Side-by-side benchmark comparison across agentic, coding, multimodal, knowledge, reasoning, and math workflows.
DeepSeek Coder 2.0 is clearly ahead on the aggregate, 66 to 31. 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 52.8 against 7.2. The single biggest benchmark swing on the page is HumanEval, 82 to 16.
DeepSeek Coder 2.0 is also the more expensive model on tokens at $0.27 input / $1.10 output per 1M tokens, versus $0.00 input / $0.00 output per 1M tokens for Ministral 3 3B (Reasoning). That is roughly Infinityx on output cost alone. Ministral 3 3B (Reasoning) 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.
Pick DeepSeek Coder 2.0 if you want the stronger benchmark profile. Ministral 3 3B (Reasoning) only becomes the better choice if you want the cheaper token bill or you want the stronger reasoning-first profile.
DeepSeek Coder 2.0
67.5
Ministral 3 3B (Reasoning)
34
DeepSeek Coder 2.0
52.8
Ministral 3 3B (Reasoning)
7.2
DeepSeek Coder 2.0
58.6
Ministral 3 3B (Reasoning)
30.4
DeepSeek Coder 2.0
75.5
Ministral 3 3B (Reasoning)
35.3
DeepSeek Coder 2.0
59.6
Ministral 3 3B (Reasoning)
25.2
DeepSeek Coder 2.0
86
Ministral 3 3B (Reasoning)
68
DeepSeek Coder 2.0
79.8
Ministral 3 3B (Reasoning)
59.7
DeepSeek Coder 2.0
80.5
Ministral 3 3B (Reasoning)
40.9
DeepSeek Coder 2.0 is ahead overall, 66 to 31. The biggest single separator in this matchup is HumanEval, where the scores are 82 and 16.
DeepSeek Coder 2.0 has the edge for knowledge tasks in this comparison, averaging 59.6 versus 25.2. 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 52.8 versus 7.2. Inside this category, HumanEval is the benchmark that creates the most daylight between them.
DeepSeek Coder 2.0 has the edge for math in this comparison, averaging 80.5 versus 40.9. Inside this category, AIME 2023 is the benchmark that creates the most daylight between them.
DeepSeek Coder 2.0 has the edge for reasoning in this comparison, averaging 75.5 versus 35.3. Inside this category, SimpleQA is the benchmark that creates the most daylight between them.
DeepSeek Coder 2.0 has the edge for agentic tasks in this comparison, averaging 67.5 versus 34. Inside this category, Terminal-Bench 2.0 is the benchmark that creates the most daylight between them.
DeepSeek Coder 2.0 has the edge for multimodal and grounded tasks in this comparison, averaging 58.6 versus 30.4. Inside this category, OfficeQA Pro is the benchmark that creates the most daylight between them.
DeepSeek Coder 2.0 has the edge for instruction following in this comparison, averaging 86 versus 68. Inside this category, IFEval is the benchmark that creates the most daylight between them.
DeepSeek Coder 2.0 has the edge for multilingual tasks in this comparison, averaging 79.8 versus 59.7. Inside this category, MGSM 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.