Head-to-head comparison across 3benchmark categories. Overall scores shown here use BenchLM's provisional ranking lane.
Claude Opus 4.7 (Adaptive)
90
MiMo-V2-Flash
61
Verified leaderboard positions: Claude Opus 4.7 (Adaptive) #5 · MiMo-V2-Flash unranked
Pick Claude Opus 4.7 (Adaptive) if you want the stronger benchmark profile. MiMo-V2-Flash only becomes the better choice if mathematics is the priority or you want the cheaper token bill.
Coding
+0.5 difference
Knowledge
+16.3 difference
Math
+50.3 difference
Claude Opus 4.7 (Adaptive)
MiMo-V2-Flash
$5 / $25
$0 / $0
N/A
129 t/s
N/A
2.14s
1M
256K
Pick Claude Opus 4.7 (Adaptive) if you want the stronger benchmark profile. MiMo-V2-Flash only becomes the better choice if mathematics is the priority or you want the cheaper token bill.
Claude Opus 4.7 (Adaptive) is clearly ahead on the provisional aggregate, 90 to 61. The gap is large enough that you do not need to squint at the spreadsheet to see the difference.
Claude Opus 4.7 (Adaptive) is also the more expensive model on tokens at $5.00 input / $25.00 output per 1M tokens, versus $0.00 input / $0.00 output per 1M tokens for MiMo-V2-Flash. That is roughly Infinityx on output cost alone. Claude Opus 4.7 (Adaptive) gives you the larger context window at 1M, compared with 256K for MiMo-V2-Flash.
Claude Opus 4.7 (Adaptive) is ahead on BenchLM's provisional leaderboard, 90 to 61. The biggest single separator in this matchup is SWE-bench Verified, where the scores are 87.6% and 73.4%.
MiMo-V2-Flash has the edge for knowledge tasks in this comparison, averaging 84.5 versus 68.2. Inside this category, GPQA is the benchmark that creates the most daylight between them.
MiMo-V2-Flash has the edge for coding in this comparison, averaging 73.4 versus 72.9. Inside this category, SWE-bench Verified is the benchmark that creates the most daylight between them.
MiMo-V2-Flash has the edge for math in this comparison, averaging 94.1 versus 43.8. Claude Opus 4.7 (Adaptive) stays close enough that the answer can still flip depending on your workload.
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