DeepSeek-R1 is a 671B parameter Mixture-of-Experts (MoE) model with 37B activated parameters per token, trained via large-scale reinforcement learning with a focus on reasoning capabilities. It incorporates two RL stages for discovering improved reasoning patterns and aligning with human preferences, along with two SFT stages for seeding reasoning and non-reasoning capabilities. The model achieves performance comparable to OpenAI-o1 across math, code, and reasoning tasks.
OpenAI o4-mini is the newest lightweight model in the o-series, engineered for efficient and capable reasoning across text and visual tasks. Optimized for speed and performance, it excels in code generation and image-based understanding, while maintaining a balance between latency and reasoning depth. The model supports a 200,000-token context window with up to 100,000 output tokens, making it suitable for extended, high-volume interactions. It handles both text and image inputs, producing textual outputs with advanced reasoning capabilities. With its compact architecture and versatile performance, o4-mini is ideal for a wide array of real-world applications demanding fast, cost-effective intelligence.
| DeepSeek-R1 | o4-mini | |
|---|---|---|
Web Site
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Provider
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Chat
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Release Date
| ||
Modalities
| text | text images |
API Providers
| DeepSeek, HuggingFace | OpenAI API |
Knowledge Cut-off Date
| Unknown | - |
Open Source
| Yes | No |
Pricing Input
| $0.55 per million tokens | $1.10 per million tokens |
Pricing Output
| $2.19 per million tokens | $4.40 per million tokens |
MMLU
| 90.8% Pass@1 Source | fort |
MMLU-Pro
| 84% EM Source | - |
MMMU
| - | 81.6% Source |
HellaSwag
| - | - |
HumanEval
| - | 14.28% Source |
MATH
| - | - |
GPQA
| 71.5% Pass@1 Source | 81.4% Source |
IFEval
| 83.3% Prompt Strict Source | - |
SimpleQA
| - | - |
AIME 2024 | - | 93.4% Source |
AIME 2025 | - | 92.7% Source |
Aider Polyglot
| - | - |
LiveCodeBench v5
| - | - |
Global MMLU (Lite)
| - | - |
MathVista
| - | - |
Mobile Application |
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