Head-to-head comparison across 3benchmark categories. Overall scores shown here use BenchLM's provisional ranking lane.
DeepSeek V4 Pro (High)
83
Kimi K2.5
64
Verified leaderboard positions: DeepSeek V4 Pro (High) #6 · Kimi K2.5 #11
Pick DeepSeek V4 Pro (High) if you want the stronger benchmark profile. Kimi K2.5 only becomes the better choice if knowledge is the priority or you want the cheaper token bill.
Agentic
+15.4 difference
Coding
+9.6 difference
Knowledge
+2.5 difference
DeepSeek V4 Pro (High)
Kimi K2.5
$1.74 / $3.48
$0.6 / $3
N/A
45 t/s
N/A
2.38s
1M
256K
Pick DeepSeek V4 Pro (High) if you want the stronger benchmark profile. Kimi K2.5 only becomes the better choice if knowledge is the priority or you want the cheaper token bill.
DeepSeek V4 Pro (High) is clearly ahead on the provisional aggregate, 83 to 64. The gap is large enough that you do not need to squint at the spreadsheet to see the difference.
DeepSeek V4 Pro (High)'s sharpest advantage is in agentic, where it averages 70 against 54.6. The single biggest benchmark swing on the page is BrowseComp, 80.4% to 60.6%. Kimi K2.5 does hit back in knowledge, so the answer changes if that is the part of the workload you care about most.
DeepSeek V4 Pro (High) is also the more expensive model on tokens at $1.74 input / $3.48 output per 1M tokens, versus $0.60 input / $3.00 output per 1M tokens for Kimi K2.5. DeepSeek V4 Pro (High) is the reasoning model in the pair, while Kimi K2.5 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. DeepSeek V4 Pro (High) gives you the larger context window at 1M, compared with 256K for Kimi K2.5.
DeepSeek V4 Pro (High) is ahead on BenchLM's provisional leaderboard, 83 to 64. The biggest single separator in this matchup is BrowseComp, where the scores are 80.4% and 60.6%.
Kimi K2.5 has the edge for knowledge tasks in this comparison, averaging 65.1 versus 62.6. Inside this category, HLE is the benchmark that creates the most daylight between them.
DeepSeek V4 Pro (High) has the edge for coding in this comparison, averaging 73.8 versus 64.2. Inside this category, LiveCodeBench is the benchmark that creates the most daylight between them.
DeepSeek V4 Pro (High) has the edge for agentic tasks in this comparison, averaging 70 versus 54.6. Inside this category, MCP Atlas is the benchmark that creates the most daylight between them.
Estimates at 50,000 req/day · 1000 tokens/req average.
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