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GPT-4o (2024-08-06) vs Qwen3.5-35B-A3B

Updated October 21, 2026. 36 benchmarks have a result for both. Coding is ranked on the Vibe Coding Index; every other board is shown as published.

Replace GPT-4o (2024-08-06) Replace Qwen3.5-35B-A3B
GPT-4o (2024-08-06)OpenAI
Coding
23.1
Overall
7.7
Output $/M
$10.00
0
Qwen3.5-35B-A3BQwen
Coding
7.7
Overall
19.3
Output $/M
$1.00
36
vs boards won of 36 shared

Decision reading

Pick GPT-4o (2024-08-06) for coding: it scores 23.1 on the Vibe Coding Index against 7.7 for Qwen3.5-35B-A3B.

Pick Qwen3.5-35B-A3B when output tokens cost 10.0x less, or when the context window is larger, 262K against 128K tokens.

Model AGPT-4o (2024-08-06)OpenAI23.1/1001 independent benchmarkNo cost per solved taskModel BQwen3.5-35B-A3BQwen7.7/1001 independent benchmarkNo cost per solved task
Shared results
36
GPT-4o (2024-08-06) only
22
Qwen3.5-35B-A3B only
9
Like-for-like categories
7 of 9

Shared results can support a head-to-head reading. Results only one model has describe coverage, not superiority.

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) 23.1 from 1 benchmark, Qwen3.5-35B-A3B 7.7 from 1 benchmark.
Widest category
Agentic work, 60.2 points apart on average over 1 shared benchmark.
Widest single gap
OTIS Mock AIME: GPT-4o (2024-08-06) 6.4% against Qwen3.5-35B-A3B 70.0%, 63.6 points apart on a 0 to 100 scale.
Output price
GPT-4o (2024-08-06) $10.00 against Qwen3.5-35B-A3B $1.00 per million output tokens, 10.0x apart.
Context window
GPT-4o (2024-08-06) 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 (2024-08-06)BarsQwen3.5-35B-A3BTies
Coding03
Intelligence01
Agentic work01
Reasoning06
Math03
Knowledge04
General018
All shared boards036
CodingLike-for-likeFour of these boards feed the Vibe Coding Index03
Coding benchmarks for GPT-4o (2024-08-06) and Qwen3.5-35B-A3B
BenchmarkGPT-4o (2024-08-06)Qwen3.5-35B-A3BLeader
Aider polyglot23.1%Not measuredOnly GPT-4o (2024-08-06) measured
SWE-bench Lite21.7%Not measuredOnly GPT-4o (2024-08-06) measured
LMArena WebDevNot measured1254Only Qwen3.5-35B-A3B measured
LiveCodeBench (Artificial Analysis run)31.7%Not measuredOnly GPT-4o (2024-08-06) measured
Terminal-Bench Hard (Artificial Analysis run)8.3%26.5%Qwen3.5-35B-A3B
ALE-BenchNot measured221.8Only Qwen3.5-35B-A3B measured
LMArena Text: coding12831410Qwen3.5-35B-A3B
LMArena Text: software and IT12781415Qwen3.5-35B-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 28 boards here
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index01
Intelligence benchmarks for GPT-4o (2024-08-06) and Qwen3.5-35B-A3B
BenchmarkGPT-4o (2024-08-06)Qwen3.5-35B-A3BLeader
AA Intelligence Index7.719.3Qwen3.5-35B-A3B
Epoch Capabilities IndexNot measured142.5Only Qwen3.5-35B-A3B measured
Agentic workLike-for-likePublic boards, shown as published, kept out of the index01
Agentic work benchmarks for GPT-4o (2024-08-06) and Qwen3.5-35B-A3B
BenchmarkGPT-4o (2024-08-06)Qwen3.5-35B-A3BLeader
τ²-Bench Telecom28.9%89.2%Qwen3.5-35B-A3B
Vending-Bench 2Not measured$463Only Qwen3.5-35B-A3B measured
Neither model has a result on the other 37 boards here
ReasoningLike-for-likePublic boards, shown as published, kept out of the index06
Reasoning benchmarks for GPT-4o (2024-08-06) and Qwen3.5-35B-A3B
BenchmarkGPT-4o (2024-08-06)Qwen3.5-35B-A3BLeader
MMMU Pro (Vals AI)64.0%Not measuredOnly GPT-4o (2024-08-06) measured
GPQA Diamond (Artificial Analysis run)52.1%84.5%Qwen3.5-35B-A3B
Humanity's Last Exam (Artificial Analysis run)2.3%21.0%Qwen3.5-35B-A3B
GPQA Diamond (Epoch AI run)49.2%83.5%Qwen3.5-35B-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 prompts12641400Qwen3.5-35B-A3B
LMArena Text: expert12411408Qwen3.5-35B-A3B
LMArena Text: hard prompts in English12771411Qwen3.5-35B-A3B
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 (2024-08-06) and Qwen3.5-35B-A3B
BenchmarkGPT-4o (2024-08-06)Qwen3.5-35B-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
OTIS Mock AIME6.4%70.0%Qwen3.5-35B-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: math12851404Qwen3.5-35B-A3B
LMArena Text: mathematical work12831410Qwen3.5-35B-A3B
Neither model has a result on the other 5 boards here
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index04
Knowledge benchmarks for GPT-4o (2024-08-06) and Qwen3.5-35B-A3B
BenchmarkGPT-4o (2024-08-06)Qwen3.5-35B-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
SimpleQA Verified26.0%Not measuredOnly GPT-4o (2024-08-06) measured
MMLU84.3%Not measuredOnly GPT-4o (2024-08-06) measured
LMArena Text: science12741413Qwen3.5-35B-A3B
LMArena Text: medicine and healthcare12521421Qwen3.5-35B-A3B
LMArena Text: legal and government12751399Qwen3.5-35B-A3B
LMArena Text: business and finance12321394Qwen3.5-35B-A3B
Neither model has a result on the other 5 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 Qwen3.5-35B-A3B
BenchmarkGPT-4o (2024-08-06)Qwen3.5-35B-A3BLeader
Neither model has a result on 9 boards here
GeneralLike-for-likePublic boards, shown as published, kept out of the index018
General benchmarks for GPT-4o (2024-08-06) and Qwen3.5-35B-A3B
BenchmarkGPT-4o (2024-08-06)Qwen3.5-35B-A3BLeader
IFBench36.0%72.5%Qwen3.5-35B-A3B
Long context reasoning (AA-LCR)41.0%72.0%Qwen3.5-35B-A3B
DTBenchNot measured80.0%Only Qwen3.5-35B-A3B measured
LMCANot measured29.5%Only Qwen3.5-35B-A3B measured
LMArena Text12831395Qwen3.5-35B-A3B
LMArena Text: instruction following12671379Qwen3.5-35B-A3B
LMArena Text: creative writing12741347Qwen3.5-35B-A3B
LMArena Vision1065Not measuredOnly GPT-4o (2024-08-06) measured
LMArena Text: English12971407Qwen3.5-35B-A3B
LMArena Text: non-English12621378Qwen3.5-35B-A3B
LMArena Text: Chinese12541457Qwen3.5-35B-A3B
LMArena Text: German12571367Qwen3.5-35B-A3B
LMArena Text: Japanese12341326Qwen3.5-35B-A3B
LMArena Text: Korean12181355Qwen3.5-35B-A3B
LMArena Text: French12631412Qwen3.5-35B-A3B
LMArena Text: Spanish12691390Qwen3.5-35B-A3B
LMArena Text: Russian12721376Qwen3.5-35B-A3B
LMArena Text: PolishNot measured1385Only Qwen3.5-35B-A3B measured
LMArena Text: multi-turn12791390Qwen3.5-35B-A3B
LMArena Text: longer queries12831389Qwen3.5-35B-A3B
LMArena Text: writing and language12901365Qwen3.5-35B-A3B
LMArena Text: entertainment and media12671347Qwen3.5-35B-A3B
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 Qwen3.5-35B-A3B
BenchmarkGPT-4o (2024-08-06)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 (2024-08-06)$0.0075Fits in one request
Qwen3.5-35B-A3B$0.0006Fits in one request

Qwen3.5-35B-A3B costs less

Repository review

50K input + 3K output tokens

GPT-4o (2024-08-06)$0.155Fits in one request
Qwen3.5-35B-A3B$0.010Fits in one request

Qwen3.5-35B-A3B costs less

Agent loop

200K input + 10K output tokens

GPT-4o (2024-08-06)$0.600Exceeds the context window
Qwen3.5-35B-A3B$0.038Fits in one request

Qwen3.5-35B-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 Qwen3.5-35B-A3B
SpecificationOpenAI GPT-4o (2024-08-06)Qwen3.5-35B-A3B
MakerOpenAIQwen
WeightsNo public weights listedOpen weights
ReleasedAugust 6, 2024February 25, 2026
Context window128K262K
Input $/Mtok$2.50$0.14
Output $/Mtok$10.00$1.00
Coding index23.17.7
Independent measurements behind it11
Cost per solved taskNot computableNot computable
SourceOpenRouter listingOpenRouter listing

Questions

Is GPT-4o (2024-08-06) better than Qwen3.5-35B-A3B for coding?

Pick GPT-4o (2024-08-06) for coding: it scores 23.1 on the Vibe Coding Index against 7.7 for Qwen3.5-35B-A3B. Pick Qwen3.5-35B-A3B when output tokens cost 10.0x less, or when the context window is larger, 262K against 128K tokens.

Which is cheaper, GPT-4o (2024-08-06) or Qwen3.5-35B-A3B?

GPT-4o (2024-08-06) costs $2.50 per million input tokens and $10.00 per million output tokens; Qwen3.5-35B-A3B costs $0.14 and $1.00. Cost per solved task is known for neither of them.

Which has the bigger context window, GPT-4o (2024-08-06) or Qwen3.5-35B-A3B?

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

How many benchmarks is the GPT-4o (2024-08-06) vs Qwen3.5-35B-A3B comparison based on?

36 benchmarks have a result for both models as of October 21, 2026. GPT-4o (2024-08-06)'s coding index rests on 1 independent benchmark 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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