The release of reasoning models has fundamentally changed how we interact with artificial intelligence. Instead of spitting out immediate answers, reasoning models spend seconds "thinking" through complex problems step-by-step. DeepSeek R1 disrupted the entire AI industry by matching OpenAI o1's performance on math, coding, and science, while being completely open-source and up to 30 times cheaper to run.
But does the open-source challenger actually beat OpenAI's polished, proprietary ecosystem? This comparison analyzes DeepSeek R1 and ChatGPT o1 side-by-side to help you decide which tool fits your workflow and budget.
Quick Comparison
| Herramienta | Nota | Características | Precio | Acción |
|---|---|---|---|---|
DeepSeek R1Mejor opción | ★ 4.6 | Open-source (MIT) · Transparent chain of thought · Distilled local models · Ultra-cheap API | Free / Pay-per-token | View DeepSeek ↗ |
ChatGPT o1 | ★ 4.7 | Premium ecosystem · Integrated Advanced Data Analysis · GPT Store · High safety standards | $20 / mo | View ChatGPT ↗ |
Key Differences at a Glance
| Feature | DeepSeek R1 | ChatGPT o1 (OpenAI o1) |
|---|---|---|
| Model Type | Open-weights (MIT License) | Closed-source (Proprietary) |
| Thinking Process (CoT) | Fully visible (raw thinking process shown) | Hidden (summarized version shown) |
| Primary Strengths | Mathematics, coding, open-source custom deployments | Logic, multimodal tasks, advanced coding workspace |
| Web Interface Price | 100% Free (unlimited usage) | Requires ChatGPT Plus ($20/mo) or Pro ($200/mo) |
| API Pricing (per 1M input/output) | $0.55 / $2.19 | $15.00 / $60.00 |
| Local Execution | Yes (distilled models from 1.5B to 70B) | No (cloud-only) |
| Multimodal Support | No (text-only reasoning in base R1) | Yes (can reason through images) |
| Ecosystem & Tools | Basic chat interface | Custom GPTs, Canvas editor, code execution |
The Core Concept: What is a Reasoning Model?
Traditional LLMs like GPT-4o or Claude 3.5 Sonnet predict the next token immediately. While they are fast, they struggle with complex logic because they cannot plan their answers or correct errors mid-thought.
Both DeepSeek R1 and ChatGPT o1 use large-scale Reinforcement Learning (RL). When given a prompt, they generate a silent internal monologue, checking their assumptions, correcting math errors, and planning their output before writing the final response. This makes them significantly better at coding, advanced mathematics, physics, and logic-heavy academic tasks.
Transparency: Visible vs. Hidden Chain of Thought
The most striking user-experience difference between these two models is how they show their thinking.
DeepSeek R1: Absolute Transparency
DeepSeek R1 shows you its entire raw reasoning process inside collapsible <think> tags. You can see the model struggle, backtrack, change its mind, and refine its approach in real time.
- The Pro: For developers and researchers, seeing the raw thinking process is invaluable. It helps you understand exactly how the model arrived at a solution, making debugging code or auditing mathematical proofs much easier.
- The Con: The thinking process can be incredibly long and verbose, sometimes taking up more screen space than the actual answer.
ChatGPT o1: The Black Box
OpenAI chose to hide the raw chain of thought. Instead of showing the model's monologue, the ChatGPT interface displays summarized thoughts like "Thinking..." followed by brief phrases like "Analyzing codebase" or "Calculating matrix."
- The Pro: The output is clean, direct, and avoids cluttering the interface.
- The Con: You have no idea if the model is reasoning correctly or simply hallucinating logic behind the scenes. OpenAI has explicitly stated they hide the chain of thought for competitive reasons and to prevent users from training other models on their CoT data.
Performance: Math, Coding, and Science
When it comes to benchmarks, the two models are neck-and-neck, but they excel in slightly different scenarios.
Mathematics (AIME & Olympiads)
DeepSeek R1 set a new standard on the American Invitational Mathematics Examination (AIME) benchmark, scoring an incredible 97.3%. OpenAI o1 (particularly the full o1 model in "pro" mode) matches this performance, hover around 96-98%. For complex math, both models are virtually equal, easily outperforming human college graduates.
Coding & Engineering (SWE-bench)
For pure algorithmic coding tasks, DeepSeek R1 is outstanding. Its ability to double-check its own syntax before outputting code makes it a favorite among software engineers.
However, ChatGPT o1 has a massive practical advantage in the web app: integrated code execution. ChatGPT can run the Python code it writes in a sandboxed environment to verify it works. DeepSeek's web interface cannot do this; it relies entirely on mental simulation. Furthermore, ChatGPT o1 integrates with Canvas, OpenAI's dedicated workspace for code and writing edits.
Science & Logic (GPQA)
On the GPQA benchmark (graduate-level science questions in physics, chemistry, and biology), both models achieve PhD-level scores. OpenAI o1 holds a slight edge in complex multi-step logical reasoning that requires broad encyclopedic knowledge, while DeepSeek R1 occasionally struggles with English-specific nuances or cultural metaphors.
Multimodal Capabilities
A major limitation of the base DeepSeek R1 model is that it is text-only. If you upload an image, chart, or PDF with diagrams, R1 cannot reason through the visual components natively.
ChatGPT o1 is fully multimodal. You can upload a complex architectural blueprint, a circuit diagram, or a physics chart, and ask o1 to analyze it using its step-by-step reasoning engine. This makes o1 significantly more versatile for engineering and design workflows.
Pricing, Limits, and API Costs
This is where the comparison becomes highly asymmetrical. DeepSeek has completely broken the economic model of proprietary AI.
Web Interface Usage
- DeepSeek R1: Available completely free on the DeepSeek web interface and mobile app, with no strict message limits.
- ChatGPT o1: Access requires ChatGPT Plus ($20/month) or Pro ($200/month). Even on paid plans, OpenAI enforces message limits (e.g., 50 messages per week for o1, which can quickly run out during a heavy coding session).
API Pricing (Per 1 Million Tokens)
For developers building applications, the cost difference is staggering:
- OpenAI o1 API: $15.00 for input tokens, $60.00 for output tokens.
- DeepSeek R1 API: $0.55 for input tokens (cached input is even cheaper at $0.14), $2.19 for output tokens.
DeepSeek R1 is nearly 30 times cheaper than OpenAI o1. For startups and enterprise applications running millions of queries daily, switching to DeepSeek R1 represents a massive cost reduction with almost zero loss in reasoning quality.
Local Execution: Open weights
Because DeepSeek R1 is open-source (MIT License), developers can download the model weights and run it on their own servers or local hardware.
DeepSeek also released distilled models (ranging from 1.5B to 70B parameters) built on top of Llama and Qwen architectures. This means you can run a highly competent reasoning model locally on a consumer-grade laptop using tools like Ollama or LM Studio. OpenAI o1 is entirely proprietary; you can only access it through OpenAI's cloud servers.
Safety, Censorship, and Alignment
As a company based in China, DeepSeek is subject to local regulatory compliance. DeepSeek R1 is censored on sensitive political topics related to Chinese history and geopolitics, where it will politely decline to answer.
OpenAI o1 is aligned according to OpenAI's safety guidelines, which heavily restrict content related to self-harm, adult material, weapon creation, and copyright violation. However, o1 is much more open and objective on global historical and geopolitical queries than R1.
Verdict: Which Reasoning Model Wins?
The choice between DeepSeek R1 and ChatGPT o1 depends on your technical needs, budget, and platform preferences:
Choose DeepSeek R1 if:
- You want elite reasoning for free: You do not want to pay $20/month to access advanced logic and coding models.
- You are a developer looking for API integration: The 30x cost savings make DeepSeek R1 the only viable choice for high-volume deployments.
- You want local privacy: You need to run a reasoning model offline on your own hardware without sending data to external servers.
- You value transparency: You want to see the exact thinking process step-by-step.
Choose ChatGPT o1 if:
- You need multimodal reasoning: You regularly work with images, charts, and diagrams.
- You want a polished workspace: You want code execution, Canvas integration, and Custom GPTs.
- You need global policy objectivity: You want a model that is not subject to Chinese local regulatory censorship.
FAQ
Is DeepSeek R1 actually better than OpenAI o1?
On pure mathematics (AIME) and code generation benchmarks, DeepSeek R1 is equal to or slightly ahead of the base OpenAI o1 model. However, the premium OpenAI o1 Pro (available in the $200/month plan) still holds a slight edge on extremely complex, multi-layered logic tasks. Additionally, o1 is multimodal, while R1 is text-only.
Does DeepSeek R1 keep my data private?
If you use the free web interface or cloud API hosted by DeepSeek, your data is sent to their servers in China. However, because the model is open-source, you can download the weights and run DeepSeek R1 completely offline on your own local server. This guarantees 100% data privacy, which is impossible with OpenAI o1.
Can I run DeepSeek R1 on a normal laptop?
You cannot run the full 671-billion parameter DeepSeek R1 model on a normal laptop, as it requires enterprise-grade GPUs. However, DeepSeek has released "distilled" versions (like the 8B or 14B models) that can easily run on a standard MacBook or gaming laptop using free tools like Ollama.