Head-to-head comparison across 3benchmark categories. Overall scores shown here use BenchLM's provisional ranking lane.
DeepSeek V4 Pro (Max)
87
MiMo-V2.5-Pro
88
Verified leaderboard positions: DeepSeek V4 Pro (Max) #2 · MiMo-V2.5-Pro unranked
Pick MiMo-V2.5-Pro if you want the stronger benchmark profile. DeepSeek V4 Pro (Max) only becomes the better choice if coding is the priority.
Agentic
+5.6 difference
Coding
+18.7 difference
Knowledge
+18.1 difference
DeepSeek V4 Pro (Max)
MiMo-V2.5-Pro
$1.74 / $3.48
$null / $null
N/A
N/A
N/A
N/A
1M
1M
Pick MiMo-V2.5-Pro if you want the stronger benchmark profile. DeepSeek V4 Pro (Max) only becomes the better choice if coding is the priority.
MiMo-V2.5-Pro finishes one point ahead on BenchLM's provisional leaderboard, 88 to 87. 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.
MiMo-V2.5-Pro is ahead on BenchLM's provisional leaderboard, 88 to 87. The biggest single separator in this matchup is HLE, where the scores are 37.7% and 48%.
DeepSeek V4 Pro (Max) has the edge for knowledge tasks in this comparison, averaging 66.1 versus 48. 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 57.2. Inside this category, SWE-bench Pro 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 68.4. Inside this category, GDPval-AA is the benchmark that creates the most daylight between them.
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