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GPT-4 vs Qwen3 32B

Updated October 21, 2026. 30 benchmarks have a result for both. Coding is ranked on the Vibe Coding Index; every other board is shown as published.

Replace GPT-4 Replace Qwen3 32B
GPT-4OpenAI
Coding
22.4
Overall
6.7
Output $/M
$60.00
0
Qwen3 32BQwen
Coding
40.0
Overall
7.3
Output $/M
$0.28
30
vs boards won of 30 shared

Decision reading

Pick Qwen3 32B for coding: it scores 40.0 on the Vibe Coding Index against 22.4 for GPT-4.

GPT-4 is neither cheaper nor larger in context, and leads no benchmark both models were measured on.

Model AGPT-4OpenAI22.4/1001 independent benchmarkNo cost per solved taskModel BQwen3 32BQwen40.0/1001 independent benchmarkNo cost per solved task
Shared results
30
GPT-4 only
15
Qwen3 32B only
12
Like-for-like categories
6 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-4 22.4 from 1 benchmark, Qwen3 32B 40.0 from 1 benchmark.
Widest category
Math, 30.0 points apart on average over 2 shared benchmarks.
Widest single gap
LMArena Text: medicine and healthcare: GPT-4 1145 against Qwen3 32B 1368, 37.2 points apart on a 0 to 100 scale.
Output price
GPT-4 $60.00 against Qwen3 32B $0.28 per million output tokens, 214.3x apart.
Context window
GPT-4 takes 8K tokens, Qwen3 32B 131K.

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-4BarsQwen3 32BTies
Coding02
Intelligence02
Reasoning04
Math02
Knowledge05
General015
All shared boards030
CodingLike-for-likeFour of these boards feed the Vibe Coding Index02
Coding benchmarks for GPT-4 and Qwen3 32B
BenchmarkGPT-4Qwen3 32BLeader
Aider polyglotNot measured40.0%Only Qwen3 32B measured
SWE-bench Verified22.4%Not measuredOnly GPT-4 measured
SWE-bench Lite39.7%Not measuredOnly GPT-4 measured
SWE-bench (full test set)12.5%Not measuredOnly GPT-4 measured
AA Coding Index13.1Not measuredOnly GPT-4 measured
LiveCodeBench (Artificial Analysis run)Not measured54.6%Only Qwen3 32B measured
SciCodeNot measured36.0%Only Qwen3 32B measured
Terminal-Bench Hard (Artificial Analysis run)Not measured3.0%Only Qwen3 32B measured
LMArena Text: coding12091357Qwen3 32B
LMArena Text: software and IT11951366Qwen3 32B
Neither model has a result on the other 28 boards here
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index02
Intelligence benchmarks for GPT-4 and Qwen3 32B
BenchmarkGPT-4Qwen3 32BLeader
AA Intelligence Index6.77.3Qwen3 32B
Epoch Capabilities Index125.7138.4Qwen3 32B
Agentic workDirectional onlyPublic boards, shown as published, kept out of the index1 board, none shared
Agentic work benchmarks for GPT-4 and Qwen3 32B
BenchmarkGPT-4Qwen3 32BLeader
τ²-Bench TelecomNot measured29.8%Only Qwen3 32B measured
Neither model has a result on the other 38 boards here
ReasoningLike-for-likePublic boards, shown as published, kept out of the index04
Reasoning benchmarks for GPT-4 and Qwen3 32B
BenchmarkGPT-4Qwen3 32BLeader
GPQA Diamond (Artificial Analysis run)34.9%66.8%Qwen3 32B
Humanity's Last Exam (Artificial Analysis run)Not measured7.4%Only Qwen3 32B measured
GPQA Diamond (Epoch AI run)Not measured65.7%Only Qwen3 32B measured
BIG-Bench Hard75.1%Not measuredOnly GPT-4 measured
LMArena Text: hard prompts12001334Qwen3 32B
LMArena Text: expert11491362Qwen3 32B
LMArena Text: hard prompts in English12091350Qwen3 32B
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 and Qwen3 32B
BenchmarkGPT-4Qwen3 32BLeader
AA Math IndexNot measured73.0Only Qwen3 32B measured
AIME 2025 (Artificial Analysis run)Not measured73.0%Only Qwen3 32B measured
OTIS Mock AIMENot measured66.9%Only Qwen3 32B measured
GSM8K92.0%Not measuredOnly GPT-4 measured
LMArena Text: math12301399Qwen3 32B
LMArena Text: mathematical work12281420Qwen3 32B
Neither model has a result on the other 7 boards here
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index05
Knowledge benchmarks for GPT-4 and Qwen3 32B
BenchmarkGPT-4Qwen3 32BLeader
MMLU Pro (Artificial Analysis run)56.2%79.8%Qwen3 32B
MMLU86.4%Not measuredOnly GPT-4 measured
AI2 Reasoning Challenge96.3%Not measuredOnly GPT-4 measured
LMArena Text: science11771372Qwen3 32B
LMArena Text: medicine and healthcare11451368Qwen3 32B
LMArena Text: legal and government11911324Qwen3 32B
LMArena Text: business and finance11451318Qwen3 32B
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 and Qwen3 32B
BenchmarkGPT-4Qwen3 32BLeader
Neither model has a result on 9 boards here
GeneralLike-for-likePublic boards, shown as published, kept out of the index015
General benchmarks for GPT-4 and Qwen3 32B
BenchmarkGPT-4Qwen3 32BLeader
IFBench33.2%36.3%Qwen3 32B
Long context reasoning (AA-LCR)Not measured0.0%Only Qwen3 32B measured
DTBench62.7%67.5%Qwen3 32B
LMCA17.1%17.3%Qwen3 32B
Fiction.LiveBenchNot measured74.2%Only Qwen3 32B measured
HellaSwag95.3%Not measuredOnly GPT-4 measured
WinoGrande87.5%Not measuredOnly GPT-4 measured
LMArena Text12061340Qwen3 32B
LMArena Text: instruction following12011305Qwen3 32B
LMArena Text: creative writing11911297Qwen3 32B
LMArena Text: English12201359Qwen3 32B
LMArena Text: non-English11941317Qwen3 32B
LMArena Text: Chinese11841357Qwen3 32B
LMArena Text: German11981341Qwen3 32B
LMArena Text: Japanese1137Not measuredOnly GPT-4 measured
LMArena Text: Korean1087Not measuredOnly GPT-4 measured
LMArena Text: French1220Not measuredOnly GPT-4 measured
LMArena Text: Spanish1197Not measuredOnly GPT-4 measured
LMArena Text: Russian11951311Qwen3 32B
LMArena Text: Polish1265Not measuredOnly GPT-4 measured
LMArena Text: multi-turn12061331Qwen3 32B
LMArena Text: longer queries11901327Qwen3 32B
LMArena Text: writing and language12191298Qwen3 32B
LMArena Text: entertainment and media11841279Qwen3 32B
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-4 and Qwen3 32B
BenchmarkGPT-4Qwen3 32BLeader
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$0.060Fits in one request
Qwen3 32B$0.0002Fits in one request

Qwen3 32B costs less

Repository review

50K input + 3K output tokens

GPT-4$1.68Exceeds the context window
Qwen3 32B$0.0048Fits in one request

Qwen3 32B costs less

Agent loop

200K input + 10K output tokens

GPT-4$6.60Exceeds the context window
Qwen3 32B$0.019Exceeds the context window

Qwen3 32B 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 and Qwen3 32B
SpecificationOpenAI GPT-4Qwen3 32B
MakerOpenAIQwen
WeightsNo public weights listedOpen weights
ReleasedMay 28, 2023April 28, 2025
Context window8K131K
Input $/Mtok$30.00$0.08
Output $/Mtok$60.00$0.28
Coding index22.440.0
Independent measurements behind it11
Cost per solved taskNot computableNot computable
SourceOpenRouter listingOpenRouter listing

Questions

Is GPT-4 better than Qwen3 32B for coding?

Pick Qwen3 32B for coding: it scores 40.0 on the Vibe Coding Index against 22.4 for GPT-4. GPT-4 is neither cheaper nor larger in context, and leads no benchmark both models were measured on.

Which is cheaper, GPT-4 or Qwen3 32B?

GPT-4 costs $30.00 per million input tokens and $60.00 per million output tokens; Qwen3 32B costs $0.08 and $0.28. Cost per solved task is known for neither of them.

Which has the bigger context window, GPT-4 or Qwen3 32B?

Qwen3 32B, with 131K tokens against 8K.

How many benchmarks is the GPT-4 vs Qwen3 32B comparison based on?

30 benchmarks have a result for both models as of October 21, 2026. GPT-4's coding index rests on 1 independent benchmark and Qwen3 32B's on 1. Where only one model has a result, the page says so instead of naming a winner.

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