Head-to-head comparison across 2benchmark categories. Overall scores shown here use BenchLM's provisional ranking lane.
MiniMax M2.7
62
Qwen3.5 397B
64
Verified leaderboard positions: MiniMax M2.7 unranked · Qwen3.5 397B #15
Pick Qwen3.5 397B if you want the stronger benchmark profile. MiniMax M2.7 only becomes the better choice if agentic is the priority or you want the cheaper token bill.
Agentic
+0.8 difference
Coding
+6.6 difference
MiniMax M2.7
Qwen3.5 397B
$0.3 / $1.2
$0.6 / $3.6
45 t/s
96 t/s
2.53s
2.44s
200K
128K
Pick Qwen3.5 397B if you want the stronger benchmark profile. MiniMax M2.7 only becomes the better choice if agentic is the priority or you want the cheaper token bill.
Qwen3.5 397B has the cleaner provisional overall profile here, landing at 64 versus 62. It is a real lead, but still close enough that category-level strengths matter more than the headline number.
Qwen3.5 397B's sharpest advantage is in coding, where it averages 60.3 against 53.7. The single biggest benchmark swing on the page is SWE-bench Pro, 56.2% to 50.9%. MiniMax M2.7 does hit back in agentic, so the answer changes if that is the part of the workload you care about most.
Qwen3.5 397B is also the more expensive model on tokens at $0.60 input / $3.60 output per 1M tokens, versus $0.30 input / $1.20 output per 1M tokens for MiniMax M2.7. That is roughly 3.0x on output cost alone. MiniMax M2.7 gives you the larger context window at 200K, compared with 128K for Qwen3.5 397B.
Qwen3.5 397B is ahead on BenchLM's provisional leaderboard, 64 to 62. The biggest single separator in this matchup is SWE-bench Pro, where the scores are 56.2% and 50.9%.
Qwen3.5 397B has the edge for coding in this comparison, averaging 60.3 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 56.2. Inside this category, Toolathlon is the benchmark that creates the most daylight between them.
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