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Model comparison

Claude Opus 4.7 vs Qwen3.5-27B

Data verified

Head-to-head evidence from 14 shared benchmark results across 6 categories. Overall scores shown here use the public BenchAlign v5 ranking lane.

71.63/100
Margin
11.0pts
← winning
60.63/100
0 category wins0 category wins

Verified leaderboard positions: Claude Opus 4.7 unranked; Qwen3.5-27B #26

BenchAlign evidence: Claude Opus 4.7 supported; Qwen3.5-27B supported. Intervals and evidence labels describe ranking uncertainty, not a guarantee for a specific workload.

Evidence parity. Claude Opus 4.7 and Qwen3.5-27B share 14 comparable benchmark results. 0 of 8 categories are comparable. 8 results are unique to Claude Opus 4.7; 15 to Qwen3.5-27B.

Updated July 15, 2026
Shared results
14
Claude Opus 4.7 only
8
Qwen3.5-27B only
15
Comparable categories
0 / 8

Benchmark data for Claude Opus 4.7 and Qwen3.5-27B is coming soon on BenchLM.

Confidence note. This is a partial-evidence comparison with 14 shared benchmark results across 6 evidence categories; 0 of 8 categories currently have scoreable aggregates for both models. Treat the verdict as directional until coverage is more balanced.

Why this result

BenchLM has partial data for these models, but not enough overlapping benchmark coverage to produce a fair score-level comparison yet.

Claude Opus 4.7 is priced at $5.00 input / $25.00 output per 1M tokens, versus $0.00 input / $0.00 output per 1M tokens for Qwen3.5-27B. Claude Opus 4.7 has the larger context window at 1M, compared with 262K for Qwen3.5-27B.

Category breakdown

Exact category averages are shown below. Not measured means BenchLM does not have enough sourced public coverage for that model and category.

Category scores and score margins for Claude Opus 4.7 and Qwen3.5-27B
CategoryClaude Opus 4.7ΔQwen3.5-27B
AgenticClaude Opus 4.7Not measuredMarginNo overlapQwen3.5-27B52.0
CodingClaude Opus 4.7Not measuredMarginNo overlapQwen3.5-27B64.9
ReasoningClaude Opus 4.7Not measuredMarginNo overlapQwen3.5-27B60.6
KnowledgeClaude Opus 4.7Not measuredMarginNo overlapQwen3.5-27B82.8
MathClaude Opus 4.738.6MarginNo overlapQwen3.5-27BNot measured
MultilingualClaude Opus 4.7Not measuredMarginNo overlapQwen3.5-27B82.2
Inst. FollowingClaude Opus 4.7Not measuredMarginNo overlapQwen3.5-27B95.0

Operational comparison

Runtime and commercial metrics are compared only when both models have a complete sourced value.

MetricClaude Opus 4.7Qwen3.5-27BComparison
Input / output priceUSD per 1M tokensClaude Opus 4.7$5 input / $25 outputQwen3.5-27B$0 input / $0 outputQwen3.5-27B has the lower combined listed price.
Generation speedtokens per secondClaude Opus 4.7Not availableQwen3.5-27BNot availableA complete speed comparison is not available.
First-answer latencyseconds to first tokenClaude Opus 4.7Not availableQwen3.5-27BNot availableA complete latency comparison is not available.
Context windowmaximum listed tokensClaude Opus 4.71MQwen3.5-27B262KClaude Opus 4.7 lists the larger context window.

Benchmark Deep Dive

Agentic
BenchmarkClaude Opus 4.7Qwen3.5-27BResult
τ²-bench resultsSource 74%93.9%Qwen3.5-27B leads
Gert LabsSource 65.59%39.41%Claude Opus 4.7 leads
ResearchClawBenchSource 20.7%Not comparable
OSWorld 2.0Source 13.9%Not comparable
Terminal-Bench 2.0Source 41.6%Not comparable
BrowseCompSource 61%Not comparable
OSWorld-VerifiedSource 56.2%Not comparable
Coding
BenchmarkClaude Opus 4.7Qwen3.5-27BResult
Vibe Code BenchSource 71.00%Not comparable
React Native EvalsSource 82.8%Not comparable
Terminal-Bench HardSource 54.5%32.6%Claude Opus 4.7 leads
AA-SciCodeSource 50.1%39.5%Claude Opus 4.7 leads
FrontierCodeSource 38.5%Not comparable
SWE-bench VerifiedSource 72.4%Not comparable
SWE-RebenchSource 58.9%Not comparable
Reasoning
BenchmarkClaude Opus 4.7Qwen3.5-27BResult
AA-LCRSource 67.0%67.3%Qwen3.5-27B leads
CritPtSource 5.1%0.9%Claude Opus 4.7 leads
LongBench v2Source 60.6%Not comparable
Knowledge
BenchmarkClaude Opus 4.7Qwen3.5-27BResult
Artificial Analysis Intelligence IndexSource 42.7%33.8%Claude Opus 4.7 leads
AA-GPQA DiamondSource 88.5%85.8%Claude Opus 4.7 leads
AA-HLESource 31.2%22.2%Claude Opus 4.7 leads
AA-Omniscience IndexSource 14.2%-42.0%Claude Opus 4.7 leads
AA-Omniscience AccuracySource 43.5%21.0%Claude Opus 4.7 leads
AA-Omniscience Hallucination RateSource 51.9%79.7%Claude Opus 4.7 leads
MMLU-ProSource 86.1%Not comparable
SuperGPQASource 65.6%Not comparable
GPQASource 85.5%Not comparable
Math
BenchmarkClaude Opus 4.7Qwen3.5-27BResult
FrontierMath v2 (Tiers 1-3)Source 43.793%Not comparable
FrontierMath v2 (Tier 4)Source 22.917%Not comparable
Multilingual
BenchmarkClaude Opus 4.7Qwen3.5-27BResult
MMLU-ProXSource 82.2%Not comparable
Multimodal
BenchmarkClaude Opus 4.7Qwen3.5-27BResult
AA-MMMU-ProSource 76.4%75.0%Claude Opus 4.7 leads
Design Arena WebsiteSource 1328Not comparable
MMMUSource 82.3%Not comparable
MMVUSource 73.3%Not comparable
MathVisionSource 86.0%Not comparable
V*Source 93.7%Not comparable
Inst. Following
BenchmarkClaude Opus 4.7Qwen3.5-27BResult
AA-IFBenchSource 43.6%75.6%Qwen3.5-27B leads
IFEvalSource 95%Not comparable
Frequently Asked Questions (3)

Can I compare Claude Opus 4.7 and Qwen3.5-27B on BenchLM yet?

Not fully yet. BenchLM is tracking both models, but the sourced benchmark breakdown for this comparison is still coming soon.

Why does this comparison show “coming soon”?

BenchLM only shows category winners and benchmark-level calls when we have sourced results that can be compared fairly. For these models, the public benchmark coverage is not complete enough yet.

What data is available for Claude Opus 4.7 and Qwen3.5-27B today?

Claude Opus 4.7: $5.00 input / $25.00 output per 1M tokens Qwen3.5-27B: $0.00 input / $0.00 output per 1M tokens Both model pages still include creator, context window, reasoning mode, and other metadata while benchmark coverage fills in.

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Last updated: July 15, 2026

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