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GPT-5.3-Codex vs Qwen3.7 Max

GPT-5.3-Codex leads Qwen3.7 Max on coding, 60.0 to 54.1 on the Vibe Coding Index, and Qwen3.7 Max costs 3.2x less per output token ($4.425 vs $14.00 per million). Updated October 21, 2026; 28 benchmarks have a result for both.

GPT-5.3-CodexOpenAI
Coding
60.0
Overall
No data
Output $/M
$14.00
9
Qwen3.7 MaxQwen
Coding
54.1
Overall
61.7
Output $/M
$4.425
19
vs boards won of 28 shared

GPT-5.3-Codex or Qwen3.7 Max: which to pick

Pick GPT-5.3-Codex for coding: it scores 60.0 on the Vibe Coding Index against 54.1 for Qwen3.7 Max.

Pick Qwen3.7 Max for output tokens 3.2x cheaper ($4.425 vs $14.00 per million) and a larger context window (1M against 400K tokens).

Shared results
28
GPT-5.3-Codex only
6
Qwen3.7 Max only
31
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-5.3-Codex 60.0 from 3 benchmarks, Qwen3.7 Max 54.1 from 3 benchmarks.
Widest category
Web design, 15.5 points apart on average over 8 shared benchmarks.
Widest single gap
Design Arena: 3D: GPT-5.3-Codex 1008 against Qwen3.7 Max 1266, 32.3 points apart on a 0 to 100 scale.
Output price
GPT-5.3-Codex $14.00 against Qwen3.7 Max $4.425 per million output tokens, 3.2x apart.
Context window
GPT-5.3-Codex takes 400K tokens, Qwen3.7 Max 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-5.3-CodexBarsQwen3.7 MaxTies
Coding53
Intelligence20
Agentic work06
Reasoning11
Web design08
General11
All shared boards919
CodingLike-for-likeSix of these boards feed the Vibe Coding Index53
Coding benchmarks for GPT-5.3-Codex and Qwen3.7 Max
BenchmarkGPT-5.3-CodexQwen3.7 MaxLeader
LMArena WebDev14071515Qwen3.7 Max
AA Coding IndexNot measured66.0Only Qwen3.7 Max measured
LiveCodeBench (Vals AI)87.3%87.1%GPT-5.3-Codex
SWE-bench Verified (Vals AI)78.0%68.8%GPT-5.3-Codex
Vibe Code Bench (Vals AI)61.8%47.7%GPT-5.3-Codex
Code migration (Vals AI)Not measured13.1%Only Qwen3.7 Max measured
IOI (Vals AI)53.8%Not measuredOnly GPT-5.3-Codex measured
Terminal-Bench 2.1 (Vals AI)Not measured61.0%Only Qwen3.7 Max measured
SciCodeNot measured49.5%Only Qwen3.7 Max measured
Terminal-Bench Hard (Artificial Analysis run)53.0%50.8%GPT-5.3-Codex
Terminal-Bench78.4%Not measuredOnly GPT-5.3-Codex measured
WeirdML79.3%Not measuredOnly GPT-5.3-Codex measured
ALE-Bench1655.21189.4GPT-5.3-Codex
LMArena WebDev: React13951514Qwen3.7 Max
LMArena WebDev: HTML14221512Qwen3.7 Max
LMArena WebDev: from an image1443Not measuredOnly GPT-5.3-Codex measured
Neither model has a result on the other 23 boards here
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index20
Intelligence benchmarks for GPT-5.3-Codex and Qwen3.7 Max
BenchmarkGPT-5.3-CodexQwen3.7 MaxLeader
AA Intelligence Index32.529.5GPT-5.3-Codex
Epoch Capabilities Index157.1154.0GPT-5.3-Codex
Agentic workLike-for-likePublic boards, shown as published, kept out of the index06
Agentic work benchmarks for GPT-5.3-Codex and Qwen3.7 Max
BenchmarkGPT-5.3-CodexQwen3.7 MaxLeader
AA Agentic IndexNot measured22.5Only Qwen3.7 Max measured
Design Arena: agents building web apps10321208Qwen3.7 Max
Design Arena: agents building full-stack apps9831191Qwen3.7 Max
Design Arena: agents building mobile apps10541155Qwen3.7 Max
Design Arena: agents building Android apps10841159Qwen3.7 Max
Design Arena: agents building Godot games11241187Qwen3.7 Max
Design Arena: agents building gamesNot measured1161Only Qwen3.7 Max measured
Design Arena: HTML slidesNot measured1158Only Qwen3.7 Max measured
Design Arena: PowerPoint slidesNot measured1197Only Qwen3.7 Max measured
Finance Agent (Vals AI)Not measured47.8%Only Qwen3.7 Max measured
Tax Agent Bench (Vals AI)Not measured15.8%Only Qwen3.7 Max measured
Legal Research Bench (Vals AI)Not measured25.5%Only Qwen3.7 Max measured
Excel Modeling Benchmark (Vals AI)Not measured57.0%Only Qwen3.7 Max measured
τ²-Bench Telecom86.0%94.7%Qwen3.7 Max
METR time horizons74.5%Not measuredOnly GPT-5.3-Codex measured
Vending-Bench 2$5,940Not measuredOnly GPT-5.3-Codex measured
Neither model has a result on the other 25 boards here
ReasoningLike-for-likePublic boards, shown as published, kept out of the index11
Reasoning benchmarks for GPT-5.3-Codex and Qwen3.7 Max
BenchmarkGPT-5.3-CodexQwen3.7 MaxLeader
GPQA DiamondNot measured90.2%Only Qwen3.7 Max measured
GPQA Diamond (Artificial Analysis run)91.5%92.3%Qwen3.7 Max
Humanity's Last Exam (Artificial Analysis run)42.5%40.5%GPT-5.3-Codex
GPQA Diamond (Epoch AI run)Not measured90.9%Only Qwen3.7 Max measured
SimpleBenchNot measured70.4%Only Qwen3.7 Max measured
Chess puzzlesNot measured26.0%Only Qwen3.7 Max measured
Mystery game puzzlesNot measured32.0%Only Qwen3.7 Max measured
EBR-benchNot measured9.5%Only Qwen3.7 Max measured
Neither model has a result on the other 14 boards here
MathDirectional onlyPublic boards, shown as published, kept out of the index4 boards, none shared
Math benchmarks for GPT-5.3-Codex and Qwen3.7 Max
BenchmarkGPT-5.3-CodexQwen3.7 MaxLeader
OTIS Mock AIMENot measured95.6%Only Qwen3.7 Max measured
FrontierMath, tiers 1 to 3Not measured64.6%Only Qwen3.7 Max measured
FrontierMath, tier 4Not measured34.1%Only Qwen3.7 Max measured
ProofBenchNot measured26.0%Only Qwen3.7 Max measured
Neither model has a result on the other 9 boards here
KnowledgeDirectional onlyPublic boards, shown as published, kept out of the index6 boards, none shared
Knowledge benchmarks for GPT-5.3-Codex and Qwen3.7 Max
BenchmarkGPT-5.3-CodexQwen3.7 MaxLeader
MMLU ProNot measured89.3%Only Qwen3.7 Max measured
LegalBench (Vals AI)Not measured84.9%Only Qwen3.7 Max measured
CorpFin (Vals AI)Not measured63.7%Only Qwen3.7 Max measured
TaxEval (Vals AI)Not measured75.3%Only Qwen3.7 Max measured
MedCode (Vals AI)Not measured38.8%Only Qwen3.7 Max measured
SimpleQA VerifiedNot measured55.8%Only Qwen3.7 Max measured
Neither model has a result on the other 12 boards here
Web designLike-for-likePublic boards, shown as published, kept out of the index08
Web design benchmarks for GPT-5.3-Codex and Qwen3.7 Max
BenchmarkGPT-5.3-CodexQwen3.7 MaxLeader
Design Arena: websites11631274Qwen3.7 Max
Design Arena: UI components11371270Qwen3.7 Max
Design Arena: game dev11611265Qwen3.7 Max
Design Arena: data viz11641275Qwen3.7 Max
Design Arena: 3D10081266Qwen3.7 Max
Design Arena: all code categories11451275Qwen3.7 Max
Design Arena: SVG11291217Qwen3.7 Max
Design Arena: ASCII art11521211Qwen3.7 Max
Neither model has a result on the other 1 board here
GeneralLike-for-likePublic boards, shown as published, kept out of the index11
General benchmarks for GPT-5.3-Codex and Qwen3.7 Max
BenchmarkGPT-5.3-CodexQwen3.7 MaxLeader
MedScribe (Vals AI)Not measured79.4%Only Qwen3.7 Max measured
IFBench75.4%80.5%Qwen3.7 Max
Long context reasoning (AA-LCR)83.3%79.0%GPT-5.3-Codex
DTBenchNot measured92.3%Only Qwen3.7 Max measured
LMCANot measured44.0%Only Qwen3.7 Max measured
Neither model has a result on the other 41 boards here
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
Image generation benchmarks for GPT-5.3-Codex and Qwen3.7 Max
BenchmarkGPT-5.3-CodexQwen3.7 MaxLeader
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-5.3-Codex$0.0088Fits in one request
Qwen3.7 Max$0.0037Fits in one request

Qwen3.7 Max costs less

Repository review

50K input + 3K output tokens

GPT-5.3-Codex$0.130Fits in one request
Qwen3.7 Max$0.087Fits in one request

Qwen3.7 Max costs less

Agent loop

200K input + 10K output tokens

GPT-5.3-Codex$0.490Fits in one request
Qwen3.7 Max$0.339Fits in one request

Qwen3.7 Max 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-5.3-Codex and Qwen3.7 Max
SpecificationOpenAI GPT-5.3-CodexQwen3.7 Max
MakerOpenAIQwen
WeightsNo public weights listedNo public weights listed
ReleasedFebruary 24, 2026May 21, 2026
Context window400K1M
Input $/Mtok$1.75$1.475
Output $/Mtok$14.00$4.425
Coding index60.054.1
Independent measurements behind it33
Cost per solved task$0.59$4.69
SourceOpenRouter listingOpenRouter listing

Questions

Is GPT-5.3-Codex better than Qwen3.7 Max for coding?

Pick GPT-5.3-Codex for coding: it scores 60.0 on the Vibe Coding Index against 54.1 for Qwen3.7 Max. Pick Qwen3.7 Max for output tokens 3.2x cheaper ($4.425 vs $14.00 per million) and a larger context window (1M against 400K tokens).

Which is cheaper, GPT-5.3-Codex or Qwen3.7 Max?

GPT-5.3-Codex costs $1.75 per million input tokens and $14.00 per million output tokens; Qwen3.7 Max costs $1.475 and $4.425. Per solved SWE-bench Verified task, GPT-5.3-Codex costs $0.59 and Qwen3.7 Max $4.69.

Which has the bigger context window, GPT-5.3-Codex or Qwen3.7 Max?

Qwen3.7 Max, with 1M tokens against 400K.

How many benchmarks is the GPT-5.3-Codex vs Qwen3.7 Max comparison based on?

28 benchmarks have a result for both models as of October 21, 2026. GPT-5.3-Codex's coding index rests on 3 independent benchmarks and Qwen3.7 Max's on 3. Where only one model has a result, the page says so instead of naming a winner.

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<p style="font:13px/1.4 sans-serif;margin:6px 0 0">Source: <a href="https://llmbenchmark.ai/compare/gpt-5-3-codex-vs-qwen3-7-max">LLMBenchmark.ai, GPT-5.3-Codex vs Qwen3.7 Max</a></p>