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uxwizz.com
#100

Qwen3 Coder Next

Qwen Release: 2026-02-03 Tested on: 2026-04-14 00:56 qwen/qwen3-coder-next::medium
80B total (3B active)MoEOpen source
(medium) (none)

Summary

Qwen3 Coder Next scores 4.7 on AI BENCHY and ranks #100. It has N/A reliability, a 27.8% pass rate, $0.008 total cost, and 10.75s average response time.

What makes Qwen3 Coder Next unique: It stands out most in Domain specific, where it ranks #2, while Anti-AI Tricks is its weakest area at #18. Its total benchmark cost is unusually low for its score range.

Model facts

Researched on 2026-08-12

Reported
Parameters
80B total (3B active)
Architecture
MoE
Availability
Open source
License
Apache-2.0

Score

4.7

Consistency

8.7

Reliability

N/A

Total Output Tokens

3,241

Total Input Tokens

0

Input Price

$0.150 / 1M

Output Price

$0.800 / 1M

Tests Correct

Wrong Tests: 15

Attempt pass rate: 27.8%

Flaky tests

3

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

Response Time (avg)

10.75s

Response Time (max): 81.80s

Response Time (total): 129.01s

Hamster playing table tennis

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

#100 Qwen3 Coder Next

medium
Invalid SVG
Cost
$0.000
Time
300.0s
Tokens
0 tok

Run history

Tested on Score Reliability Tests Correct Total Cost Compare
2026-08-14 01:38 Re-test 4.6 10.0 $0.034 Compare
2026-07-16 21:16 New test added 4.7 10.0 $0.032 Compare
2026-06-04 13:09 New test added 4.6 10.0 $0.008 Compare
2026-05-21 23:45 Suite changed 4.7 10.0 $0.008 Compare
2026-04-14 00:56 First recorded run 4.7 N/A $0.008 Current run

Run comparison

RunBenchmark coverageScoreConsistencyReliabilityTests CorrectFlaky testsTotal Output TokensTotal Input TokensTotal CostResponse Time (avg)
2026-04-14 00:56 · First recorded run54/54 attempts4.78.7N/A3/1833,2410$0.00810.75s
2026-06-04 13:09 · New test added63/63 attempts4.68.910.04/2133,31947,250$0.0088.58s
Difference+0.1-0.2-10-78-47250-$0.001+2171ms

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 3.5 8.1
Coding 4.7 1.6
Combined 3.0 10.0
Data parsing and extraction 6.5 10.0
Domain specific 5.3 10.0
General Intelligence 6.3 3.4
Instructions following 4.8 10.0
Puzzle Solving 3.1 10.0
Tool Calling 10.0 10.0

Compared models