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GPT-5.5 vs Qwen3.8 Max (0902)

Updated October 21, 2026. 103 benchmarks have a result for both. Coding is ranked on the Vibe Coding Index; every other board is shown as published.

Replace GPT-5.5 Replace Qwen3.8 Max (0902)
GPT-5.5OpenAI
Coding
67.8
Overall
38.4
Output $/M
$30.00
40
Qwen3.8 Max (0902)Qwen
Coding
63.5
Overall
45.4
Output $/M
$6.00
63
vs boards won of 103 shared

Decision reading

Pick GPT-5.5 for coding: it scores 67.8 on the Vibe Coding Index against 63.5 for Qwen3.8 Max (0902).

Pick Qwen3.8 Max (0902) when output tokens cost 5.0x less, or when a solved task costs $1.32 against $1.65.

Model AGPT-5.5OpenAI67.8/1002 independent benchmarks$1.65 per solved taskModel BQwen3.8 Max (0902)Qwen63.5/1002 independent benchmarks$1.32 per solved task
Shared results
103
GPT-5.5 only
29
Qwen3.8 Max (0902) only
10
Like-for-like categories
8 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-5.5 67.8 from 2 benchmarks, Qwen3.8 Max (0902) 63.5 from 2 benchmarks.
Widest category
Agentic work, 11.2 points apart on average over 15 shared benchmarks.
Widest single gap
Design Arena: agents building full-stack apps: GPT-5.5 1089 against Qwen3.8 Max (0902) 1305, 27.0 points apart on a 0 to 100 scale.
Output price
GPT-5.5 $30.00 against Qwen3.8 Max (0902) $6.00 per million output tokens, 5.0x apart.
Context window
GPT-5.5 takes 1.05M tokens, Qwen3.8 Max (0902) 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-5.5BarsQwen3.8 Max (0902)Ties
Coding79
Intelligence11
Agentic work411
Reasoning85
Math33
Knowledge56
Web design17
General1121
All shared boards4063
CodingLike-for-likeFour of these boards feed the Vibe Coding Index79
Coding benchmarks for GPT-5.5 and Qwen3.8 Max (0902)
BenchmarkGPT-5.5Qwen3.8 Max (0902)Leader
LiveBench coding85.1%60.3%GPT-5.5
LMArena WebDev15131674Qwen3.8 Max (0902)
AA Coding Index74.976.2Qwen3.8 Max (0902)
LiveCodeBench (Vals AI)85.3%87.8%Qwen3.8 Max (0902)
SWE-bench Verified (Vals AI)82.6%85.6%Qwen3.8 Max (0902)
Terminal-Bench 4 (Vals AI)Not measured34.3%Only Qwen3.8 Max (0902) measured
Vibe Code Bench (Vals AI)69.8%64.7%GPT-5.5
Code migration (Vals AI)45.2%24.0%GPT-5.5
ProgramBench (Vals AI)0.5%0.0%GPT-5.5
IOI (Vals AI)Not measured68.9%Only Qwen3.8 Max (0902) measured
Terminal-Bench 2.1 (Vals AI)76.4%67.4%GPT-5.5
SWE-bench Multimodal (Vals AI)Not measured42.5%Only Qwen3.8 Max (0902) measured
Vibe Code Bench 1-100 (Vals AI)Not measured12.8%Only Qwen3.8 Max (0902) measured
SkillsBench (Vals AI)62.5%42.0%GPT-5.5
CyberBench (Vals AI)Not measured28.6%Only Qwen3.8 Max (0902) measured
SciCode56.1%53.2%GPT-5.5
Terminal-Bench Hard (Artificial Analysis run)60.6%Not measuredOnly GPT-5.5 measured
Terminal-Bench84.7%Not measuredOnly GPT-5.5 measured
FrontierCode43.0%Not measuredOnly GPT-5.5 measured
FrontierSWENot measured17.8%Only Qwen3.8 Max (0902) measured
GSO-Bench40.2%Not measuredOnly GPT-5.5 measured
WeirdML84.9%Not measuredOnly GPT-5.5 measured
MirrorCode10.0%Not measuredOnly GPT-5.5 measured
ALE-Bench1943.0Not measuredOnly GPT-5.5 measured
LMArena Text: coding14941502Qwen3.8 Max (0902)
LMArena Text: software and IT14931498Qwen3.8 Max (0902)
LMArena WebDev: React15061692Qwen3.8 Max (0902)
LMArena WebDev: HTML15431649Qwen3.8 Max (0902)
LMArena WebDev: from an image15321637Qwen3.8 Max (0902)
Neither model has a result on the other 9 boards here
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index11
Intelligence benchmarks for GPT-5.5 and Qwen3.8 Max (0902)
BenchmarkGPT-5.5Qwen3.8 Max (0902)Leader
AA Intelligence Index38.445.4Qwen3.8 Max (0902)
Epoch Capabilities Index159.7157.4GPT-5.5
Agentic workLike-for-likePublic boards, shown as published, kept out of the index411
Agentic work benchmarks for GPT-5.5 and Qwen3.8 Max (0902)
BenchmarkGPT-5.5Qwen3.8 Max (0902)Leader
AA Agentic Index36.456.0Qwen3.8 Max (0902)
Design Arena: agents building web apps11171301Qwen3.8 Max (0902)
Design Arena: agents building full-stack apps10891305Qwen3.8 Max (0902)
Design Arena: agents building mobile apps11431223Qwen3.8 Max (0902)
Design Arena: agents building Android apps11691207Qwen3.8 Max (0902)
Design Arena: agents building Godot games11731234Qwen3.8 Max (0902)
Design Arena: agents building games1179Not measuredOnly GPT-5.5 measured
Design Arena: HTML slides1067Not measuredOnly GPT-5.5 measured
Design Arena: PowerPoint slides11081257Qwen3.8 Max (0902)
Design Arena: spreadsheetsNot measured868Only Qwen3.8 Max (0902) measured
LiveBench research61.6%69.9%Qwen3.8 Max (0902)
LiveBench browser48.0%32.0%GPT-5.5
LiveBench long agentic44.6%42.3%GPT-5.5
SREBench (Vals AI)3.8%Not measuredOnly GPT-5.5 measured
Finance Agent (Vals AI)51.8%50.6%GPT-5.5
Tax Agent Bench (Vals AI)21.8%32.1%Qwen3.8 Max (0902)
Legal Research Bench (Vals AI)40.4%47.6%Qwen3.8 Max (0902)
Excel Modeling Benchmark (Vals AI)64.5%60.1%GPT-5.5
Terminal-Bench-Science (Vals AI)Not measured12.9%Only Qwen3.8 Max (0902) measured
Time Horizon Index (Vals AI)8.3%Not measuredOnly GPT-5.5 measured
τ²-Bench Telecom93.9%Not measuredOnly GPT-5.5 measured
APEX-Agents55.1%63.3%Qwen3.8 Max (0902)
Remote Labor Index6.3%Not measuredOnly GPT-5.5 measured
OSWorld 2.013.0%Not measuredOnly GPT-5.5 measured
DeepResearch Bench54.0%Not measuredOnly GPT-5.5 measured
PostTrainBench27.2%Not measuredOnly GPT-5.5 measured
Vending-Bench 2$7,524Not measuredOnly GPT-5.5 measured
LMArena SearchNot measured1261Only Qwen3.8 Max (0902) measured
Neither model has a result on the other 11 boards here
ReasoningLike-for-likePublic boards, shown as published, kept out of the index85
Reasoning benchmarks for GPT-5.5 and Qwen3.8 Max (0902)
BenchmarkGPT-5.5Qwen3.8 Max (0902)Leader
GPQA Diamond93.2%93.7%Qwen3.8 Max (0902)
LiveBench reasoning89.7%88.2%GPT-5.5
MysteryMechanism (Vals AI)Not measured23.9%Only Qwen3.8 Max (0902) measured
MMMU Pro (Vals AI)88.3%88.0%GPT-5.5
GPQA Diamond (Artificial Analysis run)93.5%92.8%GPT-5.5
Humanity's Last Exam (Artificial Analysis run)45.8%43.1%GPT-5.5
GPQA Diamond (Epoch AI run)90.7%92.7%Qwen3.8 Max (0902)
ARC-AGI95.0%Not measuredOnly GPT-5.5 measured
ARC-AGI-285.0%Not measuredOnly GPT-5.5 measured
SimpleBench69.0%Not measuredOnly GPT-5.5 measured
Chess puzzles63.0%46.0%GPT-5.5
Mystery game puzzles56.0%38.0%GPT-5.5
EBR-bench34.3%Not measuredOnly GPT-5.5 measured
LMArena Text: hard prompts14891496Qwen3.8 Max (0902)
LMArena Text: expert15071507GPT-5.5
LMArena Text: hard prompts in English14831503Qwen3.8 Max (0902)
LMArena Vision: diagrams13251323GPT-5.5
LMArena Vision: homework13321336Qwen3.8 Max (0902)
Neither model has a result on the other 3 boards here
MathLike-for-likePublic boards, shown as published, kept out of the index33
Math benchmarks for GPT-5.5 and Qwen3.8 Max (0902)
BenchmarkGPT-5.5Qwen3.8 Max (0902)Leader
OTIS Mock AIME84.4%100.0%Qwen3.8 Max (0902)
FrontierMath, tiers 1 to 385.3%74.7%GPT-5.5
FrontierMath, tier 472.5%46.3%GPT-5.5
ProofBench50.0%58.0%Qwen3.8 Max (0902)
LMArena Text: math14871501Qwen3.8 Max (0902)
LMArena Text: mathematical work14961491GPT-5.5
Neither model has a result on the other 7 boards here
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index56
Knowledge benchmarks for GPT-5.5 and Qwen3.8 Max (0902)
BenchmarkGPT-5.5Qwen3.8 Max (0902)Leader
MMLU Pro88.1%88.6%Qwen3.8 Max (0902)
LegalBench (Vals AI)86.5%83.6%GPT-5.5
CaseLaw (Vals AI)66.2%Not measuredOnly GPT-5.5 measured
CorpFin (Vals AI)68.4%65.8%GPT-5.5
TaxEval (Vals AI)75.0%75.5%Qwen3.8 Max (0902)
MortgageTax (Vals AI)68.8%64.0%GPT-5.5
MedCode (Vals AI)49.1%40.7%GPT-5.5
SimpleQA Verified63.0%47.3%GPT-5.5
LMArena Text: science14851512Qwen3.8 Max (0902)
LMArena Text: medicine and healthcare14651503Qwen3.8 Max (0902)
LMArena Text: legal and government14911492Qwen3.8 Max (0902)
LMArena Text: business and finance14781480Qwen3.8 Max (0902)
Neither model has a result on the other 5 boards here
Web designLike-for-likePublic boards, shown as published, kept out of the index17
Web design benchmarks for GPT-5.5 and Qwen3.8 Max (0902)
BenchmarkGPT-5.5Qwen3.8 Max (0902)Leader
Design Arena: websites12561275Qwen3.8 Max (0902)
Design Arena: UI components12601340Qwen3.8 Max (0902)
Design Arena: game dev12941313Qwen3.8 Max (0902)
Design Arena: data viz12651281Qwen3.8 Max (0902)
Design Arena: 3D11981337Qwen3.8 Max (0902)
Design Arena: all code categories12601293Qwen3.8 Max (0902)
Design Arena: SVG1234Not measuredOnly GPT-5.5 measured
Design Arena: ASCII art12541201GPT-5.5
LiveBench design70.3%78.6%Qwen3.8 Max (0902)
GeneralLike-for-likePublic boards, shown as published, kept out of the index1121
General benchmarks for GPT-5.5 and Qwen3.8 Max (0902)
BenchmarkGPT-5.5Qwen3.8 Max (0902)Leader
LiveBench data analysis81.6%78.4%GPT-5.5
Public Benefits Bench (Vals AI)60.9%67.1%Qwen3.8 Max (0902)
SAGE (Vals AI)51.5%51.2%GPT-5.5
MedScribe (Vals AI)86.9%85.0%GPT-5.5
Vals Multimodal Index68.1%65.4%GPT-5.5
IFBench75.9%Not measuredOnly GPT-5.5 measured
Long context reasoning (AA-LCR)84.3%80.3%GPT-5.5
DTBench96.0%92.0%GPT-5.5
LMCA54.3%46.2%GPT-5.5
Surface Evolver Bench88.1%Not measuredOnly GPT-5.5 measured
Furniture assembly44.2%20.0%GPT-5.5
ExploitBench47.4%Not measuredOnly GPT-5.5 measured
CL-bench Life22.2%Not measuredOnly GPT-5.5 measured
LMArena Text14711483Qwen3.8 Max (0902)
LMArena Text: instruction following14781481Qwen3.8 Max (0902)
LMArena Text: creative writing14551477Qwen3.8 Max (0902)
LMArena Vision12971313Qwen3.8 Max (0902)
LMArena Text: English14701491Qwen3.8 Max (0902)
LMArena Text: non-English14671473Qwen3.8 Max (0902)
LMArena Text: Chinese15341539Qwen3.8 Max (0902)
LMArena Text: German14801478GPT-5.5
LMArena Text: Japanese14991473GPT-5.5
LMArena Text: Korean14601460Qwen3.8 Max (0902)
LMArena Text: French14851498Qwen3.8 Max (0902)
LMArena Text: Spanish14681489Qwen3.8 Max (0902)
LMArena Text: Russian14731482Qwen3.8 Max (0902)
LMArena Text: Polish14651471Qwen3.8 Max (0902)
LMArena Text: multi-turn14761489Qwen3.8 Max (0902)
LMArena Text: longer queries14841488Qwen3.8 Max (0902)
LMArena Text: writing and language14661477Qwen3.8 Max (0902)
LMArena Text: entertainment and media14491464Qwen3.8 Max (0902)
LMArena Vision: English12921311Qwen3.8 Max (0902)
LMArena Vision: Chinese13601358GPT-5.5
LMArena Vision: reading text13061322Qwen3.8 Max (0902)
LMArena Vision: humor12931304Qwen3.8 Max (0902)
LMArena Vision: recognizing things1231Not measuredOnly GPT-5.5 measured
LMArena Vision: creative writing13011312Qwen3.8 Max (0902)
LMArena Document1486Not measuredOnly GPT-5.5 measured
Neither model has a result on the other 8 boards here
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
Image generation benchmarks for GPT-5.5 and Qwen3.8 Max (0902)
BenchmarkGPT-5.5Qwen3.8 Max (0902)Leader
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-5.5$0.020Fits in one request
Qwen3.8 Max (0902)$0.0050Fits in one request

Qwen3.8 Max (0902) costs less

Repository review

50K input + 3K output tokens

GPT-5.5$0.340Fits in one request
Qwen3.8 Max (0902)$0.118Fits in one request

Qwen3.8 Max (0902) costs less

Agent loop

200K input + 10K output tokens

GPT-5.5$1.30Fits in one request
Qwen3.8 Max (0902)$0.460Fits in one request

Qwen3.8 Max (0902) 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-5.5 and Qwen3.8 Max (0902)
SpecificationOpenAI GPT-5.5Qwen3.8 Max (0902)
MakerOpenAIQwen
WeightsNo public weights listedNo public weights listed
ReleasedApril 24, 2026September 3, 2026
Context window1.05M1M
Input $/Mtok$5.00$2.00
Output $/Mtok$30.00$6.00
Coding index67.863.5
Independent measurements behind it22
Cost per solved task$1.65$1.32
SourceOpenRouter listingOpenRouter listing

Questions

Is GPT-5.5 better than Qwen3.8 Max (0902) for coding?

Pick GPT-5.5 for coding: it scores 67.8 on the Vibe Coding Index against 63.5 for Qwen3.8 Max (0902). Pick Qwen3.8 Max (0902) when output tokens cost 5.0x less, or when a solved task costs $1.32 against $1.65.

Which is cheaper, GPT-5.5 or Qwen3.8 Max (0902)?

GPT-5.5 costs $5.00 per million input tokens and $30.00 per million output tokens; Qwen3.8 Max (0902) costs $2.00 and $6.00. Per solved SWE-bench Verified task, GPT-5.5 costs $1.65 and Qwen3.8 Max (0902) $1.32.

Which has the bigger context window, GPT-5.5 or Qwen3.8 Max (0902)?

GPT-5.5, with 1.05M tokens against 1M.

How many benchmarks is the GPT-5.5 vs Qwen3.8 Max (0902) comparison based on?

103 benchmarks have a result for both models as of October 21, 2026. GPT-5.5's coding index rests on 2 independent benchmarks and Qwen3.8 Max (0902)'s on 2. Where only one model has a result, the page says so instead of naming a winner.

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