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#51

Kimi K2.5

Moonshot AI Release: 2026-01-27 Tested on: 2026-04-20 17:48 moonshotai/kimi-k2.5::medium
1T total (32B active)MoEWeights available
(medium) (none)

Summary

Kimi K2.5 scores 7.0 on AI BENCHY and ranks #51. It has N/A reliability, a 72.2% pass rate, $0.220 total cost, and 72.43s average response time.

What makes Kimi K2.5 unique: It stands out most in Combined, where it ranks #1, while Coding is its weakest area at #18.

Model facts

Researched on 2026-08-12

Reported
Parameters
1T total (32B active)
Architecture
MoE
Availability
Weights available
License
Modified MIT

Score

7.0

Consistency

6.8

Reliability

N/A

Total Output Tokens

127,046

Total Input Tokens

0

Input Price

$0.440 / 1M

Output Price

$2.000 / 1M

Tests Correct

Wrong Tests: 9

Attempt pass rate: 72.2%

Flaky tests

7

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

Response Time (avg)

72.43s

Response Time (max): 150.77s

Response Time (total): 796.70s

Hamster playing table tennis

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

#51 MoonshotAI: Kimi K2.5

medium
Cost
$0.030
Time
58.6s
Tokens
8,683 tok

Run history

Tested on Score Reliability Tests Correct Total Cost Compare
2026-08-14 02:00 Re-test 7.0 10.0 $0.607 Compare
2026-07-16 22:17 New test added 7.0 10.0 $0.600 Compare
2026-06-04 13:43 New test added 6.8 10.0 $0.328 Compare
2026-05-22 00:12 Suite changed 6.7 10.0 $0.314 Compare
2026-04-20 17:48 First recorded run 7.0 N/A $0.220 Current run

Run comparison

RunBenchmark coverageScoreConsistencyReliabilityTests CorrectFlaky testsTotal Output TokensTotal Input TokensTotal CostResponse Time (avg)
2026-04-20 17:48 · First recorded run54/54 attempts7.06.8N/A9/187127,0460$0.22072.43s
2026-08-14 02:00 · Re-test66/66 attempts7.07.010.010/228220,942118,496$0.60798.19s
Difference0.0-0.2-1-1-93896-118496-$0.387-25763ms

Benchmark coverage differs: 54/54 attempts (Target: 3 repeats per test) versus 66/66 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 7.3 5.8
Coding 4.7 1.6
Combined 10.0 10.0
Data parsing and extraction 10.0 10.0
Domain specific 3.5 4.4
General Intelligence 6.5 3.4
Instructions following 10.0 10.0
Puzzle Solving 5.3 7.3
Tool Calling 10.0 10.0

Compared models