Ratings and Reviews 1 Rating

Total
ease
features
design

Ratings and Reviews 0 Ratings

Total
ease
features
design
support

This software has no reviews. Be the first to write a review.

Write a Review

Alternatives to Consider

  • SearchUnify Reviews & Ratings
    150 Ratings
    Company Website
  • TrustInSoft Analyzer Reviews & Ratings
    6 Ratings
    Company Website
  • Interfacing Integrated Management System (IMS) Reviews & Ratings
    66 Ratings
    Company Website
  • All in One Accessibility Reviews & Ratings
    41 Ratings
    Company Website
  • Innoslate Reviews & Ratings
    98 Ratings
    Company Website
  • Flagsmith Reviews & Ratings
    43 Ratings
    Company Website
  • Checksum.ai Reviews & Ratings
    2 Ratings
    Company Website
  • Epsilon3 Reviews & Ratings
    265 Ratings
    Company Website
  • NINJIO Reviews & Ratings
    416 Ratings
    Company Website
  • Cadebill Reviews & Ratings
    1 Rating
    Company Website

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 North Mini Code?

North Mini Code marks the launch of Cohere's innovative agentic coding model, specifically designed for developers, and represents the initial offering in its next generation of advanced models. This compact and effective open-source solution is tailored for the independent developer community, providing exceptional software development capabilities without requiring extensive hardware resources. Utilizing a mixture-of-experts architecture, it features a total of 30 billion parameters, with 3 billion actively engaged, delivering powerful agentic coding functionalities in a streamlined format. The model is meticulously optimized for a variety of tasks, including code generation, agentic software engineering, and terminal operations, boasting an impressive context length of 256K and a maximum generation capacity of 64K. It is crafted with real-world developer practices in mind, allowing for the management of sub-agents, architecture mapping, code reviews, and supporting coding agents in overcoming complex software challenges. By integrating these capabilities, developers can significantly boost their productivity and efficiency in software development projects, making it an invaluable tool in their arsenal. As a result, North Mini Code not only facilitates better coding practices but also fosters a collaborative environment for developers to thrive.

Media

Media

Integrations Supported

.NET
C#
CSS
Cerebras
Devin
Devin Desktop
Go
HTML
JSON
JavaScript
Lua
MATLAB
Objective-C
PHP
PowerShell
Python
R
Ruby
SQL
Terraform

API Availability

API Availability

Pricing Information

$20/month
Free Version

Pricing Information

Pricing not provided

Supported Platforms

SaaS

Supported Platforms

Windows
Mac
On-Prem
Linux

Customer Service / Support

Web-Based Support

Customer Service / Support

Web-Based Support

Training Options

Documentation Hub

Training Options

Documentation Hub
Webinars
Online Training

Company Facts

Organization Name

Cognition

Date Founded

2023

Company Location

United States

Company Website

cognition.com

Company Facts

Organization Name

Cohere

Date Founded

2019

Company Location

Canada

Company Website

cohere.com/blog/north-mini-code

Categories and Features

AI Coding Models

Not specified

AI Models

Not specified

Categories and Features

AI Coding Models

Not specified

AI Models

Not specified

Open-Weight AI Models

Not specified

Popular Alternatives

Popular Alternatives

GLM-5.2 Reviews & Ratings

GLM-5.2

Z.ai
SWE-2 Reviews & Ratings

SWE-2

Cognition
SWE-1.7 Reviews & Ratings

SWE-1.7

Cognition
Kimi K2 Reviews & Ratings

Kimi K2

Moonshot AI