Side-by-side benchmark comparison across agentic, coding, multimodal, knowledge, reasoning, and math workflows.
DeepSeek V3.2 (Thinking) is clearly ahead on the aggregate, 70 to 53. The gap is large enough that you do not need to squint at the spreadsheet to see the difference.
DeepSeek V3.2 (Thinking)'s sharpest advantage is in coding, where it averages 51.2 against 24.7. The single biggest benchmark swing on the page is SWE-bench Pro, 58 to 29. Seed-2.0-Mini does hit back in multimodal & grounded, so the answer changes if that is the part of the workload you care about most.
DeepSeek V3.2 (Thinking) is the reasoning model in the pair, while Seed-2.0-Mini 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. Seed-2.0-Mini gives you the larger context window at 256K, compared with 128K for DeepSeek V3.2 (Thinking).
Pick DeepSeek V3.2 (Thinking) if you want the stronger benchmark profile. Seed-2.0-Mini only becomes the better choice if multimodal & grounded is the priority or you need the larger 256K context window.
DeepSeek V3.2 (Thinking)
69.4
Seed-2.0-Mini
46.2
DeepSeek V3.2 (Thinking)
51.2
Seed-2.0-Mini
24.7
DeepSeek V3.2 (Thinking)
71
Seed-2.0-Mini
73.1
DeepSeek V3.2 (Thinking)
80.6
Seed-2.0-Mini
64.8
DeepSeek V3.2 (Thinking)
64.4
Seed-2.0-Mini
44.6
DeepSeek V3.2 (Thinking)
85
Seed-2.0-Mini
80
DeepSeek V3.2 (Thinking)
80.8
Seed-2.0-Mini
71.8
DeepSeek V3.2 (Thinking)
85.1
Seed-2.0-Mini
65.1
DeepSeek V3.2 (Thinking) is ahead overall, 70 to 53. The biggest single separator in this matchup is SWE-bench Pro, where the scores are 58 and 29.
DeepSeek V3.2 (Thinking) has the edge for knowledge tasks in this comparison, averaging 64.4 versus 44.6. Inside this category, MMLU is the benchmark that creates the most daylight between them.
DeepSeek V3.2 (Thinking) has the edge for coding in this comparison, averaging 51.2 versus 24.7. Inside this category, SWE-bench Pro is the benchmark that creates the most daylight between them.
DeepSeek V3.2 (Thinking) has the edge for math in this comparison, averaging 85.1 versus 65.1. Inside this category, AIME 2023 is the benchmark that creates the most daylight between them.
DeepSeek V3.2 (Thinking) has the edge for reasoning in this comparison, averaging 80.6 versus 64.8. Inside this category, SimpleQA is the benchmark that creates the most daylight between them.
DeepSeek V3.2 (Thinking) has the edge for agentic tasks in this comparison, averaging 69.4 versus 46.2. Inside this category, Terminal-Bench 2.0 is the benchmark that creates the most daylight between them.
Seed-2.0-Mini has the edge for multimodal and grounded tasks in this comparison, averaging 73.1 versus 71. Inside this category, MMMU-Pro is the benchmark that creates the most daylight between them.
DeepSeek V3.2 (Thinking) has the edge for instruction following in this comparison, averaging 85 versus 80. Inside this category, IFEval is the benchmark that creates the most daylight between them.
DeepSeek V3.2 (Thinking) has the edge for multilingual tasks in this comparison, averaging 80.8 versus 71.8. 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.