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Kimi K2.5 (medium) vs Qwen3.5 Plus 2026-02-15

The average score is effectively tied at 6.4 vs 6.4. Qwen3.5 Plus 2026-02-15 has the lower benchmark cost at $0.173 vs $0.603. Qwen3.5 Plus 2026-02-15 is faster at 20.08s vs 125.76s, with pass rates of 60.9% vs 50.7%.

Last updated at: 2026-10-01

Compared models

Rank
#206
Total Output Tokens
241,096
Response Time (avg)
125.76s
Total Cost
$0.603
Rank
#203
Total Output Tokens
52,169
Response Time (avg)
20.08s
Total Cost
$0.173
Recommended model Qwen3.5 Plus 2026-02-15

It has the best score here (6.4), while costing about 3.5x less than Kimi K2.5 (medium).

Detailed comparison

Metric Kimi K2.5 Kimi K2.5 medium Release: 2026-01-27 Qwen3.5 Plus 2026-02-15 Qwen3.5 Plus 2026-02-15 none Release: 2026-02-15
Score 6.4 6.4
Rank #206 #203
Reliability 9.6 10.0
Consistency 7.1 9.4
Attempts 69/69 69/69
Tests Correct
Attempt pass rate 60.9% 50.7%
Flaky tests 8 2
Total Runs 69 69
Cost per result 6.085 1.571
Total Cost $0.603 $0.173
Input Price $0.450 / 1M $0.260 / 1M
Output Price $2.250 / 1M $1.560 / 1M
Total Input Tokens 292,271 341,703
Output Tokens 55,025 52,169
Reasoning Tokens 186,071 0
Response Time (avg) 125.76s 20.08s
Response Time (max) 566.79s 183.52s
Response Time (total) 2137.84s 341.29s
Parameters 1T total (32B active) ~397B total (~17B active)
Availability Weights available Closed

Model generation showcase

Hamster playing table tennis

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

#206 MoonshotAI: Kimi K2.5

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

#203 Qwen3.5 Plus 2026-02-15

none
Cost
$0.012
Time
153.2s
Tokens
7,787 tok

Top Models by Score

Score vs Total Cost

Response Time (avg)

Score vs Response Time (avg)

Total Output Tokens

Score vs Total Output Tokens

Category Breakdown

Coding Score Consistency Attempt pass rate Flaky tests Tests Correct Response Time (avg) Input Tokens Output Tokens Reasoning Tokens
Kimi K2.5 6.1 4.6 66.7% 2 217.49s 6,935 5,705 74,693
Qwen3.5 Plus 2026-02-15 4.3 7.9 11.1% 1 2.05s 7,913 473 0

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