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GPT-4o-mini (2024-07-18) vs Qwen3 32B

Qwen3 32B costs 1.5x less per output token than GPT-4o-mini (2024-07-18) ($0.40 vs $0.60 per million). Updated October 22, 2026; 26 benchmarks have a result for both.

Replace GPT-4o-mini (2024-07-18) Replace Qwen3 32B
GPT-4o-mini (2024-07-18)OpenAI
Coding
No data
Overall
No data
Output $/M
$0.60
0
Qwen3 32BQwen
Coding
No data
Overall
40.8
Output $/M
$0.40
26
vs boards won of 26 shared

GPT-4o-mini (2024-07-18) or Qwen3 32B: which to pick

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

Pick GPT-4o-mini (2024-07-18) for work measured by Aider polyglot or LMArena Text: coding, where it leads.

Model AGPT-4o-mini (2024-07-18)OpenAINot benchmarkedNo coding benchmarkNo cost per solved taskModel BQwen3 32BQwenNot benchmarkedNo coding benchmarkNo cost per solved task
Shared results
26
GPT-4o-mini (2024-07-18) only
20
Qwen3 32B only
19
Like-for-like categories
5 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-mini (2024-07-18) not benchmarked, Qwen3 32B not benchmarked.
Widest category
Math, 35.5 points apart on average over 3 shared benchmarks.
Widest single gap
OTIS Mock AIME: GPT-4o-mini (2024-07-18) 6.9% against Qwen3 32B 66.9%, 60.0 points apart on a 0 to 100 scale.
Output price
GPT-4o-mini (2024-07-18) $0.60 against Qwen3 32B $0.40 per million output tokens, 1.5x apart.
Context window
GPT-4o-mini (2024-07-18) takes 128K 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-4o-mini (2024-07-18)BarsQwen3 32BTies
Coding03
Reasoning04
Math03
Knowledge04
General012
All shared boards026
CodingLike-for-likeSix of these boards feed the Vibe Coding Index03
Coding benchmarks for GPT-4o-mini (2024-07-18) and Qwen3 32B
BenchmarkGPT-4o-mini (2024-07-18)Qwen3 32BLeader
Aider polyglot3.6%40.0%Qwen3 32B
LiveCodeBench (Artificial Analysis run)Not measured54.6%Only Qwen3 32B measured
SciCodeNot measured36.0%Only Qwen3 32B measured
Terminal-Bench Hard (Artificial Analysis run)Not measured3.0%Only Qwen3 32B measured
WeirdML11.8%Not measuredOnly GPT-4o-mini (2024-07-18) measured
LMArena Text: coding12901357Qwen3 32B
LMArena Text: software and IT12911366Qwen3 32B
Neither model has a result on the other 36 boards here
IntelligenceDirectional onlyPublic boards, shown as published, kept out of the index2 boards, none shared
Intelligence benchmarks for GPT-4o-mini (2024-07-18) and Qwen3 32B
BenchmarkGPT-4o-mini (2024-07-18)Qwen3 32BLeader
AA Intelligence IndexNot measured7.3Only Qwen3 32B measured
Epoch Capabilities IndexNot measured138.4Only Qwen3 32B measured
Agentic workDirectional onlyPublic boards, shown as published, kept out of the index4 boards, none shared
Agentic work benchmarks for GPT-4o-mini (2024-07-18) and Qwen3 32B
BenchmarkGPT-4o-mini (2024-07-18)Qwen3 32BLeader
τ²-Bench TelecomNot measured29.8%Only Qwen3 32B measured
BALROG17.4%Not measuredOnly GPT-4o-mini (2024-07-18) measured
Berkeley Function Calling Leaderboard (BFCL)Not measured48.7%Only Qwen3 32B measured
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 index04
Reasoning benchmarks for GPT-4o-mini (2024-07-18) and Qwen3 32B
BenchmarkGPT-4o-mini (2024-07-18)Qwen3 32BLeader
GPQA Diamond (Artificial Analysis run)Not measured66.8%Only Qwen3 32B measured
Humanity's Last Exam (Artificial Analysis run)Not measured7.4%Only Qwen3 32B measured
GPQA Diamond (Epoch AI run)37.7%65.7%Qwen3 32B
SimpleBench10.7%Not measuredOnly GPT-4o-mini (2024-07-18) measured
Chess puzzles3.0%Not measuredOnly GPT-4o-mini (2024-07-18) measured
Mystery game puzzles12.0%Not measuredOnly GPT-4o-mini (2024-07-18) measured
VPCT34.0%Not measuredOnly GPT-4o-mini (2024-07-18) measured
LMArena Text: hard prompts12671334Qwen3 32B
LMArena Text: expert12341362Qwen3 32B
LMArena Text: hard prompts in English12781350Qwen3 32B
Kagi LLM BenchmarkNot measured48.7%Only Qwen3 32B measured
Neither model has a result on the other 12 boards here
MathLike-for-likePublic boards, shown as published, kept out of the index03
Math benchmarks for GPT-4o-mini (2024-07-18) and Qwen3 32B
BenchmarkGPT-4o-mini (2024-07-18)Qwen3 32BLeader
AA Math IndexNot measured73.0Only Qwen3 32B measured
AIME 2025 (Artificial Analysis run)Not measured73.0%Only Qwen3 32B measured
OTIS Mock AIME6.9%66.9%Qwen3 32B
FrontierMath, tiers 1 to 30.7%Not measuredOnly GPT-4o-mini (2024-07-18) measured
MATH level 552.6%Not measuredOnly GPT-4o-mini (2024-07-18) measured
LMArena Text: math12671399Qwen3 32B
LMArena Text: mathematical work12711420Qwen3 32B
Neither model has a result on the other 7 boards here
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index04
Knowledge benchmarks for GPT-4o-mini (2024-07-18) and Qwen3 32B
BenchmarkGPT-4o-mini (2024-07-18)Qwen3 32BLeader
MMLU Pro (Artificial Analysis run)Not measured79.8%Only Qwen3 32B measured
SimpleQA Verified8.3%Not measuredOnly GPT-4o-mini (2024-07-18) measured
MMLU76.7%Not measuredOnly GPT-4o-mini (2024-07-18) measured
GeoBench64.0%Not measuredOnly GPT-4o-mini (2024-07-18) measured
LMArena Text: science12861372Qwen3 32B
LMArena Text: medicine and healthcare12821368Qwen3 32B
LMArena Text: legal and government13051324Qwen3 32B
LMArena Text: business and finance12651318Qwen3 32B
Neither model has a result on the other 12 boards here
Web designNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
Web design benchmarks for GPT-4o-mini (2024-07-18) and Qwen3 32B
BenchmarkGPT-4o-mini (2024-07-18)Qwen3 32BLeader
Neither model has a result on 9 boards here
GeneralLike-for-likePublic boards, shown as published, kept out of the index012
General benchmarks for GPT-4o-mini (2024-07-18) and Qwen3 32B
BenchmarkGPT-4o-mini (2024-07-18)Qwen3 32BLeader
IFBenchNot measured36.3%Only Qwen3 32B measured
Long context reasoning (AA-LCR)Not measured0.0%Only Qwen3 32B measured
DTBenchNot measured67.5%Only Qwen3 32B measured
LMCANot measured17.3%Only Qwen3 32B measured
Fiction.LiveBenchNot measured74.2%Only Qwen3 32B measured
Creative writing (Lech Mazur)67.2%Not measuredOnly GPT-4o-mini (2024-07-18) measured
LMArena Text12861340Qwen3 32B
LMArena Text: instruction following12581305Qwen3 32B
LMArena Text: creative writing12681297Qwen3 32B
LMArena Vision1066Not measuredOnly GPT-4o-mini (2024-07-18) measured
LMArena Text: English13011359Qwen3 32B
LMArena Text: non-English12661317Qwen3 32B
LMArena Text: Chinese12651357Qwen3 32B
LMArena Text: German12721341Qwen3 32B
LMArena Text: Japanese1216Not measuredOnly GPT-4o-mini (2024-07-18) measured
LMArena Text: Korean1195Not measuredOnly GPT-4o-mini (2024-07-18) measured
LMArena Text: French1297Not measuredOnly GPT-4o-mini (2024-07-18) measured
LMArena Text: Spanish1276Not measuredOnly GPT-4o-mini (2024-07-18) measured
LMArena Text: Russian12751311Qwen3 32B
LMArena Text: Polish1244Not measuredOnly GPT-4o-mini (2024-07-18) measured
LMArena Text: multi-turn12851331Qwen3 32B
LMArena Text: longer queries12891327Qwen3 32B
LMArena Text: writing and language12821298Qwen3 32B
LMArena Text: entertainment and media12531279Qwen3 32B
LMArena Vision: English1072Not measuredOnly GPT-4o-mini (2024-07-18) measured
LMArena Vision: Chinese1033Not measuredOnly GPT-4o-mini (2024-07-18) 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-mini (2024-07-18) and Qwen3 32B
BenchmarkGPT-4o-mini (2024-07-18)Qwen3 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-4o-mini (2024-07-18)$0.0004Fits in one request
Qwen3 32B$0.0003Fits in one request

Qwen3 32B costs less

Repository review

50K input + 3K output tokens

GPT-4o-mini (2024-07-18)$0.0093Fits in one request
Qwen3 32B$0.0082Fits in one request

Qwen3 32B costs less

Agent loop

200K input + 10K output tokens

GPT-4o-mini (2024-07-18)$0.036Exceeds the context window
Qwen3 32B$0.032Exceeds the context window

Qwen3 32B 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-mini (2024-07-18) and Qwen3 32B
SpecificationOpenAI GPT-4o-mini (2024-07-18)Qwen3 32B
MakerOpenAIQwen
WeightsNo public weights listedOpen weights
ReleasedJuly 18, 2024April 28, 2025
Context window128K131K
Input $/Mtok$0.15$0.14
Output $/Mtok$0.60$0.40
Coding indexNot benchmarkedNot benchmarked
Independent measurements behind it00
Cost per solved taskNot computableNot computable
SourceOpenRouter listingOpenRouter listing

Questions

Is GPT-4o-mini (2024-07-18) better than Qwen3 32B for coding?

Neither model has a coding score yet, so the two cannot be ranked on coding. Pick GPT-4o-mini (2024-07-18) for work measured by Aider polyglot or LMArena Text: coding, where it leads.

Which is cheaper, GPT-4o-mini (2024-07-18) or Qwen3 32B?

GPT-4o-mini (2024-07-18) costs $0.15 per million input tokens and $0.60 per million output tokens; Qwen3 32B costs $0.14 and $0.40. Cost per solved task is known for neither of them.

Which has the bigger context window, GPT-4o-mini (2024-07-18) or Qwen3 32B?

Qwen3 32B, with 131K tokens against 128K.

How many benchmarks is the GPT-4o-mini (2024-07-18) vs Qwen3 32B comparison based on?

26 benchmarks have a result for both models as of October 22, 2026. GPT-4o-mini (2024-07-18)'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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