Head-to-head comparison across 1benchmark categories. Overall scores shown here use BenchLM's provisional ranking lane.
Ling 2.6 Flash
44
MiMo-V2.5
74
Pick MiMo-V2.5 if you want the stronger benchmark profile. Ling 2.6 Flash only becomes the better choice if you want the cheaper token bill or you would rather avoid the extra latency and token burn of a reasoning model.
Coding
+29.1 difference
Ling 2.6 Flash
MiMo-V2.5
$0.1 / $0.3
$0.4 / $2
209.5 t/s
N/A
1.07s
N/A
262K
1M
Pick MiMo-V2.5 if you want the stronger benchmark profile. Ling 2.6 Flash only becomes the better choice if you want the cheaper token bill or you would rather avoid the extra latency and token burn of a reasoning model.
MiMo-V2.5 is clearly ahead on the provisional aggregate, 74 to 44. The gap is large enough that you do not need to squint at the spreadsheet to see the difference.
MiMo-V2.5's sharpest advantage is in coding, where it averages 56.1 against 27.
MiMo-V2.5 is also the more expensive model on tokens at $0.40 input / $2.00 output per 1M tokens, versus $0.10 input / $0.30 output per 1M tokens for Ling 2.6 Flash. That is roughly 6.7x on output cost alone. MiMo-V2.5 is the reasoning model in the pair, while Ling 2.6 Flash 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. MiMo-V2.5 gives you the larger context window at 1M, compared with 262K for Ling 2.6 Flash.
MiMo-V2.5 is ahead on BenchLM's provisional leaderboard, 74 to 44.
MiMo-V2.5 has the edge for coding in this comparison, averaging 56.1 versus 27. Ling 2.6 Flash stays close enough that the answer can still flip depending on your workload.
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