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Claude Opus 4.7 vs Qwen3.5-27B

Claude Opus 4.7 leads Qwen3.5-27B on the Artificial Analysis Intelligence Index, 40.7 to 22.9, and Qwen3.5-27B costs 16.0x less per output token ($1.56 vs $25.00 per million). Updated October 22, 2026; 51 benchmarks have a result for both.

Replace Claude Opus 4.7 Replace Qwen3.5-27B
Claude Opus 4.7Anthropic
Coding
67.5
Overall
71.6
Output $/M
$25.00
49
Qwen3.5-27BQwen
Coding
No data
Overall
No data
Output $/M
$1.56
2
vs boards won of 51 shared

Claude Opus 4.7 or Qwen3.5-27B: which to pick

Only Claude Opus 4.7 has a coding score, 67.5 on the Vibe Coding Index; Qwen3.5-27B has none, so the two cannot be ranked on coding.

Pick Qwen3.5-27B for output tokens 16.0x cheaper ($1.56 vs $25.00 per million) and work measured by τ²-Bench Telecom or IFBench, where it leads.

Model AClaude Opus 4.7Anthropic67.5/1004 independent benchmarks$2.95 per solved taskModel BQwen3.5-27BQwenNot benchmarked1 independent benchmarkNo cost per solved task
Shared results
51
Claude Opus 4.7 only
52
Qwen3.5-27B only
2
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 4.7 67.5 from 4 benchmarks, Qwen3.5-27B not benchmarked.
Widest category
Agentic work, 36.2 points apart on average over 2 shared benchmarks.
Widest single gap
Vending-Bench 2: Claude Opus 4.7 $10,937 against Qwen3.5-27B $202, 67.1 points apart on a 0 to 100 scale.
Output price
Claude Opus 4.7 $25.00 against Qwen3.5-27B $1.56 per million output tokens, 16.0x apart.
Context window
Claude Opus 4.7 takes 1M 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 4.7BarsQwen3.5-27BTies
Coding70
Intelligence10
Agentic work11
Reasoning70
Math20
Knowledge40
General271
All shared boards492
CodingLike-for-likeSix of these boards feed the Vibe Coding Index70
Coding benchmarks for Claude Opus 4.7 and Qwen3.5-27B
BenchmarkClaude Opus 4.7Qwen3.5-27BLeader
LMArena WebDev15581358Claude Opus 4.7
AA Coding Index73.6Not measuredOnly Claude Opus 4.7 measured
LiveCodeBench (Vals AI)85.1%Not measuredOnly Claude Opus 4.7 measured
SWE-bench Verified (Vals AI)82.0%Not measuredOnly Claude Opus 4.7 measured
Vibe Code Bench (Vals AI)71.0%Not measuredOnly Claude Opus 4.7 measured
Code migration (Vals AI)43.9%Not measuredOnly Claude Opus 4.7 measured
ProgramBench (Vals AI)0.0%Not measuredOnly Claude Opus 4.7 measured
Terminal-Bench 2.1 (Vals AI)68.5%Not measuredOnly Claude Opus 4.7 measured
Terminal-Bench Hard (Artificial Analysis run)54.5%32.6%Claude Opus 4.7
Terminal-Bench80.2%Not measuredOnly Claude Opus 4.7 measured
FrontierCode38.5%Not measuredOnly Claude Opus 4.7 measured
GSO-Bench44.1%Not measuredOnly Claude Opus 4.7 measured
WeirdML76.4%39.5%Claude Opus 4.7
MirrorCode31.1%Not measuredOnly Claude Opus 4.7 measured
ALE-BenchNot measured349.4Only Qwen3.5-27B measured
LMArena Text: coding15191427Claude Opus 4.7
LMArena Text: software and IT15161431Claude Opus 4.7
LMArena WebDev: React15601346Claude Opus 4.7
LMArena WebDev: HTML15541386Claude Opus 4.7
LMArena WebDev: from an image1577Not measuredOnly Claude Opus 4.7 measured
Neither model has a result on the other 19 boards here
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index10
Intelligence benchmarks for Claude Opus 4.7 and Qwen3.5-27B
BenchmarkClaude Opus 4.7Qwen3.5-27BLeader
AA Intelligence Index40.722.9Claude Opus 4.7
Epoch Capabilities Index156.8Not measuredOnly Claude Opus 4.7 measured
Agentic workLike-for-likePublic boards, shown as published, kept out of the index11
Agentic work benchmarks for Claude Opus 4.7 and Qwen3.5-27B
BenchmarkClaude Opus 4.7Qwen3.5-27BLeader
AA Agentic Index38.6Not measuredOnly Claude Opus 4.7 measured
Finance Agent (Vals AI)51.5%Not measuredOnly Claude Opus 4.7 measured
Tax Agent Bench (Vals AI)23.7%Not measuredOnly Claude Opus 4.7 measured
Legal Research Bench (Vals AI)38.5%Not measuredOnly Claude Opus 4.7 measured
Excel Modeling Benchmark (Vals AI)63.7%Not measuredOnly Claude Opus 4.7 measured
τ²-Bench Telecom88.6%93.9%Qwen3.5-27B
APEX-Agents49.2%Not measuredOnly Claude Opus 4.7 measured
OSWorld 2.018.2%Not measuredOnly Claude Opus 4.7 measured
PostTrainBench28.6%Not measuredOnly Claude Opus 4.7 measured
Vending-Bench 2$10,937$202Claude Opus 4.7
LMArena Search1230Not measuredOnly Claude Opus 4.7 measured
Neither model has a result on the other 30 boards here
ReasoningLike-for-likePublic boards, shown as published, kept out of the index70
Reasoning benchmarks for Claude Opus 4.7 and Qwen3.5-27B
BenchmarkClaude Opus 4.7Qwen3.5-27BLeader
GPQA Diamond90.2%Not measuredOnly Claude Opus 4.7 measured
MMMU Pro (Vals AI)85.5%Not measuredOnly Claude Opus 4.7 measured
GPQA Diamond (Artificial Analysis run)91.4%85.8%Claude Opus 4.7
Humanity's Last Exam (Artificial Analysis run)42.3%23.9%Claude Opus 4.7
GPQA Diamond (Epoch AI run)90.2%Not measuredOnly Claude Opus 4.7 measured
ARC-AGI93.5%Not measuredOnly Claude Opus 4.7 measured
ARC-AGI-275.8%Not measuredOnly Claude Opus 4.7 measured
SimpleBench61.7%Not measuredOnly Claude Opus 4.7 measured
Chess puzzles41.0%Not measuredOnly Claude Opus 4.7 measured
Mystery game puzzles28.0%Not measuredOnly Claude Opus 4.7 measured
EBR-bench19.0%Not measuredOnly Claude Opus 4.7 measured
LMArena Text: hard prompts15061415Claude Opus 4.7
LMArena Text: expert15211427Claude Opus 4.7
LMArena Text: hard prompts in English15081429Claude Opus 4.7
LMArena Vision: diagrams13361249Claude Opus 4.7
LMArena Vision: homework13371256Claude Opus 4.7
Kagi LLM Benchmark80.7%Not measuredOnly Claude Opus 4.7 measured
Neither model has a result on the other 5 boards here
MathLike-for-likePublic boards, shown as published, kept out of the index20
Math benchmarks for Claude Opus 4.7 and Qwen3.5-27B
BenchmarkClaude Opus 4.7Qwen3.5-27BLeader
AIME96.3%Not measuredOnly Claude Opus 4.7 measured
OTIS Mock AIME97.8%Not measuredOnly Claude Opus 4.7 measured
FrontierMath, tiers 1 to 370.2%Not measuredOnly Claude Opus 4.7 measured
FrontierMath, tier 431.7%Not measuredOnly Claude Opus 4.7 measured
ProofBench54.0%Not measuredOnly Claude Opus 4.7 measured
LMArena Text: math14981429Claude Opus 4.7
LMArena Text: mathematical work15091429Claude Opus 4.7
Neither model has a result on the other 6 boards here
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index40
Knowledge benchmarks for Claude Opus 4.7 and Qwen3.5-27B
BenchmarkClaude Opus 4.7Qwen3.5-27BLeader
MMLU Pro89.9%Not measuredOnly Claude Opus 4.7 measured
LegalBench (Vals AI)85.3%Not measuredOnly Claude Opus 4.7 measured
CaseLaw (Vals AI)68.4%Not measuredOnly Claude Opus 4.7 measured
CorpFin (Vals AI)66.1%Not measuredOnly Claude Opus 4.7 measured
TaxEval (Vals AI)75.3%Not measuredOnly Claude Opus 4.7 measured
MortgageTax (Vals AI)70.3%Not measuredOnly Claude Opus 4.7 measured
MedCode (Vals AI)54.9%Not measuredOnly Claude Opus 4.7 measured
SimpleQA Verified51.7%Not measuredOnly Claude Opus 4.7 measured
LMArena Text: science15081437Claude Opus 4.7
LMArena Text: medicine and healthcare14951425Claude Opus 4.7
LMArena Text: legal and government15041405Claude Opus 4.7
LMArena Text: business and finance14901399Claude Opus 4.7
FACTS Benchmark Suite45.5%Not measuredOnly Claude Opus 4.7 measured
Neither model has a result on the other 5 boards here
Web designNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
Web design benchmarks for Claude Opus 4.7 and Qwen3.5-27B
BenchmarkClaude Opus 4.7Qwen3.5-27BLeader
Neither model has a result on 9 boards here
GeneralLike-for-likePublic boards, shown as published, kept out of the index271
General benchmarks for Claude Opus 4.7 and Qwen3.5-27B
BenchmarkClaude Opus 4.7Qwen3.5-27BLeader
SAGE (Vals AI)56.1%Not measuredOnly Claude Opus 4.7 measured
MedScribe (Vals AI)83.0%Not measuredOnly Claude Opus 4.7 measured
Vals Multimodal Index67.4%Not measuredOnly Claude Opus 4.7 measured
IFBench58.6%75.6%Qwen3.5-27B
Long context reasoning (AA-LCR)78.7%77.7%Claude Opus 4.7
DTBench94.7%82.4%Claude Opus 4.7
LMCA52.2%34.0%Claude Opus 4.7
Furniture assembly33.3%Not measuredOnly Claude Opus 4.7 measured
ExploitBench26.5%Not measuredOnly Claude Opus 4.7 measured
LMArena Text14901409Claude Opus 4.7
LMArena Text: instruction following14981393Claude Opus 4.7
LMArena Text: creative writing14861362Claude Opus 4.7
LMArena Vision13171241Claude Opus 4.7
LMArena Text: English14961425Claude Opus 4.7
LMArena Text: non-English14801390Claude Opus 4.7
LMArena Text: Chinese15311478Claude Opus 4.7
LMArena Text: German14951392Claude Opus 4.7
LMArena Text: Japanese14741346Claude Opus 4.7
LMArena Text: Korean14641359Claude Opus 4.7
LMArena Text: French15031410Claude Opus 4.7
LMArena Text: Spanish14941407Claude Opus 4.7
LMArena Text: Russian14941390Claude Opus 4.7
LMArena Text: Polish14891375Claude Opus 4.7
LMArena Text: multi-turn15051410Claude Opus 4.7
LMArena Text: longer queries15051413Claude Opus 4.7
LMArena Text: writing and language14921380Claude Opus 4.7
LMArena Text: entertainment and media14741363Claude Opus 4.7
LMArena Vision: English13221246Claude Opus 4.7
LMArena Vision: Chinese13711301Claude Opus 4.7
LMArena Vision: reading text13271246Claude Opus 4.7
LMArena Vision: humor13091227Claude Opus 4.7
LMArena Vision: captioningNot measured1170Only Qwen3.5-27B measured
LMArena Vision: recognizing things12781210Claude Opus 4.7
LMArena Vision: creative writing13261224Claude Opus 4.7
LMArena Document1495Not measuredOnly Claude Opus 4.7 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 4.7 and Qwen3.5-27B
BenchmarkClaude Opus 4.7Qwen3.5-27BLeader
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 4.7$0.018Fits in one request
Qwen3.5-27B$0.0010Fits in one request

Qwen3.5-27B costs less

Repository review

50K input + 3K output tokens

Claude Opus 4.7$0.325Fits in one request
Qwen3.5-27B$0.014Fits in one request

Qwen3.5-27B costs less

Agent loop

200K input + 10K output tokens

Claude Opus 4.7$1.25Fits in one request
Qwen3.5-27B$0.055Fits 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 4.7 and Qwen3.5-27B
SpecificationAnthropic Claude Opus 4.7Qwen3.5-27B
MakerAnthropicQwen
WeightsNo public weights listedOpen weights
ReleasedApril 16, 2026February 25, 2026
Context window1M262K
Input $/Mtok$5.00$0.195
Output $/Mtok$25.00$1.56
Coding index67.5Not benchmarked
Independent measurements behind it41
Cost per solved task$2.95Not computable
SourceOpenRouter listingOpenRouter listing

Questions

Is Claude Opus 4.7 better than Qwen3.5-27B for coding?

Only Claude Opus 4.7 has a coding score, 67.5 on the Vibe Coding Index; Qwen3.5-27B has none, so the two cannot be ranked on coding. Pick Qwen3.5-27B for output tokens 16.0x cheaper ($1.56 vs $25.00 per million) and work measured by τ²-Bench Telecom or IFBench, where it leads.

Which is cheaper, Claude Opus 4.7 or Qwen3.5-27B?

Claude Opus 4.7 costs $5.00 per million input tokens and $25.00 per million output tokens; Qwen3.5-27B costs $0.195 and $1.56. Cost per solved task is known for Claude Opus 4.7 only.

Which has the bigger context window, Claude Opus 4.7 or Qwen3.5-27B?

Claude Opus 4.7, with 1M tokens against 262K.

How many benchmarks is the Claude Opus 4.7 vs Qwen3.5-27B comparison based on?

51 benchmarks have a result for both models as of October 22, 2026. Claude Opus 4.7's coding index rests on 4 independent benchmarks and Qwen3.5-27B's on 1. Where only one model has a result, the page says so instead of naming a winner.

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