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GPT-5 Nano vs Qwen3 32B

GPT-5 Nano leads Qwen3 32B on the Artificial Analysis Intelligence Index, 13.0 to 7.3, at about the same output price ($0.40 vs $0.40 per million). Updated October 22, 2026; 42 benchmarks have a result for both.

GPT-5 NanoOpenAI
Coding
No data
Overall
35.6
Output $/M
$0.40
16
Qwen3 32BQwen
Coding
No data
Overall
40.8
Output $/M
$0.40
26
vs boards won of 42 shared

GPT-5 Nano or Qwen3 32B: which to pick

Neither model has a coding score yet, so the two cannot be ranked on coding.

Pick GPT-5 Nano for a larger context window (400K against 131K tokens) and work measured by LMArena Text: coding or LMArena Text: software and IT, where it leads.

Shared results
42
GPT-5 Nano only
45
Qwen3 32B only
3
Like-for-like categories
7 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
GPT-5 Nano not benchmarked, Qwen3 32B not benchmarked.
Widest category
Math, 12.9 points apart on average over 5 shared benchmarks.
Widest single gap
Long context reasoning (AA-LCR): GPT-5 Nano 45.0% against Qwen3 32B 0.0%, 45.0 points apart on a 0 to 100 scale.
Output price
Both cost $0.40 per million output tokens.
Context window
GPT-5 Nano takes 400K tokens, Qwen3 32B 131K.

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
CategoryGPT-5 NanoBarsQwen3 32BTies
Coding22
Intelligence20
Agentic work20
Reasoning43
Math32
Knowledge05
General314
All shared boards1626
CodingLike-for-likeSix of these boards feed the Vibe Coding Index22
Coding benchmarks for GPT-5 Nano and Qwen3 32B
BenchmarkGPT-5 NanoQwen3 32BLeader
Aider polyglotNot measured40.0%Only Qwen3 32B measured
SWE-bench Verified34.8%Not measuredOnly GPT-5 Nano measured
LiveCodeBench (Vals AI)70.2%Not measuredOnly GPT-5 Nano measured
LiveCodeBench (Artificial Analysis run)78.9%54.6%GPT-5 Nano
SciCodeNot measured36.0%Only Qwen3 32B measured
Terminal-Bench Hard (Artificial Analysis run)17.4%3.0%GPT-5 Nano
Terminal-Bench21.8%Not measuredOnly GPT-5 Nano measured
WeirdML38.1%Not measuredOnly GPT-5 Nano measured
LMArena Text: coding13511357Qwen3 32B
LMArena Text: software and IT13451366Qwen3 32B
Neither model has a result on the other 29 boards here
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index20
Intelligence benchmarks for GPT-5 Nano and Qwen3 32B
BenchmarkGPT-5 NanoQwen3 32BLeader
AA Intelligence Index13.07.3GPT-5 Nano
Epoch Capabilities Index139.2138.4GPT-5 Nano
Agentic workLike-for-likePublic boards, shown as published, kept out of the index20
Agentic work benchmarks for GPT-5 Nano and Qwen3 32B
BenchmarkGPT-5 NanoQwen3 32BLeader
τ²-Bench Telecom36.5%29.8%GPT-5 Nano
Berkeley Function Calling Leaderboard (BFCL)51.4%48.7%GPT-5 Nano
BrowseComp-PlusNot measured10.7%Only Qwen3 32B measured
Neither model has a result on the other 38 boards here
ReasoningLike-for-likePublic boards, shown as published, kept out of the index43
Reasoning benchmarks for GPT-5 Nano and Qwen3 32B
BenchmarkGPT-5 NanoQwen3 32BLeader
GPQA Diamond63.4%Not measuredOnly GPT-5 Nano measured
MMMU Pro (Vals AI)70.9%Not measuredOnly GPT-5 Nano measured
GPQA Diamond (Artificial Analysis run)67.6%66.8%GPT-5 Nano
Humanity's Last Exam (Artificial Analysis run)9.5%7.4%GPT-5 Nano
GPQA Diamond (Epoch AI run)69.4%65.7%GPT-5 Nano
ARC-AGI20.7%Not measuredOnly GPT-5 Nano measured
ARC-AGI-22.6%Not measuredOnly GPT-5 Nano measured
Chess puzzles22.0%Not measuredOnly GPT-5 Nano measured
Mystery game puzzles9.0%Not measuredOnly GPT-5 Nano measured
VPCT37.2%Not measuredOnly GPT-5 Nano measured
LMArena Text: hard prompts13281334Qwen3 32B
LMArena Text: expert13211362Qwen3 32B
LMArena Text: hard prompts in English13381350Qwen3 32B
LMArena Vision: diagrams1141Not measuredOnly GPT-5 Nano measured
LMArena Vision: homework1157Not measuredOnly GPT-5 Nano measured
Kagi LLM Benchmark62.2%48.7%GPT-5 Nano
Neither model has a result on the other 6 boards here
MathLike-for-likePublic boards, shown as published, kept out of the index32
Math benchmarks for GPT-5 Nano and Qwen3 32B
BenchmarkGPT-5 NanoQwen3 32BLeader
AIME81.2%Not measuredOnly GPT-5 Nano measured
MATH 500 (Vals AI)93.8%Not measuredOnly GPT-5 Nano measured
MGSM (Vals AI)89.3%Not measuredOnly GPT-5 Nano measured
AA Math Index83.773.0GPT-5 Nano
AIME 2025 (Artificial Analysis run)83.7%73.0%GPT-5 Nano
OTIS Mock AIME81.1%66.9%GPT-5 Nano
FrontierMath, tiers 1 to 320.0%Not measuredOnly GPT-5 Nano measured
FrontierMath, tier 42.4%Not measuredOnly GPT-5 Nano measured
ProofBench12.0%Not measuredOnly GPT-5 Nano measured
MATH level 595.2%Not measuredOnly GPT-5 Nano measured
LMArena Text: math13171399Qwen3 32B
LMArena Text: mathematical work13261420Qwen3 32B
Neither model has a result on the other 1 board here
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index05
Knowledge benchmarks for GPT-5 Nano and Qwen3 32B
BenchmarkGPT-5 NanoQwen3 32BLeader
MMLU Pro76.1%Not measuredOnly GPT-5 Nano measured
LegalBench (Vals AI)50.1%Not measuredOnly GPT-5 Nano measured
CaseLaw (Vals AI)52.6%Not measuredOnly GPT-5 Nano measured
TaxEval (Vals AI)67.4%Not measuredOnly GPT-5 Nano measured
MortgageTax (Vals AI)53.6%Not measuredOnly GPT-5 Nano measured
MedQA (Vals AI)93.3%Not measuredOnly GPT-5 Nano measured
MedCode (Vals AI)30.4%Not measuredOnly GPT-5 Nano measured
MMLU Pro (Artificial Analysis run)78.0%79.8%Qwen3 32B
SimpleQA Verified11.7%Not measuredOnly GPT-5 Nano measured
LMArena Text: science13181372Qwen3 32B
LMArena Text: medicine and healthcare13351368Qwen3 32B
LMArena Text: legal and government12981324Qwen3 32B
LMArena Text: business and finance13111318Qwen3 32B
Neither model has a result on the other 5 boards here
Web designDirectional onlyPublic boards, shown as published, kept out of the index6 boards, none shared
Web design benchmarks for GPT-5 Nano and Qwen3 32B
BenchmarkGPT-5 NanoQwen3 32BLeader
Design Arena: websites1101Not measuredOnly GPT-5 Nano measured
Design Arena: UI components1064Not measuredOnly GPT-5 Nano measured
Design Arena: game dev1044Not measuredOnly GPT-5 Nano measured
Design Arena: data viz1056Not measuredOnly GPT-5 Nano measured
Design Arena: 3D965Not measuredOnly GPT-5 Nano measured
Design Arena: all code categories1084Not measuredOnly GPT-5 Nano measured
Neither model has a result on the other 3 boards here
GeneralLike-for-likePublic boards, shown as published, kept out of the index314
General benchmarks for GPT-5 Nano and Qwen3 32B
BenchmarkGPT-5 NanoQwen3 32BLeader
SAGE (Vals AI)30.4%Not measuredOnly GPT-5 Nano measured
MedScribe (Vals AI)72.9%Not measuredOnly GPT-5 Nano measured
IFBench67.6%36.3%GPT-5 Nano
Long context reasoning (AA-LCR)45.0%0.0%GPT-5 Nano
DTBench62.7%67.5%Qwen3 32B
LMCA7.9%17.3%Qwen3 32B
Fiction.LiveBench44.4%74.2%Qwen3 32B
LMArena Text13201340Qwen3 32B
LMArena Text: instruction following13061305GPT-5 Nano
LMArena Text: creative writing12491297Qwen3 32B
LMArena Vision1159Not measuredOnly GPT-5 Nano measured
LMArena Text: English13211359Qwen3 32B
LMArena Text: non-English13131317Qwen3 32B
LMArena Text: Chinese13561357Qwen3 32B
LMArena Text: German13271341Qwen3 32B
LMArena Text: Japanese1227Not measuredOnly GPT-5 Nano measured
LMArena Text: Korean1269Not measuredOnly GPT-5 Nano measured
LMArena Text: Spanish1360Not measuredOnly GPT-5 Nano measured
LMArena Text: Russian12961311Qwen3 32B
LMArena Text: Polish1314Not measuredOnly GPT-5 Nano measured
LMArena Text: multi-turn13111331Qwen3 32B
LMArena Text: longer queries13121327Qwen3 32B
LMArena Text: writing and language12831298Qwen3 32B
LMArena Text: entertainment and media12681279Qwen3 32B
LMArena Vision: English1170Not measuredOnly GPT-5 Nano measured
LMArena Vision: Chinese1176Not measuredOnly GPT-5 Nano measured
LMArena Vision: reading text1152Not measuredOnly GPT-5 Nano measured
LMArena Vision: humor1110Not measuredOnly GPT-5 Nano measured
Neither model has a result on the other 18 boards here
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
Image generation benchmarks for GPT-5 Nano and Qwen3 32B
BenchmarkGPT-5 NanoQwen3 32BLeader
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

GPT-5 Nano$0.0003Fits in one request
Qwen3 32B$0.0003Fits in one request

GPT-5 Nano costs less

Repository review

50K input + 3K output tokens

GPT-5 Nano$0.0037Fits in one request
Qwen3 32B$0.0082Fits in one request

GPT-5 Nano costs less

Agent loop

200K input + 10K output tokens

GPT-5 Nano$0.014Fits in one request
Qwen3 32B$0.032Exceeds the context window

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 GPT-5 Nano and Qwen3 32B
SpecificationOpenAI GPT-5 NanoQwen3 32B
MakerOpenAIQwen
WeightsNo public weights listedOpen weights
ReleasedAugust 7, 2025April 28, 2025
Context window400K131K
Input $/Mtok$0.05$0.14
Output $/Mtok$0.40$0.40
Coding indexNot benchmarkedNot benchmarked
Independent measurements behind it00
Cost per solved task$0.109Not computable
SourceOpenRouter listingOpenRouter listing

Questions

Is GPT-5 Nano better than Qwen3 32B for coding?

Neither model has a coding score yet, so the two cannot be ranked on coding. Pick GPT-5 Nano for a larger context window (400K against 131K tokens) and work measured by LMArena Text: coding or LMArena Text: software and IT, where it leads.

Which is cheaper, GPT-5 Nano or Qwen3 32B?

GPT-5 Nano costs $0.05 per million input tokens and $0.40 per million output tokens; Qwen3 32B costs $0.14 and $0.40. Cost per solved task is known for GPT-5 Nano only.

Which has the bigger context window, GPT-5 Nano or Qwen3 32B?

GPT-5 Nano, with 400K tokens against 131K.

How many benchmarks is the GPT-5 Nano vs Qwen3 32B comparison based on?

42 benchmarks have a result for both models as of October 22, 2026. GPT-5 Nano's coding index rests on 0 independent benchmarks and Qwen3 32B's on 0. Where only one model has a result, the page says so instead of naming a winner.

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