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GPT-4o (2024-08-06) vs Qwen3 30B A3B

GPT-4o (2024-08-06) leads Qwen3 30B A3B on the Artificial Analysis Intelligence Index, 7.7 to 7.6, and Qwen3 30B A3B costs 20.0x less per output token ($0.50 vs $10.00 per million). Updated October 22, 2026; 37 benchmarks have a result for both.

Replace GPT-4o (2024-08-06) Replace Qwen3 30B A3B
GPT-4o (2024-08-06)OpenAI
Coding
No data
Overall
26.3
Output $/M
$10.00
6
Qwen3 30B A3BQwen
Coding
No data
Overall
38.2
Output $/M
$0.50
31
vs boards won of 37 shared

GPT-4o (2024-08-06) or Qwen3 30B A3B: 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 LMArena Text: coding, where it leads.

Model AGPT-4o (2024-08-06)OpenAINot benchmarkedNo coding benchmarkNo cost per solved taskModel BQwen3 30B A3BQwenNot benchmarkedNo coding benchmarkNo cost per solved task
Shared results
37
GPT-4o (2024-08-06) only
21
Qwen3 30B A3B only
16
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-4o (2024-08-06) not benchmarked, Qwen3 30B A3B not benchmarked.
Widest category
Math, 27.1 points apart on average over 3 shared benchmarks.
Widest single gap
OTIS Mock AIME: GPT-4o (2024-08-06) 6.4% against Qwen3 30B A3B 62.8%, 56.4 points apart on a 0 to 100 scale.
Output price
GPT-4o (2024-08-06) $10.00 against Qwen3 30B A3B $0.50 per million output tokens, 20.0x apart.
Context window
GPT-4o (2024-08-06) takes 128K 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-4o (2024-08-06)BarsQwen3 30B A3BTies
Coding13
Intelligence10
Agentic work10
Reasoning06
Math03
Knowledge04
General315
All shared boards631
CodingLike-for-likeSix of these boards feed the Vibe Coding Index13
Coding benchmarks for GPT-4o (2024-08-06) and Qwen3 30B A3B
BenchmarkGPT-4o (2024-08-06)Qwen3 30B A3BLeader
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%50.6%Qwen3 30B A3B
Terminal-Bench Hard (Artificial Analysis run)8.3%6.8%GPT-4o (2024-08-06)
WeirdMLNot measured29.8%Only Qwen3 30B A3B measured
LMArena Text: coding12831337Qwen3 30B A3B
LMArena Text: software and IT12781340Qwen3 30B A3B
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 30B A3B
BenchmarkGPT-4o (2024-08-06)Qwen3 30B A3BLeader
AA Intelligence Index7.77.6GPT-4o (2024-08-06)
Epoch Capabilities IndexNot measured137.3Only Qwen3 30B A3B measured
Agentic workLike-for-likePublic boards, shown as published, kept out of the index10
Agentic work benchmarks for GPT-4o (2024-08-06) and Qwen3 30B A3B
BenchmarkGPT-4o (2024-08-06)Qwen3 30B A3BLeader
τ²-Bench Telecom28.9%26.0%GPT-4o (2024-08-06)
Neither model has a result on the other 41 boards here
ReasoningLike-for-likePublic boards, shown as published, kept out of the index06
Reasoning benchmarks for GPT-4o (2024-08-06) and Qwen3 30B A3B
BenchmarkGPT-4o (2024-08-06)Qwen3 30B A3BLeader
MMMU Pro (Vals AI)64.0%Not measuredOnly GPT-4o (2024-08-06) measured
GPQA Diamond (Artificial Analysis run)52.1%61.6%Qwen3 30B A3B
Humanity's Last Exam (Artificial Analysis run)2.3%6.2%Qwen3 30B A3B
GPQA Diamond (Epoch AI run)49.2%61.7%Qwen3 30B A3B
SimpleBench17.8%Not measuredOnly GPT-4o (2024-08-06) measured
Chess puzzles6.0%Not measuredOnly GPT-4o (2024-08-06) measured
LMArena Text: hard prompts12641314Qwen3 30B A3B
LMArena Text: expert12411314Qwen3 30B A3B
LMArena Text: hard prompts in English12771329Qwen3 30B A3B
Neither model has a result on the other 14 boards here
MathLike-for-likePublic boards, shown as published, kept out of the index03
Math benchmarks for GPT-4o (2024-08-06) and Qwen3 30B A3B
BenchmarkGPT-4o (2024-08-06)Qwen3 30B A3BLeader
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 measured72.3Only Qwen3 30B A3B measured
AIME 2025 (Artificial Analysis run)Not measured72.3%Only Qwen3 30B A3B measured
OTIS Mock AIME6.4%62.8%Qwen3 30B A3B
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: math12851355Qwen3 30B A3B
LMArena Text: mathematical work12831363Qwen3 30B A3B
MathArenaNot measured9.4%Only Qwen3 30B A3B measured
Neither model has a result on the other 3 boards here
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index04
Knowledge benchmarks for GPT-4o (2024-08-06) and Qwen3 30B A3B
BenchmarkGPT-4o (2024-08-06)Qwen3 30B A3BLeader
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 measured77.7%Only Qwen3 30B A3B measured
SimpleQA Verified26.0%Not measuredOnly GPT-4o (2024-08-06) measured
MMLU84.3%Not measuredOnly GPT-4o (2024-08-06) measured
LMArena Text: science12741321Qwen3 30B A3B
LMArena Text: medicine and healthcare12521318Qwen3 30B A3B
LMArena Text: legal and government12751314Qwen3 30B A3B
LMArena Text: business and finance12321309Qwen3 30B A3B
Neither model has a result on the other 7 boards here
Web designDirectional onlyPublic boards, shown as published, kept out of the index5 boards, none shared
Web design benchmarks for GPT-4o (2024-08-06) and Qwen3 30B A3B
BenchmarkGPT-4o (2024-08-06)Qwen3 30B A3BLeader
Design Arena: websitesNot measured954Only Qwen3 30B A3B measured
Design Arena: UI componentsNot measured943Only Qwen3 30B A3B measured
Design Arena: game devNot measured898Only Qwen3 30B A3B measured
Design Arena: data vizNot measured967Only Qwen3 30B A3B measured
Design Arena: all code categoriesNot measured941Only Qwen3 30B A3B measured
Neither model has a result on the other 4 boards here
GeneralLike-for-likePublic boards, shown as published, kept out of the index315
General benchmarks for GPT-4o (2024-08-06) and Qwen3 30B A3B
BenchmarkGPT-4o (2024-08-06)Qwen3 30B A3BLeader
IFBench36.0%41.5%Qwen3 30B A3B
Long context reasoning (AA-LCR)41.0%0.0%GPT-4o (2024-08-06)
DTBenchNot measured60.3%Only Qwen3 30B A3B measured
LMCANot measured15.8%Only Qwen3 30B A3B measured
Fiction.LiveBenchNot measured40.6%Only Qwen3 30B A3B measured
Creative writing (Lech Mazur)Not measured75.3%Only Qwen3 30B A3B measured
LMArena Text12831317Qwen3 30B A3B
LMArena Text: instruction following12671283Qwen3 30B A3B
LMArena Text: creative writing12741271GPT-4o (2024-08-06)
LMArena Vision1065Not measuredOnly GPT-4o (2024-08-06) measured
LMArena Text: English12971335Qwen3 30B A3B
LMArena Text: non-English12621295Qwen3 30B A3B
LMArena Text: Chinese12541347Qwen3 30B A3B
LMArena Text: German12571307Qwen3 30B A3B
LMArena Text: Japanese12341254Qwen3 30B A3B
LMArena Text: Korean12181261Qwen3 30B A3B
LMArena Text: French12631352Qwen3 30B A3B
LMArena Text: Spanish12691317Qwen3 30B A3B
LMArena Text: Russian12721291Qwen3 30B A3B
LMArena Text: PolishNot measured1299Only Qwen3 30B A3B measured
LMArena Text: multi-turn12791307Qwen3 30B A3B
LMArena Text: longer queries12831312Qwen3 30B A3B
LMArena Text: writing and language12901290Qwen3 30B A3B
LMArena Text: entertainment and media12671258GPT-4o (2024-08-06)
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 22 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 30B A3B
BenchmarkGPT-4o (2024-08-06)Qwen3 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-4o (2024-08-06)$0.0075Fits in one request
Qwen3 30B A3B$0.0004Fits in one request

Qwen3 30B A3B costs less

Repository review

50K input + 3K output tokens

GPT-4o (2024-08-06)$0.155Fits in one request
Qwen3 30B A3B$0.0075Exceeds the context window

Qwen3 30B A3B costs less

Agent loop

200K input + 10K output tokens

GPT-4o (2024-08-06)$0.600Exceeds the context window
Qwen3 30B A3B$0.029Exceeds the context window

Qwen3 30B A3B 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 30B A3B
SpecificationOpenAI GPT-4o (2024-08-06)Qwen3 30B A3B
MakerOpenAIQwen
WeightsNo public weights listedOpen weights
ReleasedAugust 6, 2024April 28, 2025
Context window128K41K
Input $/Mtok$2.50$0.12
Output $/Mtok$10.00$0.50
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 30B A3B 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 LMArena Text: coding, where it leads.

Which is cheaper, GPT-4o (2024-08-06) or Qwen3 30B A3B?

GPT-4o (2024-08-06) costs $2.50 per million input tokens and $10.00 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-4o (2024-08-06) or Qwen3 30B A3B?

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

How many benchmarks is the GPT-4o (2024-08-06) vs Qwen3 30B A3B comparison based on?

37 benchmarks have a result for both models as of October 22, 2026. GPT-4o (2024-08-06)'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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