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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 GPT‑5.6‑Cyber?

GPT-5.6-Cyber is OpenAI’s cybersecurity-specific model for approved defenders who need advanced capabilities for authorized security research and defensive operations. The model is available through Daybreak Red and is built on GPT-5.6 Sol with additional training for specialized cybersecurity tasks. It is designed to improve support for vulnerability discovery, exploit validation, security testing, exploit-chain reasoning, malware analysis, incident response, secure code review, patch validation, and vulnerability report writing. OpenAI introduced GPT-5.6-Cyber as part of an expanded Daybreak program that gives trusted defenders access to advanced AI capabilities before offensive AI is widely deployed by attackers. Daybreak Blue gives approved users access to frontier general-purpose models with defensive-security safeguards, while Daybreak Red provides access to purpose-trained cybersecurity models for more advanced authorized work. GPT-5.6-Cyber is intended to reduce unnecessary refusals in legitimate research scenarios that still require careful oversight because of their dual-use nature. OpenAI reports that the model performs strongly on internal cybersecurity completion evaluations and improves on certain benchmark tasks related to exploit development and vulnerability research. The model has also been used by OpenAI researchers to study real-world software, identify vulnerabilities, and support coordinated vulnerability disclosure. Access to Daybreak is controlled through identity verification, account security, monitoring, legal attestations, approved-use restrictions, and additional protective measures. OpenAI recommends sandboxing and isolating security workflows, monitoring agent actions, using auto-review mode, defining scope clearly, and enforcing permissions for higher-risk work.

Media

Media

Integrations Supported

.NET
C
C#
CSS
Cerebras
Devin
JSON
Kotlin
Kubernetes
Objective-C
PowerShell
Python
Ruby
SQL
Scala
Solidity
Terraform
TypeScript
YAML

Integrations Supported

OpenAI

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

OpenAI

Date Founded

2015

Company Location

United States

Company Website

openai.com

Categories and Features

AI Coding Models

Not specified

AI Models

Not specified

Categories and Features

AI Models

Not specified

AI Security

Not specified

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