Head-to-head comparison across 4benchmark categories. Overall scores shown here use BenchLM's provisional ranking lane.
Kimi K2.5 (Reasoning)
79
Qwen3.5 397B
66
Verified leaderboard positions: Kimi K2.5 (Reasoning) unranked · Qwen3.5 397B #10
Pick Kimi K2.5 (Reasoning) if you want the stronger benchmark profile. Qwen3.5 397B only becomes the better choice if agentic is the priority or you would rather avoid the extra latency and token burn of a reasoning model.
Agentic
+1.6 difference
Coding
+16.5 difference
Knowledge
+22.1 difference
Multimodal
+0.5 difference
Kimi K2.5 (Reasoning)
Qwen3.5 397B
$null / $null
$0 / $0
N/A
96 t/s
N/A
2.44s
128K
128K
Pick Kimi K2.5 (Reasoning) if you want the stronger benchmark profile. Qwen3.5 397B only becomes the better choice if agentic is the priority or you would rather avoid the extra latency and token burn of a reasoning model.
Kimi K2.5 (Reasoning) is clearly ahead on the provisional aggregate, 79 to 66. 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 knowledge, where it averages 87.3 against 65.2. The single biggest benchmark swing on the page is Terminal-Bench 2.0, 50.8% to 52.5%. Qwen3.5 397B does hit back in agentic, 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 Qwen3.5 397B 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.
Kimi K2.5 (Reasoning) is ahead on BenchLM's provisional leaderboard, 79 to 66. The biggest single separator in this matchup is Terminal-Bench 2.0, where the scores are 50.8% and 52.5%.
Kimi K2.5 (Reasoning) has the edge for knowledge tasks in this comparison, averaging 87.3 versus 65.2. Inside this category, GPQA is the benchmark that creates the most daylight between them.
Kimi K2.5 (Reasoning) has the edge for coding in this comparison, averaging 76.8 versus 60.3. Inside this category, SWE-bench Verified is the benchmark that creates the most daylight between them.
Qwen3.5 397B has the edge for agentic tasks in this comparison, averaging 56.2 versus 54.6. Inside this category, Terminal-Bench 2.0 is the benchmark that creates the most daylight between them.
Qwen3.5 397B has the edge for multimodal and grounded tasks in this comparison, averaging 79 versus 78.5. Inside this category, MMMU-Pro is the benchmark that creates the most daylight between them.
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