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GPT-4 Turbo vs Qwen-Plus

Qwen-Plus costs 38.5x less per output token than GPT-4 Turbo ($0.78 vs $30.00 per million). Updated October 21, 2026; 25 benchmarks have a result for both.

GPT-4 TurboOpenAI
Coding
No data
Overall
No data
Output $/M
$30.00
0
Qwen-PlusQwen
Coding
No data
Overall
No data
Output $/M
$0.78
25
vs boards won of 25 shared

GPT-4 Turbo or Qwen-Plus: 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.

Shared results
25
GPT-4 Turbo only
17
Qwen-Plus only
3
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-4 Turbo not benchmarked, Qwen-Plus not benchmarked.
Widest category
Knowledge, 15.5 points apart on average over 4 shared benchmarks.
Widest single gap
DTBench: GPT-4 Turbo 61.6% against Qwen-Plus 81.1%, 19.5 points apart on a 0 to 100 scale.
Output price
GPT-4 Turbo $30.00 against Qwen-Plus $0.78 per million output tokens, 38.5x apart.
Context window
GPT-4 Turbo takes 128K tokens, Qwen-Plus 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 TurboBarsQwen-PlusTies
Coding02
Reasoning03
Math02
Knowledge04
General014
All shared boards025
CodingLike-for-likeSix of these boards feed the Vibe Coding Index02
Coding benchmarks for GPT-4 Turbo and Qwen-Plus
BenchmarkGPT-4 TurboQwen-PlusLeader
AA Coding Index21.5Not measuredOnly GPT-4 Turbo measured
LiveCodeBench (Artificial Analysis run)29.1%Not measuredOnly GPT-4 Turbo measured
LMArena Text: coding12681328Qwen-Plus
LMArena Text: software and IT12671343Qwen-Plus
Neither model has a result on the other 35 boards here
IntelligenceDirectional onlyPublic boards, shown as published, kept out of the index2 boards, none shared
Intelligence benchmarks for GPT-4 Turbo and Qwen-Plus
BenchmarkGPT-4 TurboQwen-PlusLeader
AA Intelligence Index7.0Not measuredOnly GPT-4 Turbo measured
Epoch Capabilities Index127.3Not measuredOnly GPT-4 Turbo measured
Agentic workNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
Agentic work benchmarks for GPT-4 Turbo and Qwen-Plus
BenchmarkGPT-4 TurboQwen-PlusLeader
Neither model has a result on 41 boards here
ReasoningLike-for-likePublic boards, shown as published, kept out of the index03
Reasoning benchmarks for GPT-4 Turbo and Qwen-Plus
BenchmarkGPT-4 TurboQwen-PlusLeader
Humanity's Last Exam (Artificial Analysis run)3.1%Not measuredOnly GPT-4 Turbo measured
GPQA Diamond (Epoch AI run)Not measured48.1%Only Qwen-Plus measured
LMArena Text: hard prompts12511317Qwen-Plus
LMArena Text: expert12231328Qwen-Plus
LMArena Text: hard prompts in English12661333Qwen-Plus
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 Qwen-Plus
BenchmarkGPT-4 TurboQwen-PlusLeader
OTIS Mock AIMENot measured17.8%Only Qwen-Plus measured
MATH level 5Not measured65.3%Only Qwen-Plus measured
LMArena Text: math12721326Qwen-Plus
LMArena Text: mathematical work12681332Qwen-Plus
Neither model has a result on the other 9 boards here
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index04
Knowledge benchmarks for GPT-4 Turbo and Qwen-Plus
BenchmarkGPT-4 TurboQwen-PlusLeader
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: science12561352Qwen-Plus
LMArena Text: medicine and healthcare12391350Qwen-Plus
LMArena Text: legal and government12651349Qwen-Plus
LMArena Text: business and finance12221303Qwen-Plus
Neither model has a result on the other 10 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 Qwen-Plus
BenchmarkGPT-4 TurboQwen-PlusLeader
Neither model has a result on 9 boards here
GeneralLike-for-likePublic boards, shown as published, kept out of the index014
General benchmarks for GPT-4 Turbo and Qwen-Plus
BenchmarkGPT-4 TurboQwen-PlusLeader
DTBench61.6%81.1%Qwen-Plus
LMCA9.8%24.0%Qwen-Plus
LMArena Text12721326Qwen-Plus
LMArena Text: instruction following12491303Qwen-Plus
LMArena Text: creative writing12681292Qwen-Plus
LMArena Vision1090Not measuredOnly GPT-4 Turbo measured
LMArena Text: English12911339Qwen-Plus
LMArena Text: non-English12451310Qwen-Plus
LMArena Text: Chinese12421347Qwen-Plus
LMArena Text: German1259Not measuredOnly GPT-4 Turbo measured
LMArena Text: Japanese11941251Qwen-Plus
LMArena Text: Korean1187Not measuredOnly GPT-4 Turbo measured
LMArena Text: French1276Not measuredOnly GPT-4 Turbo measured
LMArena Text: Spanish1260Not measuredOnly GPT-4 Turbo measured
LMArena Text: Russian12591323Qwen-Plus
LMArena Text: Polish1302Not measuredOnly GPT-4 Turbo measured
LMArena Text: multi-turn12671336Qwen-Plus
LMArena Text: longer queries12541324Qwen-Plus
LMArena Text: writing and language12791296Qwen-Plus
LMArena Text: entertainment and media12581270Qwen-Plus
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 Qwen-Plus
BenchmarkGPT-4 TurboQwen-PlusLeader
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
Qwen-Plus$0.0006Fits in one request

Qwen-Plus costs less

Repository review

50K input + 3K output tokens

GPT-4 Turbo$0.590Fits in one request
Qwen-Plus$0.015Fits in one request

Qwen-Plus costs less

Agent loop

200K input + 10K output tokens

GPT-4 Turbo$2.30Exceeds the context window
Qwen-Plus$0.060Fits in one request

Qwen-Plus 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 Qwen-Plus
SpecificationOpenAI GPT-4 TurboQwen-Plus
MakerOpenAIQwen
WeightsNo public weights listedNo public weights listed
ReleasedApril 9, 2024February 1, 2025
Context window128K1M
Input $/Mtok$10.00$0.26
Output $/Mtok$30.00$0.78
Coding indexNot benchmarkedNot benchmarked
Independent measurements behind it00
Cost per solved taskNot computableNot computable
SourceOpenRouter listingOpenRouter listing

Questions

Is GPT-4 Turbo better than Qwen-Plus 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 Qwen-Plus?

GPT-4 Turbo costs $10.00 per million input tokens and $30.00 per million output tokens; Qwen-Plus costs $0.26 and $0.78. Cost per solved task is known for neither of them.

Which has the bigger context window, GPT-4 Turbo or Qwen-Plus?

Qwen-Plus, with 1M tokens against 128K.

How many benchmarks is the GPT-4 Turbo vs Qwen-Plus comparison based on?

25 benchmarks have a result for both models as of October 21, 2026. GPT-4 Turbo's coding index rests on 0 independent benchmarks and Qwen-Plus's on 0. Where only one model has a result, the page says so instead of naming a winner.

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