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GPT-4o (2024-08-06) vs Qwen3 14B

GPT-4o (2024-08-06) leads Qwen3 14B on the Artificial Analysis Intelligence Index, 7.7 to 6.7, and Qwen3 14B costs 43.5x less per output token ($0.23 vs $10.00 per million). Updated October 23, 2026; 10 benchmarks have a result for both.

Replace GPT-4o (2024-08-06) Replace Qwen3 14B
GPT-4o (2024-08-06)OpenAI
Coding
No data
Overall
26.3
Output $/M
$10.00
3
Qwen3 14BQwen
Coding
No data
Overall
No data
Output $/M
$0.23
7
vs boards won of 10 shared

GPT-4o (2024-08-06) or Qwen3 14B: which to pick

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

Pick GPT-4o (2024-08-06) for a larger context window (128K against 41K tokens) and work measured by LiveCodeBench (Artificial Analysis run) or τ²-Bench Telecom, where it leads.

Model AGPT-4o (2024-08-06)OpenAINot benchmarkedNo coding benchmarkNo cost per solved taskModel BQwen3 14BQwenNot benchmarkedNo coding benchmarkNo cost per solved task
Shared results
10
GPT-4o (2024-08-06) only
48
Qwen3 14B only
10
Like-for-like categories
6 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-4o (2024-08-06) not benchmarked, Qwen3 14B not benchmarked.
Widest category
Math, 60.0 points apart on average over 1 shared benchmark.
Widest single gap
OTIS Mock AIME: GPT-4o (2024-08-06) 6.4% against Qwen3 14B 66.4%, 60.0 points apart on a 0 to 100 scale.
Output price
GPT-4o (2024-08-06) $10.00 against Qwen3 14B $0.23 per million output tokens, 43.5x apart.
Context window
GPT-4o (2024-08-06) takes 128K 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-4o (2024-08-06)BarsQwen3 14BTies
Coding11
Intelligence10
Agentic work01
Reasoning03
Math01
General11
All shared boards37
CodingLike-for-likeSix of these boards feed the Vibe Coding Index11
Coding benchmarks for GPT-4o (2024-08-06) and Qwen3 14B
BenchmarkGPT-4o (2024-08-06)Qwen3 14BLeader
Aider polyglot23.1%Not measuredOnly GPT-4o (2024-08-06) measured
SWE-bench Lite21.7%Not measuredOnly GPT-4o (2024-08-06) measured
LiveCodeBench (Artificial Analysis run)31.7%52.3%Qwen3 14B
SciCodeNot measured30.7%Only Qwen3 14B measured
Terminal-Bench Hard (Artificial Analysis run)8.3%5.3%GPT-4o (2024-08-06)
LMArena Text: coding1283Not measuredOnly GPT-4o (2024-08-06) measured
LMArena Text: software and IT1278Not measuredOnly GPT-4o (2024-08-06) measured
Neither model has a result on the other 36 boards here
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index10
Intelligence benchmarks for GPT-4o (2024-08-06) and Qwen3 14B
BenchmarkGPT-4o (2024-08-06)Qwen3 14BLeader
AA Intelligence Index7.76.7GPT-4o (2024-08-06)
Epoch Capabilities IndexNot measured138.2Only Qwen3 14B measured
Agentic workLike-for-likePublic boards, shown as published, kept out of the index01
Agentic work benchmarks for GPT-4o (2024-08-06) and Qwen3 14B
BenchmarkGPT-4o (2024-08-06)Qwen3 14BLeader
τ²-Bench Telecom28.9%34.5%Qwen3 14B
Berkeley Function Calling Leaderboard (BFCL)Not measured41.0%Only Qwen3 14B measured
Neither model has a result on the other 40 boards here
ReasoningLike-for-likePublic boards, shown as published, kept out of the index03
Reasoning benchmarks for GPT-4o (2024-08-06) and Qwen3 14B
BenchmarkGPT-4o (2024-08-06)Qwen3 14BLeader
MMMU Pro (Vals AI)64.0%Not measuredOnly GPT-4o (2024-08-06) measured
GPQA Diamond (Artificial Analysis run)52.1%60.4%Qwen3 14B
Humanity's Last Exam (Artificial Analysis run)2.3%4.5%Qwen3 14B
GPQA Diamond (Epoch AI run)49.2%63.8%Qwen3 14B
SimpleBench17.8%Not measuredOnly GPT-4o (2024-08-06) measured
Chess puzzles6.0%Not measuredOnly GPT-4o (2024-08-06) measured
LMArena Text: hard prompts1264Not measuredOnly GPT-4o (2024-08-06) measured
LMArena Text: expert1241Not measuredOnly GPT-4o (2024-08-06) measured
LMArena Text: hard prompts in English1277Not measuredOnly GPT-4o (2024-08-06) measured
Kagi LLM BenchmarkNot measured49.1%Only Qwen3 14B measured
Neither model has a result on the other 13 boards here
MathLike-for-likePublic boards, shown as published, kept out of the index01
Math benchmarks for GPT-4o (2024-08-06) and Qwen3 14B
BenchmarkGPT-4o (2024-08-06)Qwen3 14BLeader
AIME14.0%Not measuredOnly GPT-4o (2024-08-06) measured
MATH 500 (Vals AI)75.2%Not measuredOnly GPT-4o (2024-08-06) measured
MGSM (Vals AI)90.7%Not measuredOnly GPT-4o (2024-08-06) measured
AA Math IndexNot measured58.0Only Qwen3 14B measured
AIME 2025 (Artificial Analysis run)Not measured58.0%Only Qwen3 14B measured
OTIS Mock AIME6.4%66.4%Qwen3 14B
FrontierMath, tiers 1 to 30.4%Not measuredOnly GPT-4o (2024-08-06) measured
MATH level 553.3%Not measuredOnly GPT-4o (2024-08-06) measured
LMArena Text: math1285Not measuredOnly GPT-4o (2024-08-06) measured
LMArena Text: mathematical work1283Not measuredOnly GPT-4o (2024-08-06) measured
Neither model has a result on the other 4 boards here
KnowledgeDirectional onlyPublic boards, shown as published, kept out of the index13 boards, none shared
Knowledge benchmarks for GPT-4o (2024-08-06) and Qwen3 14B
BenchmarkGPT-4o (2024-08-06)Qwen3 14BLeader
MMLU Pro74.1%Not measuredOnly GPT-4o (2024-08-06) measured
LegalBench (Vals AI)80.1%Not measuredOnly GPT-4o (2024-08-06) measured
CorpFin (Vals AI)39.4%Not measuredOnly GPT-4o (2024-08-06) measured
TaxEval (Vals AI)71.1%Not measuredOnly GPT-4o (2024-08-06) measured
MortgageTax (Vals AI)61.0%Not measuredOnly GPT-4o (2024-08-06) measured
MedQA (Vals AI)88.2%Not measuredOnly GPT-4o (2024-08-06) measured
MMLU Pro (Artificial Analysis run)Not measured77.4%Only Qwen3 14B measured
SimpleQA Verified26.0%Not measuredOnly GPT-4o (2024-08-06) measured
MMLU84.3%Not measuredOnly GPT-4o (2024-08-06) measured
LMArena Text: science1274Not measuredOnly GPT-4o (2024-08-06) measured
LMArena Text: medicine and healthcare1252Not measuredOnly GPT-4o (2024-08-06) measured
LMArena Text: legal and government1275Not measuredOnly GPT-4o (2024-08-06) measured
LMArena Text: business and finance1232Not measuredOnly GPT-4o (2024-08-06) measured
Neither model has a result on the other 7 boards here
Web designNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
Web design benchmarks for GPT-4o (2024-08-06) and Qwen3 14B
BenchmarkGPT-4o (2024-08-06)Qwen3 14BLeader
Neither model has a result on 9 boards here
GeneralLike-for-likePublic boards, shown as published, kept out of the index11
General benchmarks for GPT-4o (2024-08-06) and Qwen3 14B
BenchmarkGPT-4o (2024-08-06)Qwen3 14BLeader
IFBench36.0%40.5%Qwen3 14B
Long context reasoning (AA-LCR)41.0%0.0%GPT-4o (2024-08-06)
DTBenchNot measured64.0%Only Qwen3 14B measured
LMCANot measured18.2%Only Qwen3 14B measured
Fiction.LiveBenchNot measured62.5%Only Qwen3 14B measured
LMArena Text1283Not measuredOnly GPT-4o (2024-08-06) measured
LMArena Text: instruction following1267Not measuredOnly GPT-4o (2024-08-06) measured
LMArena Text: creative writing1274Not measuredOnly GPT-4o (2024-08-06) measured
LMArena Vision1065Not measuredOnly GPT-4o (2024-08-06) measured
LMArena Text: English1297Not measuredOnly GPT-4o (2024-08-06) measured
LMArena Text: non-English1262Not measuredOnly GPT-4o (2024-08-06) measured
LMArena Text: Chinese1254Not measuredOnly GPT-4o (2024-08-06) measured
LMArena Text: German1257Not measuredOnly GPT-4o (2024-08-06) measured
LMArena Text: Japanese1234Not measuredOnly GPT-4o (2024-08-06) measured
LMArena Text: Korean1218Not measuredOnly GPT-4o (2024-08-06) measured
LMArena Text: French1263Not measuredOnly GPT-4o (2024-08-06) measured
LMArena Text: Spanish1269Not measuredOnly GPT-4o (2024-08-06) measured
LMArena Text: Russian1272Not measuredOnly GPT-4o (2024-08-06) measured
LMArena Text: multi-turn1279Not measuredOnly GPT-4o (2024-08-06) measured
LMArena Text: longer queries1283Not measuredOnly GPT-4o (2024-08-06) measured
LMArena Text: writing and language1290Not measuredOnly GPT-4o (2024-08-06) measured
LMArena Text: entertainment and media1267Not measuredOnly GPT-4o (2024-08-06) measured
LMArena Vision: English1072Not measuredOnly GPT-4o (2024-08-06) measured
LMArena Vision: Chinese1009Not measuredOnly GPT-4o (2024-08-06) measured
Neither model has a result on the other 24 boards here
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
Image generation benchmarks for GPT-4o (2024-08-06) and Qwen3 14B
BenchmarkGPT-4o (2024-08-06)Qwen3 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-4o (2024-08-06)$0.0075Fits in one request
Qwen3 14B$0.0002Fits in one request

Qwen3 14B costs less

Repository review

50K input + 3K output tokens

GPT-4o (2024-08-06)$0.155Fits in one request
Qwen3 14B$0.0062Exceeds the context window

Qwen3 14B costs less

Agent loop

200K input + 10K output tokens

GPT-4o (2024-08-06)$0.600Exceeds the context window
Qwen3 14B$0.024Exceeds the context window

Qwen3 14B 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-4o (2024-08-06) and Qwen3 14B
SpecificationOpenAI GPT-4o (2024-08-06)Qwen3 14B
MakerOpenAIQwen
WeightsNo public weights listedOpen weights
ReleasedAugust 6, 2024April 28, 2025
Context window128K41K
Input $/Mtok$2.50$0.11
Output $/Mtok$10.00$0.23
Coding indexNot benchmarkedNot benchmarked
Independent measurements behind it00
Cost per solved taskNot computableNot computable
SourceOpenRouter listingOpenRouter listing

Questions

Is GPT-4o (2024-08-06) better than Qwen3 14B for coding?

Neither model has a coding score yet, so the two cannot be ranked on coding. Pick GPT-4o (2024-08-06) for a larger context window (128K against 41K tokens) and work measured by LiveCodeBench (Artificial Analysis run) or τ²-Bench Telecom, where it leads.

Which is cheaper, GPT-4o (2024-08-06) or Qwen3 14B?

GPT-4o (2024-08-06) costs $2.50 per million input tokens and $10.00 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-4o (2024-08-06) or Qwen3 14B?

GPT-4o (2024-08-06), with 128K tokens against 41K.

How many benchmarks is the GPT-4o (2024-08-06) vs Qwen3 14B comparison based on?

10 benchmarks have a result for both models as of October 23, 2026. GPT-4o (2024-08-06)'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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