Head-to-head comparison across 2benchmark categories. Overall scores shown here use BenchLM's provisional ranking lane.
DeepSeek V4 Flash
57
MiniMax M2.7
54
Verified leaderboard positions: DeepSeek V4 Flash #30 · MiniMax M2.7 unranked
Pick DeepSeek V4 Flash if you want the stronger benchmark profile. MiniMax M2.7 only becomes the better choice if agentic is the priority.
Agentic
+7.9 difference
Coding
+3.4 difference
DeepSeek V4 Flash
MiniMax M2.7
$0.14 / $0.28
$0.3 / $1.2
N/A
45 t/s
N/A
2.53s
1M
200K
Pick DeepSeek V4 Flash if you want the stronger benchmark profile. MiniMax M2.7 only becomes the better choice if agentic is the priority.
DeepSeek V4 Flash has the cleaner provisional overall profile here, landing at 57 versus 54. It is a real lead, but still close enough that category-level strengths matter more than the headline number.
DeepSeek V4 Flash's sharpest advantage is in coding, where it averages 57.1 against 53.7. The single biggest benchmark swing on the page is Terminal-Bench 2.0, 49.1% to 57%. MiniMax M2.7 does hit back in agentic, so the answer changes if that is the part of the workload you care about most.
MiniMax M2.7 is also the more expensive model on tokens at $0.30 input / $1.20 output per 1M tokens, versus $0.14 input / $0.28 output per 1M tokens for DeepSeek V4 Flash. That is roughly 4.3x on output cost alone. DeepSeek V4 Flash gives you the larger context window at 1M, compared with 200K for MiniMax M2.7.
DeepSeek V4 Flash is ahead on BenchLM's provisional leaderboard, 57 to 54. The biggest single separator in this matchup is Terminal-Bench 2.0, where the scores are 49.1% and 57%.
DeepSeek V4 Flash has the edge for coding in this comparison, averaging 57.1 versus 53.7. Inside this category, SWE-bench Pro is the benchmark that creates the most daylight between them.
MiniMax M2.7 has the edge for agentic tasks in this comparison, averaging 57 versus 49.1. Inside this category, Gert Labs is the benchmark that creates the most daylight between them.
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