Side-by-side benchmark comparison across agentic, coding, multimodal, knowledge, reasoning, and math workflows.
Mercury 2 has the cleaner overall profile here, landing at 65 versus 63. It is a real lead, but still close enough that category-level strengths matter more than the headline number.
Mercury 2's sharpest advantage is in agentic, where it averages 63.7 against 55.1. The single biggest benchmark swing on the page is MuSR, 82 to 66. Seed-2.0-Lite does hit back in multimodal & grounded, so the answer changes if that is the part of the workload you care about most.
Seed-2.0-Lite is also the more expensive model on tokens at $0.25 input / $2.00 output per 1M tokens, versus $0.25 input / $0.75 output per 1M tokens for Mercury 2. That is roughly 2.7x on output cost alone. Mercury 2 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 Mercury 2.
Pick Mercury 2 if you want the stronger benchmark profile. Seed-2.0-Lite only becomes the better choice if multimodal & grounded is the priority or you need the larger 256K context window.
Mercury 2
63.7
Seed-2.0-Lite
55.1
Mercury 2
41.1
Seed-2.0-Lite
41.4
Mercury 2
68.3
Seed-2.0-Lite
79.6
Mercury 2
80.1
Seed-2.0-Lite
73
Mercury 2
57.2
Seed-2.0-Lite
53.9
Mercury 2
84
Seed-2.0-Lite
89
Mercury 2
79.7
Seed-2.0-Lite
82.5
Mercury 2
80.9
Seed-2.0-Lite
75
Mercury 2 is ahead overall, 65 to 63. The biggest single separator in this matchup is MuSR, where the scores are 82 and 66.
Mercury 2 has the edge for knowledge tasks in this comparison, averaging 57.2 versus 53.9. Inside this category, GPQA 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 41.1. Inside this category, HumanEval is the benchmark that creates the most daylight between them.
Mercury 2 has the edge for math in this comparison, averaging 80.9 versus 75. Inside this category, AIME 2023 is the benchmark that creates the most daylight between them.
Mercury 2 has the edge for reasoning in this comparison, averaging 80.1 versus 73. Inside this category, MuSR is the benchmark that creates the most daylight between them.
Mercury 2 has the edge for agentic tasks in this comparison, averaging 63.7 versus 55.1. Inside this category, Terminal-Bench 2.0 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 68.3. 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 84. 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 79.7. Inside this category, MGSM is the benchmark that creates the most daylight between them.
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