Side-by-side benchmark comparison across agentic, coding, multimodal, knowledge, reasoning, and math workflows.
Kimi K2.5 (Reasoning) is clearly ahead on the aggregate, 76 to 63. The gap is large enough that you do not need to squint at the spreadsheet to see the difference.
Kimi K2.5 (Reasoning)'s sharpest advantage is in coding, where it averages 64.1 against 41.4. The single biggest benchmark swing on the page is SWE-bench Pro, 70 to 45. 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.
Kimi K2.5 (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 Kimi K2.5 (Reasoning).
Pick Kimi K2.5 (Reasoning) 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.
Kimi K2.5 (Reasoning)
73.1
Seed-2.0-Lite
55.1
Kimi K2.5 (Reasoning)
64.1
Seed-2.0-Lite
41.4
Kimi K2.5 (Reasoning)
74.3
Seed-2.0-Lite
79.6
Kimi K2.5 (Reasoning)
84.9
Seed-2.0-Lite
73
Kimi K2.5 (Reasoning)
69.7
Seed-2.0-Lite
53.9
Kimi K2.5 (Reasoning)
91
Seed-2.0-Lite
89
Kimi K2.5 (Reasoning)
86.7
Seed-2.0-Lite
82.5
Kimi K2.5 (Reasoning)
92.6
Seed-2.0-Lite
75
Kimi K2.5 (Reasoning) is ahead overall, 76 to 63. The biggest single separator in this matchup is SWE-bench Pro, where the scores are 70 and 45.
Kimi K2.5 (Reasoning) has the edge for knowledge tasks in this comparison, averaging 69.7 versus 53.9. Inside this category, MMLU is the benchmark that creates the most daylight between them.
Kimi K2.5 (Reasoning) has the edge for coding in this comparison, averaging 64.1 versus 41.4. Inside this category, SWE-bench Pro is the benchmark that creates the most daylight between them.
Kimi K2.5 (Reasoning) has the edge for math in this comparison, averaging 92.6 versus 75. Inside this category, AIME 2023 is the benchmark that creates the most daylight between them.
Kimi K2.5 (Reasoning) has the edge for reasoning in this comparison, averaging 84.9 versus 73. Inside this category, SimpleQA is the benchmark that creates the most daylight between them.
Kimi K2.5 (Reasoning) has the edge for agentic tasks in this comparison, averaging 73.1 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 74.3. Inside this category, MMMU-Pro is the benchmark that creates the most daylight between them.
Kimi K2.5 (Reasoning) has the edge for instruction following in this comparison, averaging 91 versus 89. Inside this category, IFEval is the benchmark that creates the most daylight between them.
Kimi K2.5 (Reasoning) has the edge for multilingual tasks in this comparison, averaging 86.7 versus 82.5. Inside this category, MMLU-ProX 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.