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Claude Opus 4.6 vs Qwen3.8 27B

Qwen3.8 27B leads Claude Opus 4.6 on coding, 74.2 to 57.2 on the Vibe Coding Index, and Qwen3.8 27B costs 9.8x less per output token ($2.55 vs $25.00 per million). Updated October 22, 2026; 63 benchmarks have a result for both.

Replace Claude Opus 4.6 Replace Qwen3.8 27B
Claude Opus 4.6Anthropic
Coding
57.2
Overall
66.0
Output $/M
$25.00
51
Qwen3.8 27BQwen
Coding
74.2
Overall
59.6
Output $/M
$2.55
12
vs boards won of 63 shared

Claude Opus 4.6 or Qwen3.8 27B: which to pick

Pick Qwen3.8 27B for coding: it scores 74.2 on the Vibe Coding Index against 57.2 for Claude Opus 4.6.

Pick Claude Opus 4.6 for work measured by LiveCodeBench (Vals AI) or LMArena Text: coding, where it leads.

Model AClaude Opus 4.6Anthropic57.2/1004 independent benchmarks$1.56 per solved taskModel BQwen3.8 27BQwen74.2/1004 independent benchmarks$1.26 per solved task
Shared results
63
Claude Opus 4.6 only
47
Qwen3.8 27B only
22
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
Claude Opus 4.6 57.2 from 4 benchmarks, Qwen3.8 27B 74.2 from 4 benchmarks.
Widest category
Math, 18.6 points apart on average over 3 shared benchmarks.
Widest single gap
ProofBench: Claude Opus 4.6 50.0% against Qwen3.8 27B 16.0%, 34.0 points apart on a 0 to 100 scale.
Output price
Claude Opus 4.6 $25.00 against Qwen3.8 27B $2.55 per million output tokens, 9.8x 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 4.6BarsQwen3.8 27BTies
Coding36
Intelligence11
Agentic work01
Reasoning92
Math30
Knowledge90
General262
All shared boards5112
CodingLike-for-likeSix of these boards feed the Vibe Coding Index36
Coding benchmarks for Claude Opus 4.6 and Qwen3.8 27B
BenchmarkClaude Opus 4.6Qwen3.8 27BLeader
SWE-bench Verified75.6%Not measuredOnly Claude Opus 4.6 measured
SWE-bench Multilingual72.0%Not measuredOnly Claude Opus 4.6 measured
LiveBench codingNot measured86.8%Only Qwen3.8 27B measured
LMArena WebDev15471593Qwen3.8 27B
AA Coding IndexNot measured68.1Only Qwen3.8 27B measured
LiveCodeBench (Vals AI)84.7%84.0%Claude Opus 4.6
SWE-bench Verified (Vals AI)78.2%86.0%Qwen3.8 27B
Vibe Code Bench (Vals AI)57.6%64.8%Qwen3.8 27B
Code migration (Vals AI)Not measured14.2%Only Qwen3.8 27B measured
ProgramBench (Vals AI)Not measured0.0%Only Qwen3.8 27B measured
IOI (Vals AI)Not measured39.1%Only Qwen3.8 27B measured
Terminal-Bench 2.1 (Vals AI)Not measured58.4%Only Qwen3.8 27B measured
SkillsBench (Vals AI)Not measured38.1%Only Qwen3.8 27B measured
CyberBench (Vals AI)Not measured67.8%Only Qwen3.8 27B measured
SciCodeNot measured46.6%Only Qwen3.8 27B measured
Terminal-Bench Hard (Artificial Analysis run)48.5%Not measuredOnly Claude Opus 4.6 measured
Terminal-Bench79.8%Not measuredOnly Claude Opus 4.6 measured
FrontierCode26.6%Not measuredOnly Claude Opus 4.6 measured
GSO-Bench41.2%Not measuredOnly Claude Opus 4.6 measured
WeirdML78.0%Not measuredOnly Claude Opus 4.6 measured
Cybench93.0%Not measuredOnly Claude Opus 4.6 measured
LMArena Text: coding15341483Claude Opus 4.6
LMArena Text: software and IT15271478Claude Opus 4.6
LMArena WebDev: React15391602Qwen3.8 27B
LMArena WebDev: HTML15591570Qwen3.8 27B
LMArena WebDev: from an image15431577Qwen3.8 27B
Neither model has a result on the other 13 boards here
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index11
Intelligence benchmarks for Claude Opus 4.6 and Qwen3.8 27B
BenchmarkClaude Opus 4.6Qwen3.8 27BLeader
AA Intelligence Index31.933.7Qwen3.8 27B
Epoch Capabilities Index155.7151.7Claude Opus 4.6
Agentic workLike-for-likePublic boards, shown as published, kept out of the index01
Agentic work benchmarks for Claude Opus 4.6 and Qwen3.8 27B
BenchmarkClaude Opus 4.6Qwen3.8 27BLeader
AA Agentic IndexNot measured45.8Only Qwen3.8 27B measured
Design Arena: agents building web apps1206Not measuredOnly Claude Opus 4.6 measured
Design Arena: agents building full-stack apps1220Not measuredOnly Claude Opus 4.6 measured
Design Arena: agents building mobile apps1207Not measuredOnly Claude Opus 4.6 measured
Design Arena: agents building Android apps1197Not measuredOnly Claude Opus 4.6 measured
Design Arena: agents building games1212Not measuredOnly Claude Opus 4.6 measured
LiveBench researchNot measured59.4%Only Qwen3.8 27B measured
LiveBench browserNot measured32.0%Only Qwen3.8 27B measured
LiveBench long agenticNot measured27.9%Only Qwen3.8 27B measured
Finance Agent (Vals AI)Not measured48.5%Only Qwen3.8 27B measured
Tax Agent Bench (Vals AI)Not measured30.9%Only Qwen3.8 27B measured
Legal Research Bench (Vals AI)Not measured36.1%Only Qwen3.8 27B measured
Excel Modeling Benchmark (Vals AI)Not measured59.7%Only Qwen3.8 27B measured
Terminal-Bench-Science (Vals AI)Not measured0.0%Only Qwen3.8 27B measured
τ²-Bench Telecom92.1%Not measuredOnly Claude Opus 4.6 measured
APEX-Agents46.3%47.5%Qwen3.8 27B
METR time horizons78.9%Not measuredOnly Claude Opus 4.6 measured
Remote Labor Index4.2%Not measuredOnly Claude Opus 4.6 measured
DeepResearch Bench55.3%Not measuredOnly Claude Opus 4.6 measured
Vending-Bench 2$8,018Not measuredOnly Claude Opus 4.6 measured
Neither model has a result on the other 21 boards here
ReasoningLike-for-likePublic boards, shown as published, kept out of the index92
Reasoning benchmarks for Claude Opus 4.6 and Qwen3.8 27B
BenchmarkClaude Opus 4.6Qwen3.8 27BLeader
GPQA Diamond89.7%88.9%Claude Opus 4.6
LiveBench reasoningNot measured80.0%Only Qwen3.8 27B measured
MMMU Pro (Vals AI)83.9%83.9%Qwen3.8 27B
GPQA Diamond (Artificial Analysis run)89.6%90.5%Qwen3.8 27B
Humanity's Last Exam (Artificial Analysis run)39.9%33.9%Claude Opus 4.6
GPQA Diamond (Epoch AI run)90.5%Not measuredOnly Claude Opus 4.6 measured
ARC-AGI94.0%87.5%Claude Opus 4.6
ARC-AGI-269.2%42.4%Claude Opus 4.6
SimpleBench67.6%Not measuredOnly Claude Opus 4.6 measured
Chess puzzles21.0%Not measuredOnly Claude Opus 4.6 measured
Mystery game puzzles25.0%Not measuredOnly Claude Opus 4.6 measured
EBR-bench12.7%Not measuredOnly Claude Opus 4.6 measured
LMArena Text: hard prompts15251459Claude Opus 4.6
LMArena Text: expert15441479Claude Opus 4.6
LMArena Text: hard prompts in English15301461Claude Opus 4.6
LMArena Vision: diagrams13401285Claude Opus 4.6
LMArena Vision: homework13371295Claude Opus 4.6
Kagi LLM Benchmark83.6%Not measuredOnly Claude Opus 4.6 measured
Neither model has a result on the other 4 boards here
MathLike-for-likePublic boards, shown as published, kept out of the index30
Math benchmarks for Claude Opus 4.6 and Qwen3.8 27B
BenchmarkClaude Opus 4.6Qwen3.8 27BLeader
AIME95.6%Not measuredOnly Claude Opus 4.6 measured
OTIS Mock AIME94.4%Not measuredOnly Claude Opus 4.6 measured
FrontierMath, tiers 1 to 366.0%Not measuredOnly Claude Opus 4.6 measured
FrontierMath, tier 426.8%Not measuredOnly Claude Opus 4.6 measured
ProofBench50.0%16.0%Claude Opus 4.6
LMArena Text: math15181455Claude Opus 4.6
LMArena Text: mathematical work15251458Claude Opus 4.6
Neither model has a result on the other 6 boards here
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index90
Knowledge benchmarks for Claude Opus 4.6 and Qwen3.8 27B
BenchmarkClaude Opus 4.6Qwen3.8 27BLeader
MMLU Pro89.1%84.3%Claude Opus 4.6
LegalBench (Vals AI)85.3%82.4%Claude Opus 4.6
CaseLaw (Vals AI)62.1%Not measuredOnly Claude Opus 4.6 measured
CorpFin (Vals AI)67.0%Not measuredOnly Claude Opus 4.6 measured
TaxEval (Vals AI)76.0%70.8%Claude Opus 4.6
MortgageTax (Vals AI)68.5%64.9%Claude Opus 4.6
MedQA (Vals AI)95.4%Not measuredOnly Claude Opus 4.6 measured
MedCode (Vals AI)49.1%28.7%Claude Opus 4.6
SimpleQA Verified47.0%Not measuredOnly Claude Opus 4.6 measured
LMArena Text: science15191467Claude Opus 4.6
LMArena Text: medicine and healthcare15041437Claude Opus 4.6
LMArena Text: legal and government15121447Claude Opus 4.6
LMArena Text: business and finance14971438Claude Opus 4.6
FACTS Benchmark Suite41.5%Not measuredOnly Claude Opus 4.6 measured
Neither model has a result on the other 4 boards here
Web designDirectional onlyPublic boards, shown as published, kept out of the index9 boards, none shared
Web design benchmarks for Claude Opus 4.6 and Qwen3.8 27B
BenchmarkClaude Opus 4.6Qwen3.8 27BLeader
Design Arena: websites1291Not measuredOnly Claude Opus 4.6 measured
Design Arena: UI components1281Not measuredOnly Claude Opus 4.6 measured
Design Arena: game dev1277Not measuredOnly Claude Opus 4.6 measured
Design Arena: data viz1279Not measuredOnly Claude Opus 4.6 measured
Design Arena: 3D1273Not measuredOnly Claude Opus 4.6 measured
Design Arena: all code categories1288Not measuredOnly Claude Opus 4.6 measured
Design Arena: SVG1227Not measuredOnly Claude Opus 4.6 measured
Design Arena: ASCII art1255Not measuredOnly Claude Opus 4.6 measured
LiveBench designNot measured75.9%Only Qwen3.8 27B measured
GeneralLike-for-likePublic boards, shown as published, kept out of the index262
General benchmarks for Claude Opus 4.6 and Qwen3.8 27B
BenchmarkClaude Opus 4.6Qwen3.8 27BLeader
LiveBench data analysisNot measured76.6%Only Qwen3.8 27B measured
SAGE (Vals AI)51.6%52.4%Qwen3.8 27B
MedScribe (Vals AI)86.7%83.8%Claude Opus 4.6
IFBench53.1%Not measuredOnly Claude Opus 4.6 measured
Long context reasoning (AA-LCR)78.0%82.0%Qwen3.8 27B
DTBench91.2%88.0%Claude Opus 4.6
LMCA55.8%41.4%Claude Opus 4.6
CL-bench20.7%Not measuredOnly Claude Opus 4.6 measured
Surface Evolver BenchNot measured45.0%Only Qwen3.8 27B measured
Furniture assembly28.3%Not measuredOnly Claude Opus 4.6 measured
CL-bench Life17.0%Not measuredOnly Claude Opus 4.6 measured
LMArena Text15011440Claude Opus 4.6
LMArena Text: instruction following15211436Claude Opus 4.6
LMArena Text: creative writing15051383Claude Opus 4.6
LMArena Vision13161269Claude Opus 4.6
LMArena Text: English15111448Claude Opus 4.6
LMArena Text: non-English14881428Claude Opus 4.6
LMArena Text: Chinese15511501Claude Opus 4.6
LMArena Text: German15001443Claude Opus 4.6
LMArena Text: Japanese14881387Claude Opus 4.6
LMArena Text: Korean14641384Claude Opus 4.6
LMArena Text: French15121465Claude Opus 4.6
LMArena Text: Spanish15101449Claude Opus 4.6
LMArena Text: Russian14971415Claude Opus 4.6
LMArena Text: Polish14991439Claude Opus 4.6
LMArena Text: multi-turn15111440Claude Opus 4.6
LMArena Text: longer queries15181448Claude Opus 4.6
LMArena Text: writing and language15021405Claude Opus 4.6
LMArena Text: entertainment and media14921393Claude Opus 4.6
LMArena Vision: English13241267Claude Opus 4.6
LMArena Vision: Chinese13701326Claude Opus 4.6
LMArena Vision: reading text13261281Claude Opus 4.6
LMArena Vision: humor13141235Claude Opus 4.6
LMArena Vision: recognizing things1274Not measuredOnly Claude Opus 4.6 measured
LMArena Vision: creative writing13311237Claude Opus 4.6
LMArena Document1507Not measuredOnly Claude Opus 4.6 measured
Neither model has a result on the other 10 boards here
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
Image generation benchmarks for Claude Opus 4.6 and Qwen3.8 27B
BenchmarkClaude Opus 4.6Qwen3.8 27BLeader
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 4.6$0.018Fits in one request
Qwen3.8 27B$0.0017Fits in one request

Qwen3.8 27B costs less

Repository review

50K input + 3K output tokens

Claude Opus 4.6$0.325Fits in one request
Qwen3.8 27B$0.029Fits in one request

Qwen3.8 27B costs less

Agent loop

200K input + 10K output tokens

Claude Opus 4.6$1.25Fits in one request
Qwen3.8 27B$0.111Fits in one request

Qwen3.8 27B 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 4.6 and Qwen3.8 27B
SpecificationAnthropic Claude Opus 4.6Qwen3.8 27B
MakerAnthropicQwen
WeightsNo public weights listedOpen weights
ReleasedFebruary 4, 2026August 14, 2026
Context window1M1M
Input $/Mtok$5.00$0.425
Output $/Mtok$25.00$2.55
Coding index57.274.2
Independent measurements behind it44
Cost per solved task$1.56$1.26
SourceOpenRouter listingOpenRouter listing

Questions

Is Claude Opus 4.6 better than Qwen3.8 27B for coding?

Pick Qwen3.8 27B for coding: it scores 74.2 on the Vibe Coding Index against 57.2 for Claude Opus 4.6. Pick Claude Opus 4.6 for work measured by LiveCodeBench (Vals AI) or LMArena Text: coding, where it leads.

Which is cheaper, Claude Opus 4.6 or Qwen3.8 27B?

Claude Opus 4.6 costs $5.00 per million input tokens and $25.00 per million output tokens; Qwen3.8 27B costs $0.425 and $2.55. Per solved SWE-bench Verified task, Claude Opus 4.6 costs $1.56 and Qwen3.8 27B $1.26.

Which has the bigger context window, Claude Opus 4.6 or Qwen3.8 27B?

Neither: both take 1M tokens.

How many benchmarks is the Claude Opus 4.6 vs Qwen3.8 27B comparison based on?

63 benchmarks have a result for both models as of October 22, 2026. Claude Opus 4.6's coding index rests on 4 independent benchmarks and Qwen3.8 27B's on 4. Where only one model has a result, the page says so instead of naming a winner.

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