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DeepCoder: A Fully Open-Source 14B Coder at O3-mini Level

Blog post from Together AI

Post Details
Company
Date Published
Author
Michael Luo*, Sijun Tan*, Roy Huang*, Ameen Patel*, Alpay Ariyak*, Qingyang Wu*, Xiaoxiang Shi, Rachel Xin, Colin Cai, Maurice Weber, Ce Zhang, Li Erran Li, Raluca Ada Popa, Ion Stoica
Word Count
2,870
Company Posts That Month
9
Language
English
Hacker News Points
31
Post removed?
No
Summary

DeepCoder-14B-Preview, a fully open-source 14B coder, achieves an impressive 60.6% Pass@1 accuracy on LiveCodeBench, matching the performance of o3-mini-2025-01-031 and o1-2024-12-17 with just 14B parameters. The model was trained using a curated high-quality training set consisting of TACO Verified problems, PrimeIntellect's SYNTHETIC-1 dataset, and LiveCodeBench problems submitted between May 1, 2023, and July 31, 2024. To accelerate end-to-end RL training, the authors introduce verl-pipeline, an optimized extension of the open-source RLHF library Verl, which achieves up to 2.5× speedup over the baseline implementation. The model demonstrates strong performance across various coding benchmarks, including LiveCodeBench, Codeforces, and HumanEval+, achieving 60.6% on LiveCodeBench and a rating of 1936 on Codeforces, comparable to the performance of o3-mini (low) and o1.

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