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DeepSeek V3.2 Exp vs GPT-5 Nano

Updated October 21, 2026. 49 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 Nano
DeepSeek V3.2 ExpDeepSeek
Coding
55.0
Overall
16.6
Output $/M
$0.41
46
GPT-5 NanoOpenAI
Coding
34.8
Overall
13.0
Output $/M
$0.40
2
vs boards won of 49 shared, 1 tied

Decision reading

Pick DeepSeek V3.2 Exp for coding: it scores 55.0 on the Vibe Coding Index against 34.8 for GPT-5 Nano.

Pick GPT-5 Nano when output tokens cost 1.0x less, or when the context window is larger, 400K against 164K tokens.

Model ADeepSeek V3.2 ExpDeepSeek55.0/1002 independent benchmarksNo cost per solved taskModel BGPT-5 NanoOpenAI34.8/1001 independent benchmark$0.109 per solved task
Shared results
49
DeepSeek V3.2 Exp only
8
GPT-5 Nano only
36
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 Nano 34.8 from 1 benchmark.
Widest category
General, 20.2 points apart on average over 21 shared benchmarks.
Widest single gap
Fiction.LiveBench: DeepSeek V3.2 Exp 83.3% against GPT-5 Nano 44.4%, 38.9 points apart on a 0 to 100 scale.
Output price
DeepSeek V3.2 Exp $0.41 against GPT-5 Nano $0.40 per million output tokens, 1.0x apart.
Context window
DeepSeek V3.2 Exp takes 164K tokens, GPT-5 Nano 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-5 NanoTies
Coding401 tie
Intelligence20
Agentic work01
Reasoning50
Math40
Knowledge50
Web design60
General201
All shared boards4621 tie
CodingLike-for-likeFour of these boards feed the Vibe Coding Index40
Coding benchmarks for DeepSeek V3.2 Exp and GPT-5 Nano
BenchmarkDeepSeek V3.2 ExpGPT-5 NanoLeader
Aider polyglot74.2%Not measuredOnly DeepSeek V3.2 Exp measured
SWE-bench VerifiedNot measured34.8%Only GPT-5 Nano measured
LMArena WebDev1272Not measuredOnly DeepSeek V3.2 Exp measured
LiveCodeBench (Vals AI)Not measured70.2%Only GPT-5 Nano measured
LiveCodeBench (Artificial Analysis run)78.9%78.9%Tie
Terminal-Bench Hard (Artificial Analysis run)31.1%17.4%DeepSeek V3.2 Exp
Terminal-BenchNot measured21.8%Only GPT-5 Nano measured
WeirdML39.5%38.1%DeepSeek V3.2 Exp
LMArena Text: coding14381351DeepSeek V3.2 Exp
LMArena Text: software and IT14381345DeepSeek V3.2 Exp
LMArena WebDev: HTML1281Not measuredOnly DeepSeek V3.2 Exp measured
Neither model has a result on the other 27 boards here
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index20
Intelligence benchmarks for DeepSeek V3.2 Exp and GPT-5 Nano
BenchmarkDeepSeek V3.2 ExpGPT-5 NanoLeader
AA Intelligence Index16.613.0DeepSeek V3.2 Exp
Epoch Capabilities Index144.9139.2DeepSeek V3.2 Exp
Agentic workLike-for-likePublic boards, shown as published, kept out of the index01
Agentic work benchmarks for DeepSeek V3.2 Exp and GPT-5 Nano
BenchmarkDeepSeek V3.2 ExpGPT-5 NanoLeader
τ²-Bench Telecom33.9%36.5%GPT-5 Nano
TheAgentCompany42.9%Not measuredOnly DeepSeek V3.2 Exp measured
Neither model has a result on the other 37 boards here
ReasoningLike-for-likePublic boards, shown as published, kept out of the index50
Reasoning benchmarks for DeepSeek V3.2 Exp and GPT-5 Nano
BenchmarkDeepSeek V3.2 ExpGPT-5 NanoLeader
GPQA DiamondNot measured63.4%Only GPT-5 Nano measured
MMMU Pro (Vals AI)Not measured70.9%Only GPT-5 Nano measured
GPQA Diamond (Artificial Analysis run)79.7%67.6%DeepSeek V3.2 Exp
Humanity's Last Exam (Artificial Analysis run)14.9%9.5%DeepSeek V3.2 Exp
GPQA Diamond (Epoch AI run)Not measured69.4%Only GPT-5 Nano measured
ARC-AGINot measured20.7%Only GPT-5 Nano measured
ARC-AGI-2Not measured2.6%Only GPT-5 Nano measured
Chess puzzlesNot measured22.0%Only GPT-5 Nano measured
Mystery game puzzlesNot measured9.0%Only GPT-5 Nano measured
VPCTNot measured37.2%Only GPT-5 Nano measured
LMArena Text: hard prompts14291328DeepSeek V3.2 Exp
LMArena Text: expert14221321DeepSeek V3.2 Exp
LMArena Text: hard prompts in English14441338DeepSeek V3.2 Exp
LMArena Vision: diagramsNot measured1141Only GPT-5 Nano measured
LMArena Vision: homeworkNot measured1157Only GPT-5 Nano measured
Neither model has a result on the other 6 boards here
MathLike-for-likePublic boards, shown as published, kept out of the index40
Math benchmarks for DeepSeek V3.2 Exp and GPT-5 Nano
BenchmarkDeepSeek V3.2 ExpGPT-5 NanoLeader
AIMENot measured81.2%Only GPT-5 Nano measured
MATH 500 (Vals AI)Not measured93.8%Only GPT-5 Nano measured
MGSM (Vals AI)Not measured89.3%Only GPT-5 Nano measured
AA Math Index87.783.7DeepSeek V3.2 Exp
AIME 2025 (Artificial Analysis run)87.7%83.7%DeepSeek V3.2 Exp
OTIS Mock AIMENot measured81.1%Only GPT-5 Nano measured
FrontierMath, tiers 1 to 3Not measured20.0%Only GPT-5 Nano measured
FrontierMath, tier 4Not measured2.4%Only GPT-5 Nano measured
ProofBenchNot measured12.0%Only GPT-5 Nano measured
MATH level 5Not measured95.2%Only GPT-5 Nano measured
LMArena Text: math14221317DeepSeek V3.2 Exp
LMArena Text: mathematical work14331326DeepSeek 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 index50
Knowledge benchmarks for DeepSeek V3.2 Exp and GPT-5 Nano
BenchmarkDeepSeek V3.2 ExpGPT-5 NanoLeader
MMLU ProNot measured76.1%Only GPT-5 Nano measured
LegalBench (Vals AI)Not measured50.1%Only GPT-5 Nano measured
CaseLaw (Vals AI)Not measured52.6%Only GPT-5 Nano measured
TaxEval (Vals AI)Not measured67.4%Only GPT-5 Nano measured
MortgageTax (Vals AI)Not measured53.6%Only GPT-5 Nano measured
MedQA (Vals AI)Not measured93.3%Only GPT-5 Nano measured
MedCode (Vals AI)Not measured30.4%Only GPT-5 Nano measured
MMLU Pro (Artificial Analysis run)85.0%78.0%DeepSeek V3.2 Exp
SimpleQA VerifiedNot measured11.7%Only GPT-5 Nano measured
LMArena Text: science14431318DeepSeek V3.2 Exp
LMArena Text: medicine and healthcare14681335DeepSeek V3.2 Exp
LMArena Text: legal and government14191298DeepSeek V3.2 Exp
LMArena Text: business and finance14121311DeepSeek V3.2 Exp
Neither model has a result on the other 4 boards here
Web designLike-for-likePublic boards, shown as published, kept out of the index60
Web design benchmarks for DeepSeek V3.2 Exp and GPT-5 Nano
BenchmarkDeepSeek V3.2 ExpGPT-5 NanoLeader
Design Arena: websites11791101DeepSeek V3.2 Exp
Design Arena: UI components11661066DeepSeek V3.2 Exp
Design Arena: game dev11451045DeepSeek V3.2 Exp
Design Arena: data viz11521056DeepSeek V3.2 Exp
Design Arena: 3D1148966DeepSeek V3.2 Exp
Design Arena: all code categories11711084DeepSeek V3.2 Exp
Design Arena: SVG1031Not measuredOnly DeepSeek V3.2 Exp measured
Neither model has a result on the other 2 boards here
GeneralLike-for-likePublic boards, shown as published, kept out of the index201
General benchmarks for DeepSeek V3.2 Exp and GPT-5 Nano
BenchmarkDeepSeek V3.2 ExpGPT-5 NanoLeader
SAGE (Vals AI)Not measured30.4%Only GPT-5 Nano measured
MedScribe (Vals AI)Not measured72.9%Only GPT-5 Nano measured
IFBench54.1%67.6%GPT-5 Nano
Long context reasoning (AA-LCR)72.3%45.0%DeepSeek V3.2 Exp
DTBench87.7%62.7%DeepSeek V3.2 Exp
LMCA29.1%7.9%DeepSeek V3.2 Exp
Fiction.LiveBench83.3%44.4%DeepSeek V3.2 Exp
CL-bench13.2%Not measuredOnly DeepSeek V3.2 Exp measured
CL-bench Life9.5%Not measuredOnly DeepSeek V3.2 Exp measured
LMArena Text14251320DeepSeek V3.2 Exp
LMArena Text: instruction following14011306DeepSeek V3.2 Exp
LMArena Text: creative writing14041249DeepSeek V3.2 Exp
LMArena VisionNot measured1159Only GPT-5 Nano measured
LMArena Text: English14411321DeepSeek V3.2 Exp
LMArena Text: non-English14041313DeepSeek V3.2 Exp
LMArena Text: Chinese14611356DeepSeek V3.2 Exp
LMArena Text: German14401327DeepSeek V3.2 Exp
LMArena Text: Japanese13311227DeepSeek V3.2 Exp
LMArena Text: Korean13721269DeepSeek V3.2 Exp
LMArena Text: French1434Not measuredOnly DeepSeek V3.2 Exp measured
LMArena Text: Spanish14411360DeepSeek V3.2 Exp
LMArena Text: Russian14121296DeepSeek V3.2 Exp
LMArena Text: Polish14351314DeepSeek V3.2 Exp
LMArena Text: multi-turn14221311DeepSeek V3.2 Exp
LMArena Text: longer queries14181312DeepSeek V3.2 Exp
LMArena Text: writing and language14071283DeepSeek V3.2 Exp
LMArena Text: entertainment and media14071268DeepSeek V3.2 Exp
LMArena Vision: EnglishNot measured1170Only GPT-5 Nano measured
LMArena Vision: ChineseNot measured1176Only GPT-5 Nano measured
LMArena Vision: reading textNot measured1152Only GPT-5 Nano measured
LMArena Vision: humorNot measured1110Only GPT-5 Nano measured
Neither model has a result on the other 15 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 Nano
BenchmarkDeepSeek V3.2 ExpGPT-5 NanoLeader
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 Nano$0.0003Fits in one request

GPT-5 Nano costs less

Repository review

50K input + 3K output tokens

DeepSeek V3.2 Exp$0.015Fits in one request
GPT-5 Nano$0.0037Fits in one request

GPT-5 Nano costs less

Agent loop

200K input + 10K output tokens

DeepSeek V3.2 Exp$0.058Exceeds the context window
GPT-5 Nano$0.014Fits in one request

GPT-5 Nano 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 Nano
SpecificationDeepSeek V3.2 ExpOpenAI GPT-5 Nano
MakerDeepSeekOpenAI
WeightsOpen weightsNo public weights listed
ReleasedSeptember 29, 2025August 7, 2025
Context window164K400K
Input $/Mtok$0.27$0.05
Output $/Mtok$0.41$0.40
Coding index55.034.8
Independent measurements behind it21
Cost per solved taskNot computable$0.109
SourceOpenRouter listingOpenRouter listing

Questions

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

Pick DeepSeek V3.2 Exp for coding: it scores 55.0 on the Vibe Coding Index against 34.8 for GPT-5 Nano. Pick GPT-5 Nano when output tokens cost 1.0x less, or when the context window is larger, 400K against 164K tokens.

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

DeepSeek V3.2 Exp costs $0.27 per million input tokens and $0.41 per million output tokens; GPT-5 Nano costs $0.05 and $0.40. Cost per solved task is known for GPT-5 Nano only.

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

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

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

49 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 Nano's on 1. Where only one model has a result, the page says so instead of naming a winner.

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