Audience

Developers, researchers, and enthusiasts wanting a tool to generate, debug, or reason about code without relying on proprietary models

About DeepCoder

DeepCoder is a fully open source code-reasoning and generation model released by Agentica Project in collaboration with Together AI. It is fine-tuned from DeepSeek-R1-Distilled-Qwen-14B using distributed reinforcement learning, achieving a 60.6% accuracy on LiveCodeBench (representing an 8% improvement over the base), a performance level that matches that of proprietary models such as o3-mini (2025-01-031 Low) and o1 while using only 14 billion parameters. It was trained over 2.5 weeks on 32 H100 GPUs with a curated dataset of roughly 24,000 coding problems drawn from verified sources (including TACO-Verified, PrimeIntellect SYNTHETIC-1, and LiveCodeBench submissions), each problem requiring a verifiable solution and at least five unit tests to ensure reliability for RL training. To handle long-range context, DeepCoder employs techniques such as iterative context lengthening and overlong filtering.

Pricing

Starting Price:
Free
Free Version:
Free Version available.

Integrations

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Company Information

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

Videos and Screen Captures

DeepCoder Screenshot 1
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Product Details

Platforms Supported
Windows
Mac
Linux
On-Premises
Training
Documentation
Support
Online

DeepCoder Frequently Asked Questions

Q: What kinds of users and organization types does DeepCoder work with?
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DeepCoder Product Features