LLMBenchmark.ai

Enter opens the highlighted result. Esc closes.

Claude Opus 4.1 vs Qwen3.5-27B

Updated October 21, 2026. 34 benchmarks have a result for both. Coding is ranked on the Vibe Coding Index; every other board is shown as published.

Replace Claude Opus 4.1 Replace Qwen3.5-27B
Claude Opus 4.1Anthropic
Coding
27.2
Overall
22.8
Output $/M
$75.00
29
Qwen3.5-27BQwen
Coding
22.6
Overall
22.9
Output $/M
$2.16
5
vs boards won of 34 shared

Decision reading

Pick Claude Opus 4.1 for coding: it scores 27.2 on the Vibe Coding Index against 22.6 for Qwen3.5-27B.

Pick Qwen3.5-27B when output tokens cost 34.7x less, or when the context window is larger, 262K against 200K tokens.

Model AClaude Opus 4.1Anthropic27.2/1001 independent benchmarkNo cost per solved taskModel BQwen3.5-27BQwen22.6/1001 independent benchmarkNo cost per solved task
Shared results
34
Claude Opus 4.1 only
37
Qwen3.5-27B only
19
Like-for-like categories
6 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 4.1 27.2 from 1 benchmark, Qwen3.5-27B 22.6 from 1 benchmark.
Widest category
Coding, 5.2 points apart on average over 5 shared benchmarks.
Widest single gap
LMArena Text: coding: Claude Opus 4.1 1479 against Qwen3.5-27B 1427, 8.7 points apart on a 0 to 100 scale.
Output price
Claude Opus 4.1 $75.00 against Qwen3.5-27B $2.16 per million output tokens, 34.7x apart.
Context window
Claude Opus 4.1 takes 200K tokens, Qwen3.5-27B 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
CategoryClaude Opus 4.1BarsQwen3.5-27BTies
Coding50
Intelligence01
Reasoning30
Math20
Knowledge22
General172
All shared boards295
CodingLike-for-likeFour of these boards feed the Vibe Coding Index50
Coding benchmarks for Claude Opus 4.1 and Qwen3.5-27B
BenchmarkClaude Opus 4.1Qwen3.5-27BLeader
LMArena WebDev13901358Claude Opus 4.1
LiveCodeBench (Vals AI)66.5%Not measuredOnly Claude Opus 4.1 measured
Terminal-Bench Hard (Artificial Analysis run)Not measured32.6%Only Qwen3.5-27B measured
Terminal-Bench38.0%Not measuredOnly Claude Opus 4.1 measured
WeirdML45.9%39.5%Claude Opus 4.1
Cybench42.0%Not measuredOnly Claude Opus 4.1 measured
ALE-BenchNot measured349.4Only Qwen3.5-27B measured
LMArena Text: coding14791427Claude Opus 4.1
LMArena Text: software and IT14561431Claude Opus 4.1
LMArena WebDev: ReactNot measured1346Only Qwen3.5-27B measured
LMArena WebDev: HTML13991386Claude Opus 4.1
Neither model has a result on the other 27 boards here
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index01
Intelligence benchmarks for Claude Opus 4.1 and Qwen3.5-27B
BenchmarkClaude Opus 4.1Qwen3.5-27BLeader
AA Intelligence Index22.822.9Qwen3.5-27B
Epoch Capabilities Index144.1Not measuredOnly Claude Opus 4.1 measured
Agentic workDirectional onlyPublic boards, shown as published, kept out of the index5 boards, none shared
Agentic work benchmarks for Claude Opus 4.1 and Qwen3.5-27B
BenchmarkClaude Opus 4.1Qwen3.5-27BLeader
τ²-Bench TelecomNot measured93.9%Only Qwen3.5-27B measured
METR time horizons66.8%Not measuredOnly Claude Opus 4.1 measured
GDPval43.6%Not measuredOnly Claude Opus 4.1 measured
DeepResearch Bench48.3%Not measuredOnly Claude Opus 4.1 measured
Vending-Bench 2Not measured$202Only Qwen3.5-27B measured
Neither model has a result on the other 34 boards here
ReasoningLike-for-likePublic boards, shown as published, kept out of the index30
Reasoning benchmarks for Claude Opus 4.1 and Qwen3.5-27B
BenchmarkClaude Opus 4.1Qwen3.5-27BLeader
GPQA Diamond76.3%Not measuredOnly Claude Opus 4.1 measured
MMMU Pro (Vals AI)77.5%Not measuredOnly Claude Opus 4.1 measured
GPQA Diamond (Artificial Analysis run)Not measured85.8%Only Qwen3.5-27B measured
Humanity's Last Exam (Artificial Analysis run)Not measured23.9%Only Qwen3.5-27B measured
GPQA Diamond (Epoch AI run)77.3%Not measuredOnly Claude Opus 4.1 measured
SimpleBench60.0%Not measuredOnly Claude Opus 4.1 measured
Mystery game puzzles21.0%Not measuredOnly Claude Opus 4.1 measured
EBR-bench7.9%Not measuredOnly Claude Opus 4.1 measured
VPCT35.0%Not measuredOnly Claude Opus 4.1 measured
LMArena Text: hard prompts14421415Claude Opus 4.1
LMArena Text: expert14381427Claude Opus 4.1
LMArena Text: hard prompts in English14511429Claude Opus 4.1
LMArena Vision: diagramsNot measured1249Only Qwen3.5-27B measured
LMArena Vision: homeworkNot measured1256Only Qwen3.5-27B measured
Neither model has a result on the other 7 boards here
MathLike-for-likePublic boards, shown as published, kept out of the index20
Math benchmarks for Claude Opus 4.1 and Qwen3.5-27B
BenchmarkClaude Opus 4.1Qwen3.5-27BLeader
AIME78.2%Not measuredOnly Claude Opus 4.1 measured
MATH 500 (Vals AI)95.4%Not measuredOnly Claude Opus 4.1 measured
MGSM (Vals AI)94.4%Not measuredOnly Claude Opus 4.1 measured
OTIS Mock AIME68.9%Not measuredOnly Claude Opus 4.1 measured
FrontierMath, tiers 1 to 312.6%Not measuredOnly Claude Opus 4.1 measured
FrontierMath, tier 42.4%Not measuredOnly Claude Opus 4.1 measured
LMArena Text: math14311429Claude Opus 4.1
LMArena Text: mathematical work14341429Claude Opus 4.1
Neither model has a result on the other 5 boards here
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index22
Knowledge benchmarks for Claude Opus 4.1 and Qwen3.5-27B
BenchmarkClaude Opus 4.1Qwen3.5-27BLeader
MMLU Pro87.9%Not measuredOnly Claude Opus 4.1 measured
LegalBench (Vals AI)83.5%Not measuredOnly Claude Opus 4.1 measured
TaxEval (Vals AI)73.7%Not measuredOnly Claude Opus 4.1 measured
MortgageTax (Vals AI)61.1%Not measuredOnly Claude Opus 4.1 measured
MedQA (Vals AI)93.6%Not measuredOnly Claude Opus 4.1 measured
MedCode (Vals AI)47.2%Not measuredOnly Claude Opus 4.1 measured
LMArena Text: science14221437Qwen3.5-27B
LMArena Text: medicine and healthcare14161425Qwen3.5-27B
LMArena Text: legal and government14211405Claude Opus 4.1
LMArena Text: business and finance14061399Claude Opus 4.1
Neither model has a result on the other 7 boards here
Web designDirectional onlyPublic boards, shown as published, kept out of the index8 boards, none shared
Web design benchmarks for Claude Opus 4.1 and Qwen3.5-27B
BenchmarkClaude Opus 4.1Qwen3.5-27BLeader
Design Arena: websites1177Not measuredOnly Claude Opus 4.1 measured
Design Arena: UI components1164Not measuredOnly Claude Opus 4.1 measured
Design Arena: game dev1172Not measuredOnly Claude Opus 4.1 measured
Design Arena: data viz1166Not measuredOnly Claude Opus 4.1 measured
Design Arena: 3D1153Not measuredOnly Claude Opus 4.1 measured
Design Arena: all code categories1171Not measuredOnly Claude Opus 4.1 measured
Design Arena: SVG1152Not measuredOnly Claude Opus 4.1 measured
Design Arena: ASCII art1167Not measuredOnly Claude Opus 4.1 measured
Neither model has a result on the other 1 board here
GeneralLike-for-likePublic boards, shown as published, kept out of the index172
General benchmarks for Claude Opus 4.1 and Qwen3.5-27B
BenchmarkClaude Opus 4.1Qwen3.5-27BLeader
SAGE (Vals AI)31.4%Not measuredOnly Claude Opus 4.1 measured
MedScribe (Vals AI)73.9%Not measuredOnly Claude Opus 4.1 measured
IFBenchNot measured75.6%Only Qwen3.5-27B measured
Long context reasoning (AA-LCR)Not measured77.7%Only Qwen3.5-27B measured
DTBench80.0%82.4%Qwen3.5-27B
LMCA37.1%34.0%Claude Opus 4.1
Creative writing (Lech Mazur)84.7%Not measuredOnly Claude Opus 4.1 measured
LMArena Text14191409Claude Opus 4.1
LMArena Text: instruction following14351393Claude Opus 4.1
LMArena Text: creative writing14121362Claude Opus 4.1
LMArena VisionNot measured1241Only Qwen3.5-27B measured
LMArena Text: English14331425Claude Opus 4.1
LMArena Text: non-English14051390Claude Opus 4.1
LMArena Text: Chinese14271478Qwen3.5-27B
LMArena Text: German14131392Claude Opus 4.1
LMArena Text: Japanese13771346Claude Opus 4.1
LMArena Text: Korean13811359Claude Opus 4.1
LMArena Text: French14331410Claude Opus 4.1
LMArena Text: Spanish14481407Claude Opus 4.1
LMArena Text: Russian14221390Claude Opus 4.1
LMArena Text: Polish14131375Claude Opus 4.1
LMArena Text: multi-turn14441410Claude Opus 4.1
LMArena Text: longer queries14551413Claude Opus 4.1
LMArena Text: writing and language14181380Claude Opus 4.1
LMArena Text: entertainment and media13981363Claude Opus 4.1
LMArena Vision: EnglishNot measured1246Only Qwen3.5-27B measured
LMArena Vision: ChineseNot measured1301Only Qwen3.5-27B measured
LMArena Vision: reading textNot measured1246Only Qwen3.5-27B measured
LMArena Vision: humorNot measured1227Only Qwen3.5-27B measured
LMArena Vision: captioningNot measured1170Only Qwen3.5-27B measured
LMArena Vision: recognizing thingsNot measured1210Only Qwen3.5-27B measured
LMArena Vision: creative writingNot measured1224Only Qwen3.5-27B measured
Neither model has a result on the other 14 boards here
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
Image generation benchmarks for Claude Opus 4.1 and Qwen3.5-27B
BenchmarkClaude Opus 4.1Qwen3.5-27BLeader
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 4.1$0.052Fits in one request
Qwen3.5-27B$0.0014Fits in one request

Qwen3.5-27B costs less

Repository review

50K input + 3K output tokens

Claude Opus 4.1$0.975Fits in one request
Qwen3.5-27B$0.020Fits in one request

Qwen3.5-27B costs less

Agent loop

200K input + 10K output tokens

Claude Opus 4.1$3.75Exceeds the context window
Qwen3.5-27B$0.076Fits in one request

Qwen3.5-27B 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 4.1 and Qwen3.5-27B
SpecificationAnthropic Claude Opus 4.1Qwen3.5-27B
MakerAnthropicQwen
WeightsNo public weights listedOpen weights
ReleasedAugust 5, 2025February 25, 2026
Context window200K262K
Input $/Mtok$15.00$0.27
Output $/Mtok$75.00$2.16
Coding index27.222.6
Independent measurements behind it11
Cost per solved taskNot computableNot computable
SourceOpenRouter listingOpenRouter listing

Questions

Is Claude Opus 4.1 better than Qwen3.5-27B for coding?

Pick Claude Opus 4.1 for coding: it scores 27.2 on the Vibe Coding Index against 22.6 for Qwen3.5-27B. Pick Qwen3.5-27B when output tokens cost 34.7x less, or when the context window is larger, 262K against 200K tokens.

Which is cheaper, Claude Opus 4.1 or Qwen3.5-27B?

Claude Opus 4.1 costs $15.00 per million input tokens and $75.00 per million output tokens; Qwen3.5-27B costs $0.27 and $2.16. Cost per solved task is known for neither of them.

Which has the bigger context window, Claude Opus 4.1 or Qwen3.5-27B?

Qwen3.5-27B, with 262K tokens against 200K.

How many benchmarks is the Claude Opus 4.1 vs Qwen3.5-27B comparison based on?

34 benchmarks have a result for both models as of October 21, 2026. Claude Opus 4.1's coding index rests on 1 independent benchmark and Qwen3.5-27B's on 1. Where only one model has a result, the page says so instead of naming a winner.

Compare next