Head-to-head comparison across 3benchmark categories. Overall scores shown here use BenchLM's provisional ranking lane.
DeepSeek V4 Pro (Max)
87
Kimi 2.6
86
Verified leaderboard positions: DeepSeek V4 Pro (Max) #2 · Kimi 2.6 #5
Pick DeepSeek V4 Pro (Max) if you want the stronger benchmark profile. Kimi 2.6 only becomes the better choice if its workflow or ecosystem matters more than the raw scoreboard.
Agentic
+0.9 difference
Coding
+3.9 difference
Knowledge
+12.3 difference
DeepSeek V4 Pro (Max)
Kimi 2.6
$1.74 / $3.48
$0.95 / $4
N/A
N/A
N/A
N/A
1M
256K
Pick DeepSeek V4 Pro (Max) if you want the stronger benchmark profile. Kimi 2.6 only becomes the better choice if its workflow or ecosystem matters more than the raw scoreboard.
DeepSeek V4 Pro (Max) finishes one point ahead on BenchLM's provisional leaderboard, 87 to 86. That is enough to call, but not enough to treat as a blowout. This matchup comes down to a few meaningful edges rather than one model dominating the board.
DeepSeek V4 Pro (Max)'s sharpest advantage is in knowledge, where it averages 66.1 against 53.8. The single biggest benchmark swing on the page is LiveCodeBench, 93.5% to 89.6%.
Kimi 2.6 is also the more expensive model on tokens at $0.95 input / $4.00 output per 1M tokens, versus $1.74 input / $3.48 output per 1M tokens for DeepSeek V4 Pro (Max). DeepSeek V4 Pro (Max) gives you the larger context window at 1M, compared with 256K for Kimi 2.6.
DeepSeek V4 Pro (Max) is ahead on BenchLM's provisional leaderboard, 87 to 86. The biggest single separator in this matchup is LiveCodeBench, where the scores are 93.5% and 89.6%.
DeepSeek V4 Pro (Max) has the edge for knowledge tasks in this comparison, averaging 66.1 versus 53.8. Inside this category, HLE is the benchmark that creates the most daylight between them.
DeepSeek V4 Pro (Max) has the edge for coding in this comparison, averaging 75.9 versus 72. Inside this category, Vibe Code Bench is the benchmark that creates the most daylight between them.
DeepSeek V4 Pro (Max) has the edge for agentic tasks in this comparison, averaging 74 versus 73.1. 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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