Side-by-side benchmark comparison across agentic, coding, multimodal, knowledge, reasoning, and math workflows.
Seed-2.0-Lite has the cleaner overall profile here, landing at 63 versus 61. It is a real lead, but still close enough that category-level strengths matter more than the headline number.
Seed-2.0-Lite's sharpest advantage is in instruction following, where it averages 89 against 83. The single biggest benchmark swing on the page is MRCRv2, 77 to 67. Mistral Large 3 does hit back in knowledge, so the answer changes if that is the part of the workload you care about most.
Mistral Large 3 is also the more expensive model on tokens at $2.00 input / $6.00 output per 1M tokens, versus $0.25 input / $2.00 output per 1M tokens for Seed-2.0-Lite. That is roughly 3.0x on output cost alone. Seed-2.0-Lite gives you the larger context window at 256K, compared with 128K for Mistral Large 3.
Pick Seed-2.0-Lite if you want the stronger benchmark profile. Mistral Large 3 only becomes the better choice if knowledge is the priority.
Seed-2.0-Lite
55.1
Mistral Large 3
52.5
Seed-2.0-Lite
41.4
Mistral Large 3
41
Seed-2.0-Lite
79.6
Mistral Large 3
75.5
Seed-2.0-Lite
73
Mistral Large 3
70.6
Seed-2.0-Lite
53.9
Mistral Large 3
57.1
Seed-2.0-Lite
89
Mistral Large 3
83
Seed-2.0-Lite
82.5
Mistral Large 3
78.8
Seed-2.0-Lite
75
Mistral Large 3
77.3
Seed-2.0-Lite is ahead overall, 63 to 61. The biggest single separator in this matchup is MRCRv2, where the scores are 77 and 67.
Mistral Large 3 has the edge for knowledge tasks in this comparison, averaging 57.1 versus 53.9. 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 41. Inside this category, HumanEval is the benchmark that creates the most daylight between them.
Mistral Large 3 has the edge for math in this comparison, averaging 77.3 versus 75. 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 70.6. Inside this category, MRCRv2 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 52.5. 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 75.5. 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 83. 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 78.8. 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.