported Terraform Supported TypeScript Supported XML Supported Show More Integrations View All 32 Integrations
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