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 48. 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 44.7. The single biggest benchmark swing on the page is MMMU-Pro, 80 to 37.
Nemotron Ultra 253B 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 32K for Nemotron Ultra 253B.
Pick Seed-2.0-Lite if you want the stronger benchmark profile. Nemotron Ultra 253B only becomes the better choice if you want the stronger reasoning-first profile.
Seed-2.0-Lite
55.1
Nemotron Ultra 253B
46.7
Seed-2.0-Lite
41.4
Nemotron Ultra 253B
33.7
Seed-2.0-Lite
79.6
Nemotron Ultra 253B
44.7
Seed-2.0-Lite
73
Nemotron Ultra 253B
53.3
Seed-2.0-Lite
53.9
Nemotron Ultra 253B
42.4
Seed-2.0-Lite
89
Nemotron Ultra 253B
78
Seed-2.0-Lite
82.5
Nemotron Ultra 253B
70.1
Seed-2.0-Lite
75
Nemotron Ultra 253B
59.7
Seed-2.0-Lite is ahead overall, 63 to 48. The biggest single separator in this matchup is MMMU-Pro, where the scores are 80 and 37.
Seed-2.0-Lite has the edge for knowledge tasks in this comparison, averaging 53.9 versus 42.4. 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 33.7. 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 59.7. 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 53.3. 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 46.7. 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 44.7. 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 78. 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 70.1. 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.