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uxwizz.com
#27

Qwen3.7 Max

Qwen Release: 2026-05-22 Tested on: 2026-05-21 23:54 qwen/qwen3.7-max::none
~1T total (~40B active)MoEClosedEstimated
(medium) (none)

Summary

Qwen3.7 Max scores 7.9 on AI BENCHY and ranks #27. It has 10.0 reliability, a 70.0% pass rate, $0.101 total cost, and 1.30s average response time.

What makes Qwen3.7 Max unique: It stands out most in Domain specific, where it ranks #1, while Anti-AI Tricks is its weakest area at #18. 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

Estimated
Parameters
~1T total (~40B active)
Architecture
MoE
Availability
Closed
License
-

Best estimate from public evidence; the vendor did not disclose every value. Vendor does not disclose the count.

Score

7.9

Consistency

10.0

Total Output Tokens

1,988

Total Input Tokens

0

Input Price

$2.500 / 1M

Output Price

$7.500 / 1M

Tests Correct

Wrong Tests: 6

Attempt pass rate: 70.0%

Flaky tests

0

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

Response Time (avg)

1.30s

Response Time (max): 3.92s

Response Time (total): 25.95s

Hamster playing table tennis

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

#27 Qwen3.7 Max

none
Cost
$0.046
Time
195.0s
Tokens
12,171 tok

Run history

Tested on Score Reliability Tests Correct Total Cost Compare
2026-08-14 01:44 Re-test 7.4 9.9 $0.197 Compare
2026-07-16 21:33 New test added 7.4 9.9 $0.197 Compare
2026-06-04 13:21 New test added 7.7 10.0 $0.054 Compare
2026-05-21 23:54 Initial run 7.9 10.0 $0.101 Current run

Run comparison

RunBenchmark coverageScoreConsistencyReliabilityTests CorrectFlaky testsTotal Output TokensTotal Input TokensTotal CostResponse Time (avg)
2026-05-21 23:54 · Initial run60/60 attempts7.910.010.014/2001,9880$0.1011.30s
2026-08-14 01:44 · Re-test66/66 attempts7.410.09.915/22012,44695,992$0.1974.56s
Difference+0.50.0+0.1-10-10458-95992-$0.097-3261ms

Benchmark coverage differs: 60/60 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 6.5 10.0
Coding 6.8 10.0
Combined 3.0 10.0
Data parsing and extraction 10.0 10.0
Domain specific 7.7 10.0
General Intelligence 10.0 10.0
Instructions following 10.0 10.0
Puzzle Solving 10.0 10.0
Tool Calling 10.0 10.0
Trivia 3.0 10.0

Compared models