Head-to-head comparison across 2benchmark categories. Overall scores shown here use BenchLM's provisional ranking lane.
DeepSeek V4 Flash (Max)
77
MiniMax M2.7
63
Verified leaderboard positions: DeepSeek V4 Flash (Max) #12 · MiniMax M2.7 unranked
Pick DeepSeek V4 Flash (Max) if you want the stronger benchmark profile. MiniMax M2.7 only becomes the better choice if you would rather avoid the extra latency and token burn of a reasoning model.
Agentic
+6.3 difference
Coding
+20.0 difference
DeepSeek V4 Flash (Max)
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 (Max) if you want the stronger benchmark profile. MiniMax M2.7 only becomes the better choice if you would rather avoid the extra latency and token burn of a reasoning model.
DeepSeek V4 Flash (Max) is clearly ahead on the provisional aggregate, 77 to 63. The gap is large enough that you do not need to squint at the spreadsheet to see the difference.
DeepSeek V4 Flash (Max)'s sharpest advantage is in coding, where it averages 73.7 against 53.7. The single biggest benchmark swing on the page is SWE-bench Pro, 52.6% to 56.2%.
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 (Max). That is roughly 4.3x on output cost alone. DeepSeek V4 Flash (Max) is the reasoning model in the pair, while MiniMax M2.7 is not. That usually helps on harder chain-of-thought-heavy tests, but it can also mean more latency and more token spend in real use. DeepSeek V4 Flash (Max) gives you the larger context window at 1M, compared with 200K for MiniMax M2.7.
DeepSeek V4 Flash (Max) is ahead on BenchLM's provisional leaderboard, 77 to 63. The biggest single separator in this matchup is SWE-bench Pro, where the scores are 52.6% and 56.2%.
DeepSeek V4 Flash (Max) has the edge for coding in this comparison, averaging 73.7 versus 53.7. Inside this category, SWE-bench Pro is the benchmark that creates the most daylight between them.
DeepSeek V4 Flash (Max) has the edge for agentic tasks in this comparison, averaging 63.3 versus 57. Inside this category, Toolathlon is the benchmark that creates the most daylight between them.
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