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GPT-4.1 Nano vs Qwen3 30B A3B

GPT-4.1 Nano leads Qwen3 30B A3B on the Artificial Analysis Intelligence Index, 7.8 to 7.6, and GPT-4.1 Nano costs 1.3x less per output token ($0.40 vs $0.50 per million). Updated October 22, 2026; 47 benchmarks have a result for both.

Replace GPT-4.1 Nano Replace Qwen3 30B A3B
GPT-4.1 NanoOpenAI
Coding
No data
Overall
24.7
Output $/M
$0.40
5
Qwen3 30B A3BQwen
Coding
No data
Overall
38.2
Output $/M
$0.50
42
vs boards won of 47 shared

GPT-4.1 Nano or Qwen3 30B A3B: which to pick

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

Pick GPT-4.1 Nano for output tokens 1.3x cheaper ($0.40 vs $0.50 per million) and a larger context window (1.05M against 41K tokens).

Model AGPT-4.1 NanoOpenAINot benchmarkedNo coding benchmarkNo cost per solved taskModel BQwen3 30B A3BQwenNot benchmarkedNo coding benchmarkNo cost per solved task
Shared results
47
GPT-4.1 Nano only
24
Qwen3 30B A3B only
6
Like-for-like categories
8 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-4.1 Nano not benchmarked, Qwen3 30B A3B not benchmarked.
Widest category
Math, 31.7 points apart on average over 5 shared benchmarks.
Widest single gap
AIME 2025 (Artificial Analysis run): GPT-4.1 Nano 24.0% against Qwen3 30B A3B 72.3%, 48.3 points apart on a 0 to 100 scale.
Output price
GPT-4.1 Nano $0.40 against Qwen3 30B A3B $0.50 per million output tokens, 1.3x apart.
Context window
GPT-4.1 Nano takes 1.05M tokens, Qwen3 30B A3B 41K.

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-4.1 NanoBarsQwen3 30B A3BTies
Coding05
Intelligence11
Agentic work01
Reasoning06
Math05
Knowledge05
Web design32
General117
All shared boards542
CodingLike-for-likeSix of these boards feed the Vibe Coding Index05
Coding benchmarks for GPT-4.1 Nano and Qwen3 30B A3B
BenchmarkGPT-4.1 NanoQwen3 30B A3BLeader
Aider polyglot8.9%Not measuredOnly GPT-4.1 Nano measured
AA Coding Index11.1Not measuredOnly GPT-4.1 Nano measured
LiveCodeBench (Vals AI)42.7%Not measuredOnly GPT-4.1 Nano measured
LiveCodeBench (Artificial Analysis run)32.6%50.6%Qwen3 30B A3B
Terminal-Bench Hard (Artificial Analysis run)3.8%6.8%Qwen3 30B A3B
WeirdML19.0%29.8%Qwen3 30B A3B
LMArena Text: coding13061337Qwen3 30B A3B
LMArena Text: software and IT13051340Qwen3 30B A3B
Neither model has a result on the other 35 boards here
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index11
Intelligence benchmarks for GPT-4.1 Nano and Qwen3 30B A3B
BenchmarkGPT-4.1 NanoQwen3 30B A3BLeader
AA Intelligence Index7.87.6GPT-4.1 Nano
Epoch Capabilities Index129.5137.3Qwen3 30B A3B
Agentic workLike-for-likePublic boards, shown as published, kept out of the index01
Agentic work benchmarks for GPT-4.1 Nano and Qwen3 30B A3B
BenchmarkGPT-4.1 NanoQwen3 30B A3BLeader
τ²-Bench Telecom17.3%26.0%Qwen3 30B A3B
Berkeley Function Calling Leaderboard (BFCL)33.1%Not measuredOnly GPT-4.1 Nano measured
Neither model has a result on the other 40 boards here
ReasoningLike-for-likePublic boards, shown as published, kept out of the index06
Reasoning benchmarks for GPT-4.1 Nano and Qwen3 30B A3B
BenchmarkGPT-4.1 NanoQwen3 30B A3BLeader
GPQA Diamond50.8%Not measuredOnly GPT-4.1 Nano measured
MMMU Pro (Vals AI)55.0%Not measuredOnly GPT-4.1 Nano measured
GPQA Diamond (Artificial Analysis run)51.2%61.6%Qwen3 30B A3B
Humanity's Last Exam (Artificial Analysis run)3.8%6.2%Qwen3 30B A3B
GPQA Diamond (Epoch AI run)48.9%61.7%Qwen3 30B A3B
ARC-AGI0.0%Not measuredOnly GPT-4.1 Nano measured
ARC-AGI-20.0%Not measuredOnly GPT-4.1 Nano measured
Chess puzzles0.0%Not measuredOnly GPT-4.1 Nano measured
LMArena Text: hard prompts12861314Qwen3 30B A3B
LMArena Text: expert12711314Qwen3 30B A3B
LMArena Text: hard prompts in English12931329Qwen3 30B A3B
Kagi LLM Benchmark33.3%Not measuredOnly GPT-4.1 Nano measured
Neither model has a result on the other 11 boards here
MathLike-for-likePublic boards, shown as published, kept out of the index05
Math benchmarks for GPT-4.1 Nano and Qwen3 30B A3B
BenchmarkGPT-4.1 NanoQwen3 30B A3BLeader
AIME26.5%Not measuredOnly GPT-4.1 Nano measured
MATH 500 (Vals AI)80.2%Not measuredOnly GPT-4.1 Nano measured
MGSM (Vals AI)69.3%Not measuredOnly GPT-4.1 Nano measured
AA Math Index24.072.3Qwen3 30B A3B
AIME 2025 (Artificial Analysis run)24.0%72.3%Qwen3 30B A3B
OTIS Mock AIME28.9%62.8%Qwen3 30B A3B
MATH level 570.0%Not measuredOnly GPT-4.1 Nano measured
LMArena Text: math12741355Qwen3 30B A3B
LMArena Text: mathematical work12741363Qwen3 30B A3B
MathArenaNot measured9.4%Only Qwen3 30B A3B measured
Neither model has a result on the other 4 boards here
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index05
Knowledge benchmarks for GPT-4.1 Nano and Qwen3 30B A3B
BenchmarkGPT-4.1 NanoQwen3 30B A3BLeader
MMLU Pro63.5%Not measuredOnly GPT-4.1 Nano measured
LegalBench (Vals AI)61.1%Not measuredOnly GPT-4.1 Nano measured
CorpFin (Vals AI)42.1%Not measuredOnly GPT-4.1 Nano measured
TaxEval (Vals AI)60.8%Not measuredOnly GPT-4.1 Nano measured
MortgageTax (Vals AI)52.8%Not measuredOnly GPT-4.1 Nano measured
MedQA (Vals AI)68.2%Not measuredOnly GPT-4.1 Nano measured
MMLU Pro (Artificial Analysis run)65.7%77.7%Qwen3 30B A3B
SimpleQA Verified6.0%Not measuredOnly GPT-4.1 Nano measured
LMArena Text: science12971321Qwen3 30B A3B
LMArena Text: medicine and healthcare12761318Qwen3 30B A3B
LMArena Text: legal and government13001314Qwen3 30B A3B
LMArena Text: business and finance12671309Qwen3 30B A3B
Neither model has a result on the other 8 boards here
Web designLike-for-likePublic boards, shown as published, kept out of the index32
Web design benchmarks for GPT-4.1 Nano and Qwen3 30B A3B
BenchmarkGPT-4.1 NanoQwen3 30B A3BLeader
Design Arena: websites973954GPT-4.1 Nano
Design Arena: UI components913943Qwen3 30B A3B
Design Arena: game dev970898GPT-4.1 Nano
Design Arena: data viz891967Qwen3 30B A3B
Design Arena: 3D924Not measuredOnly GPT-4.1 Nano measured
Design Arena: all code categories962941GPT-4.1 Nano
Neither model has a result on the other 3 boards here
GeneralLike-for-likePublic boards, shown as published, kept out of the index117
General benchmarks for GPT-4.1 Nano and Qwen3 30B A3B
BenchmarkGPT-4.1 NanoQwen3 30B A3BLeader
IFBench32.0%41.5%Qwen3 30B A3B
Long context reasoning (AA-LCR)20.3%0.0%GPT-4.1 Nano
DTBench52.5%60.3%Qwen3 30B A3B
LMCA5.5%15.8%Qwen3 30B A3B
Fiction.LiveBench25.0%40.6%Qwen3 30B A3B
Creative writing (Lech Mazur)Not measured75.3%Only Qwen3 30B A3B measured
LMArena Text12851317Qwen3 30B A3B
LMArena Text: instruction following12661283Qwen3 30B A3B
LMArena Text: creative writing12601271Qwen3 30B A3B
LMArena Vision1063Not measuredOnly GPT-4.1 Nano measured
LMArena Text: English13031335Qwen3 30B A3B
LMArena Text: non-English12601295Qwen3 30B A3B
LMArena Text: Chinese12701347Qwen3 30B A3B
LMArena Text: German12881307Qwen3 30B A3B
LMArena Text: Japanese11981254Qwen3 30B A3B
LMArena Text: KoreanNot measured1261Only Qwen3 30B A3B measured
LMArena Text: FrenchNot measured1352Only Qwen3 30B A3B measured
LMArena Text: SpanishNot measured1317Only Qwen3 30B A3B measured
LMArena Text: Russian12611291Qwen3 30B A3B
LMArena Text: PolishNot measured1299Only Qwen3 30B A3B measured
LMArena Text: multi-turn12771307Qwen3 30B A3B
LMArena Text: longer queries12831312Qwen3 30B A3B
LMArena Text: writing and language12611290Qwen3 30B A3B
LMArena Text: entertainment and media12431258Qwen3 30B A3B
LMArena Vision: English1101Not measuredOnly GPT-4.1 Nano measured
Neither model has a result on the other 23 boards here
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
Image generation benchmarks for GPT-4.1 Nano and Qwen3 30B A3B
BenchmarkGPT-4.1 NanoQwen3 30B A3BLeader
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-4.1 Nano$0.0003Fits in one request
Qwen3 30B A3B$0.0004Fits in one request

GPT-4.1 Nano costs less

Repository review

50K input + 3K output tokens

GPT-4.1 Nano$0.0062Fits in one request
Qwen3 30B A3B$0.0075Exceeds the context window

GPT-4.1 Nano costs less

Agent loop

200K input + 10K output tokens

GPT-4.1 Nano$0.024Fits in one request
Qwen3 30B A3B$0.029Exceeds the context window

GPT-4.1 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-4.1 Nano and Qwen3 30B A3B
SpecificationOpenAI GPT-4.1 NanoQwen3 30B A3B
MakerOpenAIQwen
WeightsNo public weights listedOpen weights
ReleasedApril 14, 2025April 28, 2025
Context window1.05M41K
Input $/Mtok$0.10$0.12
Output $/Mtok$0.40$0.50
Coding indexNot benchmarkedNot benchmarked
Independent measurements behind it00
Cost per solved taskNot computableNot computable
SourceOpenRouter listingOpenRouter listing

Questions

Is GPT-4.1 Nano better than Qwen3 30B A3B for coding?

Neither model has a coding score yet, so the two cannot be ranked on coding. Pick GPT-4.1 Nano for output tokens 1.3x cheaper ($0.40 vs $0.50 per million) and a larger context window (1.05M against 41K tokens).

Which is cheaper, GPT-4.1 Nano or Qwen3 30B A3B?

GPT-4.1 Nano costs $0.10 per million input tokens and $0.40 per million output tokens; Qwen3 30B A3B costs $0.12 and $0.50. Cost per solved task is known for neither of them.

Which has the bigger context window, GPT-4.1 Nano or Qwen3 30B A3B?

GPT-4.1 Nano, with 1.05M tokens against 41K.

How many benchmarks is the GPT-4.1 Nano vs Qwen3 30B A3B comparison based on?

47 benchmarks have a result for both models as of October 22, 2026. GPT-4.1 Nano's coding index rests on 0 independent benchmarks and Qwen3 30B A3B's on 0. Where only one model has a result, the page says so instead of naming a winner.

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