Side-by-side benchmark comparison across knowledge, coding, math, and reasoning.
DeepSeek Coder 2.0 is clearly ahead on the aggregate, 73 to 56. The gap is large enough that you do not need to squint at the spreadsheet to see the difference.
DeepSeek Coder 2.0's sharpest advantage is in coding, where it averages 59.3 against 49.3. The single biggest benchmark swing on the page is IFEval, 86 to 93.9. o3-mini does hit back in knowledge, so the answer changes if that is the part of the workload you care about most.
o3-mini is also the more expensive model on tokens at $1.10 input / $4.40 output per 1M tokens, versus $0.27 input / $1.10 output per 1M tokens for DeepSeek Coder 2.0. That is roughly 4.0x on output cost alone. o3-mini is the reasoning model in the pair, while DeepSeek Coder 2.0 is not. That usually helps on harder chain-of-thought-heavy tests, but it can also mean more latency and more token spend in real use. o3-mini gives you the larger context window at 200K, compared with 128K for DeepSeek Coder 2.0.
Pick DeepSeek Coder 2.0 if you want the stronger benchmark profile. o3-mini only becomes the better choice if knowledge is the priority or you need the larger 200K context window.
DeepSeek Coder 2.0
66.3
o3-mini
82.1
DeepSeek Coder 2.0
59.3
o3-mini
49.3
DeepSeek Coder 2.0
80.1
o3-mini
87.3
DeepSeek Coder 2.0
86
o3-mini
93.9
DeepSeek Coder 2.0 is ahead overall, 73 to 56. The biggest single separator in this matchup is IFEval, where the scores are 86 and 93.9.
o3-mini has the edge for knowledge tasks in this comparison, averaging 82.1 versus 66.3. Inside this category, MMLU is the benchmark that creates the most daylight between them.
DeepSeek Coder 2.0 has the edge for coding in this comparison, averaging 59.3 versus 49.3. Inside this category, SWE-bench Verified is the benchmark that creates the most daylight between them.
o3-mini has the edge for math in this comparison, averaging 87.3 versus 80.1. Inside this category, AIME 2024 is the benchmark that creates the most daylight between them.
o3-mini has the edge for instruction following in this comparison, averaging 93.9 versus 86. Inside this category, IFEval is the benchmark that creates the most daylight between them.
Get notified when new models drop, benchmark scores change, or the leaderboard shifts. One email per week.
Free. No spam. Unsubscribe anytime. We only store derived location metadata for consent routing.