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uxwizz.com
#83

GLM 5 Turbo

Z.ai Release: 2026-03-15 Tested on: 2026-04-11 01:19 z-ai/glm-5-turbo::none
744B total (40B active)MoEClosed
(medium) (none)

Summary

GLM 5 Turbo scores 5.5 on AI BENCHY and ranks #83. It has N/A reliability, a 37.0% pass rate, $0.032 total cost, and 2.94s average response time.

What makes GLM 5 Turbo unique: Its total benchmark cost is unusually low for its score range. It is notably fast compared with similar models.

Archived model: this model is no longer updated or tested on new tests.

Model facts

Researched on 2026-08-12

Reported
Parameters
744B total (40B active)
Architecture
MoE
Availability
Closed
License
-

Family size is reported; exact API snapshot is closed.

Score

5.5

Consistency

9.2

Reliability

N/A

Total Output Tokens

1,775

Total Input Tokens

0

Input Price

$1.200 / 1M

Output Price

$4.000 / 1M

Tests Correct

Wrong Tests: 12

Attempt pass rate: 37.0%

Flaky tests

2

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

Response Time (avg)

2.94s

Response Time (max): 8.21s

Response Time (total): 52.98s

Hamster playing table tennis

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

#83 GLM 5 Turbo

none
Cost
$0.047
Time
129.2s
Tokens
11,775 tok

Run history

Tested on Score Reliability Tests Correct Total Cost Compare
2026-06-04 13:05 Re-test 5.1 10.0 $0.047 Compare
2026-06-04 13:05 Re-test 5.1 10.0 $0.047 Compare
2026-06-04 13:05 New test added 5.2 10.0 $0.047 Compare
2026-05-21 23:41 Suite changed 5.3 10.0 $0.037 Compare
2026-04-11 01:19 First recorded run 5.5 N/A $0.032 Current run

Run comparison

RunBenchmark coverageScoreConsistencyReliabilityTests CorrectFlaky testsTotal Output TokensTotal Input TokensTotal CostResponse Time (avg)
2026-04-11 01:19 · First recorded run54/54 attempts5.59.2N/A6/1821,7750$0.0322.94s
2026-05-21 23:41 · Suite changed60/60 attempts5.39.310.06/2021,8090$0.0372.83s
Difference+0.2-0.100-340-$0.006+114ms

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

Category Breakdown

Category Score Consistency Tests Correct
Anti-AI Tricks 3.0 10.0
Coding 5.3 3.4
Combined 3.0 10.0
Data parsing and extraction 10.0 10.0
Domain specific 5.3 10.0
General Intelligence 4.2 9.9
Instructions following 6.5 10.0
Puzzle Solving 5.5 7.4
Tool Calling 10.0 10.0

Compared models