Enter opens the highlighted result. Esc closes.

GPT-5 vs Qwen3 VL 235B A22B Instruct

GPT-5 leads Qwen3 VL 235B A22B Instruct on the Artificial Analysis Intelligence Index, 23.0 to 9.9, and Qwen3 VL 235B A22B Instruct costs 5.3x less per output token ($1.90 vs $10.00 per million). Updated October 22, 2026; 49 benchmarks have a result for both.

GPT-5OpenAI
Coding
38.8
Overall
51.5
Output $/M
$10.00
17
Qwen3 VL 235B A22B InstructQwen
Coding
No data
Overall
No data
Output $/M
$1.90
32
vs boards won of 49 shared

GPT-5 or Qwen3 VL 235B A22B Instruct: which to pick

Only GPT-5 has a coding score, 38.8 on the Vibe Coding Index; Qwen3 VL 235B A22B Instruct has none, so the two cannot be ranked on coding.

Pick Qwen3 VL 235B A22B Instruct for output tokens 5.3x cheaper ($1.90 vs $10.00 per million) and work measured by LMArena Text: coding or LMArena Text: software and IT, where it leads.

Shared results
49
GPT-5 only
64
Qwen3 VL 235B A22B Instruct only
0
Like-for-like categories
7 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-5 38.8 from 3 benchmarks, Qwen3 VL 235B A22B Instruct not benchmarked.
Widest category
Agentic work, 32.5 points apart on average over 1 shared benchmark.
Widest single gap
τ²-Bench Telecom: GPT-5 86.5% against Qwen3 VL 235B A22B Instruct 54.1%, 32.5 points apart on a 0 to 100 scale.
Output price
GPT-5 $10.00 against Qwen3 VL 235B A22B Instruct $1.90 per million output tokens, 5.3x apart.
Context window
GPT-5 takes 400K tokens, Qwen3 VL 235B A22B Instruct 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-5BarsQwen3 VL 235B A22B InstructTies
Coding22
Intelligence10
Agentic work10
Reasoning34
Math22
Knowledge14
General720
All shared boards1732
CodingLike-for-likeSix of these boards feed the Vibe Coding Index22
Coding benchmarks for GPT-5 and Qwen3 VL 235B A22B Instruct
BenchmarkGPT-5Qwen3 VL 235B A22B InstructLeader
Aider polyglot88.0%Not measuredOnly GPT-5 measured
SWE-bench Verified74.4%Not measuredOnly GPT-5 measured
LMArena WebDev1418Not measuredOnly GPT-5 measured
AA Coding Index37.8Not measuredOnly GPT-5 measured
LiveCodeBench (Vals AI)85.9%Not measuredOnly GPT-5 measured
SWE-bench Verified (Vals AI)69.0%Not measuredOnly GPT-5 measured
Vibe Code Bench (Vals AI)20.1%Not measuredOnly GPT-5 measured
LiveCodeBench (Artificial Analysis run)84.6%64.6%GPT-5
Terminal-Bench Hard (Artificial Analysis run)37.9%11.4%GPT-5
Terminal-Bench49.6%Not measuredOnly GPT-5 measured
GSO-Bench6.9%Not measuredOnly GPT-5 measured
WeirdML60.7%Not measuredOnly GPT-5 measured
ALE-Bench807.6Not measuredOnly GPT-5 measured
LMArena Text: coding14361438Qwen3 VL 235B A22B Instruct
LMArena Text: software and IT14201442Qwen3 VL 235B A22B Instruct
LMArena WebDev: HTML1427Not measuredOnly GPT-5 measured
SciCode0.0%Not measuredOnly GPT-5 measured
Neither model has a result on the other 22 boards here
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index10
Intelligence benchmarks for GPT-5 and Qwen3 VL 235B A22B Instruct
BenchmarkGPT-5Qwen3 VL 235B A22B InstructLeader
AA Intelligence Index23.09.9GPT-5
Epoch Capabilities Index150.0Not measuredOnly GPT-5 measured
Agentic workLike-for-likePublic boards, shown as published, kept out of the index10
Agentic work benchmarks for GPT-5 and Qwen3 VL 235B A22B Instruct
BenchmarkGPT-5Qwen3 VL 235B A22B InstructLeader
τ²-Bench Telecom86.5%54.1%GPT-5
METR time horizons69.6%Not measuredOnly GPT-5 measured
Remote Labor Index1.7%Not measuredOnly GPT-5 measured
GDPval34.8%Not measuredOnly GPT-5 measured
BALROG32.8%Not measuredOnly GPT-5 measured
DeepResearch Bench49.6%Not measuredOnly GPT-5 measured
BrowseComp-Plus80.0%Not measuredOnly GPT-5 measured
Neither model has a result on the other 34 boards here
ReasoningLike-for-likePublic boards, shown as published, kept out of the index34
Reasoning benchmarks for GPT-5 and Qwen3 VL 235B A22B Instruct
BenchmarkGPT-5Qwen3 VL 235B A22B InstructLeader
GPQA Diamond85.6%Not measuredOnly GPT-5 measured
MMMU Pro (Vals AI)81.5%Not measuredOnly GPT-5 measured
GPQA Diamond (Artificial Analysis run)85.4%77.2%GPT-5
Humanity's Last Exam (Artificial Analysis run)28.5%11.9%GPT-5
GPQA Diamond (Epoch AI run)86.2%Not measuredOnly GPT-5 measured
ARC-AGI65.7%Not measuredOnly GPT-5 measured
ARC-AGI-29.9%Not measuredOnly GPT-5 measured
SimpleBench56.7%Not measuredOnly GPT-5 measured
Chess puzzles36.0%Not measuredOnly GPT-5 measured
Mystery game puzzles23.0%Not measuredOnly GPT-5 measured
EBR-bench12.7%Not measuredOnly GPT-5 measured
VPCT66.0%Not measuredOnly GPT-5 measured
LMArena Text: hard prompts14151428Qwen3 VL 235B A22B Instruct
LMArena Text: expert14191442Qwen3 VL 235B A22B Instruct
LMArena Text: hard prompts in English14191439Qwen3 VL 235B A22B Instruct
LMArena Vision: diagrams12521255Qwen3 VL 235B A22B Instruct
LMArena Vision: homework12781277GPT-5
Kagi LLM Benchmark72.7%Not measuredOnly GPT-5 measured
Neither model has a result on the other 4 boards here
MathLike-for-likePublic boards, shown as published, kept out of the index22
Math benchmarks for GPT-5 and Qwen3 VL 235B A22B Instruct
BenchmarkGPT-5Qwen3 VL 235B A22B InstructLeader
AIME93.4%Not measuredOnly GPT-5 measured
MATH 500 (Vals AI)96.0%Not measuredOnly GPT-5 measured
MGSM (Vals AI)92.8%Not measuredOnly GPT-5 measured
AA Math Index94.388.3GPT-5
AIME 2025 (Artificial Analysis run)94.3%88.3%GPT-5
OTIS Mock AIME91.4%Not measuredOnly GPT-5 measured
FrontierMath, tiers 1 to 355.4%Not measuredOnly GPT-5 measured
FrontierMath, tier 422.0%Not measuredOnly GPT-5 measured
ProofBench18.0%Not measuredOnly GPT-5 measured
MATH level 598.1%Not measuredOnly GPT-5 measured
LMArena Text: math14071425Qwen3 VL 235B A22B Instruct
LMArena Text: mathematical work14051419Qwen3 VL 235B A22B Instruct
Neither model has a result on the other 1 board here
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index14
Knowledge benchmarks for GPT-5 and Qwen3 VL 235B A22B Instruct
BenchmarkGPT-5Qwen3 VL 235B A22B InstructLeader
MMLU Pro86.5%Not measuredOnly GPT-5 measured
LegalBench (Vals AI)86.0%Not measuredOnly GPT-5 measured
CaseLaw (Vals AI)66.5%Not measuredOnly GPT-5 measured
CorpFin (Vals AI)61.1%Not measuredOnly GPT-5 measured
TaxEval (Vals AI)73.4%Not measuredOnly GPT-5 measured
MortgageTax (Vals AI)65.5%Not measuredOnly GPT-5 measured
MedQA (Vals AI)96.3%Not measuredOnly GPT-5 measured
MedCode (Vals AI)49.6%Not measuredOnly GPT-5 measured
MMLU Pro (Artificial Analysis run)87.1%83.6%GPT-5
SimpleQA Verified50.1%Not measuredOnly GPT-5 measured
GeoBench81.0%Not measuredOnly GPT-5 measured
LMArena Text: science14161444Qwen3 VL 235B A22B Instruct
LMArena Text: medicine and healthcare14131431Qwen3 VL 235B A22B Instruct
LMArena Text: legal and government14311438Qwen3 VL 235B A22B Instruct
LMArena Text: business and finance14001433Qwen3 VL 235B A22B Instruct
FACTS Benchmark Suite56.5%Not measuredOnly GPT-5 measured
Neither model has a result on the other 2 boards here
Web designDirectional onlyPublic boards, shown as published, kept out of the index8 boards, none shared
Web design benchmarks for GPT-5 and Qwen3 VL 235B A22B Instruct
BenchmarkGPT-5Qwen3 VL 235B A22B InstructLeader
Design Arena: websites1184Not measuredOnly GPT-5 measured
Design Arena: UI components1177Not measuredOnly GPT-5 measured
Design Arena: game dev1185Not measuredOnly GPT-5 measured
Design Arena: data viz1221Not measuredOnly GPT-5 measured
Design Arena: 3D1055Not measuredOnly GPT-5 measured
Design Arena: all code categories1167Not measuredOnly GPT-5 measured
Design Arena: SVG1188Not measuredOnly GPT-5 measured
Design Arena: ASCII art1141Not measuredOnly GPT-5 measured
Neither model has a result on the other 1 board here
GeneralLike-for-likePublic boards, shown as published, kept out of the index720
General benchmarks for GPT-5 and Qwen3 VL 235B A22B Instruct
BenchmarkGPT-5Qwen3 VL 235B A22B InstructLeader
SAGE (Vals AI)43.7%Not measuredOnly GPT-5 measured
MedScribe (Vals AI)83.7%Not measuredOnly GPT-5 measured
IFBench73.1%56.5%GPT-5
Long context reasoning (AA-LCR)78.2%63.7%GPT-5
DTBench90.7%Not measuredOnly GPT-5 measured
LMCA40.0%Not measuredOnly GPT-5 measured
Fiction.LiveBench97.2%Not measuredOnly GPT-5 measured
Creative writing (Lech Mazur)86.0%Not measuredOnly GPT-5 measured
LMArena Text14061420Qwen3 VL 235B A22B Instruct
LMArena Text: instruction following13881406Qwen3 VL 235B A22B Instruct
LMArena Text: creative writing13651366Qwen3 VL 235B A22B Instruct
LMArena Vision12321247Qwen3 VL 235B A22B Instruct
LMArena Text: English14091429Qwen3 VL 235B A22B Instruct
LMArena Text: non-English13971405Qwen3 VL 235B A22B Instruct
LMArena Text: Chinese14221463Qwen3 VL 235B A22B Instruct
LMArena Text: German14161424Qwen3 VL 235B A22B Instruct
LMArena Text: Japanese14091385GPT-5
LMArena Text: Korean13601394Qwen3 VL 235B A22B Instruct
LMArena Text: French14091452Qwen3 VL 235B A22B Instruct
LMArena Text: Spanish13991428Qwen3 VL 235B A22B Instruct
LMArena Text: Russian14071408Qwen3 VL 235B A22B Instruct
LMArena Text: Polish14311419GPT-5
LMArena Text: multi-turn14261428Qwen3 VL 235B A22B Instruct
LMArena Text: longer queries13991419Qwen3 VL 235B A22B Instruct
LMArena Text: writing and language13841392Qwen3 VL 235B A22B Instruct
LMArena Text: entertainment and media13791368GPT-5
LMArena Vision: English12311256Qwen3 VL 235B A22B Instruct
LMArena Vision: Chinese12671283Qwen3 VL 235B A22B Instruct
LMArena Vision: reading text12461253Qwen3 VL 235B A22B Instruct
LMArena Vision: humor12191209GPT-5
LMArena Vision: captioning12121281Qwen3 VL 235B A22B Instruct
LMArena Vision: recognizing things12631249GPT-5
LMArena Vision: creative writing12101220Qwen3 VL 235B A22B Instruct
Neither model has a result on the other 13 boards here
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
Image generation benchmarks for GPT-5 and Qwen3 VL 235B A22B Instruct
BenchmarkGPT-5Qwen3 VL 235B A22B InstructLeader
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-5$0.0063Fits in one request
Qwen3 VL 235B A22B Instruct$0.0012Fits in one request

Qwen3 VL 235B A22B Instruct costs less

Repository review

50K input + 3K output tokens

GPT-5$0.092Fits in one request
Qwen3 VL 235B A22B Instruct$0.016Fits in one request

Qwen3 VL 235B A22B Instruct costs less

Agent loop

200K input + 10K output tokens

GPT-5$0.350Fits in one request
Qwen3 VL 235B A22B Instruct$0.061Fits in one request

Qwen3 VL 235B A22B Instruct 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-5 and Qwen3 VL 235B A22B Instruct
SpecificationOpenAI GPT-5Qwen3 VL 235B A22B Instruct
MakerOpenAIQwen
WeightsNo public weights listedOpen weights
ReleasedAugust 7, 2025September 23, 2025
Context window400K262K
Input $/Mtok$1.25$0.21
Output $/Mtok$10.00$1.90
Coding index38.8Not benchmarked
Independent measurements behind it30
Cost per solved task$0.39Not computable
SourceOpenRouter listingOpenRouter listing

Questions

Is GPT-5 better than Qwen3 VL 235B A22B Instruct for coding?

Only GPT-5 has a coding score, 38.8 on the Vibe Coding Index; Qwen3 VL 235B A22B Instruct has none, so the two cannot be ranked on coding. Pick Qwen3 VL 235B A22B Instruct for output tokens 5.3x cheaper ($1.90 vs $10.00 per million) and work measured by LMArena Text: coding or LMArena Text: software and IT, where it leads.

Which is cheaper, GPT-5 or Qwen3 VL 235B A22B Instruct?

GPT-5 costs $1.25 per million input tokens and $10.00 per million output tokens; Qwen3 VL 235B A22B Instruct costs $0.21 and $1.90. Cost per solved task is known for GPT-5 only.

Which has the bigger context window, GPT-5 or Qwen3 VL 235B A22B Instruct?

GPT-5, with 400K tokens against 262K.

How many benchmarks is the GPT-5 vs Qwen3 VL 235B A22B Instruct comparison based on?

49 benchmarks have a result for both models as of October 22, 2026. GPT-5's coding index rests on 3 independent benchmarks and Qwen3 VL 235B A22B Instruct's on 0. Where only one model has a result, the page says so instead of naming a winner.

Compare next