Deepseek New Age ChatGPT
DeepSeek is a Chinese artificial intelligence company that has rapidly gained attention for its development of advanced large language models (LLMs), notably the DeepSeek-R1 and V3 models. Founded in July 2023 by Liang Wenfeng, DeepSeek is headquartered in Hangzhou, Zhejiang, and is owned and funded by the Chinese hedge fund High-Flyer.

What is DeepSeek
DeepSeek is a Chinese AI startup founded in 2023 that develops open-source large language models (LLMs) designed to compete directly with ChatGPT. Built for speed, scalability, and affordability, DeepSeek aims to democratize AI tools for global users — especially in emerging markets like India.
Key Features of DeepSeek:
- Cost-Effective AI Development: DeepSeek’s models are notable for their cost efficiency. For instance, the V3 model was reportedly trained for approximately $6 million, significantly less than the $100 million cost associated with training models like OpenAI’s GPT-4.
- Open-Source Accessibility: The DeepSeek-R1 model is released under the MIT License, allowing developers and organizations to access, modify, and integrate the model into their applications without licensing constraints.
- Advanced Reasoning Capabilities: DeepSeek-R1 excels in complex reasoning tasks, including mathematical problem-solving and code generation, performing comparably to leading models like OpenAI’s o1.
🚀 DeepSeek’s Vision and Technology
DeepSeek’s core innovation lies in its multi-expert reasoning model, allowing specialized “reasoning agents” to collaborate for better accuracy.
Recent versions — DeepSeek-V3 and DeepSeek-R1 — claim enhanced contextual understanding and longer conversation memory, making it a strong contender in everyday AI applications.
🧩 Fun fact: DeepSeek’s developers claim their model costs 10x less to train and deploy than GPT-4-class models.
How does deepseek work
Model Architecture: Mixture-of-Experts (MoE)
Both DeepSeek-R1 and DeepSeek-V3 utilize a Mixture-of-Experts (MoE) architecture. This design comprises a vast network of 671 billion parameters, but only 37 billion are activated per token during processing. This selective activation allows the models to handle complex tasks while maintaining computational efficiency.
Training Approaches
- DeepSeek-R1: This model employs a reinforcement learning (RL)-first training strategy, focusing on enhancing reasoning capabilities from the outset. This approach enables R1 to excel in tasks requiring deep problem-solving and logical reasoning.
- DeepSeek-V3: In contrast, V3 follows a traditional training pipeline, starting with supervised fine-tuning followed by reinforcement learning. This method ensures a broad understanding of language and tasks.
How to run deepseek r1 locally
Here’s a clear and practical guide for running DeepSeek R1 locally on your machine:
Option 1: Using Ollama (Recommended)
- Install Ollama
- On macOS/Linux:
curl -fsSL https://ollama.com/install.sh | sh - On Windows: Download the installer from the Ollama website.
- On macOS/Linux:
- Download a DeepSeek R1 Model
- Choose a version based on your hardware:
ollama pull deepseek-r1 # default ollama pull deepseek-r1:8b ollama pull deepseek-r1:14b ollama pull deepseek-r1:32b ollama pull deepseek-r1:70b
- Choose a version based on your hardware:
- Run the Model Locally
ollama serve & ollama run deepseek-r1:8bReplace8bwith14b,32b, etc., to use different model sizes.
Option 2: Integrate with Open WebUI via llama.cpp
For a browser-based/chat interface using llama.cpp:
- Install llama.cpp (build from source or download binaries)
- Download the Quantized Model
- Example with 131 GB GGUF model:
from huggingface_hub import snapshot_download snapshot_download( repo_id="unsloth/DeepSeek-R1-GGUF", allow_patterns=["*UD-IQ1_S*"] )
- Example with 131 GB GGUF model:
- Start the
llama.cppServercd llama.cpp/build/bin ./llama-server \ --model /path/to/DeepSeek-R1-UD-IQ1_S-00001-of-00003.gguf \ --port 10000 \ --ctx-size 1024 \ --n-gpu-layers 40 - Connect to Open WebUI
Visithttp://127.0.0.1:10000to chat with DeepSeek R1.
Option 3: Run Distilled Models (easier sys requirements)
If your hardware is limited, use smaller distilled versions:
- Models available via HuggingFace:
DeepSeek-R1-Distill-Qwen-8B,14B,32B, etc.
- Run using
vLLM:vllm serve deepseek-ai/DeepSeek-R1-Distill-Qwen-32B \ --tensor-parallel-size 2 \ --max-model-len 32768 \ --enforce-eager - Or use
sglang:python3 -m sglang.launch_server \ --model deepseek-ai/DeepSeek-R1-Distill-Qwen-32B \ --trust-remote-code --tp 2
Option 4: Follow Community Guides
Several open-source guides detail full setup flows (Windows/macOS/Linux), including installing llama.cpp, configuring WebUI, and automating with scripts.
Performance & Hardware Considerations
- Full R1 (671 B parameters): Needs ≥64 GB RAM + 24 GB GPU (like RTX 4090)
→ ~5 tokens/sec with GPU, ~1 token/sec CPU-only. - Smaller Ollama models: 8B or 14B are manageable on mid-range consumer PCs; use 32B+ for serious workloads.
Summary
| Tool / Approach | Model Sizes | Interface | Hardware Needs |
|---|---|---|---|
| Ollama | 1.5B – 70B | Terminal | Everyday PC (CPU), GPU for larger |
| llama.cpp + WebUI | 162 GB quantized 671B model | Web browser | 64 GB RAM, high-end GPU |
| Distill models + vLLM | 8B / 14B / 32B / 70B | API/WebUI | Moderate to high-end GPU |
| Community guides (Git) | Varies | Scripts/WebUI | Varies based on model |
Choose Ollama for simplicity and immediate access, or use llama.cpp + WebUI for a full-featured web interface. Distilled models are great if you’re resource-limited. Community resources make setup easier across all platforms.
⚙️ DeepSeek vs. ChatGPT: What Sets Them Apart
| Feature | DeepSeek | ChatGPT (OpenAI) |
|---|---|---|
| Origin | China | USA |
| Model Type | Open-Source LLM | Proprietary |
| Accuracy (NewsGuard Audit) | 17% factual accuracy | 97% factual accuracy |
| Availability | Global (restricted in some regions) | Global |
| Cost | Free / low-tier API | Subscription (ChatGPT Plus) |
| Core Strength | Cost efficiency, reasoning | Reliability, creativity |
While DeepSeek appeals to developers and cost-sensitive users, ChatGPT still leads in reliability and global trust.
⚠️ Recent Controversies & Security Concerns
DeepSeek’s rise hasn’t been without challenges.
In early 2025, Australia and Czechia banned the app from government devices citing national-security risks, alleging potential user-data sharing with Chinese servers.
This raised questions over AI sovereignty and privacy compliance worldwide.
Still, DeepSeek continues to attract developers, thanks to its open-source flexibility and community-driven architecture.
🌏 Impact on India & Global AI Ecosystem
DeepSeek’s affordability has drawn attention from Indian startups, universities, and independent developers looking for accessible AI tools.
Its open model aligns with India’s Digital India initiative, promoting local AI adoption while reducing dependency on Western platforms.
However, policymakers remain cautious, emphasizing data privacy, localization, and transparency in foreign AI adoption.
How to buy deepseek stock
You cannot currently buy shares of DeepSeek, as it remains a privately held company with no public stock listing.
Not Publicly Listed: DeepSeek isn’t trading on any stock exchange—no NASDAQ, no NYSE, no Hong Kong listing.
Privately Funded: It’s fully owned by Chinese hedge fund High‑Flyer, founded by Liang Wenfeng, with no current plans for an IPO.
Why is deepseek better than chatgpt
DeepSeek outpaces ChatGPT in several key areas, particularly for technical users:
1. Efficiency & Cost
- Mixture-of-Experts (MoE) architecture activates only part of its 671 B parameters (~37 B), drastically reducing compute and inference costs.
- Training DeepSeek-R1 cost around $5.6 M using 2,000 H800 GPUs, compared to ChatGPT’s ~$100 M.
- API pricing is significantly cheaper—only $0.48–$0.55 per million tokens, versus ChatGPT’s $3–15.
2. Technical & Reasoning Strength
- Mathematical & coding tasks: DeepSeek hits 90–98%+ accuracy on benchmark math tests and competitive coding problems, often exceeding ChatGPT’s performance.
- Provides clear chain-of-thought step-by-step reasoning, aiding debugging and logic validation—ideal for engineering and academic use.
3. Open-Source & Customizability
- DeepSeek’s models are MIT-licensed and publicly available, enabling local deployment, customization, and full ownership of AI workflows.
- ChatGPT is closed-source and cloud-only, with limited customization beyond API usage.
4. Performance & Accessibility
- Response speeds match or outperform mid-tier ChatGPT, especially in technical domains.
- Supports long contexts (128K tokens), making it ideal for processing regional data, long documents, and technical logs.
- While ChatGPT has built-in multimodal support (images, voice) and polished UI, DeepSeek is catching up, especially for users comfortable with self-hosted tools.
5. Trade-offs & Limitations
- DeepSeek applies censorship to politically sensitive queries (e.g., Taiwan, Tiananmen) as per Chinese regulations.
- It leans technical—excellent for math, logic, code—but less effective for creative writing, generative storytelling, and general-purpose conversation.
Bottom Line
DeepSeek outshines ChatGPT when it comes to:
| Advantage Area | DeepSeek Strength |
|---|---|
| Technical accuracy | High—math, code, logic |
| Cost & efficiency | Low-cost, fast inference |
| Customization | Open-source, deploy anywhere |
| Long-context tasks | Handles huge input volumes |
But ChatGPT still leads in:
- Creative, conversational nuance
- Multimodal support & polished UI
- Broader general-purpose applications
Who Should Choose DeepSeek?
- Developers, data scientists, and researchers focused on technical domains
- Organizations needing localized, private AI
- Cost-conscious users seeking powerful AI without high fees
If your work centers on algorithms, code, math, or self-hosted freedom, DeepSeek is a compelling choice potentially better suited than ChatGPT for your needs.
🔬 Latest Updates: DeepSeek-R1 and Future Outlook
- DeepSeek-R1 (2025) introduces improved factual consistency and multi-language capabilities.
- Collaboration with global open-source communities aims to rival Meta’s LLaMA and OpenAI’s GPT line.
- Despite accuracy limitations, DeepSeek’s cost structure could disrupt enterprise AI markets if improved responsibly.
💬 The Smart Innovator’s Take
DeepSeek embodies both promise and peril — it’s an exciting push for open AI innovation but also a wake-up call for regulators and users to balance affordability with security.
As AI continues to globalize, the world may soon see multiple “ChatGPT alternatives” shaping how we interact with intelligence itself.
Why is DeepSeek banned?
DeepSeek has been banned on government devices in countries like Australia and Czechia due to national-security and data-privacy concerns. Officials allege that DeepSeek’s apps could share user data with Chinese servers under local cybersecurity laws, raising risks around surveillance and data misuse.
What is DeepSeek used for?
DeepSeek is used for AI-powered text generation, reasoning, and automation tasks — similar to ChatGPT. It’s designed for content creation, research assistance, programming help, and business automation, while offering low-cost access to large language model capabilities for developers and enterprises worldwide.
💡 In simple terms: DeepSeek helps users write, code, analyze data, and automate workflows — all using AI.
Is DeepSeek available in India?
Yes—existing users can access the DeepSeek app in India, but new registrations from outside mainland China are currently restricted.
Details:
- The DeepSeek app is listed on the Google Play Store and Apple App Store in India.
- However, DeepSeek has flagged that new sign-ups are limited to mainland China due to “large-scale malicious attacks” on its services — making it difficult for new Indian users to register.
- According to Indian government sources, the model underlying DeepSeek has been deemed safe for use, but with conditions like data-localisation and export controls hanging over future availability.
Is DeepSeek AI free to use?
DeepSeek offers a free tier for everyday chat use, allowing users to interact with its models at no cost. However, advanced capabilities—such as high-volume API access, enterprise integration, or extended token limits—may require a paid plan or be offered by third-party platforms with usage restrictions.
Has DeepSeek banned in India?
No — DeepSeek has not been banned across India for the general public. However, the Ministry of Finance issued a directive on January 29, 2025, instructing government employees to avoid using DeepSeek and similar AI tools (like ChatGPT) on official devices, due to concerns about confidentiality of government data.
Indian External Affairs Minister S. Jaishankar has also clarified that there is no decision yet on a complete ban of DeepSeek in India.
FAQs about DeepSeek
DeepSeek is a Chinese AI company developing open-source large language models to rival ChatGPT in affordability and performance.
Yes, DeepSeek is real and actively developing models like DeepSeek-V3 and R1, but several governments have expressed data-security concerns.
DeepSeek focuses on cost-efficient, reasoning-based AI, while ChatGPT offers more polished, reliable responses and broader integration support.
Experts warn of data-sharing risks. Australia and Czechia have banned its use on official devices over security concerns.
Not yet. Audits show DeepSeek achieves about 17% accuracy, far below ChatGPT’s 97%, but rapid iteration continues.
Yes, though it may face regulatory reviews; many Indian developers are already experimenting with its open-source models.
Future updates aim for better multilingual understanding, safer data practices, and global collaboration.
Conclusion
DeepSeek represents a significant development in the AI landscape, offering cost-effective and powerful language models. However, potential users should weigh these benefits against the reported privacy and security concerns, especially considering the app’s data handling practices and compliance with government regulations.
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