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#78

DeepSeek V4 Pro

DeepSeek Release: 2026-04-24 Tested on: 2026-04-29 14:46 deepseek/deepseek-v4-pro::none
(high) (none)

Summary

DeepSeek V4 Pro scores 6.2 on AI BENCHY and ranks #78. It has 7.9 reliability, a 48.2% pass rate, $0.043 total cost, and 14.01s average response time.

What makes DeepSeek V4 Pro unique: It stands out most in Domain specific, where it ranks #2, while Anti-AI Tricks is its weakest area at #17. Its total benchmark cost is unusually low for its score range.

Score

6.2

Consistency

8.7

Total Output Tokens

3,903

Total Input Tokens

0

Input Price

$0.435 / 1M

Output Price

$0.870 / 1M

Tests Correct

Wrong Tests: 11

Attempt pass rate: 48.2%

Flaky tests

3

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

Response Time (avg)

14.01s

Response Time (max): 58.65s

Response Time (total): 252.12s

Hamster playing table tennis

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

#78 DeepSeek V4 Pro

none
Invalid SVG
Cost
$0.000
Time
300.0s
Tokens
0 tok

Run history

Tested on Score Reliability Tests Correct Total Cost Compare
2026-07-16 23:18 New test added 6.9 10.0 $0.096 Compare
2026-06-16 15:17 Re-test 7.2 9.9 $0.034 Compare
2026-06-16 14:39 Suite changed 7.2 9.9 $0.030 Compare
2026-06-04 14:24 New test added 5.7 8.5 $0.025 Compare
2026-05-22 00:38 Suite changed 6.0 8.1 $0.046 Compare
2026-04-29 14:46 Re-test 6.2 7.9 $0.043 Current run
2026-04-24 09:19 Initial run 3.1 N/A $0.009 Compare

Run comparison

RunScoreConsistencyReliabilityTests CorrectFlaky testsTotal Output TokensTotal Input TokensTotal CostResponse Time (avg)
2026-04-29 14:46 · Re-test6.28.77.97/1833,9030$0.04314.01s
2026-04-24 09:19 · Initial run3.17.2N/A0/1865910$0.00944.40s
Difference+3.1+1.5+7-3+33120+$0.034-30391ms

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 8.0
Coding 7.1 3.7
Combined 9.5 10.0
Data parsing and extraction 10.0 10.0
Domain specific 5.3 10.0
General Intelligence 4.3 9.9
Instructions following 6.3 10.0
Puzzle Solving 6.0 7.1
Tool Calling 10.0 10.0

Compared models