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Qwen3.8 27B (medium) vs GLM 5.2 (high)

GLM 5.2 (high) leads on average score with 8.0 vs 7.8. Qwen3.8 27B (medium) has the lower benchmark cost at ~$0.058 vs $1.623. Qwen3.8 27B (medium) is faster at 33.05s vs 69.86s, with pass rates of 66.7% vs 69.7%.

Last updated at: 2026-09-29

Compared models

Rank
#109
Total Output Tokens
136,162
Response Time (avg)
33.05s
Total Cost
~$0.058
Rank
#94
Total Output Tokens
364,655
Response Time (avg)
69.86s
Total Cost
$1.623
Recommended model Qwen3.8 27B (medium)

Its score stays close to the best score here (7.8 vs 8.0), while costing about 28.4x less than GLM 5.2 (high).

Detailed comparison

Metric Qwen3.8 27B Qwen3.8 27B medium Release: 2026-08-14 GLM 5.2 GLM 5.2 high Release: 2026-06-17
Score 7.8 8.0
Rank #109 #94
Reliability 9.6 10.0
Consistency 9.7 8.6
Attempts 66/66 66/66
Tests Correct
Attempt pass rate 66.7% 69.7%
Flaky tests 1 3
Total Runs 66 66
Cost per result ~0.409 6.849
Total Cost ~$0.058 $1.623
Input Price N/A $0.234 / 1M
Output Price N/A $4.400 / 1M
Total Input Tokens 98,266 83,822
Output Tokens 1,861 72,040
Reasoning Tokens 134,301 292,615
Response Time (avg) 33.05s 69.86s
Response Time (max) 214.63s 599.43s
Response Time (total) 694.04s 1536.98s
Parameters 27.3B 744B total (40B active)
Availability Weights available Open source

Model generation showcase

Hamster playing table tennis

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

#109 Qwen3.8 27B

medium
Cost
~$0.002
Time
43.4s
Tokens
2,956 tok

#94 GLM 5.2

high
Reached the allocated time limit (300 seconds) without receiving showcase output.
Cost
$0.000
Time
300.0s
Tokens
0 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
Qwen3.8 27B 10.0 10.0 100.0% 0 40.50s 7,893 585 26,808
GLM 5.2 6.4 8.6 33.3% 0 73.03s 5,124 2,302 22,546

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