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uxwizz.com
#95

MiMo-V2.5

Xiaomi Release: 2026-04-22 Tested on: 2026-04-22 21:39 xiaomi/mimo-v2.5::none
310B total (15B active)MoEOpen source
(medium) (none)

Summary

MiMo-V2.5 scores 5.1 on AI BENCHY and ranks #95. It has N/A reliability, a 27.8% pass rate, $0.019 total cost, and 1.05s average response time.

What makes MiMo-V2.5 unique: It stands out most in Coding, where it ranks #1, while Anti-AI Tricks is its weakest area at #17. Its total benchmark cost is unusually low for its score range. It is notably fast compared with similar models.

Model facts

Researched on 2026-08-12

Reported
Parameters
310B total (15B active)
Architecture
MoE
Availability
Open source
License
MIT

Score

5.1

Consistency

10.0

Reliability

N/A

Total Output Tokens

2,177

Total Input Tokens

0

Input Price

$0.400 / 1M

Output Price

$2.000 / 1M

Tests Correct

Wrong Tests: 13

Attempt pass rate: 27.8%

Flaky tests

0

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

Response Time (avg)

1.05s

Response Time (max): 2.43s

Response Time (total): 18.94s

Hamster playing table tennis

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

#95 MiMo-V2.5

none
Cost
$0.007
Time
267.4s
Tokens
25,283 tok

Run history

Tested on Score Reliability Tests Correct Total Cost Compare
2026-08-14 02:25 Re-test 5.1 10.0 $0.025 Compare
2026-07-16 22:42 New test added 5.1 10.0 $0.025 Compare
2026-06-04 13:48 New test added 4.9 10.0 $0.007 Compare
2026-05-22 12:51 New test added 4.8 10.0 $0.021 Compare
2026-05-08 15:33 Suite changed 4.9 10.0 $0.019 Compare
2026-04-22 21:39 First recorded run 5.1 N/A $0.019 Current run

Run comparison

RunBenchmark coverageScoreConsistencyReliabilityTests CorrectFlaky testsTotal Output TokensTotal Input TokensTotal CostResponse Time (avg)
2026-04-22 21:39 · First recorded run54/54 attempts5.110.0N/A5/1802,1770$0.0191.05s
2026-06-04 13:48 · New test added63/63 attempts4.99.610.05/2112,26741,985$0.0072.20s
Difference+0.2+0.40-1-90-41985+$0.012-1148ms

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 4.8 10.0
Coding 10.0 10.0
Combined 3.0 10.0
Data parsing and extraction 6.5 10.0
Domain specific 3.0 10.0
General Intelligence 4.6 10.0
Instructions following 6.5 10.0
Puzzle Solving 3.4 10.0
Tool Calling 10.0 10.0

Compared models