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DeepSeek V3.2 vs GPT-4o (2024-08-06)

Updated October 21, 2026. 42 benchmarks have a result for both. Coding is ranked on the Vibe Coding Index; every other board is shown as published.

Replace DeepSeek V3.2 Replace GPT-4o (2024-08-06)
DeepSeek V3.2DeepSeek
Coding
54.4
Overall
21.5
Output $/M
$0.42
39
GPT-4o (2024-08-06)OpenAI
Coding
23.1
Overall
7.7
Output $/M
$10.00
3
vs boards won of 42 shared

Decision reading

Pick DeepSeek V3.2 for coding: it scores 54.4 on the Vibe Coding Index against 23.1 for GPT-4o (2024-08-06).

Pick GPT-4o (2024-08-06) when what matters is MGSM (Vals AI) or LegalBench (Vals AI), where it leads.

Model ADeepSeek V3.2DeepSeek54.4/1002 independent benchmarks$0.99 per solved taskModel BGPT-4o (2024-08-06)OpenAI23.1/1001 independent benchmarkNo cost per solved task
Shared results
42
DeepSeek V3.2 only
33
GPT-4o (2024-08-06) only
16
Like-for-like categories
7 of 9

Shared results can support a head-to-head reading. Results only one model has describe coverage, not superiority.

Which one for your work

Each card is decided by one number both models carry. Where only one has it, the card says so and makes no call.

At a glance

Coding index
DeepSeek V3.2 54.4 from 2 benchmarks, GPT-4o (2024-08-06) 23.1 from 1 benchmark.
Widest category
Agentic work, 61.7 points apart on average over 1 shared benchmark.
Widest single gap
AIME: DeepSeek V3.2 84.6% against GPT-4o (2024-08-06) 14.0%, 70.6 points apart on a 0 to 100 scale.
Output price
DeepSeek V3.2 $0.42 against GPT-4o (2024-08-06) $10.00 per million output tokens, 23.8x apart.
Context window
DeepSeek V3.2 takes 164K tokens, GPT-4o (2024-08-06) 128K.

Benchmark by benchmark

First the score: boards each model leads, per category, where both have a result. Then every board, a category to a fold; bars are each result on a 0 to 100 scale, so compare the two in a row, not one row with another.

Boards won, where both have a result
CategoryDeepSeek V3.2BarsGPT-4o (2024-08-06)Ties
Coding40
Intelligence10
Agentic work10
Reasoning50
Math31
Knowledge72
General180
All shared boards393
CodingLike-for-likeFour of these boards feed the Vibe Coding Index40
Coding benchmarks for DeepSeek V3.2 and GPT-4o (2024-08-06)
BenchmarkDeepSeek V3.2GPT-4o (2024-08-06)Leader
Aider polyglotNot measured23.1%Only GPT-4o (2024-08-06) measured
SWE-bench Verified70.0%Not measuredOnly DeepSeek V3.2 measured
SWE-bench LiteNot measured21.7%Only GPT-4o (2024-08-06) measured
SWE-bench Multilingual59.0%Not measuredOnly DeepSeek V3.2 measured
LMArena WebDev1362Not measuredOnly DeepSeek V3.2 measured
AA Coding Index44.2Not measuredOnly DeepSeek V3.2 measured
LiveCodeBench (Vals AI)80.7%Not measuredOnly DeepSeek V3.2 measured
SWE-bench Verified (Vals AI)67.6%Not measuredOnly DeepSeek V3.2 measured
Vibe Code Bench (Vals AI)5.1%Not measuredOnly DeepSeek V3.2 measured
LiveCodeBench (Artificial Analysis run)86.2%31.7%DeepSeek V3.2
Terminal-Bench Hard (Artificial Analysis run)35.6%8.3%DeepSeek V3.2
Terminal-Bench39.6%Not measuredOnly DeepSeek V3.2 measured
LMArena Text: coding14531283DeepSeek V3.2
LMArena Text: software and IT14491278DeepSeek V3.2
LMArena WebDev: React1350Not measuredOnly DeepSeek V3.2 measured
LMArena WebDev: HTML1371Not measuredOnly DeepSeek V3.2 measured
Neither model has a result on the other 22 boards here
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index10
Intelligence benchmarks for DeepSeek V3.2 and GPT-4o (2024-08-06)
BenchmarkDeepSeek V3.2GPT-4o (2024-08-06)Leader
AA Intelligence Index21.57.7DeepSeek V3.2
Epoch Capabilities Index146.1Not measuredOnly DeepSeek V3.2 measured
Agentic workLike-for-likePublic boards, shown as published, kept out of the index10
Agentic work benchmarks for DeepSeek V3.2 and GPT-4o (2024-08-06)
BenchmarkDeepSeek V3.2GPT-4o (2024-08-06)Leader
τ²-Bench Telecom90.6%28.9%DeepSeek V3.2
APEX-Agents21.3%Not measuredOnly DeepSeek V3.2 measured
Vending-Bench 2$1,034Not measuredOnly DeepSeek V3.2 measured
Neither model has a result on the other 36 boards here
ReasoningLike-for-likePublic boards, shown as published, kept out of the index50
Reasoning benchmarks for DeepSeek V3.2 and GPT-4o (2024-08-06)
BenchmarkDeepSeek V3.2GPT-4o (2024-08-06)Leader
GPQA Diamond80.3%Not measuredOnly DeepSeek V3.2 measured
MMMU Pro (Vals AI)Not measured64.0%Only GPT-4o (2024-08-06) measured
GPQA Diamond (Artificial Analysis run)84.0%52.1%DeepSeek V3.2
Humanity's Last Exam (Artificial Analysis run)24.6%2.3%DeepSeek V3.2
GPQA Diamond (Epoch AI run)Not measured49.2%Only GPT-4o (2024-08-06) measured
ARC-AGI57.0%Not measuredOnly DeepSeek V3.2 measured
ARC-AGI-24.0%Not measuredOnly DeepSeek V3.2 measured
SimpleBenchNot measured17.8%Only GPT-4o (2024-08-06) measured
Chess puzzlesNot measured6.0%Only GPT-4o (2024-08-06) measured
LMArena Text: hard prompts14341264DeepSeek V3.2
LMArena Text: expert14361241DeepSeek V3.2
LMArena Text: hard prompts in English14461277DeepSeek V3.2
Neither model has a result on the other 9 boards here
MathLike-for-likePublic boards, shown as published, kept out of the index31
Math benchmarks for DeepSeek V3.2 and GPT-4o (2024-08-06)
BenchmarkDeepSeek V3.2GPT-4o (2024-08-06)Leader
AIME84.6%14.0%DeepSeek V3.2
MATH 500 (Vals AI)Not measured75.2%Only GPT-4o (2024-08-06) measured
MGSM (Vals AI)86.0%90.7%GPT-4o (2024-08-06)
AA Math Index92.0Not measuredOnly DeepSeek V3.2 measured
AIME 2025 (Artificial Analysis run)92.0%Not measuredOnly DeepSeek V3.2 measured
OTIS Mock AIMENot measured6.4%Only GPT-4o (2024-08-06) measured
FrontierMath, tiers 1 to 3Not measured0.4%Only GPT-4o (2024-08-06) measured
MATH level 5Not measured53.3%Only GPT-4o (2024-08-06) measured
LMArena Text: math14351285DeepSeek V3.2
LMArena Text: mathematical work14401283DeepSeek V3.2
Neither model has a result on the other 3 boards here
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index72
Knowledge benchmarks for DeepSeek V3.2 and GPT-4o (2024-08-06)
BenchmarkDeepSeek V3.2GPT-4o (2024-08-06)Leader
MMLU Pro84.9%74.1%DeepSeek V3.2
LegalBench (Vals AI)76.1%80.1%GPT-4o (2024-08-06)
CaseLaw (Vals AI)55.4%Not measuredOnly DeepSeek V3.2 measured
CorpFin (Vals AI)51.0%39.4%DeepSeek V3.2
TaxEval (Vals AI)68.2%71.1%GPT-4o (2024-08-06)
MortgageTax (Vals AI)Not measured61.0%Only GPT-4o (2024-08-06) measured
MedQA (Vals AI)93.9%88.2%DeepSeek V3.2
MMLU Pro (Artificial Analysis run)86.2%Not measuredOnly DeepSeek V3.2 measured
SimpleQA VerifiedNot measured26.0%Only GPT-4o (2024-08-06) measured
MMLUNot measured84.3%Only GPT-4o (2024-08-06) measured
LMArena Text: science14461274DeepSeek V3.2
LMArena Text: medicine and healthcare14401252DeepSeek V3.2
LMArena Text: legal and government14251275DeepSeek V3.2
LMArena Text: business and finance14101232DeepSeek V3.2
Neither model has a result on the other 3 boards here
Web designDirectional onlyPublic boards, shown as published, kept out of the index8 boards, none shared
Web design benchmarks for DeepSeek V3.2 and GPT-4o (2024-08-06)
BenchmarkDeepSeek V3.2GPT-4o (2024-08-06)Leader
Design Arena: websites1175Not measuredOnly DeepSeek V3.2 measured
Design Arena: UI components1149Not measuredOnly DeepSeek V3.2 measured
Design Arena: game dev1132Not measuredOnly DeepSeek V3.2 measured
Design Arena: data viz1158Not measuredOnly DeepSeek V3.2 measured
Design Arena: 3D1133Not measuredOnly DeepSeek V3.2 measured
Design Arena: all code categories1164Not measuredOnly DeepSeek V3.2 measured
Design Arena: SVG1032Not measuredOnly DeepSeek V3.2 measured
Design Arena: ASCII art1082Not measuredOnly DeepSeek V3.2 measured
Neither model has a result on the other 1 board here
GeneralLike-for-likePublic boards, shown as published, kept out of the index180
General benchmarks for DeepSeek V3.2 and GPT-4o (2024-08-06)
BenchmarkDeepSeek V3.2GPT-4o (2024-08-06)Leader
IFBench60.7%36.0%DeepSeek V3.2
Long context reasoning (AA-LCR)73.3%41.0%DeepSeek V3.2
DTBench85.6%Not measuredOnly DeepSeek V3.2 measured
LMCA28.8%Not measuredOnly DeepSeek V3.2 measured
CL-bench12.4%Not measuredOnly DeepSeek V3.2 measured
CL-bench Life7.4%Not measuredOnly DeepSeek V3.2 measured
LMArena Text14251283DeepSeek V3.2
LMArena Text: instruction following14131267DeepSeek V3.2
LMArena Text: creative writing14001274DeepSeek V3.2
LMArena VisionNot measured1065Only GPT-4o (2024-08-06) measured
LMArena Text: English14391297DeepSeek V3.2
LMArena Text: non-English14091262DeepSeek V3.2
LMArena Text: Chinese14551254DeepSeek V3.2
LMArena Text: German14131257DeepSeek V3.2
LMArena Text: Japanese13741234DeepSeek V3.2
LMArena Text: Korean13701218DeepSeek V3.2
LMArena Text: French14291263DeepSeek V3.2
LMArena Text: Spanish14241269DeepSeek V3.2
LMArena Text: Russian14241272DeepSeek V3.2
LMArena Text: Polish1419Not measuredOnly DeepSeek V3.2 measured
LMArena Text: multi-turn14271279DeepSeek V3.2
LMArena Text: longer queries14281283DeepSeek V3.2
LMArena Text: writing and language14071290DeepSeek V3.2
LMArena Text: entertainment and media13951267DeepSeek V3.2
LMArena Vision: EnglishNot measured1072Only GPT-4o (2024-08-06) measured
LMArena Vision: ChineseNot measured1009Only GPT-4o (2024-08-06) measured
Neither model has a result on the other 20 boards here
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
Image generation benchmarks for DeepSeek V3.2 and GPT-4o (2024-08-06)
BenchmarkDeepSeek V3.2GPT-4o (2024-08-06)Leader
Neither model has a result on 5 boards here

What each workload costs

Three fixed token mixes at each model's listed price, so per-token rates become a bill.

Chat turn

1K input + 500 output tokens

DeepSeek V3.2$0.0005Fits in one request
GPT-4o (2024-08-06)$0.0075Fits in one request

DeepSeek V3.2 costs less

Repository review

50K input + 3K output tokens

DeepSeek V3.2$0.015Fits in one request
GPT-4o (2024-08-06)$0.155Fits in one request

DeepSeek V3.2 costs less

Agent loop

200K input + 10K output tokens

DeepSeek V3.2$0.060Exceeds the context window
GPT-4o (2024-08-06)$0.600Exceeds the context window

DeepSeek V3.2 costs less

Listed OpenRouter rates, without cache or batch discounts. A workload that does not fit a model's context window would need splitting.

Specification differences

The leading value in a row is marked; a row with a missing value names no leader. Our two rows are marked in red.

Specifications of DeepSeek V3.2 and GPT-4o (2024-08-06)
SpecificationDeepSeek V3.2OpenAI GPT-4o (2024-08-06)
MakerDeepSeekOpenAI
WeightsOpen weightsNo public weights listed
ReleasedDecember 1, 2025August 6, 2024
Context window164K128K
Input $/Mtok$0.28$2.50
Output $/Mtok$0.42$10.00
Coding index54.423.1
Independent measurements behind it21
Cost per solved task$0.99Not computable
SourceOpenRouter listingOpenRouter listing

Questions

Is DeepSeek V3.2 better than GPT-4o (2024-08-06) for coding?

Pick DeepSeek V3.2 for coding: it scores 54.4 on the Vibe Coding Index against 23.1 for GPT-4o (2024-08-06). Pick GPT-4o (2024-08-06) when what matters is MGSM (Vals AI) or LegalBench (Vals AI), where it leads.

Which is cheaper, DeepSeek V3.2 or GPT-4o (2024-08-06)?

DeepSeek V3.2 costs $0.28 per million input tokens and $0.42 per million output tokens; GPT-4o (2024-08-06) costs $2.50 and $10.00. Cost per solved task is known for DeepSeek V3.2 only.

Which has the bigger context window, DeepSeek V3.2 or GPT-4o (2024-08-06)?

DeepSeek V3.2, with 164K tokens against 128K.

How many benchmarks is the DeepSeek V3.2 vs GPT-4o (2024-08-06) comparison based on?

42 benchmarks have a result for both models as of October 21, 2026. DeepSeek V3.2's coding index rests on 2 independent benchmarks and GPT-4o (2024-08-06)'s on 1. Where only one model has a result, the page says so instead of naming a winner.

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