DeepSeek has continuously refined its large language models (LLMs), introducing multiple iterations, each with specific advancements and improvements. Below, we explore the various versions, their capabilities, and GitHub repositories.
DeepSeek Coder
📅 Release Date: November 2023
🎯 Purpose: Open-source model tailored for programming tasks.
📝 Description: DeepSeek Coder is a specialized code-focused language model designed to enhance software engineering comprehension. Built from the ground up, it was trained on a dataset comprising 87% code and 13% natural language, totaling 2 trillion tokens in English and Chinese.
🔗 GitHub Repository: DeepSeek-Coder
DeepSeek LLM
📅 Release Date: December 2023
🎯 Purpose: DeepSeek’s first multi-purpose language model.
📝 Description: DeepSeek LLM is a cutting-edge language model with 67 billion parameters. It has been trained on a dataset containing 2 trillion tokens in both English and Chinese. DeepSeek has also open-sourced its 7B and 67B versions (both base and chat) to encourage further research.
🔗 GitHub Repository: DeepSeek-LLM
DeepSeek V2
📅 Release Date: May 2024
🎯 Purpose: Designed for greater efficiency and cost-effectiveness compared to its predecessor.
📝 Description: DeepSeek V2 is a sophisticated open-source Mixture of Experts (MoE) model that optimizes processing power while minimizing training costs. It features 236 billion parameters, with only 21 billion activated per token, ensuring efficient inference.
🔗 GitHub Repository: DeepSeek-V2
DeepSeek Coder V2
📅 Release Date: July 2024
⚙️ Parameters: 236 billion
📜 Context Window: 128,000 tokens
🎯 Purpose: Built to tackle complex programming challenges.
📝 Description: DeepSeek Coder V2 is an advanced Mixture of Experts (MoE) language model, designed to achieve GPT-4 Turbo-level performance in coding tasks.
🔗 GitHub Repository: DeepSeek-Coder-V2
DeepSeek V3
📅 Release Date: December 2024
⚙️ Parameters: 671 billion
📜 Context Window: 128,000 tokens
🎯 Purpose: A highly flexible MoE model for handling diverse tasks.
📝 Description: DeepSeek V3 represents a new level of performance in open-source AI. With 671 billion parameters, it optimizes efficiency by activating only 37 billion per token, reducing computational load while maintaining high accuracy.
🔗 GitHub Repository: DeepSeek-V3
DeepSeek R1
📅 Release Date: January 2025
⚙️ Parameters: 671 billion
📜 Context Window: 128,000 tokens
🎯 Purpose: Built for advanced reasoning tasks, offering a cost-effective alternative to OpenAI’s models.
📝 Description: DeepSeek R1 is a specialized reasoning model developed by DeepSeek AI, designed for logical inference, mathematical problem-solving, and decision-making tasks. It powers the chatbot DeepThink, positioning DeepSeek as a strong competitor to ChatGPT.
🔗 GitHub Repository: DeepSeek-R1
Janus Pro 7B
📅 Release Date: January 2025
🎯 Purpose: A multimodal AI model for image understanding and generation.
📝 Description: Janus Pro 7B is a state-of-the-art open-source AI model capable of both image comprehension and text-to-image generation. It has demonstrated superior benchmark performance compared to OpenAI’s DALLE-3 and Stability AI’s Stable Diffusion.
🔗 GitHub Repository: Janus
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