Updated Aug 23, 2026Verified Benchmark Data

DeepSeek-R1 vs OpenAI o1: The Ultimate Reasoning Models Benchmark Comparison

Definitive comparison of DeepSeek-R1 and OpenAI o1. Evaluating AIME 2024 (79.8% vs 79.2%), MATH-500 (97.3% vs 96.4%), Codeforces 2,029 ELO, 27x price difference, and MIT open weights.

DeepSeek-R1

by DeepSeek

9.8/10

Overall Rating

Best Mathematics & Competition Coding ValueBest for Enterprise Privacy & Self-Hosting

DeepSeek's flagship open-weights reasoning model with 671B MoE architecture (37B active), pure RL incentive mechanisms, and competition-level math mastery.

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128Ktokens context window

33Ktokens max output

Pay-as-you-go APIper month (Plus / Pro)

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OpenAI o1

by OpenAI

9.7/10

Overall Rating

Best Scientific Research & Vision Reasoning

OpenAI's breakthrough reasoning model with internal Chain-of-Thought planning. Excels in complex STEM problem solving, competitive coding, and policy compliance.

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200Ktokens context window

100Ktokens max output

$200/month (o1 Pro)per month (Pro / Team)

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Our Pick: DeepSeek-R1

DeepSeek-R1 takes the editorial crown due to matching OpenAI o1 on math and coding benchmarks while being 27x cheaper and providing complete open weights for the global developer ecosystem.

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Benchmark Performance

Side-by-side results on major industry benchmarks (higher is better)

DeepSeek-R1

OpenAI o1

100

90.8%

91.8%

71.5%

75.2%

97.3%

96.4%

98.5%

98.8%

49.2%

48.9%

1,357

1,353

MMLU(Knowledge)

GPQA(Graduate Q&A)

MATH(Competition)

ARC(Reasoning)

SWE-bench(Engineering)

LMSYS Arena ELO(Human Preference)

Feature Comparison

Compare core capabilities and tool support.

Feature	DeepSeek-R1	OpenAI o1
Text & Code Generation
Image & Vision Understanding
Video & Audio Generation
Web Browsing / Search
Code Execution Environment
Autonomous Computer Use
Long Context Window
Multi-step Agentic Workflows
Custom Bots / Extensions
Fine-tuning

Use Case Ratings

How each model performs in real-world scenarios (1-10).

Use Case	DeepSeek-R1	OpenAI o1
Coding & Development	10	10
Writing & Content Creation	8	8
Research & Analysis	10	10
Creative Tasks	7	7
Data Analysis	10	10
Conversation & Nuance	8	8
Education & Tutoring	10	10
Math & Science	10	10
Summarization	9	9

Pricing Comparison(Per 1M Tokens)

Model	Input Tokens	Output Tokens	Blended Cost	Monthly (100M tokens)
DeepSeek-R1	$0.55	$2.19	~$0.96	~$96
OpenAI o1	$15.00	$60.00	~$26.25	~$2,625

DeepSeek-R1 is 96% cheaper

For the same performance tier, DeepSeek-R1 offers exactly half the API cost of OpenAI o1.

Pros & Cons

DeepSeek-R1

Pros

Record competition math performance: 79.8% AIME 2024 Pass@1 and 97.3% MATH-500
2,029 ELO rating on Codeforces (96.3rd percentile of competitive programmers)
Unbeatable economics ($0.55 in / $2.19 out vs $15.00 / $60.00 on o1)
100% open weights under MIT license with Distill models (1.5B to 70B)

Cons

Reasoning chains take additional time before output begins
No vision or image analysis support in base R1

OpenAI o1

Pros

Top-tier graduate scientific reasoning (75.2% GPQA Diamond)
Huge 200,000 token context window and 100,000 max output tokens
Vision reasoning support (can inspect complex engineering schematics)
Deep enterprise alignment and safety compliance

Cons

Extremely expensive API pricing ($15.00 input / $60.00 output per 1M tokens)
Hidden chain-of-thought (reasoning tokens cannot be viewed raw in API)

Frequently Asked Questions

Is DeepSeek-R1 really as smart as OpenAI o1 in math and coding?

Yes. Verified benchmarks show DeepSeek-R1 scores 79.8% on AIME 2024 (vs 79.2% on o1), 97.3% on MATH-500 (vs 96.4% on o1), and 49.2% on SWE-Bench Verified.

How much cheaper is DeepSeek-R1 compared to OpenAI o1?

DeepSeek-R1 is approximately 27x cheaper. DeepSeek charges $0.55/M input and $2.19/M output, compared to OpenAI o1's $15.00/M input and $60.00/M output.

Can I run DeepSeek-R1 on my local computer?

Yes. The distilled versions (such as DeepSeek-R1-Distill-Qwen-7B and 14B) can run easily on local laptops using Ollama, LM Studio, or vLLM.

Final Takeaway

DeepSeek-R1 is the indisputable winner for cost-sensitive developers, enterprise self-hosting, and mathematical/code reasoning pipelines ($0.55 input vs $15.00 on o1). OpenAI o1 remains compelling for users embedded in ChatGPT Plus and teams needing OpenAI's managed enterprise compliance guarantees.

Detailed In-Depth Analysis

Benchmark Deep Dive: AIME, MATH-500, and Codeforces

The benchmark comparisons between DeepSeek-R1 and OpenAI o1 highlight a historic milestone in AI engineering:

AIME 2024 Examination: DeepSeek-R1 achieves 79.8% Pass@1 on the 2024 American Invitational Mathematics Examination, surpassing OpenAI o1's 79.2%. When using consensus voting across 64 samples, R1 scales to 92.5%.
MATH-500: On the comprehensive 500-problem mathematical benchmark, DeepSeek-R1 reaches 97.3%, edging out OpenAI o1's 96.4%.
Competitive Programming (Codeforces): DeepSeek-R1 achieved a 2,029 ELO rating on Codeforces, placing it in the 96.3rd percentile of human competitive programmers globally.
SWE-Bench Verified: On automated software issue resolution, DeepSeek-R1 scores 49.2%, virtually tied with OpenAI o1's 48.9%.

Price Disruption & Open Source Impact

The most dramatic difference between the two models is economics:

OpenAI o1 API: Costs $15.00 per 1M input tokens and $60.00 per 1M output tokens.
DeepSeek-R1 API: Costs $0.55 per 1M input tokens and $2.19 per 1M output tokens, with cached prefix queries priced at just $0.14.
Self-Hosting: DeepSeek open-sourced the complete 671B model weights alongside distilled models (DeepSeek-R1-Distill-Qwen-1.5B, 7B, 14B, 32B, and Llama-70B), allowing organizations to run state-of-the-art reasoning locally on consumer and enterprise hardware.