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A Showdown of ChatGPT vs DeepSeek in Solving Programming Tasks

arXiv 2503.13549 ↗First posted 16 Mar 2025cs.SE cs.AIcited by 0

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Abstract (arXiv)

The advancement of large language models (LLMs) has created a competitive landscape for AI-assisted programming tools. This study evaluates two leading models: ChatGPT 03-mini and DeepSeek-R1 on their ability to solve competitive programming tasks from Codeforces. Using 29 programming tasks of three levels of easy, medium, and hard difficulty, we assessed the outcome of both models by their accepted solutions, memory efficiency, and runtime performance. Our results indicate that while both models perform similarly on easy tasks, ChatGPT outperforms DeepSeek-R1 on medium-difficulty tasks, achieving a 54.5% success rate compared to DeepSeek 18.1%. Both models struggled with hard tasks, thus highlighting some ongoing challenges LLMs face in handling highly complex programming problems. These findings highlight key differences in both model capabilities and their computational power, offering valuable insights for developers and researchers working to advance AI-driven programming tools.

Key facts. No citing papers in the map yet (data through 7 Oct 2026). Builds on 11 of its 26 references that are in the map. First posted on arXiv 16 Mar 2025.

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References · 11

  1. 2024DeepSeek-Coder-V2: Breaking the Barrier of Closed-Source Models in Code Intelligencecited by 325
  2. 2023The Impact of AI on Developer Productivity: Evidence from GitHub Copilotcited by 264
  3. 2024Large Language Models Must Be Taught to Know What They Don't Knowcited by 99
  4. 2023How Novices Use LLM-Based Code Generators to Solve CS1 Coding Tasks in a Self-Paced Learning Environmentcited by 55
  5. 2023AI-assisted coding: Experiments with GPT-4cited by 43
  6. 2024How Beginning Programmers and Code LLMs (Mis)read Each Othercited by 31
  7. 2023L2CEval: Evaluating Language-to-Code Generation Capabilities of Large Language Modelscited by 22
  8. 2025Token-Hungry, Yet Precise: DeepSeek R1 Highlights the Need for Multi-Step Reasoning Over Speed in MATHcited by 10
  9. 2025A Comparison of DeepSeek and Other LLMscited by 10
  10. 2024StuGPTViz: A Visual Analytics Approach to Understand Student-ChatGPT Interactionscited by 7
  11. 2025From Idea to Implementation: Evaluating the Influence of Large Language Models in Software Development -- An Opinion Papercited by 3

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  1. 2025Challenges and Applications of Large Language Models: A Comparison of GPT and DeepSeek family of models
  2. 2024DeepSeek LLM: Scaling Open-Source Language Models with Longtermism
  3. 2025Comparative Evaluation of ChatGPT and DeepSeek Across Key NLP Tasks: Strengths, Weaknesses, and Domain-Specific Performance
  4. 2025Comparative Analysis Based on DeepSeek, ChatGPT, and Google Gemini: Features, Techniques, Performance, Future Prospects
  5. 2024Evaluating ChatGPT-3.5 Efficiency in Solving Coding Problems of Different Complexity Levels: An Empirical Analysis
  6. 2024ChatGPT Alternative Solutions: Large Language Models Survey
  7. 2025A Review of DeepSeek Models' Key Innovative Techniques
  8. 2025DeepSeek vs. ChatGPT vs. Claude: A Comparative Study for Scientific Computing and Scientific Machine Learning Tasks