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DeepSeek V4 Flash 0423 (high) vs GLM 5 (medium)

GLM 5 (medium) leads on average score with 7.7 vs 7.6. DeepSeek V4 Flash 0423 (high) has the lower benchmark cost at $0.039 vs $0.228. GLM 5 (medium) is faster at 33.54s vs 51.81s, with pass rates of 69.7% vs 78.8%.

Last updated at: 2026-09-08

Compared models

Rank
#92
Total Output Tokens
211,310
Response Time (avg)
51.81s
Total Cost
$0.039
Rank
#88
Total Output Tokens
124,566
Response Time (avg)
33.54s
Total Cost
$0.228
Recommended model DeepSeek V4 Flash 0423 (high)

Its score stays close to the best score here (7.6 vs 7.7), while costing about 5.9x less than GLM 5 (medium).

Detailed comparison

Metric DeepSeek V4 Flash 0423 DeepSeek V4 Flash 0423 high Release: 2026-04-24 GLM 5 GLM 5 medium Release: 2026-02-12
Score 7.6 7.7
Rank #92 #88
Reliability 10.0 10.0
Consistency 8.5 8.1
Attempts 66/66 63/66
Tests Correct
Attempt pass rate 69.7% 78.8%
Flaky tests 4 4
Total Runs 66 63
Cost per result 0.446 1.668
Total Cost $0.039 $0.228
Input Price $0.083 / 1M $0.600 / 1M
Output Price $0.165 / 1M $1.920 / 1M
Total Input Tokens 108,480 35,224
Output Tokens 37,229 21,570
Reasoning Tokens 174,081 102,996
Response Time (avg) 51.81s 33.54s
Response Time (max) 218.13s 99.85s
Response Time (total) 1139.75s 435.99s
Parameters 284B total (13B active) 744B total (40B active)
Availability Open source Open source

Model generation showcase

Hamster playing table tennis

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

#92 DeepSeek V4 Flash 0423

high
Cost
$0.003
Time
93.1s
Tokens
7,926 tok

#88 GLM 5

medium
Cost
$0.005
Time
20.7s
Tokens
2,068 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 0423 7.8 10.0 66.7% 0 50.60s 7,279 395 34,862
GLM 5 10.0 10.0 100.0% 0 74.30s 7,254 2,997 52,930

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