DeepSeek

Category: Current AI Models

Definition

DeepSeek is a Chinese artificial intelligence company that develops cost-efficient, open-source large language models that rival leading Western AI systems. Founded in July 2023, the company shocked the tech world in January 2025 with its R1 reasoning model that matched OpenAI's performance at a fraction of the cost.

How It Works

DeepSeek employs innovative techniques to dramatically reduce training costs and computational requirements:

• Mixture-of-Experts (MoE) Architecture: Uses 671 billion parameters but activates only a subset for each task, improving efficiency
• Mixed-Precision Training: Performs computations in 8-bit and 12-bit floating point instead of standard 32-bit, reducing memory and compute needs
• Reinforcement Learning Without SFT: Pioneered training reasoning capabilities purely through reinforcement learning, skipping supervised fine-tuning
• Efficient Engineering: Custom optimization including dedicated GPU cores for communication and dynamic expert placement

The company claims to have trained DeepSeek-V3 for just $6 million, compared to GPT-4's reported $100 million cost, using approximately one-tenth the computing power.

Why It Matters

DeepSeek fundamentally challenged the assumption that leading-edge AI requires massive financial resources and computing power. Their success demonstrates that innovation in training methods can overcome hardware limitations.

Key impacts include:

• Open Source Leadership: All models released under MIT License, democratizing access to frontier AI
• Market Disruption: Triggered a $600 billion drop in Nvidia's market cap and broader tech stock selloff
• Geopolitical Implications: Proves China can compete in AI despite U.S. export restrictions on advanced chips
• Cost Revolution: Shows that efficient techniques can reduce AI development costs by 95%+

Model Family

Current Models (as of August 2025):

• DeepSeek-R1-0528: Latest reasoning model with improved accuracy, reduced hallucinations, and support for system prompts
• DeepSeek-R1: January 2025 release that matches OpenAI o1 on reasoning benchmarks
• DeepSeek-V3: December 2024 base model with 671B parameters and 128K context window
• DeepSeek-R1-Distill: Smaller versions (including 8B parameter model) that run on consumer hardware
• Janus-Pro-7B: Vision model for understanding and generating images

Performance:

• Outperforms Llama 3.1 and Qwen 2.5 on standard benchmarks
• Matches GPT-4o and Claude 3.5 Sonnet on many tasks
• Excels particularly in math, coding, and reasoning challenges
• DeepSeek app surpassed ChatGPT as #1 on iOS App Store in January 2025

Technical Innovations

DeepSeek's efficiency comes from several breakthroughs:

• Direct reinforcement learning without supervised pre-training
• Dynamic load balancing across distributed systems
• Overlapping computation and communication to minimize latency
• Distillation techniques that preserve large model capabilities in smaller versions

Related Terms

• Mixture of Experts
• Open Source
• Reinforcement Learning
• Model Distillation
• Chinese AI
• Reasoning Models
• Cost-Efficient AI

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