Average Ratings 0 Ratings
Average Ratings 0 Ratings
Description
DeepCoder, an entirely open-source model for code reasoning and generation, has been developed through a partnership between Agentica Project and Together AI. Leveraging the foundation of DeepSeek-R1-Distilled-Qwen-14B, it has undergone fine-tuning via distributed reinforcement learning, achieving a notable accuracy of 60.6% on LiveCodeBench, which marks an 8% enhancement over its predecessor. This level of performance rivals that of proprietary models like o3-mini (2025-01-031 Low) and o1, all while operating with only 14 billion parameters. The training process spanned 2.5 weeks on 32 H100 GPUs, utilizing a carefully curated dataset of approximately 24,000 coding challenges sourced from validated platforms, including TACO-Verified, PrimeIntellect SYNTHETIC-1, and submissions to LiveCodeBench. Each problem mandated a legitimate solution along with a minimum of five unit tests to guarantee reliability during reinforcement learning training. Furthermore, to effectively manage long-range context, DeepCoder incorporates strategies such as iterative context lengthening and overlong filtering, ensuring it remains adept at handling complex coding tasks. This innovative approach allows DeepCoder to maintain high standards of accuracy and reliability in its code generation capabilities.
Description
Qwen2.5-Coder-32B-Instruct has emerged as the leading open-source code model, effectively rivaling the coding prowess of GPT-4o. It not only exhibits robust and comprehensive programming skills but also demonstrates solid general and mathematical abilities. Currently, Qwen2.5-Coder encompasses six widely used model sizes tailored to the various needs of developers. We investigate the practicality of Qwen2.5-Coder across two different scenarios, such as code assistance and artifact generation, presenting examples that illustrate its potential use cases in practical applications. As the premier model in this open-source initiative, Qwen2.5-Coder-32B-Instruct has outperformed many other open-source models on several prominent code generation benchmarks, showcasing competitive capabilities alongside GPT-4o. Additionally, the skill of code repair is crucial for programmers, and Qwen2.5-Coder-32B-Instruct proves to be an invaluable tool for users aiming to troubleshoot and rectify coding errors, thereby streamlining the programming process and enhancing efficiency. This combination of functionalities positions Qwen2.5-Coder as an indispensable resource in the software development landscape.
API Access
Has API
API Access
Has API
Integrations
Hugging Face
Alibaba Cloud
C
C++
CSS
Clojure
Elixir
F#
Go
HTML
Integrations
Hugging Face
Alibaba Cloud
C
C++
CSS
Clojure
Elixir
F#
Go
HTML
Pricing Details
Free
Free Trial
Free Version
Pricing Details
Free
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
Alibaba
Founded
1999
Country
China
Website
qwenlm.github.io/blog/qwen2.5-coder-family/