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GPT-4o-mini (2024-07-18) vs Qwen3 30B A3B Instruct 2507

Qwen3 30B A3B Instruct 2507 costs 2.0x less per output token than GPT-4o-mini (2024-07-18) ($0.30 vs $0.60 per million). Updated October 22, 2026; 30 benchmarks have a result for both.

Replace GPT-4o-mini (2024-07-18) Replace Qwen3 30B A3B Instruct 2507
GPT-4o-mini (2024-07-18)OpenAI
Coding
No data
Overall
No data
Output $/M
$0.60
0
Qwen3 30B A3B Instruct 2507Qwen
Coding
No data
Overall
41.5
Output $/M
$0.30
30
vs boards won of 30 shared

GPT-4o-mini (2024-07-18) or Qwen3 30B A3B Instruct 2507: 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 LMArena Text: coding or LMArena Text: software and IT, where it leads.

Model AGPT-4o-mini (2024-07-18)OpenAINot benchmarkedNo coding benchmarkNo cost per solved taskModel BQwen3 30B A3B Instruct 2507QwenNot benchmarkedNo coding benchmarkNo cost per solved task
Shared results
30
GPT-4o-mini (2024-07-18) only
16
Qwen3 30B A3B Instruct 2507 only
15
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 30B A3B Instruct 2507 not benchmarked.
Widest category
Math, 33.3 points apart on average over 3 shared benchmarks.
Widest single gap
OTIS Mock AIME: GPT-4o-mini (2024-07-18) 6.9% against Qwen3 30B A3B Instruct 2507 62.2%, 55.3 points apart on a 0 to 100 scale.
Output price
GPT-4o-mini (2024-07-18) $0.60 against Qwen3 30B A3B Instruct 2507 $0.30 per million output tokens, 2.0x apart.
Context window
GPT-4o-mini (2024-07-18) takes 128K tokens, Qwen3 30B A3B Instruct 2507 262K.

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 30B A3B Instruct 2507Ties
Coding02
Reasoning04
Math03
Knowledge04
General017
All shared boards030
CodingLike-for-likeSix of these boards feed the Vibe Coding Index02
Coding benchmarks for GPT-4o-mini (2024-07-18) and Qwen3 30B A3B Instruct 2507
BenchmarkGPT-4o-mini (2024-07-18)Qwen3 30B A3B Instruct 2507Leader
Aider polyglot3.6%Not measuredOnly GPT-4o-mini (2024-07-18) measured
LiveCodeBench (Artificial Analysis run)Not measured70.7%Only Qwen3 30B A3B Instruct 2507 measured
SciCodeNot measured33.0%Only Qwen3 30B A3B Instruct 2507 measured
Terminal-Bench Hard (Artificial Analysis run)Not measured6.1%Only Qwen3 30B A3B Instruct 2507 measured
WeirdML11.8%Not measuredOnly GPT-4o-mini (2024-07-18) measured
LMArena Text: coding12901416Qwen3 30B A3B Instruct 2507
LMArena Text: software and IT12911417Qwen3 30B A3B Instruct 2507
Neither model has a result on the other 36 boards here
IntelligenceDirectional onlyPublic boards, shown as published, kept out of the index1 board, none shared
Intelligence benchmarks for GPT-4o-mini (2024-07-18) and Qwen3 30B A3B Instruct 2507
BenchmarkGPT-4o-mini (2024-07-18)Qwen3 30B A3B Instruct 2507Leader
AA Intelligence IndexNot measured7.5Only Qwen3 30B A3B Instruct 2507 measured
Neither model has a result on the other 1 board here
Agentic workDirectional onlyPublic boards, shown as published, kept out of the index3 boards, none shared
Agentic work benchmarks for GPT-4o-mini (2024-07-18) and Qwen3 30B A3B Instruct 2507
BenchmarkGPT-4o-mini (2024-07-18)Qwen3 30B A3B Instruct 2507Leader
τ²-Bench TelecomNot measured28.1%Only Qwen3 30B A3B Instruct 2507 measured
BALROG17.4%Not measuredOnly GPT-4o-mini (2024-07-18) measured
Berkeley Function Calling Leaderboard (BFCL)Not measured41.4%Only Qwen3 30B A3B Instruct 2507 measured
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-4o-mini (2024-07-18) and Qwen3 30B A3B Instruct 2507
BenchmarkGPT-4o-mini (2024-07-18)Qwen3 30B A3B Instruct 2507Leader
GPQA Diamond (Artificial Analysis run)Not measured70.7%Only Qwen3 30B A3B Instruct 2507 measured
Humanity's Last Exam (Artificial Analysis run)Not measured10.3%Only Qwen3 30B A3B Instruct 2507 measured
GPQA Diamond (Epoch AI run)37.7%55.6%Qwen3 30B A3B Instruct 2507
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 prompts12671398Qwen3 30B A3B Instruct 2507
LMArena Text: expert12341397Qwen3 30B A3B Instruct 2507
LMArena Text: hard prompts in English12781406Qwen3 30B A3B Instruct 2507
Neither model has a result on the other 13 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 30B A3B Instruct 2507
BenchmarkGPT-4o-mini (2024-07-18)Qwen3 30B A3B Instruct 2507Leader
AA Math IndexNot measured66.3Only Qwen3 30B A3B Instruct 2507 measured
AIME 2025 (Artificial Analysis run)Not measured66.3%Only Qwen3 30B A3B Instruct 2507 measured
OTIS Mock AIME6.9%62.2%Qwen3 30B A3B Instruct 2507
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: math12671394Qwen3 30B A3B Instruct 2507
LMArena Text: mathematical work12711411Qwen3 30B A3B Instruct 2507
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 30B A3B Instruct 2507
BenchmarkGPT-4o-mini (2024-07-18)Qwen3 30B A3B Instruct 2507Leader
MMLU Pro (Artificial Analysis run)Not measured80.5%Only Qwen3 30B A3B Instruct 2507 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: science12861393Qwen3 30B A3B Instruct 2507
LMArena Text: medicine and healthcare12821392Qwen3 30B A3B Instruct 2507
LMArena Text: legal and government13051387Qwen3 30B A3B Instruct 2507
LMArena Text: business and finance12651389Qwen3 30B A3B Instruct 2507
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 30B A3B Instruct 2507
BenchmarkGPT-4o-mini (2024-07-18)Qwen3 30B A3B Instruct 2507Leader
Neither model has a result on 9 boards here
GeneralLike-for-likePublic boards, shown as published, kept out of the index017
General benchmarks for GPT-4o-mini (2024-07-18) and Qwen3 30B A3B Instruct 2507
BenchmarkGPT-4o-mini (2024-07-18)Qwen3 30B A3B Instruct 2507Leader
IFBenchNot measured50.7%Only Qwen3 30B A3B Instruct 2507 measured
Long context reasoning (AA-LCR)Not measured61.3%Only Qwen3 30B A3B Instruct 2507 measured
DTBenchNot measured67.2%Only Qwen3 30B A3B Instruct 2507 measured
LMCANot measured22.4%Only Qwen3 30B A3B Instruct 2507 measured
Creative writing (Lech Mazur)67.2%Not measuredOnly GPT-4o-mini (2024-07-18) measured
LMArena Text12861384Qwen3 30B A3B Instruct 2507
LMArena Text: instruction following12581363Qwen3 30B A3B Instruct 2507
LMArena Text: creative writing12681317Qwen3 30B A3B Instruct 2507
LMArena Vision1066Not measuredOnly GPT-4o-mini (2024-07-18) measured
LMArena Text: English13011391Qwen3 30B A3B Instruct 2507
LMArena Text: non-English12661372Qwen3 30B A3B Instruct 2507
LMArena Text: Chinese12651432Qwen3 30B A3B Instruct 2507
LMArena Text: German12721379Qwen3 30B A3B Instruct 2507
LMArena Text: Japanese12161337Qwen3 30B A3B Instruct 2507
LMArena Text: Korean11951330Qwen3 30B A3B Instruct 2507
LMArena Text: French12971419Qwen3 30B A3B Instruct 2507
LMArena Text: Spanish12761404Qwen3 30B A3B Instruct 2507
LMArena Text: Russian12751369Qwen3 30B A3B Instruct 2507
LMArena Text: Polish12441353Qwen3 30B A3B Instruct 2507
LMArena Text: multi-turn12851378Qwen3 30B A3B Instruct 2507
LMArena Text: longer queries12891378Qwen3 30B A3B Instruct 2507
LMArena Text: writing and language12821336Qwen3 30B A3B Instruct 2507
LMArena Text: entertainment and media12531334Qwen3 30B A3B Instruct 2507
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 23 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 30B A3B Instruct 2507
BenchmarkGPT-4o-mini (2024-07-18)Qwen3 30B A3B Instruct 2507Leader
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 30B A3B Instruct 2507$0.0002Fits in one request

Qwen3 30B A3B Instruct 2507 costs less

Repository review

50K input + 3K output tokens

GPT-4o-mini (2024-07-18)$0.0093Fits in one request
Qwen3 30B A3B Instruct 2507$0.0054Fits in one request

Qwen3 30B A3B Instruct 2507 costs less

Agent loop

200K input + 10K output tokens

GPT-4o-mini (2024-07-18)$0.036Exceeds the context window
Qwen3 30B A3B Instruct 2507$0.021Fits in one request

Qwen3 30B A3B Instruct 2507 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 30B A3B Instruct 2507
SpecificationOpenAI GPT-4o-mini (2024-07-18)Qwen3 30B A3B Instruct 2507
MakerOpenAIQwen
WeightsNo public weights listedOpen weights
ReleasedJuly 18, 2024July 29, 2025
Context window128K262K
Input $/Mtok$0.15$0.09
Output $/Mtok$0.60$0.30
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 30B A3B Instruct 2507 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 LMArena Text: coding or LMArena Text: software and IT, where it leads.

Which is cheaper, GPT-4o-mini (2024-07-18) or Qwen3 30B A3B Instruct 2507?

GPT-4o-mini (2024-07-18) costs $0.15 per million input tokens and $0.60 per million output tokens; Qwen3 30B A3B Instruct 2507 costs $0.09 and $0.30. Cost per solved task is known for neither of them.

Which has the bigger context window, GPT-4o-mini (2024-07-18) or Qwen3 30B A3B Instruct 2507?

Qwen3 30B A3B Instruct 2507, with 262K tokens against 128K.

How many benchmarks is the GPT-4o-mini (2024-07-18) vs Qwen3 30B A3B Instruct 2507 comparison based on?

30 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 30B A3B Instruct 2507's on 0. Where only one model has a result, the page says so instead of naming a winner.

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