DeepSeek

DeepSeek is a Chinese artificial intelligence company and research lab founded in July 2023 in Hangzhou by Liang Wenfeng, who also co-founded the quantitative hedge fund High-Flyer. Initially focused on AI-driven trading algorithms, High-Flyer transitioned into AGI research, spinning off DeepSeek as an independent entity. The company gained global recognition in January 2025 with the release of DeepSeek-R1, a reasoning-focused large language model (LLM) that rivals OpenAI’s GPT-4 and o1 models in performance but was developed for a fraction of the cost (under $6 million compared to OpenAI’s estimated $100 million for GPT-4).

Key milestones include:

• November 2023: Release of DeepSeek Coder, an open-source model specialised for coding tasks.

• January 2025: Launch of the DeepSeek chatbot app, which quickly topped Apple’s App Store and Google Play, surpassing ChatGPT in downloads.

• May 2025: Release of DeepSeek-R1-0528, featuring enhanced reasoning depth, system prompts, JSON output, and reduced hallucination rates.

DeepSeek’s rapid rise triggered a significant tech stock sell-off, wiping nearly $600 billion from Nvidia’s market cap and sparking geopolitical concerns about AI dominance. Despite restrictions on AI chip exports to China, DeepSeek leveraged innovative training techniques (e.g., mixture-of-experts architecture) to achieve state-of-the-art performance with limited hardware.

2. Features and Functionality

DeepSeek combines advanced reasoning capabilities with open-source flexibility:

• Reasoning Transparency: Unlike many AI models, DeepSeek explicitly shows its step-by-step thought process when solving complex problems (e.g., coding, mathematics), enhancing trust and verifiability.

• Multimodal Support: Processes text, images (via Janus-Pro-7B), and documents (PDFs, spreadsheets) for tasks like data analysis and research summarisation.

• Coding Excellence: DeepSeek-Coder supports 338 programming languages and features a 128K token context window, ideal for debugging, code generation, and technical documentation.

• Multilingual Capabilities: Strong performance in English and Chinese, with support for other languages like Spanish and German, though English remains its strongest suit.

• Open-Source Access: Models are released under the MIT License, allowing developers to customise, self-host, and integrate them into applications without restrictive licensing.

• Cost-Effective API: Pricing is significantly cheaper than competitors (e.g., $0.55 per million input tokens for DeepSeek-R1 vs. $15 for OpenAI’s o1).

• Local Deployment: Can be run on-premises via tools like Ollama, providing data privacy and offline access.

3. Pros & Cons Table

4. Overall Rating

4.5/5 ★★★★☆
DeepSeek excels in reasoning transparency, coding support, and cost-effectiveness, making it ideal for developers, researchers, and businesses seeking open-source AI alternatives. However, geopolitical restrictions, data privacy concerns, and occasional inconsistencies prevent a perfect score. Versus competitors:

• vs. ChatGPT: Better reasoning transparency and cost but weaker ecosystem integration.

• vs. Claude: Stronger coding capabilities but less polished conversational flow.

5. Key Reviews with Links

1. DigitalDefynd (2025):

   • Verdict: “Revolutionises data analysis and automation but requires careful handling of privacy concerns.” Highlights its scalability across industries.

   • Full Review

2. TechPoint Africa (2025):

   • Verdict: “Matches GPT-4 stride for stride—for free.” Praises reasoning transparency but notes niche topic limitations.

   • User Experience

3. Scientific American (2025):

   • Verdict: “A Sputnik moment for AI.” Highlights low-cost training and open-source access but questions geopolitical implications.

   • In-Depth Analysis

4. SlideSpeak (2025):

   • Verdict: “Excellent for research and content generation but cannot create presentations directly.” Recommends pairing with tools like SlideSpeak for slides.

   • Use Case Review

Summary: Key Points

• 🏆 Core Strength: Reasoning transparency and coding proficiency, with step-by-step problem-solving that rivals top models213.

• 🚀 Key Differentiator: Open-source access and local deployment options, providing unparalleled flexibility and cost savings.

• 🎯 Ideal For:

  • Developers and researchers needing customisable, self-hosted AI.

  • Businesses seeking cost-effective automation for coding, data analysis, and content generation.

  • Avoid if operating in restricted regions (e.g., U.S. government, EU) or handling highly sensitive data.

• ⚠️ Critical Considerations:

  • Data privacy risks due to Chinese data storage laws.

  • Geopolitical tensions may affect accessibility and future development.

• 💰 Pricing:

  • Free for basic use.

  • API costs are 90% cheaper than OpenAI (e.g., $0.55 vs. $15 per million input tokens).

• 🛠️ Ecosystem: Integrates with tools like Ollama for local deployment but lacks broad third-party support.