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DeepSeek V4 Flash 0731 (medium) vs GLM 5.3 Flash (high)

The average score is effectively tied at 7.3 vs 7.3. GLM 5.3 Flash (high) has the lower benchmark cost at $0.029 vs $0.046. GLM 5.3 Flash (high) is faster at 25.36s vs 84.66s, with pass rates of 71.2% vs 66.7%.

Last updated at: 2026-08-26

Rank
#105
Total Output Tokens
550,855
Response Time (avg)
84.66s
Total Cost
$0.046
Rank
#102
Total Output Tokens
78,318
Response Time (avg)
25.36s
Total Cost
$0.029
Recommended model GLM 5.3 Flash (high)

It has the best score here (7.3), while costing about 1.6x less than DeepSeek V4 Flash 0731 (medium).

Detailed comparison

Metric DeepSeek V4 Flash 0731 DeepSeek V4 Flash 0731 medium Release: 2026-08-01 GLM 5.3 Flash GLM 5.3 Flash high Release: 2026-08-26
Score 7.3 7.3
Rank #105 #102
Reliability 10.0 10.0
Consistency 7.1 8.9
Attempts 66/66 66/66
Tests Correct
Attempt pass rate 71.2% 66.7%
Flaky tests 8 3
Total Runs 66 66
Cost per result 0.960 0.216
Total Cost $0.046 $0.029
Input Price $0.060 / 1M $0.075 / 1M
Output Price $0.120 / 1M $0.250 / 1M
Total Input Tokens 89,819 113,003
Output Tokens 58,398 11,558
Reasoning Tokens 492,457 66,760
Response Time (avg) 84.66s 25.36s
Response Time (max) 288.78s 163.41s
Response Time (total) 1862.46s 558.01s
Parameters 284B total (13B active) 320B total (18B active)
Availability Closed Open source

Model generation showcase

Hamster playing table tennis

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

#105 DeepSeek V4 Flash 0731

medium
Cost
$0.004
Time
93.3s
Tokens
13,252 tok

#102 GLM 5.3 Flash

high
Cost
$0.003
Time
186.7s
Tokens
10,486 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
DeepSeek V4 Flash 0731 6.4 4.4 77.8% 2 198.78s 6,032 4,109 160,154
GLM 5.3 Flash 8.2 7.2 88.9% 1 19.62s 7,317 373 9,973

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