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DeepSeek V3.2 Exp vs GPT-5

Updated October 21, 2026. 54 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 Exp Replace GPT-5
DeepSeek V3.2 ExpDeepSeek
Coding
55.0
Overall
16.6
Output $/M
$0.41
27
GPT-5OpenAI
Coding
72.2
Overall
23.0
Output $/M
$10.00
27
vs boards won of 54 shared

Decision reading

Pick GPT-5 for coding: it scores 72.2 on the Vibe Coding Index against 55.0 for DeepSeek V3.2 Exp.

Pick DeepSeek V3.2 Exp when output tokens cost 24.4x less, or when what matters is LMArena Text: coding or LMArena Text: software and IT, where it leads.

Model ADeepSeek V3.2 ExpDeepSeek55.0/1002 independent benchmarksNo cost per solved taskModel BGPT-5OpenAI72.2/1003 independent benchmarks$0.39 per solved task
Shared results
54
DeepSeek V3.2 Exp only
3
GPT-5 only
55
Like-for-like categories
8 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 Exp 55.0 from 2 benchmarks, GPT-5 72.2 from 3 benchmarks.
Widest category
Agentic work, 52.6 points apart on average over 1 shared benchmark.
Widest single gap
τ²-Bench Telecom: DeepSeek V3.2 Exp 33.9% against GPT-5 86.5%, 52.6 points apart on a 0 to 100 scale.
Output price
DeepSeek V3.2 Exp $0.41 against GPT-5 $10.00 per million output tokens, 24.4x apart.
Context window
DeepSeek V3.2 Exp takes 164K tokens, GPT-5 400K.

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 V3.2 ExpBarsGPT-5Ties
Coding26
Intelligence02
Agentic work01
Reasoning32
Math22
Knowledge32
Web design25
General157
All shared boards2727
CodingLike-for-likeFour of these boards feed the Vibe Coding Index26
Coding benchmarks for DeepSeek V3.2 Exp and GPT-5
BenchmarkDeepSeek V3.2 ExpGPT-5Leader
Aider polyglot74.2%88.0%GPT-5
SWE-bench VerifiedNot measured74.4%Only GPT-5 measured
LMArena WebDev12721418GPT-5
AA Coding IndexNot measured37.8Only GPT-5 measured
LiveCodeBench (Vals AI)Not measured85.9%Only GPT-5 measured
SWE-bench Verified (Vals AI)Not measured69.0%Only GPT-5 measured
Vibe Code Bench (Vals AI)Not measured20.1%Only GPT-5 measured
LiveCodeBench (Artificial Analysis run)78.9%84.6%GPT-5
Terminal-Bench Hard (Artificial Analysis run)31.1%37.9%GPT-5
Terminal-BenchNot measured49.6%Only GPT-5 measured
GSO-BenchNot measured6.9%Only GPT-5 measured
WeirdML39.5%60.7%GPT-5
ALE-BenchNot measured807.6Only GPT-5 measured
LMArena Text: coding14381436DeepSeek V3.2 Exp
LMArena Text: software and IT14381420DeepSeek V3.2 Exp
LMArena WebDev: HTML12811427GPT-5
Neither model has a result on the other 22 boards here
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index02
Intelligence benchmarks for DeepSeek V3.2 Exp and GPT-5
BenchmarkDeepSeek V3.2 ExpGPT-5Leader
AA Intelligence Index16.623.0GPT-5
Epoch Capabilities Index144.9150.0GPT-5
Agentic workLike-for-likePublic boards, shown as published, kept out of the index01
Agentic work benchmarks for DeepSeek V3.2 Exp and GPT-5
BenchmarkDeepSeek V3.2 ExpGPT-5Leader
τ²-Bench Telecom33.9%86.5%GPT-5
METR time horizonsNot measured69.6%Only GPT-5 measured
Remote Labor IndexNot measured1.7%Only GPT-5 measured
GDPvalNot measured34.8%Only GPT-5 measured
BALROGNot measured32.8%Only GPT-5 measured
DeepResearch BenchNot measured49.6%Only GPT-5 measured
TheAgentCompany42.9%Not measuredOnly DeepSeek V3.2 Exp measured
Neither model has a result on the other 32 boards here
ReasoningLike-for-likePublic boards, shown as published, kept out of the index32
Reasoning benchmarks for DeepSeek V3.2 Exp and GPT-5
BenchmarkDeepSeek V3.2 ExpGPT-5Leader
GPQA DiamondNot measured85.6%Only GPT-5 measured
MMMU Pro (Vals AI)Not measured81.5%Only GPT-5 measured
GPQA Diamond (Artificial Analysis run)79.7%85.4%GPT-5
Humanity's Last Exam (Artificial Analysis run)14.9%28.5%GPT-5
GPQA Diamond (Epoch AI run)Not measured86.2%Only GPT-5 measured
ARC-AGINot measured65.7%Only GPT-5 measured
ARC-AGI-2Not measured9.9%Only GPT-5 measured
SimpleBenchNot measured56.7%Only GPT-5 measured
Chess puzzlesNot measured36.0%Only GPT-5 measured
Mystery game puzzlesNot measured23.0%Only GPT-5 measured
EBR-benchNot measured12.7%Only GPT-5 measured
VPCTNot measured66.0%Only GPT-5 measured
LMArena Text: hard prompts14291415DeepSeek V3.2 Exp
LMArena Text: expert14221419DeepSeek V3.2 Exp
LMArena Text: hard prompts in English14441419DeepSeek V3.2 Exp
LMArena Vision: diagramsNot measured1252Only GPT-5 measured
LMArena Vision: homeworkNot measured1278Only GPT-5 measured
Neither model has a result on the other 4 boards here
MathLike-for-likePublic boards, shown as published, kept out of the index22
Math benchmarks for DeepSeek V3.2 Exp and GPT-5
BenchmarkDeepSeek V3.2 ExpGPT-5Leader
AIMENot measured93.4%Only GPT-5 measured
MATH 500 (Vals AI)Not measured96.0%Only GPT-5 measured
MGSM (Vals AI)Not measured92.8%Only GPT-5 measured
AA Math Index87.794.3GPT-5
AIME 2025 (Artificial Analysis run)87.7%94.3%GPT-5
OTIS Mock AIMENot measured91.4%Only GPT-5 measured
FrontierMath, tiers 1 to 3Not measured55.4%Only GPT-5 measured
FrontierMath, tier 4Not measured22.0%Only GPT-5 measured
ProofBenchNot measured18.0%Only GPT-5 measured
MATH level 5Not measured98.1%Only GPT-5 measured
LMArena Text: math14221407DeepSeek V3.2 Exp
LMArena Text: mathematical work14331405DeepSeek V3.2 Exp
Neither model has a result on the other 1 board here
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index32
Knowledge benchmarks for DeepSeek V3.2 Exp and GPT-5
BenchmarkDeepSeek V3.2 ExpGPT-5Leader
MMLU ProNot measured86.5%Only GPT-5 measured
LegalBench (Vals AI)Not measured86.0%Only GPT-5 measured
CaseLaw (Vals AI)Not measured66.5%Only GPT-5 measured
CorpFin (Vals AI)Not measured61.1%Only GPT-5 measured
TaxEval (Vals AI)Not measured73.4%Only GPT-5 measured
MortgageTax (Vals AI)Not measured65.5%Only GPT-5 measured
MedQA (Vals AI)Not measured96.3%Only GPT-5 measured
MedCode (Vals AI)Not measured49.6%Only GPT-5 measured
MMLU Pro (Artificial Analysis run)85.0%87.1%GPT-5
SimpleQA VerifiedNot measured50.1%Only GPT-5 measured
GeoBenchNot measured81.0%Only GPT-5 measured
LMArena Text: science14431416DeepSeek V3.2 Exp
LMArena Text: medicine and healthcare14681413DeepSeek V3.2 Exp
LMArena Text: legal and government14191431GPT-5
LMArena Text: business and finance14121400DeepSeek V3.2 Exp
Neither model has a result on the other 2 boards here
Web designLike-for-likePublic boards, shown as published, kept out of the index25
Web design benchmarks for DeepSeek V3.2 Exp and GPT-5
BenchmarkDeepSeek V3.2 ExpGPT-5Leader
Design Arena: websites11791185GPT-5
Design Arena: UI components11661179GPT-5
Design Arena: game dev11451185GPT-5
Design Arena: data viz11521221GPT-5
Design Arena: 3D11481056DeepSeek V3.2 Exp
Design Arena: all code categories11711168DeepSeek V3.2 Exp
Design Arena: SVG10311188GPT-5
Design Arena: ASCII artNot measured1140Only GPT-5 measured
Neither model has a result on the other 1 board here
GeneralLike-for-likePublic boards, shown as published, kept out of the index157
General benchmarks for DeepSeek V3.2 Exp and GPT-5
BenchmarkDeepSeek V3.2 ExpGPT-5Leader
SAGE (Vals AI)Not measured43.7%Only GPT-5 measured
MedScribe (Vals AI)Not measured83.7%Only GPT-5 measured
IFBench54.1%73.1%GPT-5
Long context reasoning (AA-LCR)72.3%78.2%GPT-5
DTBench87.7%90.7%GPT-5
LMCA29.1%40.0%GPT-5
Fiction.LiveBench83.3%97.2%GPT-5
Creative writing (Lech Mazur)Not measured86.0%Only GPT-5 measured
CL-bench13.2%Not measuredOnly DeepSeek V3.2 Exp measured
CL-bench Life9.5%Not measuredOnly DeepSeek V3.2 Exp measured
LMArena Text14251406DeepSeek V3.2 Exp
LMArena Text: instruction following14011388DeepSeek V3.2 Exp
LMArena Text: creative writing14041365DeepSeek V3.2 Exp
LMArena VisionNot measured1232Only GPT-5 measured
LMArena Text: English14411409DeepSeek V3.2 Exp
LMArena Text: non-English14041397DeepSeek V3.2 Exp
LMArena Text: Chinese14611422DeepSeek V3.2 Exp
LMArena Text: German14401416DeepSeek V3.2 Exp
LMArena Text: Japanese13311409GPT-5
LMArena Text: Korean13721360DeepSeek V3.2 Exp
LMArena Text: French14341409DeepSeek V3.2 Exp
LMArena Text: Spanish14411399DeepSeek V3.2 Exp
LMArena Text: Russian14121407DeepSeek V3.2 Exp
LMArena Text: Polish14351431DeepSeek V3.2 Exp
LMArena Text: multi-turn14221426GPT-5
LMArena Text: longer queries14181399DeepSeek V3.2 Exp
LMArena Text: writing and language14071384DeepSeek V3.2 Exp
LMArena Text: entertainment and media14071379DeepSeek V3.2 Exp
LMArena Vision: EnglishNot measured1231Only GPT-5 measured
LMArena Vision: ChineseNot measured1267Only GPT-5 measured
LMArena Vision: reading textNot measured1246Only GPT-5 measured
LMArena Vision: humorNot measured1219Only GPT-5 measured
LMArena Vision: captioningNot measured1212Only GPT-5 measured
LMArena Vision: recognizing thingsNot measured1263Only GPT-5 measured
LMArena Vision: creative writingNot measured1210Only GPT-5 measured
Neither model has a result on the other 11 boards here
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
Image generation benchmarks for DeepSeek V3.2 Exp and GPT-5
BenchmarkDeepSeek V3.2 ExpGPT-5Leader
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 Exp$0.0005Fits in one request
GPT-5$0.0063Fits in one request

DeepSeek V3.2 Exp costs less

Repository review

50K input + 3K output tokens

DeepSeek V3.2 Exp$0.015Fits in one request
GPT-5$0.092Fits in one request

DeepSeek V3.2 Exp costs less

Agent loop

200K input + 10K output tokens

DeepSeek V3.2 Exp$0.058Exceeds the context window
GPT-5$0.350Fits in one request

DeepSeek V3.2 Exp 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 Exp and GPT-5
SpecificationDeepSeek V3.2 ExpOpenAI GPT-5
MakerDeepSeekOpenAI
WeightsOpen weightsNo public weights listed
ReleasedSeptember 29, 2025August 7, 2025
Context window164K400K
Input $/Mtok$0.27$1.25
Output $/Mtok$0.41$10.00
Coding index55.072.2
Independent measurements behind it23
Cost per solved taskNot computable$0.39
SourceOpenRouter listingOpenRouter listing

Questions

Is DeepSeek V3.2 Exp better than GPT-5 for coding?

Pick GPT-5 for coding: it scores 72.2 on the Vibe Coding Index against 55.0 for DeepSeek V3.2 Exp. Pick DeepSeek V3.2 Exp when output tokens cost 24.4x less, or when what matters is LMArena Text: coding or LMArena Text: software and IT, where it leads.

Which is cheaper, DeepSeek V3.2 Exp or GPT-5?

DeepSeek V3.2 Exp costs $0.27 per million input tokens and $0.41 per million output tokens; GPT-5 costs $1.25 and $10.00. Cost per solved task is known for GPT-5 only.

Which has the bigger context window, DeepSeek V3.2 Exp or GPT-5?

GPT-5, with 400K tokens against 164K.

How many benchmarks is the DeepSeek V3.2 Exp vs GPT-5 comparison based on?

54 benchmarks have a result for both models as of October 21, 2026. DeepSeek V3.2 Exp's coding index rests on 2 independent benchmarks and GPT-5's on 3. Where only one model has a result, the page says so instead of naming a winner.

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