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GPT-3.5 Turbo vs Qwen3 14B

Qwen3 14B leads GPT-3.5 Turbo on the Artificial Analysis Intelligence Index, 6.7 to 5.5, and Qwen3 14B costs 6.5x less per output token ($0.23 vs $1.50 per million). Updated October 22, 2026; 5 benchmarks have a result for both.

Replace GPT-3.5 Turbo Replace Qwen3 14B
GPT-3.5 TurboOpenAI
Coding
No data
Overall
No data
Output $/M
$1.50
0
Qwen3 14BQwen
Coding
No data
Overall
No data
Output $/M
$0.23
5
vs boards won of 5 shared

GPT-3.5 Turbo or Qwen3 14B: which to pick

Neither model has a coding score yet, so the two cannot be ranked on coding.

Pick GPT-3.5 Turbo for work measured by AA Intelligence Index or GPQA Diamond (Artificial Analysis run), where it leads.

Model AGPT-3.5 TurboOpenAINot benchmarkedNo coding benchmarkNo cost per solved taskModel BQwen3 14BQwenNot benchmarkedNo coding benchmarkNo cost per solved task
Shared results
5
GPT-3.5 Turbo only
8
Qwen3 14B only
15
Like-for-like categories
4 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-3.5 Turbo not benchmarked, Qwen3 14B not benchmarked.
Widest category
Knowledge, 31.2 points apart on average over 1 shared benchmark.
Widest single gap
MMLU Pro (Artificial Analysis run): GPT-3.5 Turbo 46.2% against Qwen3 14B 77.4%, 31.2 points apart on a 0 to 100 scale.
Output price
GPT-3.5 Turbo $1.50 against Qwen3 14B $0.23 per million output tokens, 6.5x apart.
Context window
GPT-3.5 Turbo takes 16K tokens, Qwen3 14B 41K.

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-3.5 TurboBarsQwen3 14BTies
Intelligence01
Reasoning01
Knowledge01
General02
All shared boards05
CodingDirectional onlySix of these boards feed the Vibe Coding Index5 boards, none shared
Coding benchmarks for GPT-3.5 Turbo and Qwen3 14B
BenchmarkGPT-3.5 TurboQwen3 14BLeader
AA Coding Index10.7Not measuredOnly GPT-3.5 Turbo measured
LiveCodeBench (Artificial Analysis run)Not measured52.3%Only Qwen3 14B measured
SciCodeNot measured30.7%Only Qwen3 14B measured
Terminal-Bench Hard (Artificial Analysis run)Not measured5.3%Only Qwen3 14B measured
SciCode0.0%Not measuredOnly GPT-3.5 Turbo measured
Neither model has a result on the other 38 boards here
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index01
Intelligence benchmarks for GPT-3.5 Turbo and Qwen3 14B
BenchmarkGPT-3.5 TurboQwen3 14BLeader
AA Intelligence Index5.56.7Qwen3 14B
Epoch Capabilities IndexNot measured138.2Only Qwen3 14B measured
Agentic workDirectional onlyPublic boards, shown as published, kept out of the index2 boards, none shared
Agentic work benchmarks for GPT-3.5 Turbo and Qwen3 14B
BenchmarkGPT-3.5 TurboQwen3 14BLeader
τ²-Bench TelecomNot measured34.5%Only Qwen3 14B measured
Berkeley Function Calling Leaderboard (BFCL)Not measured41.0%Only Qwen3 14B measured
Neither model has a result on the other 40 boards here
ReasoningLike-for-likePublic boards, shown as published, kept out of the index01
Reasoning benchmarks for GPT-3.5 Turbo and Qwen3 14B
BenchmarkGPT-3.5 TurboQwen3 14BLeader
GPQA Diamond30.6%Not measuredOnly GPT-3.5 Turbo measured
GPQA Diamond (Artificial Analysis run)29.7%60.4%Qwen3 14B
Humanity's Last Exam (Artificial Analysis run)Not measured4.5%Only Qwen3 14B measured
GPQA Diamond (Epoch AI run)Not measured63.8%Only Qwen3 14B measured
BIG-Bench Hard61.6%Not measuredOnly GPT-3.5 Turbo measured
Kagi LLM BenchmarkNot measured49.1%Only Qwen3 14B measured
Neither model has a result on the other 17 boards here
MathDirectional onlyPublic boards, shown as published, kept out of the index4 boards, none shared
Math benchmarks for GPT-3.5 Turbo and Qwen3 14B
BenchmarkGPT-3.5 TurboQwen3 14BLeader
AA Math IndexNot measured58.0Only Qwen3 14B measured
AIME 2025 (Artificial Analysis run)Not measured58.0%Only Qwen3 14B measured
OTIS Mock AIMENot measured66.4%Only Qwen3 14B measured
GSM8K57.8%Not measuredOnly GPT-3.5 Turbo measured
Neither model has a result on the other 10 boards here
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index01
Knowledge benchmarks for GPT-3.5 Turbo and Qwen3 14B
BenchmarkGPT-3.5 TurboQwen3 14BLeader
LegalBench (Vals AI)64.4%Not measuredOnly GPT-3.5 Turbo measured
MedQA (Vals AI)58.5%Not measuredOnly GPT-3.5 Turbo measured
MMLU Pro (Artificial Analysis run)46.2%77.4%Qwen3 14B
MMLU68.5%Not measuredOnly GPT-3.5 Turbo measured
Neither model has a result on the other 16 boards here
Web designNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
Web design benchmarks for GPT-3.5 Turbo and Qwen3 14B
BenchmarkGPT-3.5 TurboQwen3 14BLeader
Neither model has a result on 9 boards here
GeneralLike-for-likePublic boards, shown as published, kept out of the index02
General benchmarks for GPT-3.5 Turbo and Qwen3 14B
BenchmarkGPT-3.5 TurboQwen3 14BLeader
IFBenchNot measured40.5%Only Qwen3 14B measured
Long context reasoning (AA-LCR)Not measured0.0%Only Qwen3 14B measured
DTBench48.5%64.0%Qwen3 14B
LMCA9.7%18.2%Qwen3 14B
Fiction.LiveBenchNot measured62.5%Only Qwen3 14B measured
Neither model has a result on the other 43 boards here
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
Image generation benchmarks for GPT-3.5 Turbo and Qwen3 14B
BenchmarkGPT-3.5 TurboQwen3 14BLeader
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-3.5 Turbo$0.0013Fits in one request
Qwen3 14B$0.0002Fits in one request

Qwen3 14B costs less

Repository review

50K input + 3K output tokens

GPT-3.5 Turbo$0.029Exceeds the context window
Qwen3 14B$0.0062Exceeds the context window

Qwen3 14B costs less

Agent loop

200K input + 10K output tokens

GPT-3.5 Turbo$0.115Exceeds the context window
Qwen3 14B$0.024Exceeds the context window

Qwen3 14B 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-3.5 Turbo and Qwen3 14B
SpecificationOpenAI GPT-3.5 TurboQwen3 14B
MakerOpenAIQwen
WeightsNo public weights listedOpen weights
ReleasedMay 28, 2023April 28, 2025
Context window16K41K
Input $/Mtok$0.50$0.11
Output $/Mtok$1.50$0.23
Coding indexNot benchmarkedNot benchmarked
Independent measurements behind it00
Cost per solved taskNot computableNot computable
SourceOpenRouter listingOpenRouter listing

Questions

Is GPT-3.5 Turbo better than Qwen3 14B for coding?

Neither model has a coding score yet, so the two cannot be ranked on coding. Pick GPT-3.5 Turbo for work measured by AA Intelligence Index or GPQA Diamond (Artificial Analysis run), where it leads.

Which is cheaper, GPT-3.5 Turbo or Qwen3 14B?

GPT-3.5 Turbo costs $0.50 per million input tokens and $1.50 per million output tokens; Qwen3 14B costs $0.11 and $0.23. Cost per solved task is known for neither of them.

Which has the bigger context window, GPT-3.5 Turbo or Qwen3 14B?

Qwen3 14B, with 41K tokens against 16K.

How many benchmarks is the GPT-3.5 Turbo vs Qwen3 14B comparison based on?

5 benchmarks have a result for both models as of October 22, 2026. GPT-3.5 Turbo's coding index rests on 0 independent benchmarks and Qwen3 14B's on 0. Where only one model has a result, the page says so instead of naming a winner.

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