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Claude Opus 4.8 vs Qwen3.8 Max (0902)

Updated October 21, 2026. 105 benchmarks have a result for both. Coding is ranked on the Vibe Coding Index; every other board is shown as published.

Replace Claude Opus 4.8 Replace Qwen3.8 Max (0902)
Claude Opus 4.8Anthropic
Coding
66.0
Overall
41.8
Output $/M
$25.00
38
Qwen3.8 Max (0902)Qwen
Coding
63.5
Overall
45.4
Output $/M
$6.00
67
vs boards won of 105 shared

Decision reading

Pick Claude Opus 4.8 for coding: it scores 66.0 on the Vibe Coding Index against 63.5 for Qwen3.8 Max (0902).

Pick Qwen3.8 Max (0902) when output tokens cost 4.2x less, or when a solved task costs $1.32 against $2.17.

Model AClaude Opus 4.8Anthropic66.0/1002 independent benchmarks$2.17 per solved taskModel BQwen3.8 Max (0902)Qwen63.5/1002 independent benchmarks$1.32 per solved task
Shared results
105
Claude Opus 4.8 only
21
Qwen3.8 Max (0902) only
8
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
Claude Opus 4.8 66.0 from 2 benchmarks, Qwen3.8 Max (0902) 63.5 from 2 benchmarks.
Widest category
Agentic work, 10.0 points apart on average over 17 shared benchmarks.
Widest single gap
LiveBench browser: Claude Opus 4.8 96.0% against Qwen3.8 Max (0902) 32.0%, 64.0 points apart on a 0 to 100 scale.
Output price
Claude Opus 4.8 $25.00 against Qwen3.8 Max (0902) $6.00 per million output tokens, 4.2x apart.
Context window
Both take 1M tokens.

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
CategoryClaude Opus 4.8BarsQwen3.8 Max (0902)Ties
Coding88
Intelligence11
Agentic work611
Reasoning49
Math42
Knowledge65
Web design26
General725
All shared boards3867
CodingLike-for-likeFour of these boards feed the Vibe Coding Index88
Coding benchmarks for Claude Opus 4.8 and Qwen3.8 Max (0902)
BenchmarkClaude Opus 4.8Qwen3.8 Max (0902)Leader
LiveBench coding77.3%60.3%Claude Opus 4.8
LMArena WebDev15561674Qwen3.8 Max (0902)
AA Coding Index74.376.2Qwen3.8 Max (0902)
LiveCodeBench (Vals AI)87.8%87.8%Qwen3.8 Max (0902)
SWE-bench Verified (Vals AI)88.6%85.6%Claude Opus 4.8
Terminal-Bench 4 (Vals AI)23.2%34.3%Qwen3.8 Max (0902)
Vibe Code Bench (Vals AI)82.7%64.7%Claude Opus 4.8
Code migration (Vals AI)47.3%24.0%Claude Opus 4.8
ProgramBench (Vals AI)1.0%0.0%Claude Opus 4.8
IOI (Vals AI)Not measured68.9%Only Qwen3.8 Max (0902) measured
Terminal-Bench 2.1 (Vals AI)71.9%67.4%Claude Opus 4.8
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)59.2%42.0%Claude Opus 4.8
CyberBench (Vals AI)Not measured28.6%Only Qwen3.8 Max (0902) measured
SciCode54.4%53.2%Claude Opus 4.8
Terminal-Bench Hard (Artificial Analysis run)58.3%Not measuredOnly Claude Opus 4.8 measured
FrontierCode46.5%Not measuredOnly Claude Opus 4.8 measured
FrontierSWENot measured17.8%Only Qwen3.8 Max (0902) measured
GSO-Bench47.1%Not measuredOnly Claude Opus 4.8 measured
WeirdML82.9%Not measuredOnly Claude Opus 4.8 measured
LMArena Text: coding14901502Qwen3.8 Max (0902)
LMArena Text: software and IT14881498Qwen3.8 Max (0902)
LMArena WebDev: React15571692Qwen3.8 Max (0902)
LMArena WebDev: HTML15431649Qwen3.8 Max (0902)
LMArena WebDev: from an imageNot measured1637Only Qwen3.8 Max (0902) measured
Neither model has a result on the other 12 boards here
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index11
Intelligence benchmarks for Claude Opus 4.8 and Qwen3.8 Max (0902)
BenchmarkClaude Opus 4.8Qwen3.8 Max (0902)Leader
AA Intelligence Index41.845.4Qwen3.8 Max (0902)
Epoch Capabilities Index159.0157.4Claude Opus 4.8
Agentic workLike-for-likePublic boards, shown as published, kept out of the index611
Agentic work benchmarks for Claude Opus 4.8 and Qwen3.8 Max (0902)
BenchmarkClaude Opus 4.8Qwen3.8 Max (0902)Leader
AA Agentic Index41.956.0Qwen3.8 Max (0902)
Design Arena: agents building web apps12331301Qwen3.8 Max (0902)
Design Arena: agents building full-stack apps12491305Qwen3.8 Max (0902)
Design Arena: agents building mobile apps12221223Qwen3.8 Max (0902)
Design Arena: agents building Android apps12371207Claude Opus 4.8
Design Arena: agents building Godot games12311234Qwen3.8 Max (0902)
Design Arena: agents building games1238Not measuredOnly Claude Opus 4.8 measured
Design Arena: HTML slides1221Not measuredOnly Claude Opus 4.8 measured
Design Arena: PowerPoint slides12271257Qwen3.8 Max (0902)
Design Arena: spreadsheetsNot measured868Only Qwen3.8 Max (0902) measured
LiveBench research81.8%69.9%Claude Opus 4.8
LiveBench browser96.0%32.0%Claude Opus 4.8
LiveBench long agentic48.3%42.3%Claude Opus 4.8
Finance Agent (Vals AI)53.9%50.6%Claude Opus 4.8
Tax Agent Bench (Vals AI)30.0%32.1%Qwen3.8 Max (0902)
Legal Research Bench (Vals AI)43.8%47.6%Qwen3.8 Max (0902)
Excel Modeling Benchmark (Vals AI)69.4%60.1%Claude Opus 4.8
Terminal-Bench-Science (Vals AI)4.3%12.9%Qwen3.8 Max (0902)
Time Horizon Index (Vals AI)11.8%Not measuredOnly Claude Opus 4.8 measured
τ²-Bench Telecom94.4%Not measuredOnly Claude Opus 4.8 measured
APEX-Agents48.9%63.3%Qwen3.8 Max (0902)
Remote Labor Index8.3%Not measuredOnly Claude Opus 4.8 measured
OSWorld 2.020.6%Not measuredOnly Claude Opus 4.8 measured
DeepResearch Bench50.2%Not measuredOnly Claude Opus 4.8 measured
PostTrainBench33.8%Not measuredOnly Claude Opus 4.8 measured
Vending-Bench 2$5,787Not measuredOnly Claude Opus 4.8 measured
LMArena Search12041261Qwen3.8 Max (0902)
Neither model has a result on the other 12 boards here
ReasoningLike-for-likePublic boards, shown as published, kept out of the index49
Reasoning benchmarks for Claude Opus 4.8 and Qwen3.8 Max (0902)
BenchmarkClaude Opus 4.8Qwen3.8 Max (0902)Leader
GPQA Diamond92.4%93.7%Qwen3.8 Max (0902)
LiveBench reasoning89.2%88.2%Claude Opus 4.8
MysteryMechanism (Vals AI)Not measured23.9%Only Qwen3.8 Max (0902) measured
MMMU Pro (Vals AI)86.6%88.0%Qwen3.8 Max (0902)
GPQA Diamond (Artificial Analysis run)92.0%92.8%Qwen3.8 Max (0902)
Humanity's Last Exam (Artificial Analysis run)48.7%43.1%Claude Opus 4.8
GPQA Diamond (Epoch AI run)91.0%92.7%Qwen3.8 Max (0902)
ARC-AGI92.5%Not measuredOnly Claude Opus 4.8 measured
ARC-AGI-272.1%Not measuredOnly Claude Opus 4.8 measured
SimpleBench64.8%Not measuredOnly Claude Opus 4.8 measured
Chess puzzles52.0%46.0%Claude Opus 4.8
Mystery game puzzles36.0%38.0%Qwen3.8 Max (0902)
EBR-bench28.6%Not measuredOnly Claude Opus 4.8 measured
LMArena Text: hard prompts14821496Qwen3.8 Max (0902)
LMArena Text: expert15031507Qwen3.8 Max (0902)
LMArena Text: hard prompts in English14871503Qwen3.8 Max (0902)
LMArena Vision: diagrams13151323Qwen3.8 Max (0902)
LMArena Vision: homework13371336Claude Opus 4.8
Neither model has a result on the other 3 boards here
MathLike-for-likePublic boards, shown as published, kept out of the index42
Math benchmarks for Claude Opus 4.8 and Qwen3.8 Max (0902)
BenchmarkClaude Opus 4.8Qwen3.8 Max (0902)Leader
OTIS Mock AIME98.3%100.0%Qwen3.8 Max (0902)
FrontierMath, tiers 1 to 380.0%74.7%Claude Opus 4.8
FrontierMath, tier 456.1%46.3%Claude Opus 4.8
ProofBench69.0%58.0%Claude Opus 4.8
LMArena Text: math14861501Qwen3.8 Max (0902)
LMArena Text: mathematical work14971491Claude Opus 4.8
Neither model has a result on the other 7 boards here
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index65
Knowledge benchmarks for Claude Opus 4.8 and Qwen3.8 Max (0902)
BenchmarkClaude Opus 4.8Qwen3.8 Max (0902)Leader
MMLU Pro89.6%88.6%Claude Opus 4.8
LegalBench (Vals AI)83.6%83.6%Qwen3.8 Max (0902)
CorpFin (Vals AI)66.7%65.8%Claude Opus 4.8
TaxEval (Vals AI)75.6%75.5%Claude Opus 4.8
MortgageTax (Vals AI)69.9%64.0%Claude Opus 4.8
MedCode (Vals AI)53.2%40.7%Claude Opus 4.8
SimpleQA Verified53.0%47.3%Claude Opus 4.8
LMArena Text: science14771512Qwen3.8 Max (0902)
LMArena Text: medicine and healthcare14641503Qwen3.8 Max (0902)
LMArena Text: legal and government14771492Qwen3.8 Max (0902)
LMArena Text: business and finance14581480Qwen3.8 Max (0902)
Neither model has a result on the other 6 boards here
Web designLike-for-likePublic boards, shown as published, kept out of the index26
Web design benchmarks for Claude Opus 4.8 and Qwen3.8 Max (0902)
BenchmarkClaude Opus 4.8Qwen3.8 Max (0902)Leader
Design Arena: websites12581275Qwen3.8 Max (0902)
Design Arena: UI components12561340Qwen3.8 Max (0902)
Design Arena: game dev12641313Qwen3.8 Max (0902)
Design Arena: data viz12401281Qwen3.8 Max (0902)
Design Arena: 3D12231337Qwen3.8 Max (0902)
Design Arena: all code categories12551293Qwen3.8 Max (0902)
Design Arena: SVG1194Not measuredOnly Claude Opus 4.8 measured
Design Arena: ASCII art12761201Claude Opus 4.8
LiveBench design78.8%78.6%Claude Opus 4.8
GeneralLike-for-likePublic boards, shown as published, kept out of the index725
General benchmarks for Claude Opus 4.8 and Qwen3.8 Max (0902)
BenchmarkClaude Opus 4.8Qwen3.8 Max (0902)Leader
LiveBench data analysis66.0%78.4%Qwen3.8 Max (0902)
Public Benefits Bench (Vals AI)68.1%67.1%Claude Opus 4.8
SAGE (Vals AI)54.8%51.2%Claude Opus 4.8
MedScribe (Vals AI)85.8%85.0%Claude Opus 4.8
Vals Multimodal Index70.9%65.4%Claude Opus 4.8
IFBench62.2%Not measuredOnly Claude Opus 4.8 measured
Long context reasoning (AA-LCR)77.7%80.3%Qwen3.8 Max (0902)
DTBench94.9%92.0%Claude Opus 4.8
LMCA57.5%46.2%Claude Opus 4.8
Surface Evolver Bench87.5%Not measuredOnly Claude Opus 4.8 measured
Furniture assembly42.5%20.0%Claude Opus 4.8
LMArena Text14611483Qwen3.8 Max (0902)
LMArena Text: instruction following14761481Qwen3.8 Max (0902)
LMArena Text: creative writing14541477Qwen3.8 Max (0902)
LMArena Vision12941313Qwen3.8 Max (0902)
LMArena Text: English14681491Qwen3.8 Max (0902)
LMArena Text: non-English14501473Qwen3.8 Max (0902)
LMArena Text: Chinese15061539Qwen3.8 Max (0902)
LMArena Text: German14721478Qwen3.8 Max (0902)
LMArena Text: Japanese14421473Qwen3.8 Max (0902)
LMArena Text: Korean14311460Qwen3.8 Max (0902)
LMArena Text: French14811498Qwen3.8 Max (0902)
LMArena Text: Spanish14651489Qwen3.8 Max (0902)
LMArena Text: Russian14741482Qwen3.8 Max (0902)
LMArena Text: Polish14591471Qwen3.8 Max (0902)
LMArena Text: multi-turn14761489Qwen3.8 Max (0902)
LMArena Text: longer queries14831488Qwen3.8 Max (0902)
LMArena Text: writing and language14611477Qwen3.8 Max (0902)
LMArena Text: entertainment and media14401464Qwen3.8 Max (0902)
LMArena Vision: English12931311Qwen3.8 Max (0902)
LMArena Vision: Chinese13461358Qwen3.8 Max (0902)
LMArena Vision: reading text13031322Qwen3.8 Max (0902)
LMArena Vision: humor12821304Qwen3.8 Max (0902)
LMArena Vision: creative writing13011312Qwen3.8 Max (0902)
LMArena Document1475Not measuredOnly Claude Opus 4.8 measured
Neither model has a result on the other 11 boards here
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
Image generation benchmarks for Claude Opus 4.8 and Qwen3.8 Max (0902)
BenchmarkClaude Opus 4.8Qwen3.8 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

Claude Opus 4.8$0.018Fits 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

Claude Opus 4.8$0.325Fits 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

Claude Opus 4.8$1.25Fits 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 Claude Opus 4.8 and Qwen3.8 Max (0902)
SpecificationAnthropic Claude Opus 4.8Qwen3.8 Max (0902)
MakerAnthropicQwen
WeightsNo public weights listedNo public weights listed
ReleasedMay 27, 2026September 3, 2026
Context window1M1M
Input $/Mtok$5.00$2.00
Output $/Mtok$25.00$6.00
Coding index66.063.5
Independent measurements behind it22
Cost per solved task$2.17$1.32
SourceOpenRouter listingOpenRouter listing

Questions

Is Claude Opus 4.8 better than Qwen3.8 Max (0902) for coding?

Pick Claude Opus 4.8 for coding: it scores 66.0 on the Vibe Coding Index against 63.5 for Qwen3.8 Max (0902). Pick Qwen3.8 Max (0902) when output tokens cost 4.2x less, or when a solved task costs $1.32 against $2.17.

Which is cheaper, Claude Opus 4.8 or Qwen3.8 Max (0902)?

Claude Opus 4.8 costs $5.00 per million input tokens and $25.00 per million output tokens; Qwen3.8 Max (0902) costs $2.00 and $6.00. Per solved SWE-bench Verified task, Claude Opus 4.8 costs $2.17 and Qwen3.8 Max (0902) $1.32.

Which has the bigger context window, Claude Opus 4.8 or Qwen3.8 Max (0902)?

Neither: both take 1M tokens.

How many benchmarks is the Claude Opus 4.8 vs Qwen3.8 Max (0902) comparison based on?

105 benchmarks have a result for both models as of October 21, 2026. Claude Opus 4.8'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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<p style="font:13px/1.4 sans-serif;margin:6px 0 0">Source: <a href="https://llmbenchmark.ai/compare/claude-opus-4-8-vs-qwen3-8-max-0902">LLMBenchmark.ai, Claude Opus 4.8 vs Qwen3.8 Max (0902)</a></p>