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DeepSeek V3.2 vs GPT-4 Turbo

DeepSeek V3.2 leads GPT-4 Turbo on the Artificial Analysis Intelligence Index, 21.5 to 7.0, and DeepSeek V3.2 costs 34.1x less per output token ($0.88 vs $30.00 per million). Updated October 21, 2026; 38 benchmarks have a result for both.

Replace DeepSeek V3.2 Replace GPT-4 Turbo
DeepSeek V3.2DeepSeek
Coding
30.0
Overall
37.9
Output $/M
$0.88
37
GPT-4 TurboOpenAI
Coding
No data
Overall
No data
Output $/M
$30.00
1
vs boards won of 38 shared

DeepSeek V3.2 or GPT-4 Turbo: which to pick

Only DeepSeek V3.2 has a coding score, 30.0 on the Vibe Coding Index; GPT-4 Turbo has none, so the two cannot be ranked on coding.

Pick GPT-4 Turbo for work measured by LegalBench (Vals AI), where it leads.

Model ADeepSeek V3.2DeepSeek30.0/1003 independent benchmarks$0.99 per solved taskModel BGPT-4 TurboOpenAINot benchmarkedNo coding benchmarkNo cost per solved task
Shared results
38
DeepSeek V3.2 only
37
GPT-4 Turbo only
4
Like-for-like categories
6 of 9

Only benchmarks that tested both models count toward a pick; a result only one model has is shown but not compared.

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 30.0 from 3 benchmarks, GPT-4 Turbo not benchmarked.
Widest category
Coding, 35.3 points apart on average over 4 shared benchmarks.
Widest single gap
LiveCodeBench (Artificial Analysis run): DeepSeek V3.2 86.2% against GPT-4 Turbo 29.1%, 57.1 points apart on a 0 to 100 scale.
Output price
DeepSeek V3.2 $0.88 against GPT-4 Turbo $30.00 per million output tokens, 34.1x apart.
Context window
DeepSeek V3.2 takes 164K tokens, GPT-4 Turbo 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-4 TurboTies
Coding40
Intelligence20
Reasoning40
Math20
Knowledge61
General190
All shared boards371
CodingLike-for-likeSix of these boards feed the Vibe Coding Index40
Coding benchmarks for DeepSeek V3.2 and GPT-4 Turbo
BenchmarkDeepSeek V3.2GPT-4 TurboLeader
SWE-bench Verified70.0%Not measuredOnly DeepSeek V3.2 measured
SWE-bench Multilingual59.0%Not measuredOnly DeepSeek V3.2 measured
LMArena WebDev1362Not measuredOnly DeepSeek V3.2 measured
AA Coding Index44.221.5DeepSeek V3.2
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%29.1%DeepSeek V3.2
Terminal-Bench Hard (Artificial Analysis run)35.6%Not measuredOnly DeepSeek V3.2 measured
Terminal-Bench39.6%Not measuredOnly DeepSeek V3.2 measured
LMArena Text: coding14531268DeepSeek V3.2
LMArena Text: software and IT14491267DeepSeek 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 25 boards here
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index20
Intelligence benchmarks for DeepSeek V3.2 and GPT-4 Turbo
BenchmarkDeepSeek V3.2GPT-4 TurboLeader
AA Intelligence Index21.57.0DeepSeek V3.2
Epoch Capabilities Index146.1127.3DeepSeek V3.2
Agentic workDirectional onlyPublic boards, shown as published, kept out of the index3 boards, none shared
Agentic work benchmarks for DeepSeek V3.2 and GPT-4 Turbo
BenchmarkDeepSeek V3.2GPT-4 TurboLeader
τ²-Bench Telecom90.6%Not measuredOnly DeepSeek V3.2 measured
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 38 boards here
ReasoningLike-for-likePublic boards, shown as published, kept out of the index40
Reasoning benchmarks for DeepSeek V3.2 and GPT-4 Turbo
BenchmarkDeepSeek V3.2GPT-4 TurboLeader
GPQA Diamond80.3%Not measuredOnly DeepSeek V3.2 measured
GPQA Diamond (Artificial Analysis run)84.0%Not measuredOnly DeepSeek V3.2 measured
Humanity's Last Exam (Artificial Analysis run)24.6%3.1%DeepSeek V3.2
ARC-AGI57.0%Not measuredOnly DeepSeek V3.2 measured
ARC-AGI-24.0%Not measuredOnly DeepSeek V3.2 measured
LMArena Text: hard prompts14341251DeepSeek V3.2
LMArena Text: expert14361223DeepSeek V3.2
LMArena Text: hard prompts in English14461266DeepSeek V3.2
Neither model has a result on the other 14 boards here
MathLike-for-likePublic boards, shown as published, kept out of the index20
Math benchmarks for DeepSeek V3.2 and GPT-4 Turbo
BenchmarkDeepSeek V3.2GPT-4 TurboLeader
AIME84.6%Not measuredOnly DeepSeek V3.2 measured
MGSM (Vals AI)86.0%Not measuredOnly DeepSeek V3.2 measured
AA Math Index92.0Not measuredOnly DeepSeek V3.2 measured
AIME 2025 (Artificial Analysis run)92.0%Not measuredOnly DeepSeek V3.2 measured
LMArena Text: math14351272DeepSeek V3.2
LMArena Text: mathematical work14401268DeepSeek V3.2
Neither model has a result on the other 7 boards here
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index61
Knowledge benchmarks for DeepSeek V3.2 and GPT-4 Turbo
BenchmarkDeepSeek V3.2GPT-4 TurboLeader
MMLU Pro84.9%Not measuredOnly DeepSeek V3.2 measured
LegalBench (Vals AI)76.1%80.5%GPT-4 Turbo
CaseLaw (Vals AI)55.4%Not measuredOnly DeepSeek V3.2 measured
CorpFin (Vals AI)51.0%Not measuredOnly DeepSeek V3.2 measured
TaxEval (Vals AI)68.2%Not measuredOnly DeepSeek V3.2 measured
MedQA (Vals AI)93.9%82.0%DeepSeek V3.2
MMLU Pro (Artificial Analysis run)86.2%69.4%DeepSeek V3.2
MMLUNot measured81.3%Only GPT-4 Turbo measured
LMArena Text: science14461256DeepSeek V3.2
LMArena Text: medicine and healthcare14401239DeepSeek V3.2
LMArena Text: legal and government14251265DeepSeek V3.2
LMArena Text: business and finance14101222DeepSeek V3.2
Neither model has a result on the other 6 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-4 Turbo
BenchmarkDeepSeek V3.2GPT-4 TurboLeader
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 art1083Not 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 index190
General benchmarks for DeepSeek V3.2 and GPT-4 Turbo
BenchmarkDeepSeek V3.2GPT-4 TurboLeader
IFBench60.7%Not measuredOnly DeepSeek V3.2 measured
Long context reasoning (AA-LCR)73.3%Not measuredOnly DeepSeek V3.2 measured
DTBench85.6%61.6%DeepSeek V3.2
LMCA28.8%9.8%DeepSeek V3.2
CL-bench12.4%Not measuredOnly DeepSeek V3.2 measured
CL-bench Life7.4%Not measuredOnly DeepSeek V3.2 measured
LMArena Text14251272DeepSeek V3.2
LMArena Text: instruction following14131249DeepSeek V3.2
LMArena Text: creative writing14001268DeepSeek V3.2
LMArena VisionNot measured1090Only GPT-4 Turbo measured
LMArena Text: English14391291DeepSeek V3.2
LMArena Text: non-English14091245DeepSeek V3.2
LMArena Text: Chinese14551242DeepSeek V3.2
LMArena Text: German14131259DeepSeek V3.2
LMArena Text: Japanese13741194DeepSeek V3.2
LMArena Text: Korean13701187DeepSeek V3.2
LMArena Text: French14291276DeepSeek V3.2
LMArena Text: Spanish14241260DeepSeek V3.2
LMArena Text: Russian14241259DeepSeek V3.2
LMArena Text: Polish14191302DeepSeek V3.2
LMArena Text: multi-turn14271267DeepSeek V3.2
LMArena Text: longer queries14281254DeepSeek V3.2
LMArena Text: writing and language14071279DeepSeek V3.2
LMArena Text: entertainment and media13951258DeepSeek V3.2
LMArena Vision: EnglishNot measured1097Only GPT-4 Turbo measured
LMArena Vision: ChineseNot measured1045Only GPT-4 Turbo 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-4 Turbo
BenchmarkDeepSeek V3.2GPT-4 TurboLeader
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$0.0007Fits in one request
GPT-4 Turbo$0.025Fits in one request

DeepSeek V3.2 costs less

Repository review

50K input + 3K output tokens

DeepSeek V3.2$0.017Fits in one request
GPT-4 Turbo$0.590Fits in one request

DeepSeek V3.2 costs less

Agent loop

200K input + 10K output tokens

DeepSeek V3.2$0.067Exceeds the context window
GPT-4 Turbo$2.30Exceeds 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-4 Turbo
SpecificationDeepSeek V3.2OpenAI GPT-4 Turbo
MakerDeepSeekOpenAI
WeightsOpen weightsNo public weights listed
ReleasedDecember 1, 2025April 9, 2024
Context window164K128K
Input $/Mtok$0.29$10.00
Output $/Mtok$0.88$30.00
Coding index30.0Not benchmarked
Independent measurements behind it30
Cost per solved task$0.99Not computable
SourceOpenRouter listingOpenRouter listing

Questions

Is DeepSeek V3.2 better than GPT-4 Turbo for coding?

Only DeepSeek V3.2 has a coding score, 30.0 on the Vibe Coding Index; GPT-4 Turbo has none, so the two cannot be ranked on coding. Pick GPT-4 Turbo for work measured by LegalBench (Vals AI), where it leads.

Which is cheaper, DeepSeek V3.2 or GPT-4 Turbo?

DeepSeek V3.2 costs $0.29 per million input tokens and $0.88 per million output tokens; GPT-4 Turbo costs $10.00 and $30.00. Cost per solved task is known for DeepSeek V3.2 only.

Which has the bigger context window, DeepSeek V3.2 or GPT-4 Turbo?

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

How many benchmarks is the DeepSeek V3.2 vs GPT-4 Turbo comparison based on?

38 benchmarks have a result for both models as of October 21, 2026. DeepSeek V3.2's coding index rests on 3 independent benchmarks and GPT-4 Turbo's on 0. Where only one model has a result, the page says so instead of naming a winner.

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