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GPT-4 Turbo vs Qwen3.5-Flash

Qwen3.5-Flash costs 115.4x less per output token than GPT-4 Turbo ($0.26 vs $30.00 per million). Updated October 22, 2026; 32 benchmarks have a result for both.

Replace GPT-4 Turbo Replace Qwen3.5-Flash
GPT-4 TurboOpenAI
Coding
No data
Overall
No data
Output $/M
$30.00
0
Qwen3.5-FlashQwen
Coding
41.1
Overall
50.1
Output $/M
$0.26
32
vs boards won of 32 shared

GPT-4 Turbo or Qwen3.5-Flash: which to pick

Only Qwen3.5-Flash has a coding score, 41.1 on the Vibe Coding Index; GPT-4 Turbo has none, so the two cannot be ranked on coding.

Compare them on price, context and the boards below.

Model AGPT-4 TurboOpenAINot benchmarkedNo coding benchmarkNo cost per solved taskModel BQwen3.5-FlashQwen41.1/1002 independent benchmarks$0.40 per solved task
Shared results
32
GPT-4 Turbo only
10
Qwen3.5-Flash only
23
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-Flash 41.1 from 2 benchmarks.
Widest category
Reasoning, 26.6 points apart on average over 3 shared benchmarks.
Widest single gap
LMArena Text: Chinese: GPT-4 Turbo 1242 against Qwen3.5-Flash 1445, 33.9 points apart on a 0 to 100 scale.
Output price
GPT-4 Turbo $30.00 against Qwen3.5-Flash $0.26 per million output tokens, 115.4x apart.
Context window
GPT-4 Turbo takes 128K tokens, Qwen3.5-Flash 1M.

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-FlashTies
Coding02
Intelligence01
Reasoning03
Math02
Knowledge05
General019
All shared boards032
CodingLike-for-likeSix of these boards feed the Vibe Coding Index02
Coding benchmarks for GPT-4 Turbo and Qwen3.5-Flash
BenchmarkGPT-4 TurboQwen3.5-FlashLeader
LMArena WebDevNot measured1244Only Qwen3.5-Flash measured
AA Coding Index21.5Not measuredOnly GPT-4 Turbo measured
LiveCodeBench (Vals AI)Not measured83.3%Only Qwen3.5-Flash measured
SWE-bench Verified (Vals AI)Not measured64.4%Only Qwen3.5-Flash measured
LiveCodeBench (Artificial Analysis run)29.1%Not measuredOnly GPT-4 Turbo measured
ALE-BenchNot measured265.9Only Qwen3.5-Flash measured
LMArena Text: coding12681412Qwen3.5-Flash
LMArena Text: software and IT12671416Qwen3.5-Flash
LMArena WebDev: ReactNot measured1229Only Qwen3.5-Flash measured
LMArena WebDev: HTMLNot measured1291Only Qwen3.5-Flash measured
Neither model has a result on the other 33 boards here
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index01
Intelligence benchmarks for GPT-4 Turbo and Qwen3.5-Flash
BenchmarkGPT-4 TurboQwen3.5-FlashLeader
AA Intelligence Index7.0Not measuredOnly GPT-4 Turbo measured
Epoch Capabilities Index127.3143.5Qwen3.5-Flash
Agentic workNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
Agentic work benchmarks for GPT-4 Turbo and Qwen3.5-Flash
BenchmarkGPT-4 TurboQwen3.5-FlashLeader
Neither model has a result on 42 boards here
ReasoningLike-for-likePublic boards, shown as published, kept out of the index03
Reasoning benchmarks for GPT-4 Turbo and Qwen3.5-Flash
BenchmarkGPT-4 TurboQwen3.5-FlashLeader
GPQA DiamondNot measured82.8%Only Qwen3.5-Flash measured
MMMU Pro (Vals AI)Not measured81.9%Only Qwen3.5-Flash measured
Humanity's Last Exam (Artificial Analysis run)3.1%Not measuredOnly GPT-4 Turbo measured
GPQA Diamond (Epoch AI run)Not measured82.3%Only Qwen3.5-Flash measured
Chess puzzlesNot measured14.0%Only Qwen3.5-Flash measured
Mystery game puzzlesNot measured20.0%Only Qwen3.5-Flash measured
LMArena Text: hard prompts12511403Qwen3.5-Flash
LMArena Text: expert12231407Qwen3.5-Flash
LMArena Text: hard prompts in English12661409Qwen3.5-Flash
Neither model has a result on the other 14 boards here
MathLike-for-likePublic boards, shown as published, kept out of the index02
Math benchmarks for GPT-4 Turbo and Qwen3.5-Flash
BenchmarkGPT-4 TurboQwen3.5-FlashLeader
AIMENot measured92.5%Only Qwen3.5-Flash measured
OTIS Mock AIMENot measured84.4%Only Qwen3.5-Flash measured
FrontierMath, tiers 1 to 3Not measured18.2%Only Qwen3.5-Flash measured
LMArena Text: math12721407Qwen3.5-Flash
LMArena Text: mathematical work12681413Qwen3.5-Flash
Neither model has a result on the other 9 boards here
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index05
Knowledge benchmarks for GPT-4 Turbo and Qwen3.5-Flash
BenchmarkGPT-4 TurboQwen3.5-FlashLeader
MMLU ProNot measured84.1%Only Qwen3.5-Flash measured
LegalBench (Vals AI)80.5%84.3%Qwen3.5-Flash
CaseLaw (Vals AI)Not measured56.0%Only Qwen3.5-Flash measured
CorpFin (Vals AI)Not measured63.6%Only Qwen3.5-Flash measured
TaxEval (Vals AI)Not measured72.2%Only Qwen3.5-Flash measured
MortgageTax (Vals AI)Not measured67.4%Only Qwen3.5-Flash measured
MedQA (Vals AI)82.0%Not measuredOnly GPT-4 Turbo measured
MedCode (Vals AI)Not measured33.0%Only Qwen3.5-Flash measured
MMLU Pro (Artificial Analysis run)69.4%Not measuredOnly GPT-4 Turbo measured
SimpleQA VerifiedNot measured20.3%Only Qwen3.5-Flash measured
MMLU81.3%Not measuredOnly GPT-4 Turbo measured
LMArena Text: science12561415Qwen3.5-Flash
LMArena Text: medicine and healthcare12391407Qwen3.5-Flash
LMArena Text: legal and government12651398Qwen3.5-Flash
LMArena Text: business and finance12221394Qwen3.5-Flash
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-4 Turbo and Qwen3.5-Flash
BenchmarkGPT-4 TurboQwen3.5-FlashLeader
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-Flash
BenchmarkGPT-4 TurboQwen3.5-FlashLeader
SAGE (Vals AI)Not measured42.5%Only Qwen3.5-Flash measured
MedScribe (Vals AI)Not measured70.6%Only Qwen3.5-Flash measured
DTBench61.6%82.9%Qwen3.5-Flash
LMCA9.8%29.1%Qwen3.5-Flash
LMArena Text12721397Qwen3.5-Flash
LMArena Text: instruction following12491374Qwen3.5-Flash
LMArena Text: creative writing12681343Qwen3.5-Flash
LMArena Vision1090Not measuredOnly GPT-4 Turbo measured
LMArena Text: English12911404Qwen3.5-Flash
LMArena Text: non-English12451385Qwen3.5-Flash
LMArena Text: Chinese12421445Qwen3.5-Flash
LMArena Text: German12591390Qwen3.5-Flash
LMArena Text: Japanese11941369Qwen3.5-Flash
LMArena Text: Korean11871344Qwen3.5-Flash
LMArena Text: French12761413Qwen3.5-Flash
LMArena Text: Spanish12601400Qwen3.5-Flash
LMArena Text: Russian12591380Qwen3.5-Flash
LMArena Text: Polish13021376Qwen3.5-Flash
LMArena Text: multi-turn12671393Qwen3.5-Flash
LMArena Text: longer queries12541392Qwen3.5-Flash
LMArena Text: writing and language12791369Qwen3.5-Flash
LMArena Text: entertainment and media12581347Qwen3.5-Flash
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-Flash
BenchmarkGPT-4 TurboQwen3.5-FlashLeader
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-Flash$0.0002Fits in one request

Qwen3.5-Flash costs less

Repository review

50K input + 3K output tokens

GPT-4 Turbo$0.590Fits in one request
Qwen3.5-Flash$0.0040Fits in one request

Qwen3.5-Flash costs less

Agent loop

200K input + 10K output tokens

GPT-4 Turbo$2.30Exceeds the context window
Qwen3.5-Flash$0.016Fits in one request

Qwen3.5-Flash 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-Flash
SpecificationOpenAI GPT-4 TurboQwen3.5-Flash
MakerOpenAIQwen
WeightsNo public weights listedNo public weights listed
ReleasedApril 9, 2024February 25, 2026
Context window128K1M
Input $/Mtok$10.00$0.065
Output $/Mtok$30.00$0.26
Coding indexNot benchmarked41.1
Independent measurements behind it02
Cost per solved taskNot computable$0.40
SourceOpenRouter listingOpenRouter listing

Questions

Is GPT-4 Turbo better than Qwen3.5-Flash for coding?

Only Qwen3.5-Flash has a coding score, 41.1 on the Vibe Coding Index; GPT-4 Turbo has none, so the two cannot be ranked on coding. Compare them on price, context and the boards below.

Which is cheaper, GPT-4 Turbo or Qwen3.5-Flash?

GPT-4 Turbo costs $10.00 per million input tokens and $30.00 per million output tokens; Qwen3.5-Flash costs $0.065 and $0.26. Cost per solved task is known for Qwen3.5-Flash only.

Which has the bigger context window, GPT-4 Turbo or Qwen3.5-Flash?

Qwen3.5-Flash, with 1M tokens against 128K.

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

32 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-Flash's on 2. Where only one model has a result, the page says so instead of naming a winner.

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