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GPT-4.1 Nano vs Qwen3 14B

GPT-4.1 Nano leads Qwen3 14B on the Artificial Analysis Intelligence Index, 7.8 to 6.7, and Qwen3 14B costs 1.7x less per output token ($0.23 vs $0.40 per million). Updated October 22, 2026; 19 benchmarks have a result for both.

GPT-4.1 NanoOpenAI
Coding
No data
Overall
24.7
Output $/M
$0.40
2
Qwen3 14BQwen
Coding
No data
Overall
No data
Output $/M
$0.23
17
vs boards won of 19 shared

GPT-4.1 Nano or Qwen3 14B: which to pick

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

Pick GPT-4.1 Nano for a larger context window (1.05M against 41K tokens) and work measured by LiveCodeBench (Artificial Analysis run) or Terminal-Bench Hard (Artificial Analysis run), where it leads.

Shared results
19
GPT-4.1 Nano only
52
Qwen3 14B only
1
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-4.1 Nano not benchmarked, Qwen3 14B not benchmarked.
Widest category
Math, 35.2 points apart on average over 3 shared benchmarks.
Widest single gap
Fiction.LiveBench: GPT-4.1 Nano 25.0% against Qwen3 14B 62.5%, 37.5 points apart on a 0 to 100 scale.
Output price
GPT-4.1 Nano $0.40 against Qwen3 14B $0.23 per million output tokens, 1.7x apart.
Context window
GPT-4.1 Nano takes 1.05M tokens, Qwen3 14B 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 14BTies
Coding02
Intelligence11
Agentic work02
Reasoning04
Math03
Knowledge01
General14
All shared boards217
CodingLike-for-likeSix of these boards feed the Vibe Coding Index02
Coding benchmarks for GPT-4.1 Nano and Qwen3 14B
BenchmarkGPT-4.1 NanoQwen3 14BLeader
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%52.3%Qwen3 14B
SciCodeNot measured30.7%Only Qwen3 14B measured
Terminal-Bench Hard (Artificial Analysis run)3.8%5.3%Qwen3 14B
WeirdML19.0%Not measuredOnly GPT-4.1 Nano measured
LMArena Text: coding1306Not measuredOnly GPT-4.1 Nano measured
LMArena Text: software and IT1305Not measuredOnly GPT-4.1 Nano measured
Neither model has a result on the other 30 boards here
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index11
Intelligence benchmarks for GPT-4.1 Nano and Qwen3 14B
BenchmarkGPT-4.1 NanoQwen3 14BLeader
AA Intelligence Index7.86.7GPT-4.1 Nano
Epoch Capabilities Index129.5138.2Qwen3 14B
Agentic workLike-for-likePublic boards, shown as published, kept out of the index02
Agentic work benchmarks for GPT-4.1 Nano and Qwen3 14B
BenchmarkGPT-4.1 NanoQwen3 14BLeader
τ²-Bench Telecom17.3%34.5%Qwen3 14B
Berkeley Function Calling Leaderboard (BFCL)33.1%41.0%Qwen3 14B
Neither model has a result on the other 39 boards here
ReasoningLike-for-likePublic boards, shown as published, kept out of the index04
Reasoning benchmarks for GPT-4.1 Nano and Qwen3 14B
BenchmarkGPT-4.1 NanoQwen3 14BLeader
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%60.4%Qwen3 14B
Humanity's Last Exam (Artificial Analysis run)3.8%4.5%Qwen3 14B
GPQA Diamond (Epoch AI run)48.9%63.8%Qwen3 14B
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 prompts1286Not measuredOnly GPT-4.1 Nano measured
LMArena Text: expert1271Not measuredOnly GPT-4.1 Nano measured
LMArena Text: hard prompts in English1293Not measuredOnly GPT-4.1 Nano measured
Kagi LLM Benchmark33.3%49.1%Qwen3 14B
Neither model has a result on the other 10 boards here
MathLike-for-likePublic boards, shown as published, kept out of the index03
Math benchmarks for GPT-4.1 Nano and Qwen3 14B
BenchmarkGPT-4.1 NanoQwen3 14BLeader
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 Index24.058.0Qwen3 14B
AIME 2025 (Artificial Analysis run)24.0%58.0%Qwen3 14B
OTIS Mock AIME28.9%66.4%Qwen3 14B
MATH level 570.0%Not measuredOnly GPT-4.1 Nano measured
LMArena Text: math1274Not measuredOnly GPT-4.1 Nano measured
LMArena Text: mathematical work1274Not measuredOnly GPT-4.1 Nano measured
Neither model has a result on the other 4 boards here
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index01
Knowledge benchmarks for GPT-4.1 Nano and Qwen3 14B
BenchmarkGPT-4.1 NanoQwen3 14BLeader
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%77.4%Qwen3 14B
SimpleQA Verified6.0%Not measuredOnly GPT-4.1 Nano measured
LMArena Text: science1297Not measuredOnly GPT-4.1 Nano measured
LMArena Text: medicine and healthcare1276Not measuredOnly GPT-4.1 Nano measured
LMArena Text: legal and government1300Not measuredOnly GPT-4.1 Nano measured
LMArena Text: business and finance1267Not measuredOnly GPT-4.1 Nano measured
Neither model has a result on the other 6 boards here
Web designDirectional onlyPublic boards, shown as published, kept out of the index6 boards, none shared
Web design benchmarks for GPT-4.1 Nano and Qwen3 14B
BenchmarkGPT-4.1 NanoQwen3 14BLeader
Design Arena: websites972Not measuredOnly GPT-4.1 Nano measured
Design Arena: UI components913Not measuredOnly GPT-4.1 Nano measured
Design Arena: game dev970Not measuredOnly GPT-4.1 Nano measured
Design Arena: data viz891Not measuredOnly GPT-4.1 Nano measured
Design Arena: 3D924Not measuredOnly GPT-4.1 Nano measured
Design Arena: all code categories962Not measuredOnly GPT-4.1 Nano measured
Neither model has a result on the other 3 boards here
GeneralLike-for-likePublic boards, shown as published, kept out of the index14
General benchmarks for GPT-4.1 Nano and Qwen3 14B
BenchmarkGPT-4.1 NanoQwen3 14BLeader
IFBench32.0%40.5%Qwen3 14B
Long context reasoning (AA-LCR)20.3%0.0%GPT-4.1 Nano
DTBench52.5%64.0%Qwen3 14B
LMCA5.5%18.2%Qwen3 14B
Fiction.LiveBench25.0%62.5%Qwen3 14B
LMArena Text1285Not measuredOnly GPT-4.1 Nano measured
LMArena Text: instruction following1266Not measuredOnly GPT-4.1 Nano measured
LMArena Text: creative writing1260Not measuredOnly GPT-4.1 Nano measured
LMArena Vision1063Not measuredOnly GPT-4.1 Nano measured
LMArena Text: English1303Not measuredOnly GPT-4.1 Nano measured
LMArena Text: non-English1260Not measuredOnly GPT-4.1 Nano measured
LMArena Text: Chinese1270Not measuredOnly GPT-4.1 Nano measured
LMArena Text: German1288Not measuredOnly GPT-4.1 Nano measured
LMArena Text: Japanese1198Not measuredOnly GPT-4.1 Nano measured
LMArena Text: Russian1261Not measuredOnly GPT-4.1 Nano measured
LMArena Text: multi-turn1277Not measuredOnly GPT-4.1 Nano measured
LMArena Text: longer queries1283Not measuredOnly GPT-4.1 Nano measured
LMArena Text: writing and language1261Not measuredOnly GPT-4.1 Nano measured
LMArena Text: entertainment and media1243Not measuredOnly GPT-4.1 Nano measured
LMArena Vision: English1101Not measuredOnly GPT-4.1 Nano measured
Neither model has a result on the other 26 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 14B
BenchmarkGPT-4.1 NanoQwen3 14BLeader
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 14B$0.0002Fits in one request

Qwen3 14B costs less

Repository review

50K input + 3K output tokens

GPT-4.1 Nano$0.0062Fits in one request
Qwen3 14B$0.0062Exceeds the context window

Qwen3 14B costs less

Agent loop

200K input + 10K output tokens

GPT-4.1 Nano$0.024Fits in one request
Qwen3 14B$0.024Exceeds 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 14B
SpecificationOpenAI GPT-4.1 NanoQwen3 14B
MakerOpenAIQwen
WeightsNo public weights listedOpen weights
ReleasedApril 14, 2025April 28, 2025
Context window1.05M41K
Input $/Mtok$0.10$0.11
Output $/Mtok$0.40$0.23
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 14B for coding?

Neither model has a coding score yet, so the two cannot be ranked on coding. Pick GPT-4.1 Nano for a larger context window (1.05M against 41K tokens) and work measured by LiveCodeBench (Artificial Analysis run) or Terminal-Bench Hard (Artificial Analysis run), where it leads.

Which is cheaper, GPT-4.1 Nano or Qwen3 14B?

GPT-4.1 Nano costs $0.10 per million input tokens and $0.40 per million output tokens; Qwen3 14B costs $0.11 and $0.23. Cost per solved task is known for neither of them.

Which has the bigger context window, GPT-4.1 Nano or Qwen3 14B?

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

How many benchmarks is the GPT-4.1 Nano vs Qwen3 14B comparison based on?

19 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 14B's on 0. Where only one model has a result, the page says so instead of naming a winner.

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