This comparison highlights the key differences between o3-mini and DeepSeek-R1 in terms of performance benchmarks and model features.DeepSeek-R1 shows better performance in some coding and math tasks
Benchmark Comparison
Benchmark | o3-mini | DeepSeek-R1 |
---|---|---|
Codeforces (Competitive Programming Platform) | 1997 | 2029 |
AIME 2024 (American Invitational Mathematics Examination) | 78.2% | 79.8% |
GPQA (General-Purpose Question Answering) | 74.9% | 71.5% |
MMLU (Massive Multitask Language Understanding) | Not available | 90.8% |
MMLU-Pro (Massive Multitask Language Understanding - Pro Version) | Not available | 84% |
IFEval (Instruction-Following Evaluation) | Not available | 83.3% |
Key Features Comparison
Feature | o3-mini | DeepSeek-R1 |
---|---|---|
Architecture | Not specified | Mixture of Experts (MoE) |
Total Parameters | Not specified | 671 billion |
Active Parameters | Not specified | 37 billion per forward pass |
Training Approach | Reinforcement learning, Deliberative alignment | Multi-stage training with RL and SFT |
Reasoning Levels | Low, medium, high | Not specified |
Chain of Thought | Yes | Yes |
Input Context Window | 200K tokens | 128K tokens |
Maximum Output | 100K tokens | 32K tokens |
Function Calling | Yes | Not specified |
Structured Outputs | Yes | Not specified |
Developer Messages | Supported | Not specified |
Safety Approach | Deliberative alignment | Not specified |
Open Source | No | Yes |
Customization | Not specified | Supports fine-tuning |
Deployment Options | ChatGPT, API | API, mobile app, cloud services |
Unsafe Response Rate | 1.19% | 11.98% |
Release Date | January 31, 2025. | January 21, 2025 |
This expanded comparison highlights the different approaches and features of o3-mini and DeepSeek-R1, showcasing their unique architectures, training methodologies, and capabilities.
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