AI BENCHY
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#69

DeepSeek V3.2

DeepSeek Release: 2025-12-01 Tested on: 2026-04-20 17:48 deepseek/deepseek-v3.2::none
671B total (37B active)MoEOpen source
(medium) (none)

Summary

DeepSeek V3.2 scores 6.1 on AI BENCHY and ranks #69. It has N/A reliability, a 50.0% pass rate, $0.016 total cost, and 12.09s average response time.

What makes DeepSeek V3.2 unique: Its total benchmark cost is unusually low for its score range.

Model facts

Researched on 2026-08-12

Reported
Parameters
671B total (37B active)
Architecture
MoE
Availability
Open source
License
MIT
Parameter source Availability source

Score

6.1

Consistency

8.1

Reliability

N/A

Total Cost (Current Price)

$0.016

Total Output Tokens

8,384

Total Input Tokens

0

Input Price

$0.252 / 1M

Output Price

$0.378 / 1M

Tests Correct

Wrong Tests: 11

Attempt pass rate: 50.0%

Flaky tests

4

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

Response Time (avg)

12.09s

Response Time (max): 115.89s

Response Time (total): 217.56s

Wrong answer: 8 Extra formatting: 2 Invalid tool call: 1

Hamster playing table tennis

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

#69 DeepSeek V3.2

none
Cost
$0.002
Time
7.0s
Tokens
1,046 tok

Run history

Tested on Score Reliability Tests Correct Total Cost Compare
2026-08-14 02:58 Re-test 5.0 10.0 $0.054 ↑ Compare
2026-07-16 23:15 New test added 5.0 10.0 $0.054 ↑ Compare
2026-06-04 14:22 New test added 5.2 10.0 $0.017 ↓ Compare
2026-05-22 00:35 Suite changed 5.6 10.0 $0.018 Compare
2026-05-08 15:31 Suite changed 5.7 10.0 $0.016 Compare
2026-04-20 17:48 First recorded run 6.1 N/A $0.016 Current run

Run comparison

RunBenchmark coverageScoreConsistencyReliabilityTests CorrectFlaky testsTotal Output TokensTotal Input TokensTotal CostResponse Time (avg)
2026-04-20 17:48 · First recorded run54/54 attempts6.18.1N/A7/1848,3840$0.01612.09s
2026-05-22 00:35 · Suite changed60/60 attempts5.68.010.07/20511,1630$0.01814.46s
Difference—+0.6+0.10-1-27790-$0.002-2374ms

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

Quick Compare

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Category Breakdown

Category Score Consistency Tests Correct
Anti-AI Tricks 3.2 9.8
Coding 2.4 1.3
Combined 6.5 10.0
Data parsing and extraction 6.3 5.8
Domain specific 3.6 7.2
General Intelligence 10.0 10.0
Instructions following 10.0 10.0
Puzzle Solving 8.5 7.5
Tool Calling 10.0 10.0

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