AI BENCHY
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#25

MiMo-V2.5-Pro

Xiaomi Release: 2026-04-22 Tested on: 2026-04-22 22:54 xiaomi/mimo-v2.5-pro::medium
1.02T total (42B active)MoEOpen source
(medium) (none)

Summary

MiMo-V2.5-Pro scores 8.1 on AI BENCHY and ranks #25. It has N/A reliability, a 75.9% pass rate, $0.201 total cost, and 16.17s average response time.

What makes MiMo-V2.5-Pro unique: Its total benchmark cost is unusually low for its score range.

Model facts

Researched on 2026-08-12

Reported
Parameters
1.02T total (42B active)
Architecture
MoE
Availability
Open source
License
MIT

Score

8.1

Consistency

8.8

Reliability

N/A

Total Output Tokens

55,306

Total Input Tokens

0

Input Price

$1.000 / 1M

Output Price

$3.000 / 1M

Tests Correct

Wrong Tests: 6

Attempt pass rate: 75.9%

Flaky tests

3

Flaky tests had mixed outcomes across runs (at least one pass and one fail).

Response Time (avg)

16.17s

Response Time (max): 84.22s

Response Time (total): 291.09s

Hamster playing table tennis

Prompt: Create a detailed SVG illustration of a hamster playing table tennis.

#25 MiMo-V2.5-Pro

medium
Reached the allocated time limit (300 seconds) without receiving showcase output.
Cost
$0.000
Time
300.0s
Tokens
0 tok

Run history

Tested on Score Reliability Tests Correct Total Cost Compare
2026-08-14 02:43 Re-test 6.8 10.0 $0.221 Compare
2026-07-16 22:50 New test added 6.9 10.0 $0.187 Compare
2026-06-04 13:52 New test added 7.5 10.0 $0.106 Compare
2026-05-08 15:28 Suite changed 8.1 10.0 $0.200 Compare
2026-04-22 22:54 First recorded run 8.1 N/A $0.201 Current run

Run comparison

RunBenchmark coverageScoreConsistencyReliabilityTests CorrectFlaky testsTotal Output TokensTotal Input TokensTotal CostResponse Time (avg)
2026-04-22 22:54 · First recorded run54/54 attempts8.18.8N/A12/18355,3060$0.20116.17s
2026-06-04 13:52 · New test added63/63 attempts7.58.510.012/214102,75740,854$0.10626.13s
Difference+0.6+0.30-1-47451-40854+$0.096-9954ms

Benchmark coverage differs: 54/54 attempts (Target: 3 repeats per test) versus 63/63 attempts (Target: 3 repeats per test). Totals and repeat-sensitive metrics are not directly comparable.

These two runs used different benchmark suites, so the deltas reflect both model changes and suite changes.

Charts

Choose the first model, then click a second model to open a side-by-side page.

Total Output Tokens

Score vs Total Output Tokens

Quick Compare

Category Breakdown

Category Score Consistency Tests Correct
Anti-AI Tricks 10.0 10.0
Coding 10.0 10.0
Combined 10.0 10.0
Data parsing and extraction 7.3 5.8
Domain specific 5.3 10.0
General Intelligence 5.1 3.3
Instructions following 9.9 10.0
Puzzle Solving 6.7 7.9
Tool Calling 10.0 10.0

Compared models