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#55

Qwen3.6 27B

Qwen Release: 2026-04-20 Tested on: 2026-04-27 21:48 qwen/qwen3.6-27b::medium
27BDenseOpen source
(medium) (none)

Summary

Qwen3.6 27B scores 7.0 on AI BENCHY and ranks #55. It has 10.0 reliability, a 64.8% pass rate, $0.209 total cost, and 50.53s average response time.

What makes Qwen3.6 27B unique: Its total benchmark cost is unusually low for its score range.

Model facts

Researched on 2026-08-12

Reported
Parameters
27B
Architecture
Dense
Availability
Open source
License
Apache-2.0

Score

7.0

Consistency

7.9

Total Output Tokens

99,362

Total Input Tokens

0

Input Price

$0.500 / 1M

Output Price

$2.000 / 1M

Tests Correct

Wrong Tests: 9

Attempt pass rate: 64.8%

Flaky tests

5

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

Response Time (avg)

50.53s

Response Time (max): 168.22s

Response Time (total): 909.49s

Hamster playing table tennis

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

#55 Qwen3.6 27B

medium
Cost
$0.009
Time
39.6s
Tokens
3,090 tok

Run history

Tested on Score Reliability Tests Correct Total Cost Compare
2026-08-14 01:41 Re-test 6.5 10.0 $1.045 Compare
2026-07-16 22:13 New test added 6.5 10.0 $0.779 Compare
2026-06-04 13:21 New test added 6.8 10.0 $0.444 Compare
2026-05-21 23:59 Suite changed 6.6 9.9 $0.272 Compare
2026-04-27 21:48 New test added 7.0 10.0 $0.209 Current run
2026-04-27 21:31 First recorded run 7.9 10.0 $0.043 Compare

This run used a different benchmark suite. Keep suite changes in mind when reading historical movement.

Run comparison

RunBenchmark coverageScoreConsistencyReliabilityTests CorrectFlaky testsTotal Output TokensTotal Input TokensTotal CostResponse Time (avg)
2026-04-27 21:48 · New test added54/54 attempts7.07.910.09/18599,3620$0.20950.53s
2026-05-21 23:59 · Suite changed60/60 attempts6.68.19.99/205118,7040$0.27257.65s
Difference+0.4-0.2+0.100-193420-$0.063-7125ms

Benchmark coverage differs: 54/54 attempts (Target: 3 repeats per test) versus 60/60 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 8.3 10.0
Coding 10.0 10.0
Combined 7.0 3.7
Data parsing and extraction 3.5 1.4
Domain specific 2.9 7.2
General Intelligence 6.5 3.4
Instructions following 10.0 10.0
Puzzle Solving 7.7 10.0
Tool Calling 10.0 10.0

Compared models