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
86
Verified leaderboard positions: DeepSeek V4 Pro (Max) #5 · MiMo-V2.5-Pro unranked
Pick DeepSeek V4 Pro (Max) if you want the stronger benchmark profile. MiMo-V2.5-Pro only becomes the better choice if its workflow or ecosystem matters more than the raw scoreboard.
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 DeepSeek V4 Pro (Max) if you want the stronger benchmark profile. MiMo-V2.5-Pro 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 coding, where it averages 75.9 against 57.2. The single biggest benchmark swing on the page is HLE, 37.7% to 48%.
DeepSeek V4 Pro (Max) is ahead on BenchLM's provisional leaderboard, 87 to 86. 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, AA-Omniscience Hallucination Rate 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, Terminal-Bench Hard 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, APEX-Agents-AA is the benchmark that creates the most daylight between them.
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