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DeepSeek-R1-Distill-Qwen-32B vs OpenAI o3-mini

Rows highlighted in warm gray are where the models differ. Numbers carry their as-of date and primary source.

Specs

Field A: DeepSeek-R1-Distill-Qwen-32B B: OpenAI o3-mini
Released 2025-01-202025-01-31
Developer DeepSeekOpenAI
Openness OpenProprietary
License MITProprietary
OSI-approved yesno
Data released nono
Training code nono
Architecture denseunknown
Total params 32B
Active params
Experts
Context window 128K200K
Attention gqaunknown
Position enc. ropeunknown
Pretraining tokens
Post-training sftrlhf
Training hardware
$/M input $0.00$1.10
$/M output $0.00$4.40
Output tok/sec 0145.3

Benchmarks

Missing scores render as not reported; never inferred. Bold highlights the leader per benchmark.

General reasoning

MMLU-Pro 73.9 2026-05-21 79.1 2026-05-21
GPQA-Diamond 62.1 2025-01-22 79.7 2025-01-31

Code

SWE-Bench Verified 49.3 2025-01-31
LiveCodeBench 57.2 2025-01-22 71.7 2026-05-21

Math

MATH 94.1 2026-05-21 97.3 2026-05-21
AIME 2024 72.6 2025-01-22 87.3 2025-01-31
AIME 2025 63.0 2026-05-21

Context · A

Dense Qwen2.5-32B base supervised-fine-tuned on reasoning traces sampled from DeepSeek-R1. The sweet-spot distill of the series: small enough to run on a single high-memory GPU, and reported by DeepSeek as outperforming OpenAI o1-mini on AIME 2024 and MATH-500.

Context · B

Released January 31, 2025 as a smaller, faster o-series reasoning model with three selectable effort levels (low, medium, high). Positioned by OpenAI as a specialized alternative to o1 for technical domains requiring precision and speed at a fraction of o1's cost.

DeepSeek-R1-Distill-Qwen-32B detail → · OpenAI o3-mini detail →