Head-to-head comparison across 2benchmark categories. Overall scores shown here use BenchLM's provisional ranking lane.
DeepSeek V4 Flash
59
MiniMax M2.7
63
Verified leaderboard positions: DeepSeek V4 Flash #23 · MiniMax M2.7 unranked
Pick MiniMax M2.7 if you want the stronger benchmark profile. DeepSeek V4 Flash only becomes the better choice if coding is the priority or you want the cheaper token bill.
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 MiniMax M2.7 if you want the stronger benchmark profile. DeepSeek V4 Flash only becomes the better choice if coding is the priority or you want the cheaper token bill.
MiniMax M2.7 is clearly ahead on the provisional aggregate, 63 to 59. The gap is large enough that you do not need to squint at the spreadsheet to see the difference.
MiniMax M2.7's sharpest advantage is in agentic, where it averages 57 against 49.1. The single biggest benchmark swing on the page is Terminal-Bench 2.0, 49.1% to 57%. DeepSeek V4 Flash does hit back in coding, 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.
MiniMax M2.7 is ahead on BenchLM's provisional leaderboard, 63 to 59. 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, Terminal-Bench 2.0 is the benchmark that creates the most daylight between them.
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