Side-by-side benchmark comparison across agentic, coding, multimodal, knowledge, reasoning, and math workflows.
Seed-2.0-Lite is clearly ahead on the aggregate, 63 to 31. The gap is large enough that you do not need to squint at the spreadsheet to see the difference.
Seed-2.0-Lite's sharpest advantage is in multimodal & grounded, where it averages 79.6 against 30.4. The single biggest benchmark swing on the page is MMMU-Pro, 80 to 25.
Seed-2.0-Lite is also the more expensive model on tokens at $0.25 input / $2.00 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 Seed-2.0-Lite 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-Lite gives you the larger context window at 256K, compared with 128K for Ministral 3 3B (Reasoning).
Pick Seed-2.0-Lite 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.
Seed-2.0-Lite
55.1
Ministral 3 3B (Reasoning)
34
Seed-2.0-Lite
41.4
Ministral 3 3B (Reasoning)
7.2
Seed-2.0-Lite
79.6
Ministral 3 3B (Reasoning)
30.4
Seed-2.0-Lite
73
Ministral 3 3B (Reasoning)
35.3
Seed-2.0-Lite
53.9
Ministral 3 3B (Reasoning)
25.2
Seed-2.0-Lite
89
Ministral 3 3B (Reasoning)
68
Seed-2.0-Lite
82.5
Ministral 3 3B (Reasoning)
59.7
Seed-2.0-Lite
75
Ministral 3 3B (Reasoning)
40.9
Seed-2.0-Lite is ahead overall, 63 to 31. The biggest single separator in this matchup is MMMU-Pro, where the scores are 80 and 25.
Seed-2.0-Lite has the edge for knowledge tasks in this comparison, averaging 53.9 versus 25.2. Inside this category, MMLU is the benchmark that creates the most daylight between them.
Seed-2.0-Lite has the edge for coding in this comparison, averaging 41.4 versus 7.2. Inside this category, HumanEval is the benchmark that creates the most daylight between them.
Seed-2.0-Lite has the edge for math in this comparison, averaging 75 versus 40.9. Inside this category, AIME 2023 is the benchmark that creates the most daylight between them.
Seed-2.0-Lite has the edge for reasoning in this comparison, averaging 73 versus 35.3. Inside this category, SimpleQA is the benchmark that creates the most daylight between them.
Seed-2.0-Lite has the edge for agentic tasks in this comparison, averaging 55.1 versus 34. Inside this category, BrowseComp is the benchmark that creates the most daylight between them.
Seed-2.0-Lite has the edge for multimodal and grounded tasks in this comparison, averaging 79.6 versus 30.4. Inside this category, MMMU-Pro is the benchmark that creates the most daylight between them.
Seed-2.0-Lite has the edge for instruction following in this comparison, averaging 89 versus 68. Inside this category, IFEval is the benchmark that creates the most daylight between them.
Seed-2.0-Lite has the edge for multilingual tasks in this comparison, averaging 82.5 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.