SWE-2
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What is SWE-2?
SWE-2 is Cognition’s coding model for software engineering agents, developed to improve the balance between capability, reasoning cost, and execution efficiency. The model is post-trained from Kimi K3, a multi-trillion-parameter model that had already received extensive reinforcement learning for agentic coding. Cognition further trained SWE-2 with a reinforcement learning algorithm that optimizes several reasoning-effort levels during a single training run. These effort levels let users trade off speed and cost against deeper planning, codebase exploration, and verification for more difficult assignments. SWE-2 is designed to reduce the over-exploration seen in earlier models by identifying relevant files and implementation paths more quickly. Its software engineering abilities include repository analysis, code writing and editing, debugging, testing, build and lint workflows, terminal tasks, and verification of completed work. The model places additional emphasis on writing end-to-end tests, catching edge cases and regressions, and gathering evidence instead of simply accepting assumptions in a prompt. Cognition’s training approach also uses cost penalties tied to the model’s performance frontier, length-weighted reward baselines, speculative decoding improvements, low-precision inference techniques, and expanded reinforcement learning data. Training data includes more diverse repositories, additional instruction-following requirements, and iterative verifier improvements designed to reduce reward hacking and false validation. SWE-2 is benchmarked against models such as GPT-6 Astra, GPT-5.6 Sol, Fable 5.1, Grok 4.6, and Kimi K3, with Cognition positioning it around strong coding performance at substantially lower cost. SWE-2 is intended for use across Cognition’s Devin ecosystem, including Desktop and CLI, with rollout to Devin Web and Fusion.
What is Gemini 4 Krypton?
Gemini 4 Krypton is a reportedly experimental large language model associated with Google DeepMind's next generation of Gemini artificial intelligence systems. Although Google has not officially announced the model, unofficial testing reports suggest that it may represent a more computationally intensive approach to AI reasoning and code generation. The model has been discussed as a potential successor or higher-capability alternative to existing Gemini 4 variants, including Argon and Carbon. Early demonstrations attributed to Krypton highlight its apparent ability to generate complex websites, interactive interfaces, animations, and substantial software implementations from written prompts. Testers have reported that the model sometimes requires considerably longer processing times while generating more extensive code than comparable Gemini systems. These observations have led to speculation that Krypton may prioritize detailed planning, implementation depth, and comprehensive task execution over response speed. Potential applications include full-stack application development, automated programming, interface prototyping, technical problem-solving, and AI-driven software engineering workflows. The model could also support advanced research and autonomous agent development if it incorporates the broader reasoning and multimodal capabilities associated with Google's Gemini platform. Important details such as context window size, API access, supported modalities, pricing, licensing, and official evaluation results have not been publicly verified. If Google releases Krypton with capabilities resembling those shown in early demonstrations, it may offer developers and enterprises another option for tackling computationally demanding programming and reasoning tasks.
Media
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Integrations Supported
.NET
C
C#
CSS
Go
Kotlin
Lua
Objective-C
PHP
PowerShell
Integrations Supported
.NET
C
C#
CSS
Go
Kotlin
Lua
Objective-C
PHP
PowerShell
API Availability
API Availability
Has API
Pricing Information
$20/month
Free Version
Pricing Information
Pricing not provided
Supported Platforms
SaaS
Supported Platforms
SaaS
Customer Service / Support
Web-Based Support
Customer Service / Support
Web-Based Support
Training Options
Documentation Hub
Training Options
Documentation Hub
Company Facts
Organization Name
Cognition
Date Founded
2023
Company Location
United States
Company Website
cognition.com
Company Facts
Organization Name
Date Founded
1998
Company Location
United States
Company Website
gemini.com
Categories and Features
AI Coding Models
Not specified
AI Models
Not specified
Categories and Features
AI Coding Models
Not specified
AI Models
Not specified
AI Reasoning Models
Not specified
AI Vision Models
Not specified
Foundation Models
Not specified
Large Language Models
Not specified
Multimodal Models
Not specified