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GPT-4o-mini (2024-07-18) vs Qwen3.5-35B-A3B

GPT-4o-mini (2024-07-18) costs 2.2x less per output token than Qwen3.5-35B-A3B ($0.60 vs $1.30 per million). Updated October 22, 2026; 30 benchmarks have a result for both.

Replace GPT-4o-mini (2024-07-18) Replace Qwen3.5-35B-A3B
GPT-4o-mini (2024-07-18)OpenAI
Coding
No data
Overall
No data
Output $/M
$0.60
0
Qwen3.5-35B-A3BQwen
Coding
No data
Overall
53.5
Output $/M
$1.30
30
vs boards won of 30 shared

GPT-4o-mini (2024-07-18) or Qwen3.5-35B-A3B: 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 output tokens 2.2x cheaper ($0.60 vs $1.30 per million) and 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 BQwen3.5-35B-A3BQwenNot benchmarked1 independent benchmarkNo cost per solved task
Shared results
30
GPT-4o-mini (2024-07-18) only
16
Qwen3.5-35B-A3B only
16
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, Qwen3.5-35B-A3B not benchmarked.
Widest category
Math, 36.3 points apart on average over 3 shared benchmarks.
Widest single gap
OTIS Mock AIME: GPT-4o-mini (2024-07-18) 6.9% against Qwen3.5-35B-A3B 70.0%, 63.1 points apart on a 0 to 100 scale.
Output price
GPT-4o-mini (2024-07-18) $0.60 against Qwen3.5-35B-A3B $1.30 per million output tokens, 2.2x apart.
Context window
GPT-4o-mini (2024-07-18) takes 128K tokens, Qwen3.5-35B-A3B 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)BarsQwen3.5-35B-A3BTies
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 Qwen3.5-35B-A3B
BenchmarkGPT-4o-mini (2024-07-18)Qwen3.5-35B-A3BLeader
Aider polyglot3.6%Not measuredOnly GPT-4o-mini (2024-07-18) measured
LMArena WebDevNot measured1254Only Qwen3.5-35B-A3B measured
Terminal-Bench Hard (Artificial Analysis run)Not measured26.5%Only Qwen3.5-35B-A3B measured
WeirdML11.8%Not measuredOnly GPT-4o-mini (2024-07-18) measured
ALE-BenchNot measured221.8Only Qwen3.5-35B-A3B measured
LMArena Text: coding12901410Qwen3.5-35B-A3B
LMArena Text: software and IT12911415Qwen3.5-35B-A3B
LMArena WebDev: ReactNot measured1238Only Qwen3.5-35B-A3B measured
LMArena WebDev: HTMLNot measured1301Only Qwen3.5-35B-A3B measured
Neither model has a result on the other 34 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 Qwen3.5-35B-A3B
BenchmarkGPT-4o-mini (2024-07-18)Qwen3.5-35B-A3BLeader
AA Intelligence IndexNot measured19.3Only Qwen3.5-35B-A3B measured
Epoch Capabilities IndexNot measured142.5Only Qwen3.5-35B-A3B measured
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 Qwen3.5-35B-A3B
BenchmarkGPT-4o-mini (2024-07-18)Qwen3.5-35B-A3BLeader
τ²-Bench TelecomNot measured89.2%Only Qwen3.5-35B-A3B measured
BALROG17.4%Not measuredOnly GPT-4o-mini (2024-07-18) measured
Vending-Bench 2Not measured$463Only Qwen3.5-35B-A3B 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 Qwen3.5-35B-A3B
BenchmarkGPT-4o-mini (2024-07-18)Qwen3.5-35B-A3BLeader
GPQA Diamond (Artificial Analysis run)Not measured84.5%Only Qwen3.5-35B-A3B measured
Humanity's Last Exam (Artificial Analysis run)Not measured21.0%Only Qwen3.5-35B-A3B measured
GPQA Diamond (Epoch AI run)37.7%83.5%Qwen3.5-35B-A3B
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 prompts12671400Qwen3.5-35B-A3B
LMArena Text: expert12341408Qwen3.5-35B-A3B
LMArena Text: hard prompts in English12781411Qwen3.5-35B-A3B
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 Qwen3.5-35B-A3B
BenchmarkGPT-4o-mini (2024-07-18)Qwen3.5-35B-A3BLeader
OTIS Mock AIME6.9%70.0%Qwen3.5-35B-A3B
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: math12671404Qwen3.5-35B-A3B
LMArena Text: mathematical work12711410Qwen3.5-35B-A3B
MathArenaNot measured14.7%Only Qwen3.5-35B-A3B measured
Neither model has a result on the other 8 boards here
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index04
Knowledge benchmarks for GPT-4o-mini (2024-07-18) and Qwen3.5-35B-A3B
BenchmarkGPT-4o-mini (2024-07-18)Qwen3.5-35B-A3BLeader
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: science12861413Qwen3.5-35B-A3B
LMArena Text: medicine and healthcare12821421Qwen3.5-35B-A3B
LMArena Text: legal and government13051399Qwen3.5-35B-A3B
LMArena Text: business and finance12651394Qwen3.5-35B-A3B
Neither model has a result on the other 13 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 Qwen3.5-35B-A3B
BenchmarkGPT-4o-mini (2024-07-18)Qwen3.5-35B-A3BLeader
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 Qwen3.5-35B-A3B
BenchmarkGPT-4o-mini (2024-07-18)Qwen3.5-35B-A3BLeader
IFBenchNot measured72.5%Only Qwen3.5-35B-A3B measured
Long context reasoning (AA-LCR)Not measured72.0%Only Qwen3.5-35B-A3B measured
DTBenchNot measured80.0%Only Qwen3.5-35B-A3B measured
LMCANot measured29.5%Only Qwen3.5-35B-A3B measured
Creative writing (Lech Mazur)67.2%Not measuredOnly GPT-4o-mini (2024-07-18) measured
LMArena Text12861395Qwen3.5-35B-A3B
LMArena Text: instruction following12581379Qwen3.5-35B-A3B
LMArena Text: creative writing12681347Qwen3.5-35B-A3B
LMArena Vision1066Not measuredOnly GPT-4o-mini (2024-07-18) measured
LMArena Text: English13011407Qwen3.5-35B-A3B
LMArena Text: non-English12661378Qwen3.5-35B-A3B
LMArena Text: Chinese12651457Qwen3.5-35B-A3B
LMArena Text: German12721367Qwen3.5-35B-A3B
LMArena Text: Japanese12161326Qwen3.5-35B-A3B
LMArena Text: Korean11951355Qwen3.5-35B-A3B
LMArena Text: French12971412Qwen3.5-35B-A3B
LMArena Text: Spanish12761390Qwen3.5-35B-A3B
LMArena Text: Russian12751376Qwen3.5-35B-A3B
LMArena Text: Polish12441385Qwen3.5-35B-A3B
LMArena Text: multi-turn12851390Qwen3.5-35B-A3B
LMArena Text: longer queries12891389Qwen3.5-35B-A3B
LMArena Text: writing and language12821365Qwen3.5-35B-A3B
LMArena Text: entertainment and media12531347Qwen3.5-35B-A3B
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 Qwen3.5-35B-A3B
BenchmarkGPT-4o-mini (2024-07-18)Qwen3.5-35B-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-mini (2024-07-18)$0.0004Fits in one request
Qwen3.5-35B-A3B$0.0008Fits in one request

GPT-4o-mini (2024-07-18) costs less

Repository review

50K input + 3K output tokens

GPT-4o-mini (2024-07-18)$0.0093Fits in one request
Qwen3.5-35B-A3B$0.012Fits in one request

GPT-4o-mini (2024-07-18) costs less

Agent loop

200K input + 10K output tokens

GPT-4o-mini (2024-07-18)$0.036Exceeds the context window
Qwen3.5-35B-A3B$0.045Fits in one request

GPT-4o-mini (2024-07-18) 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 Qwen3.5-35B-A3B
SpecificationOpenAI GPT-4o-mini (2024-07-18)Qwen3.5-35B-A3B
MakerOpenAIQwen
WeightsNo public weights listedOpen weights
ReleasedJuly 18, 2024February 25, 2026
Context window128K262K
Input $/Mtok$0.15$0.1625
Output $/Mtok$0.60$1.30
Coding indexNot benchmarkedNot benchmarked
Independent measurements behind it01
Cost per solved taskNot computableNot computable
SourceOpenRouter listingOpenRouter listing

Questions

Is GPT-4o-mini (2024-07-18) better than Qwen3.5-35B-A3B 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 output tokens 2.2x cheaper ($0.60 vs $1.30 per million) and 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 Qwen3.5-35B-A3B?

GPT-4o-mini (2024-07-18) costs $0.15 per million input tokens and $0.60 per million output tokens; Qwen3.5-35B-A3B costs $0.1625 and $1.30. Cost per solved task is known for neither of them.

Which has the bigger context window, GPT-4o-mini (2024-07-18) or Qwen3.5-35B-A3B?

Qwen3.5-35B-A3B, with 262K tokens against 128K.

How many benchmarks is the GPT-4o-mini (2024-07-18) vs Qwen3.5-35B-A3B 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 Qwen3.5-35B-A3B's on 1. Where only one model has a result, the page says so instead of naming a winner.

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