Head-to-head comparison across 2benchmark categories. Overall scores shown here use BenchLM's provisional ranking lane.
DeepSeek V3
36
Kimi K2.5 (Reasoning)
76
Pick Kimi K2.5 (Reasoning) if you want the stronger benchmark profile. DeepSeek V3 only becomes the better choice if you want the cheaper token bill or you would rather avoid the extra latency and token burn of a reasoning model.
Coding
+37.6 difference
Knowledge
+17.3 difference
DeepSeek V3
Kimi K2.5 (Reasoning)
$0.27 / $1.1
$0.6 / $3
N/A
N/A
N/A
N/A
128K
128K
Pick Kimi K2.5 (Reasoning) if you want the stronger benchmark profile. DeepSeek V3 only becomes the better choice if you want the cheaper token bill 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, 76 to 36. 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 76.8 against 39.2. The single biggest benchmark swing on the page is SWE-bench Verified, 42% to 76.8%.
Kimi K2.5 (Reasoning) is also the more expensive model on tokens at $0.60 input / $3.00 output per 1M tokens, versus $0.27 input / $1.10 output per 1M tokens for DeepSeek V3. That is roughly 2.7x on output cost alone. Kimi K2.5 (Reasoning) is the reasoning model in the pair, while DeepSeek V3 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, 76 to 36. The biggest single separator in this matchup is SWE-bench Verified, where the scores are 42% and 76.8%.
Kimi K2.5 (Reasoning) has the edge for knowledge tasks in this comparison, averaging 87.3 versus 70. 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 39.2. Inside this category, SWE-bench Verified is the benchmark that creates the most daylight between them.
Estimates at 50,000 req/day · 1000 tokens/req average.
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