Head-to-head comparison across 1benchmark categories. Overall scores shown here use BenchLM's provisional ranking lane.
Claude Haiku 4.5
59
MiMo-V2.5
74
Pick MiMo-V2.5 if you want the stronger benchmark profile. Claude Haiku 4.5 only becomes the better choice if coding is the priority or you would rather avoid the extra latency and token burn of a reasoning model.
Coding
+17.2 difference
Claude Haiku 4.5
MiMo-V2.5
$1 / $5
$0.4 / $2
N/A
N/A
N/A
N/A
200K
1M
Pick MiMo-V2.5 if you want the stronger benchmark profile. Claude Haiku 4.5 only becomes the better choice if coding is the priority 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 59. The gap is large enough that you do not need to squint at the spreadsheet to see the difference.
Claude Haiku 4.5 is also the more expensive model on tokens at $1.00 input / $5.00 output per 1M tokens, versus $0.40 input / $2.00 output per 1M tokens for MiMo-V2.5. That is roughly 2.5x on output cost alone. MiMo-V2.5 is the reasoning model in the pair, while Claude Haiku 4.5 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 200K for Claude Haiku 4.5.
MiMo-V2.5 is ahead on BenchLM's provisional leaderboard, 74 to 59.
Claude Haiku 4.5 has the edge for coding in this comparison, averaging 73.3 versus 56.1. MiMo-V2.5 stays close enough that the answer can still flip depending on your workload.
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