Artificial Intelligence has seen tremendous growth in recent years, with advanced models like OpenAI’s ChatGPT leading the charge in natural language processing. However, a new contender, DeepSeek, has emerged, and it’s making waves by adopting a distinct approach to AI model development. While ChatGPT has been a benchmark for generative AI, DeepSeek is challenging the status quo with its innovative methodologies and open-source philosophy. In this blog, we will explore how DeepSeek differentiates itself from ChatGPT and why it has become a rising star in the AI industry.
What is DeepSeek LLM?
DeepSeek LLM is an advanced language model comprising 67 billion parameters. It has been trained from scratch on a vast dataset of 2 trillion tokens in both English and Chinese. In order to foster research, the DeepSeek Team has made DeepSeek LLM 7B/67B Base and DeepSeek LLM 7B/67B Chat open source for the research community.
DeepSeek R1 is an AI model from Hong Kong’s High-Flyer Capital. It is fully open-source and 96.4% cheaper than OpenAI o1. OpenAI o1 costs $60 per 1M tokens, while DeepSeek R1 costs just $2.19.
In this blog, we will explore how DeepSeek compares to ChatGPT, analyzing their differences in design, performance, and accessibility.
Cost-Effectiveness in Model Development
One of the most notable distinctions between DeepSeek and ChatGPT lies in their development costs. DeepSeek’s R1 model, which offers competitive reasoning capabilities, was developed for under $6 million, a fraction of what comparable models like ChatGPT require. This cost-efficiency is achieved through optimized training techniques and the use of approximately 2,048 AI accelerators. In contrast, OpenAI’s models demand significantly larger computational resources and investments.
By making advanced AI more accessible through reduced costs, DeepSeek is democratizing AI technologies, ensuring that smaller organizations can also benefit from state-of-the-art solutions.
DeepSeek stands out for its cost-effectiveness. Its training and deployment costs are significantly lower than those of ChatGPT, enabling broader accessibility for smaller organizations and developers. For example, the DeepSeek R1 model, which rivals ChatGPT in reasoning and general capabilities, was developed for a fraction of the cost of OpenAI’s models.
Additionally, DeepSeek is open-source and available under an MIT license. This transparency allows developers to explore, fine-tune, and deploy the model freely, fostering innovation and collaboration. In contrast, ChatGPT is a proprietary model that restricts direct access to its architecture and datasets, offering API access instead.
Core Architecture and Training
Both DeepSeek and ChatGPT are built on transformer architectures, which leverage self-attention mechanisms to generate context-aware responses. However, their approaches to training and optimization differ significantly:
- DeepSeek LLM:
- Trained on 2 trillion tokens in both English and Chinese.
- Utilizes a mix of curated internet text, math, code, and domain-specific datasets.
- Features Group-Query Attention (GQA) in the 67B model, enhancing scalability and performance.
- Incorporates reinforcement learning methods focusing on reasoning and preference alignment.
- Uses innovative techniques like “aha moments” to improve chain-of-thought reasoning.
- ChatGPT:
- Built on OpenAI’s proprietary GPT-4 architecture.
- Trained on diverse datasets with an emphasis on conversational tasks.
- Employs Reinforcement Learning with Human Feedback (RLHF) to ensure user-centric and contextually appropriate responses.
- Features a closed training process that limits external contributions or adaptations.
Open-Source vs. Proprietary Models
DeepSeek’s open-source philosophy is a key differentiator. By making its models freely available, DeepSeek fosters an environment of shared innovation, enabling smaller players to fine-tune and adapt the model for their specific needs. This democratization of AI contrasts sharply with OpenAI’s closed model, which limits modifications and requires paid access to its API.
However, this openness also comes with challenges, such as potential misuse or fine-tuning for harmful purposes. OpenAI’s closed ecosystem ensures tighter control over its applications, which may appeal to enterprise users prioritizing security and compliance.
Training Efficiency
Training an AI model is a resource-intensive process, but DeepSeek has showcased exceptional efficiency in this area. The R1 model was trained in less than two months, demonstrating how DeepSeek’s streamlined processes reduce time-to-market without compromising quality.
In comparison, OpenAI’s models, including ChatGPT, often require extended training durations due to the complexity of their architectures and the scale of datasets. While these efforts result in highly capable models, they also add to the overall cost and time investment.
Performance Across Domains
Reasoning and General Capabilities
- DeepSeek: Matches or slightly surpasses ChatGPT in reasoning tasks, as demonstrated by its performance on benchmarks like MMLU and ChineseQA. Its multi-lingual training also gives it an edge in handling Chinese language tasks.
- ChatGPT: Remains a leader in reasoning and contextual understanding, but its performance advantage narrows when compared to DeepSeek R1.
Coding and Mathematics
- DeepSeek: Achieves outstanding results in coding (HumanEval Pass@1: 73.78) and mathematics (GSM8K 0-shot: 84.1%). Its efficiency and cost-effectiveness make it a practical choice for developers.
- ChatGPT: While strong in coding and math, it is costlier and less accessible for smaller-scale use cases.
Creative Writing and Personality
- DeepSeek: Offers a freer, more creative writing style with minimal censorship, allowing users to explore a wider range of topics and conversational styles.
- ChatGPT: Excels in structured and coherent content generation but may feel overly formal or constrained due to stricter RLHF alignment.
Competitive Performance
Despite its lower costs and shorter training time, DeepSeek’s R1 model delivers reasoning capabilities on par with ChatGPT. This achievement highlights the potential of DeepSeek’s innovative techniques, challenging the assumption that high performance requires extensive resources.
ChatGPT, while powerful, has set high benchmarks with its contextual understanding and language generation capabilities. However, DeepSeek’s ability to match these standards with fewer resources is a testament to its disruptive potential in the AI landscape.
Impact on the Industry
DeepSeek’s rise has triggered notable market reactions, with investors reassessing the competitive landscape. Major technology companies, including NVIDIA, have experienced fluctuations in stock prices as DeepSeek’s advancements reshape expectations for AI development.
The open-source nature of DeepSeek’s offerings also encourages a broader adoption of AI technologies across industries, reducing dependency on proprietary platforms like ChatGPT. This shift has the potential to create a more inclusive AI ecosystem.
Key Use Cases
DeepSeek:
- Ideal for researchers and developers seeking customizable, high-performance models.
- Supports local deployment for organizations with specific privacy or compliance needs.
- Excels in multilingual applications, particularly in Chinese.
ChatGPT:
- Best suited for enterprises requiring robust APIs and reliable support.
- Popular for customer service, content creation, and conversational AI solutions.
- Favored by users seeking a polished, ready-to-use product.
The Broader Impact on the AI Industry
DeepSeek’s rise signals a shift in the AI landscape. By delivering a high-performing, open-source alternative to ChatGPT, it challenges the dominance of established players like OpenAI. This competition is likely to drive innovation, reduce costs, and accelerate the adoption of AI across industries.
For smaller organizations, DeepSeek represents an opportunity to leverage cutting-edge AI without the high costs associated with proprietary solutions. For the AI community, it embodies a shift toward openness and collaboration, enabling rapid advancements in the field.
Making API Calls
Differences
| Feature | DeepSeek API | ChatGPT API |
|---|---|---|
| Base URL Flexibility | DeepSeek offers multiple base URLs (https://api.deepseek.com and https://api.deepseek.com/v1). However, the /v1 does not indicate versioning of models. | ChatGPT uses a single base URL format (https://api.openai.com/v1/chat/completions). |
| Model Versions | Models like deepseek-chat (DeepSeek-V3) and deepseek-reasoner (DeepSeek-R1) are available. Each has a clear purpose: conversational or reasoning tasks. | Models like gpt-3.5-turbo, gpt-4t, text-embedding-3-small, and fine-tuned variants serve various purposes but aren’t segmented into “reasoner” or “chat” as DeepSeek does. |
| API Key | DeepSeek API keys are obtained via their platform (“apply for an API key”). | ChatGPT API keys are generated from OpenAI’s user dashboard. |
| Version Relationships | DeepSeek’s /v1 endpoint does not correspond to a specific version of the model. | ChatGPT’s /v1 endpoint aligns with GPT model versions (e.g., GPT-4, GPT-3.5). |
| Additional Models | DeepSeek explicitly supports a reasoning-focused model (deepseek-reasoner). | ChatGPT does not distinguish between reasoning-specific and chat-specific models. |
| Deployment Focus | DeepSeek emphasizes compatibility with OpenAI but has proprietary upgrades like DeepSeek-V3 and DeepSeek-R1 for advanced reasoning. | ChatGPT provides general-purpose GPT models for both reasoning and chat capabilities. |
Comparison Between DeepSeek Products and ChatGPT (OpenAI) Products
DeepSeek Products
- DeepSeek App:
A dedicated application for accessing DeepSeek’s AI capabilities, tailored for end-users seeking conversational AI or advanced reasoning tasks.
- DeepSeek Chat:
A conversational model (DeepSeek-V3) designed for chat-based interactions. It provides natural, human-like responses optimized for customer support and general inquiries.
- DeepSeek Platform:
A platform providing tools, APIs, and integrations for developers to incorporate DeepSeek’s models (e.g., DeepSeek-V3, DeepSeek-R1) into their applications.
- API Pricing:
Offers transparent and competitive pricing for API usage, based on features like the number of tokens processed and access to specific models.
- Service Status:
Provides a real-time dashboard for monitoring the availability and performance of DeepSeek’s services and APIs.
ChatGPT (OpenAI) Products
- Operator Research Preview (Jan 23, 2025):
A new feature in preview for advanced research and operator testing with OpenAI’s AI tools.
- Sora (Dec 9, 2024):
A specialized release for a new AI capability, emphasizing interactivity and innovation.
- ChatGPT Pro (Dec 5, 2024):
A premium subscription plan offering faster response times, priority access to new features, and extended usage limits.
- ChatGPT Search (Oct 31, 2024):
A feature introducing search capabilities within ChatGPT, allowing users to query external information seamlessly.
- Canvas (Oct 3, 2024):
A tool for writing and coding collaboratively, integrated into ChatGPT to provide a more interactive development environment.
- Realtime API (Oct 1, 2024):
Introduced to enable real-time AI model interactions for developers, optimized for low-latency applications.
- Vision in the Fine-Tuning API (Oct 1, 2024):
Enables vision-based fine-tuning of models, incorporating image data into training processes.
- Prompt Caching (Oct 1, 2024):
A feature aimed at improving API efficiency by caching frequent prompts for faster responses.
The Key Differences
- DeepSeek focuses on integrating conversational AI and reasoning models into standalone apps and developer platforms, emphasizing compatibility with OpenAI’s ecosystem.
- ChatGPT (OpenAI) delivers a broader suite of tools, including premium features (Pro), collaborative environments (Canvas), advanced APIs (Realtime, Vision Fine-Tuning), and research-oriented tools (Operator Research Preview).
Conclusion
DeepSeek and ChatGPT represent two distinct approaches to AI development: one prioritizing openness and cost-efficiency, the other focusing on performance and enterprise-grade solutions. Both have their strengths and weaknesses, but the emergence of DeepSeek highlights the growing diversity in the AI ecosystem. As the competition heats up, users and developers alike stand to benefit from the enhanced capabilities and accessibility of these transformative technologies.
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