DeepSWE

DeepSWE

Agentica Project
KAT-Coder-Pro V2

KAT-Coder-Pro V2

StreamLake
+
+

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About

DeepSWE is a fully open source, state-of-the-art coding agent built on top of the Qwen3-32B foundation model and trained exclusively via reinforcement learning (RL), without supervised finetuning or distillation from proprietary models. It is developed using rLLM, Agentica’s open source RL framework for language agents. DeepSWE operates as an agent; it interacts with a simulated development environment (via the R2E-Gym environment) using a suite of tools (file editor, search, shell-execution, submit/finish), enabling it to navigate codebases, edit multiple files, compile/run tests, and iteratively produce patches or complete engineering tasks. DeepSWE exhibits emergent behaviors beyond simple code generation; when presented with bugs or feature requests, the agent reasons about edge cases, seeks existing tests in the repository, proposes patches, writes extra tests for regressions, and dynamically adjusts its “thinking” effort.

About

KAT-Coder is an agentic AI coding system designed to go beyond traditional autocomplete tools by enabling end-to-end software development workflows driven by reasoning, planning, and execution. It is positioned as a flagship coding model within the KAT ecosystem, built specifically for “agentic coding,” where the model does not just generate snippets but can diagnose issues, propose fixes, run tests, and iterate across multiple files as part of a continuous development loop. It integrates directly with developer environments through API endpoints and proxy layers compatible with tools like Claude Code, allowing seamless use inside existing IDE workflows without changing the interface developers are already familiar with. KAT-Coder is trained using a multi-stage pipeline that includes supervised fine-tuning and large-scale reinforcement learning, enabling it to understand programming context, and reason over complex tasks.

Platforms Supported

Windows
Mac
Linux
Cloud
On-Premises
iPhone
iPad
Android
Chromebook

Platforms Supported

Windows
Mac
Linux
Cloud
On-Premises
iPhone
iPad
Android
Chromebook

Audience

Software engineers, researchers, and developers seeking a solution to assist with real-world coding tasks such as bug-fixing, pull-request automation, and multi-file code edits

Audience

Software developers and engineering teams who need an AI agent capable of handling end-to-end coding tasks, from debugging and refactoring to multi-file implementation within real development environments

Support

Phone Support
24/7 Live Support
Online

Support

Phone Support
24/7 Live Support
Online

API

Offers API

API

Offers API

Screenshots and Videos

Screenshots and Videos

Pricing

Free
Free Version
Free Trial

Pricing

$0.30 per month
Free Version
Free Trial

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 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

Training

Documentation
Webinars
Live Online
In Person

Training

Documentation
Webinars
Live Online
In Person

Company Information

Agentica Project
Founded: 2025
United States
agentica-project.com

Company Information

StreamLake
United States
www.streamlake.ai/product/kat-coder

Alternatives

Devstral 2

Devstral 2

Mistral AI

Alternatives

Devstral Small 2

Devstral Small 2

Mistral AI
DeepCoder

DeepCoder

Agentica Project
DeepCoder

DeepCoder

Agentica Project
KAT-Coder-Pro V2

KAT-Coder-Pro V2

StreamLake
DeepSWE

DeepSWE

Agentica Project
StarCoder

StarCoder

BigCode

Categories

Categories

Integrations

Claude
MiniMax
OpenAI
OpenClaw
Together AI

Integrations

Claude
MiniMax
OpenAI
OpenClaw
Together AI
Claim DeepSWE and update features and information
Claim DeepSWE and update features and information
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Claim KAT-Coder-Pro V2 and update features and information