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GPT-4 Turbo vs Qwen3.5-35B-A3B

Qwen3.5-35B-A3B leads GPT-4 Turbo on the Artificial Analysis Intelligence Index, 19.3 to 7.0, and Qwen3.5-35B-A3B costs 23.1x less per output token ($1.30 vs $30.00 per million). Updated October 22, 2026; 33 benchmarks have a result for both.

Replace GPT-4 Turbo Replace Qwen3.5-35B-A3B
GPT-4 TurboOpenAI
Coding
No data
Overall
No data
Output $/M
$30.00
0
Qwen3.5-35B-A3BQwen
Coding
No data
Overall
53.5
Output $/M
$1.30
33
vs boards won of 33 shared

GPT-4 Turbo 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-4 Turbo for work measured by LMArena Text: coding or LMArena Text: software and IT, where it leads.

Model AGPT-4 TurboOpenAINot benchmarkedNo coding benchmarkNo cost per solved taskModel BQwen3.5-35B-A3BQwenNot benchmarked1 independent benchmarkNo cost per solved task
Shared results
33
GPT-4 Turbo only
9
Qwen3.5-35B-A3B only
13
Like-for-like categories
6 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-4 Turbo not benchmarked, Qwen3.5-35B-A3B not benchmarked.
Widest category
Knowledge, 26.9 points apart on average over 4 shared benchmarks.
Widest single gap
LMArena Text: Chinese: GPT-4 Turbo 1242 against Qwen3.5-35B-A3B 1457, 35.7 points apart on a 0 to 100 scale.
Output price
GPT-4 Turbo $30.00 against Qwen3.5-35B-A3B $1.30 per million output tokens, 23.1x apart.
Context window
GPT-4 Turbo 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-4 TurboBarsQwen3.5-35B-A3BTies
Coding02
Intelligence02
Reasoning04
Math02
Knowledge04
General019
All shared boards033
CodingLike-for-likeSix of these boards feed the Vibe Coding Index02
Coding benchmarks for GPT-4 Turbo and Qwen3.5-35B-A3B
BenchmarkGPT-4 TurboQwen3.5-35B-A3BLeader
LMArena WebDevNot measured1254Only Qwen3.5-35B-A3B measured
AA Coding Index21.5Not measuredOnly GPT-4 Turbo measured
LiveCodeBench (Artificial Analysis run)29.1%Not measuredOnly GPT-4 Turbo measured
Terminal-Bench Hard (Artificial Analysis run)Not measured26.5%Only Qwen3.5-35B-A3B measured
ALE-BenchNot measured221.8Only Qwen3.5-35B-A3B measured
LMArena Text: coding12681410Qwen3.5-35B-A3B
LMArena Text: software and IT12671415Qwen3.5-35B-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
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index02
Intelligence benchmarks for GPT-4 Turbo and Qwen3.5-35B-A3B
BenchmarkGPT-4 TurboQwen3.5-35B-A3BLeader
AA Intelligence Index7.019.3Qwen3.5-35B-A3B
Epoch Capabilities Index127.3142.5Qwen3.5-35B-A3B
Agentic workDirectional onlyPublic boards, shown as published, kept out of the index2 boards, none shared
Agentic work benchmarks for GPT-4 Turbo and Qwen3.5-35B-A3B
BenchmarkGPT-4 TurboQwen3.5-35B-A3BLeader
τ²-Bench TelecomNot measured89.2%Only Qwen3.5-35B-A3B measured
Vending-Bench 2Not measured$463Only Qwen3.5-35B-A3B measured
Neither model has a result on the other 40 boards here
ReasoningLike-for-likePublic boards, shown as published, kept out of the index04
Reasoning benchmarks for GPT-4 Turbo and Qwen3.5-35B-A3B
BenchmarkGPT-4 TurboQwen3.5-35B-A3BLeader
GPQA Diamond (Artificial Analysis run)Not measured84.5%Only Qwen3.5-35B-A3B measured
Humanity's Last Exam (Artificial Analysis run)3.1%21.0%Qwen3.5-35B-A3B
GPQA Diamond (Epoch AI run)Not measured83.5%Only Qwen3.5-35B-A3B measured
LMArena Text: hard prompts12511400Qwen3.5-35B-A3B
LMArena Text: expert12231408Qwen3.5-35B-A3B
LMArena Text: hard prompts in English12661411Qwen3.5-35B-A3B
Neither model has a result on the other 17 boards here
MathLike-for-likePublic boards, shown as published, kept out of the index02
Math benchmarks for GPT-4 Turbo and Qwen3.5-35B-A3B
BenchmarkGPT-4 TurboQwen3.5-35B-A3BLeader
OTIS Mock AIMENot measured70.0%Only Qwen3.5-35B-A3B measured
LMArena Text: math12721404Qwen3.5-35B-A3B
LMArena Text: mathematical work12681410Qwen3.5-35B-A3B
MathArenaNot measured14.7%Only Qwen3.5-35B-A3B measured
Neither model has a result on the other 10 boards here
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index04
Knowledge benchmarks for GPT-4 Turbo and Qwen3.5-35B-A3B
BenchmarkGPT-4 TurboQwen3.5-35B-A3BLeader
LegalBench (Vals AI)80.5%Not measuredOnly GPT-4 Turbo measured
MedQA (Vals AI)82.0%Not measuredOnly GPT-4 Turbo measured
MMLU Pro (Artificial Analysis run)69.4%Not measuredOnly GPT-4 Turbo measured
MMLU81.3%Not measuredOnly GPT-4 Turbo measured
LMArena Text: science12561413Qwen3.5-35B-A3B
LMArena Text: medicine and healthcare12391421Qwen3.5-35B-A3B
LMArena Text: legal and government12651399Qwen3.5-35B-A3B
LMArena Text: business and finance12221394Qwen3.5-35B-A3B
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-4 Turbo and Qwen3.5-35B-A3B
BenchmarkGPT-4 TurboQwen3.5-35B-A3BLeader
Neither model has a result on 9 boards here
GeneralLike-for-likePublic boards, shown as published, kept out of the index019
General benchmarks for GPT-4 Turbo and Qwen3.5-35B-A3B
BenchmarkGPT-4 TurboQwen3.5-35B-A3BLeader
IFBenchNot measured72.5%Only Qwen3.5-35B-A3B measured
Long context reasoning (AA-LCR)Not measured72.0%Only Qwen3.5-35B-A3B measured
DTBench61.6%80.0%Qwen3.5-35B-A3B
LMCA9.8%29.5%Qwen3.5-35B-A3B
LMArena Text12721395Qwen3.5-35B-A3B
LMArena Text: instruction following12491379Qwen3.5-35B-A3B
LMArena Text: creative writing12681347Qwen3.5-35B-A3B
LMArena Vision1090Not measuredOnly GPT-4 Turbo measured
LMArena Text: English12911407Qwen3.5-35B-A3B
LMArena Text: non-English12451378Qwen3.5-35B-A3B
LMArena Text: Chinese12421457Qwen3.5-35B-A3B
LMArena Text: German12591367Qwen3.5-35B-A3B
LMArena Text: Japanese11941326Qwen3.5-35B-A3B
LMArena Text: Korean11871355Qwen3.5-35B-A3B
LMArena Text: French12761412Qwen3.5-35B-A3B
LMArena Text: Spanish12601390Qwen3.5-35B-A3B
LMArena Text: Russian12591376Qwen3.5-35B-A3B
LMArena Text: Polish13021385Qwen3.5-35B-A3B
LMArena Text: multi-turn12671390Qwen3.5-35B-A3B
LMArena Text: longer queries12541389Qwen3.5-35B-A3B
LMArena Text: writing and language12791365Qwen3.5-35B-A3B
LMArena Text: entertainment and media12581347Qwen3.5-35B-A3B
LMArena Vision: English1097Not measuredOnly GPT-4 Turbo measured
LMArena Vision: Chinese1045Not measuredOnly GPT-4 Turbo measured
Neither model has a result on the other 24 boards here
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
Image generation benchmarks for GPT-4 Turbo and Qwen3.5-35B-A3B
BenchmarkGPT-4 TurboQwen3.5-35B-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-4 Turbo$0.025Fits in one request
Qwen3.5-35B-A3B$0.0008Fits in one request

Qwen3.5-35B-A3B costs less

Repository review

50K input + 3K output tokens

GPT-4 Turbo$0.590Fits in one request
Qwen3.5-35B-A3B$0.012Fits in one request

Qwen3.5-35B-A3B costs less

Agent loop

200K input + 10K output tokens

GPT-4 Turbo$2.30Exceeds the context window
Qwen3.5-35B-A3B$0.045Fits 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-4 Turbo and Qwen3.5-35B-A3B
SpecificationOpenAI GPT-4 TurboQwen3.5-35B-A3B
MakerOpenAIQwen
WeightsNo public weights listedOpen weights
ReleasedApril 9, 2024February 25, 2026
Context window128K262K
Input $/Mtok$10.00$0.1625
Output $/Mtok$30.00$1.30
Coding indexNot benchmarkedNot benchmarked
Independent measurements behind it01
Cost per solved taskNot computableNot computable
SourceOpenRouter listingOpenRouter listing

Questions

Is GPT-4 Turbo 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-4 Turbo for work measured by LMArena Text: coding or LMArena Text: software and IT, where it leads.

Which is cheaper, GPT-4 Turbo or Qwen3.5-35B-A3B?

GPT-4 Turbo costs $10.00 per million input tokens and $30.00 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-4 Turbo or Qwen3.5-35B-A3B?

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

How many benchmarks is the GPT-4 Turbo vs Qwen3.5-35B-A3B comparison based on?

33 benchmarks have a result for both models as of October 22, 2026. GPT-4 Turbo'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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