Open AI vs. DeepSeek

Artificial intelligence is developing and rapidly changing the digital environment of the world. Two organizations attracting significant global attention; DeepSeek, a Chinese AI startup, and OpenAI, a leading American AI research laboratory. Both organizations have developed significant progress in large language models (LLMs) yet maintain separate methods of operation and different pricing models and guiding principles.

The Chinese startup DeepSeek has established itself as a major competitor in the AI market and possibly could be a major competitor of OpenAI.

DeepSeek-R1 represents DeepSeek’s Chinese AI research lab’s internationally recognized model that matches industry leaders OpenAI in reasoning capabilities and code generation while demonstrating superior efficiency. It stands apart from many Chinese AI firms by operating independently from large tech conglomerates/giant companies. It develops resource-efficient AI technology despite U.S. semiconductor export restrictions on China. Through its open-source methodology and research team DeepSeek works to spread AI technology access while competing against Western AI market leaders.

The Chinese entrepreneur Liang Wenfeng established DeepSeek in 2023 to enter the AI market. The company has experienced exceptional growth during its short operational period. It released its open-source models for U.S. download in early January 2025 which triggered a dramatic increase in user popularity. The application outpaced OpenAI’s ChatGPT app in iPhone download rankings. Big giants which were thought to be the master of AI in their field and their hardware (semiconductors) are losing their stocks after its launch and popularity.

What is DeepSeek?

The Chinese AI startup DeepSeek AI established “DeepSeek” as its advanced artificial intelligence (AI) model following its foundation in May 2023. The AI system distinguishes itself through its fast computing power together with detailed contextual understanding capabilities thus positioning itself as a significant competitor in the AI sphere. The company achieve this success on their own capabilities due to semiconductors restriction.

Available Versions of DeepSeek

Currently, DeepSeek offers two versions of its AI models:

• DeepSeek V3: DeepSeek V3 became available on December 26, 2024, with a 128K token input context and an 8K token output capacity.
• DeepSeek R1: The January 20, 2025 release of DeepSeek R1 supports 128K token input while offering 32K token output capability.

The models specifically trained for the Chinese language perform exceptional linguistic comprehension and processing.

Technical Architecture of DeepSeek

The Mixture of Experts (MoE) architecture in DeepSeek activates specific subsets of its parameters to perform each task. The computational design approach enables improved performance with decreased resource usage than traditional dense AI models require. The technological rivalry between the United States and China resembles Cold War dynamics yet DeepSeek’s growing prominence stems mainly from its outstanding performance and economical operation.

Independent assessments show DeepSeek-R1 matches the performance of OpenAI’s O1 model while requiring significantly less operational cost. This is achieved through:

• DeepSeek utilizes 2,048 NVIDIA H800 GPUs in a cluster configuration to optimize GPU usage; providing better value than high-end accelerators used by other AI models.
• The model shows signs of requiring fewer training data points than its market competitors.
• The open-source release of DeepSeek under an MIT license allows developers across the community to adopt its functionality.

Availability and Deployment on Azure AI

The DeepSeek models remain absent from the Azure AI model catalog at this time. DeepSeek users need to submit a request before obtaining approval to use the system. Organizations acquire GPU capacity through Azure AI Infrastructure VM Portfolio to independently deploy and operate the model.

DeepSeek-R1

A Cost-Efficient AI Model

DeepSeek-R1 is the company’s latest model because it performs better than OpenAI and Meta’s most advanced AI models while requiring less training expense and being more efficient. It successfully optimized its model training without needing high-performance AI accelerators which Western companies struggle to obtain because of U.S. export restrictions.

The DeepSeek-R1 and DeepSeek-V3 models secured positions among the top 10 on Chatbots which is a performance benchmarking platform operated by the University of California Berkeley. DeepSeek reports that their models surpass and match the performance levels of competitive artificial intelligence systems when doing mathematical reasoning and answering questions about general knowledge.

Cost Efficiency and Industry Skepticism

DeepSeek announced that its most recent AI model required a $5.6 million training investment while industry experts predict similar models need between $100 million and $1 billion for training. Stacy Rasgon from Bernstein has criticized DeepSeek’s reported cost data as deceptive because it appears misleading to him.

What is OpenAI?

An organization which focuses on artificial intelligence research for human advancement operates as OpenAI which exists as a private scientific entity (previously was a non-profit organization). In 2015 Elon Musk along with Sam Altman and other successful business leaders founded OpenAI in San Francisco USA.

Ownership and Funding Structure

OpenAI began as a non-profit but switched to a for-profit structure so it could sustain research activities and development. The company received funding from influential investors, including:

• Elon Musk (Tesla, SpaceX) started OpenAI before, he left the company in 2018 to establish his own company xAI.
• Sam Altman (OpenAI’s current CEO).
• Reid Hoffman (LinkedIn co-founder).
• Peter Thiel (PayPal co-founder).
• Microsoft stands as OpenAI’s principal financial supporter and technological alliance partner.

OpenAI continues its operations with Microsoft as substantial financial backing and additional institutional support from NVIDIA, JPMorgan Chase, Citi and SoftBank and Fidelity Investments.

OpenAI o1

A Next-Generation AI Model

OpenAI o1 represents the latest release from OpenAI’s Generative AI series which focuses on improving deep reasoning abilities and structured output generation. The model demonstrates exceptional suitability for inventory management and customer support alongside financial analysis applications.

Key Features of OpenAI o1

• The model processes 200K tokens through its Expanded Context Window which produces detailed responses with contextual accuracy.
• It can produce lengthy responses which reach 100K tokens; making it suitable for complex multi-layered query processing.
• Developers can use JSON schemas to format outputs through structured output formatting which ensures both precision and structured response formats.
• Allows users to select from three reasoning effort settings that optimize performance based on task requirements.

The AI development efforts of DeepSeek and OpenAI have resulted in substantial progress through their separate capabilities while maintaining competitive relations.

DeepSeek distinguishes itself through its economic system design combined with open-source availability and targeted Chinese language processing capabilities.

OpenAI leads the industry through its sophisticated reasoning models and its substantial funding and its deep connection to Microsoft’s cloud infrastructure.

The escalating competition between these AI research organizations drives their ongoing innovations which determine and speed up the evolution of large language models while steering global AI development and adoption.

 

Comparison: OpenAI vs. DeepSeek

The table delivers an in-depth comparison of OpenAI and DeepSeek which details their distinct pricing models alongside performance metrics and accessibility features and application areas.

Comparison Table: OpenAI vs. DeepSeek

Feature	OpenAI (GPT-4, GPT-4o, o1)	DeepSeek (DeepSeek-R1)
Model Type	Proprietary (closed-source)	Open-source
Best Use Cases	Advanced reasoning, structured responses, coding, scientific research	Real-time applications, language translation, and high-speed inference
Accessibility	Available through paid API and ChatGPT subscriptions	Free for most users and available for local deployment
Pricing	ChatGPT Plus: $20/month; API pricing: ~$7.50 per million tokens	API pricing: ~$0.14 per million tokens (27x cheaper than OpenAI)
Performance	Superior in deep analytical tasks, general knowledge, and language fluency	Stronger in logical reasoning, mathematics, and technical coding tasks
Integration	Supports Microsoft Azure and API-based integrations	Can be self-hosted on personal or enterprise hardware
Data Privacy	Relies on cloud-based processing	Able to run locally, ensuring full data privacy
Scalability	Optimized for large-scale cloud deployments	Flexible due to open-source availability
Community and Support	Backed by OpenAI’s enterprise partnerships and Microsoft	Supported by open-source contributors and community forums
Ethical Considerations	Includes content moderation, bias controls, and AI safety measures	Less restrictive, allowing users to bypass certain limitations

Comparative Analysis of DeepSeek and OpenAI

DeepSeek’s Commitment to Open-Source Development

Openness stands as a major difference that separates DeepSeek from OpenAI. Through its open-source AI approach, DeepSeek enables users to access, modify and execute the DeepSeek R1 model directly on their personal devices. Through this method, users maintain complete data sovereignty while preventing their information from being shared with external servers.

OpenAI began as an open research organization but now operates with closed-source AI development policies for its newest AI systems. It prevent users from accessing the system’s base architecture.

Cost-Effectiveness

Users receive better pricing from DeepSeek than from OpenAI.

The DeepSeek-R1 API provides pricing at $0.14 for each 1 million tokens which equals approximately 750,000 words.

The OpenAI O1 API costs $7.50 for processing 1 million tokens.

The lower pricing structure of DeepSeek makes it an affordable solution for organizations that need to process large amounts of AI data. Users of ChatGPT need to subscribe to a $20/month paid tier but DeepSeek provides free access to most features.

Performance in Specialized Tasks

DeepSeek demonstrates better technical capabilities than OpenAI’s ChatGPT while ChatGPT maintains superiority for conversational AI and creative writing and real-time knowledge-based operations.

User feedback suggests that DeepSeek outperforms ChatGPT in areas such as:

• Logical reasoning
• Programming and coding assistance
• Mathematical problem-solving

The benchmark results confirm the observations made by users. DeepSeek-R1 performed better than OpenAI in the American Invitational Mathematics Examination (AIME) 2024 by reaching a 79.8% accuracy score while OpenAI scored 79.2%.

OpenAI’s models show exceptional performance across multiple domains through their success in Massive Multitask Language Understanding (MMLU) benchmark testing.

Founding and Mission

“Liang Wenfeng” created “DeepSeek” through his startup because he previously co-founded AI-driven algorithmic trading through High-Flyer hedge fund. The AI achievements from High-Flyer’s operations motivated the company to initiate their open-source initiative which promotes advanced AI accessibility.

OpenAI established itself in 2015 to create artificial general intelligence (AGI) that would benefit everyone on Earth. OpenAI progressed to a capped-profit model while establishing valuable partnerships with Microsoft as its primary source of sustained financing.

Model Development and Computational Efficiency

The DeepSeek team made a significant cost-efficient AI. DeepSeek-R1’s development cost less than $6 million because the team applied efficient training methods alongside optimized algorithms.

OpenAI’s GPT-4 model and its counterparts require hundreds of millions of dollars for training expenses according to estimates. OpenAI’s extensive training data requirements generate substantial computational expenses which become reflected in its operational costs.

Open-Source and Proprietary AI Models

The fundamental difference between DeepSeek AI and OpenAI emerges through their different methods of handling model accessibility alongside distribution strategies.

DeepSeek AI provides DeepSeek-R1 free of any cost to developers worldwide through its fully open-source platform. Open-source accessibility enables users to work with models without limitations; promoting collaboration and transparency and innovation throughout the AI domain.

The organization began with open research but has gradually transitioned toward a proprietary model structure. The advanced models including GPT-4 exist only through commercial partnerships which require paying for API services to access them. Through limited model access OpenAI is able to monitor both model deployment and application across its services to maintain ethical compliance and safety standards.

Use Cases

OpenAI

• The creative writing feature of ChatGPT alongside its content generation abilities produces premium quality written material.
• The Code Assistance feature of OpenAI’s Codex enables GitHub Copilot to boost developer productivity.
• AI-Powered Art and Design: DALL-E creates visual content through text inputs
• The Enterprise version of ChatGPT implements artificial intelligence for business automation applications.
• OpenAI o1 proves better than other options when addressing scientific research and advanced programming tasks along with complex operations.

DeepSeek

• AI-Powered Search Engines are optimal for knowledge retrieval together with search response optimization tasks.
• Multilingual NLP Applications: Better for processing cross-language AI.
• AI developers who require free customizable AI models will benefit from Open-Source AI Development.

The successful implementation of an AI model depends on performance.

Strengths and Weaknesses of OpenAI and DeepSeek

Strengths of OpenAI

• The AI models from OpenAI include GPT-4 alongside DALL•E and Codex and Whisper.
• OpenAI stands as the industry leader in developing generative AI systems for text, code, and image applications.
• Strong support for enterprise applications (ChatGPT Enterprise, API access).
• The company provides dependable high-performance models that serve both commercial and research purposes.

Weaknesses of OpenAI

• Most AI models operate as paid registered systems.
• OpenAI maintains restricted visibility about its entire training dataset information.
• Premium AI services from OpenAI come with high price tags.

Strengths of DeepSeek

• Users can access the open-source AI model known as DeepSeek without charge through developer licenses.
• The platform emphasizes search retrieval tasks because this technique enables efficient automated knowledge management and question resolution systems.
• The platform’s multilingual NLP features enable the processing of numerous language sets effectively.
• The deployment system supports various applications that integrate AI technology.

Weaknesses of DeepSeek

• The product line is limited because DeepSeek lacks AI-powered image and code generation capabilities which OpenAI provides.
• The platform remains under development since OpenAI’s models have gained broader adoption.
• The DeepSeek platform operates with a less developed enterprise solution base than OpenAI does.

Price

DeepSeek provides users with benchmark performance at a lower price point than OpenAI while maintaining equivalent benchmark performance. It offers its services without charge to all users who register for free without requiring credit card information or subscription commitments unlike OpenAI’s premium access model that costs $20 per month.

API pricing demonstrates substantial differences in cost between these systems. DeepSeek provides its API services at a cost 27 times lower than OpenAI’s while offering the same workload available for $10 instead of $270.

Using DeepSeek enables users to eliminate cloud dependencies while reducing privacy concerns and usage restrictions in a way that reflects the benefits of owning software locally instead of using cloud-based services. The source code behind OpenAI’s models stays inaccessible and proprietary to outside researchers and practitioners.

Final Verdict: which one is better?

Category	Winner	Reasoning
Performance in Reasoning and Structured Outputs	OpenAI	OpenAI models excel in structured tasks, coding and in-depth reasoning.
Cost-Effectiveness	DeepSeek	DeepSeek is 27x cheaper in API pricing and free for many users.
Open-Source Availability	DeepSeek	Unlike OpenAI, DeepSeek is a fully open-source model, allowing local deployment.
Ease of Access	DeepSeek	No subscription is required; users can access and run it locally.
Scalability & Enterprise Support	OpenAI	OpenAI integrates with Microsoft Azure, offering enterprise-grade support and cloud-based scalability.
Privacy & Security	DeepSeek	DeepSeek’s local deployment option ensures full user data control.
Best for Real-Time Applications	DeepSeek	DeepSeek performs better in low-latency tasks such as language translation and rapid inference.
Best for AI-Powered Businesses & Enterprises	OpenAI	OpenAI is backed by strong commercial partnerships, ensuring better long-term enterprise support.

Final Verdict

• Choose OpenAI: Users who need structured reasoning along with deep analytical outputs, enterprise support, and cloud-based scalability should select it.
• Choose DeepSeek: Users who desire cost-effective operations together with data protection and local platform execution of open-source services would benefit from DeepSeek.

Businesses should consider implementing a hybrid strategy by using OpenAI for complex reasoning operations while utilizing DeepSeek for its cost-effective AI processing needs.

Summary and Final Reviews

The analysis of DeepSeek along with OpenAI o1 reveals their strengths within the system. The combination of DeepSeek’s speed and quick inference capabilities complements OpenAI’s strength in structured reasoning and complex problem-solving and analytical complexity; making it ideal for scientific and programming and mathematical applications.

One must avoid relying solely or singly on one AI model to execute an impactful AI strategy. A hybrid AI system built from multiple models matched to task requirements and cost evaluation efforts results in the best AI execution effectiveness. Organizations that focus on cost-effectiveness combine OpenAI models with DeepSeek for standard operations. This approach allows businesses to balance performance and cost while optimizing their return on investment (ROI). The accessible deployment model enables enterprises to scale operations and minimize costs which accelerates market entry and simplifies management of self-hosted AI models such as DeepSeek.

AI development continues to create multiple possibilities for different application needs. What are the differences you have observed between these different models? Please feel free to exchange your thoughts about this topic or contact us if you have any queries.

All the information given above and below in this article is taken from multiple resources, and can’t be acceptable for any legal proof in any court of the world. Omissions and mistakes are possible as it’s just the beginning of DeepSeek, let’s see what will happen in the future. Either both organizations run paralled to eachother or one surpass other company.

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