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Description
DeepSWE is an innovative and fully open-source coding agent that utilizes the Qwen3-32B foundation model, trained solely through reinforcement learning (RL) without any supervised fine-tuning or reliance on proprietary model distillation. Created with rLLM, which is Agentica’s open-source RL framework for language-based agents, DeepSWE operates as a functional agent within a simulated development environment facilitated by the R2E-Gym framework. This allows it to leverage a variety of tools, including a file editor, search capabilities, shell execution, and submission features, enabling the agent to efficiently navigate codebases, modify multiple files, compile code, run tests, and iteratively create patches or complete complex engineering tasks. Beyond simple code generation, DeepSWE showcases advanced emergent behaviors; when faced with bugs or new feature requests, it thoughtfully reasons through edge cases, searches for existing tests within the codebase, suggests patches, develops additional tests to prevent regressions, and adapts its cognitive approach based on the task at hand. This flexibility and capability make DeepSWE a powerful tool in the realm of software development.
Description
Holo3.1 represents H Company’s advanced suite of swift and localized computer-use agents designed for seamless operation across web, desktop, and mobile platforms, while ensuring better integration within various agent frameworks and deployment targets. Drawing from the Qwen family, Holo3.1 significantly enhances reliability in the diverse environments where these agents are utilized, tackling the distribution changes that arise on mobile devices, alternative agent frameworks, and varied execution environments. The latest version broadens Holo3’s functionality, going beyond mere browser and desktop control, with notable advancements in mobile automation; for instance, the performance in AndroidWorld has surged from 67% to 79.3% for the 35B-A3B model, while the smaller 4B and 9B variants have also shown improvements from 58% to 71%. In addition, Holo3.1 brings forth native support for function-calling protocols alongside structured JSON outputs, which aids teams in integrating the model into third-party agent ecosystems, achieving almost identical performance between function-calling and native execution. This release marks a significant step in enhancing the versatility and effectiveness of computer-use agents across multiple platforms.
API Access
Has API
API Access
Has API
Pricing Details
Free
Free Trial
Free Version
Pricing Details
No price information available.
Free Trial
Free Version
Deployment
Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook
Deployment
Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook
Customer Support
Business Hours
Live Rep (24/7)
Online Support
Customer Support
Business Hours
Live Rep (24/7)
Online Support
Types of Training
Training Docs
Webinars
Live Training (Online)
In Person
Types of Training
Training Docs
Webinars
Live Training (Online)
In Person
Vendor Details
Company Name
Agentica Project
Founded
2025
Country
United States
Website
agentica-project.com
Vendor Details
Company Name
H Company
Country
France
Website
hcompany.ai/holo3.1