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Model comparison

Claude Opus 4.7 (Adaptive) vs Qwen3.7 Max

Data verified

Head-to-head evidence from 25 shared benchmark results across 6 categories. Overall scores shown here use the public BenchAlign v5 ranking lane.

66.27/100
Margin
6.6pts
winning →
72.84/100
2 category wins2 category wins

Public leaderboard positions: Claude Opus 4.7 (Adaptive) #27 (Estimated); Qwen3.7 Max #10 (Supported). Intervals and evidence labels describe ranking uncertainty, not a guarantee for a specific workload.

Evidence parity. Claude Opus 4.7 (Adaptive) and Qwen3.7 Max share 25 comparable benchmark results. 4 of 8 categories are comparable. 13 results are unique to Claude Opus 4.7 (Adaptive); 33 to Qwen3.7 Max.

Updated July 23, 2026
Shared results
25
Claude Opus 4.7 (Adaptive) only
13
Qwen3.7 Max only
33
Comparable categories
4 / 8

Pick Qwen3.7 Max if you want the stronger benchmark profile. Claude Opus 4.7 (Adaptive) only becomes the better choice if agentic is the priority.

Confidence note. This is a partial-evidence comparison with 25 shared benchmark results across 6 evidence categories; 4 of 8 categories currently have scoreable aggregates for both models. Treat the verdict as directional until coverage is more balanced.

Why this result

Qwen3.7 Max is clearly ahead on the BenchAlign aggregate, 72.84 to 66.27. The gap is large enough that you do not need to squint at the spreadsheet to see the difference.

Qwen3.7 Max's sharpest advantage is in reasoning, where it averages 90.4 against 75.8. The single biggest benchmark swing on the page is HLE, 54.7% to 41.4%. Claude Opus 4.7 (Adaptive) does hit back in agentic, so the answer changes if that is the part of the workload you care about most.

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 (Adaptive) and Qwen3.7 Max
CategoryClaude Opus 4.7 (Adaptive)ΔQwen3.7 Max
ReasoningClaude Opus 4.7 (Adaptive)75.8Margin→ 14.6Qwen3.7 Max90.4
AgenticClaude Opus 4.7 (Adaptive)75.1Margin← 5.4Qwen3.7 Max69.7
KnowledgeClaude Opus 4.7 (Adaptive)60.0Margin→ 4.2Qwen3.7 Max64.2
CodingClaude Opus 4.7 (Adaptive)78.6Margin← 0.7Qwen3.7 Max77.9
MathClaude Opus 4.7 (Adaptive)Not measuredMarginNo overlapQwen3.7 Max97.1
MultilingualClaude Opus 4.7 (Adaptive)Not measuredMarginNo overlapQwen3.7 Max87.0
MultimodalClaude Opus 4.7 (Adaptive)65.1MarginNo overlapQwen3.7 MaxNot measured
Inst. FollowingClaude Opus 4.7 (Adaptive)Not measuredMarginNo overlapQwen3.7 Max84.4

Decisive benchmark drivers

The largest measured benchmark gaps in this matchup, with exact reported values.

More
A · Claude Opus 4.7 (Adaptive)B · Qwen3.7 Max

  1. HLE

    Knowledge
    Source ↗
    A 54.7%B 41.4%
    Winner: Claude Opus 4.7 (Adaptive)Δ 13.3
    HLE: Claude Opus 4.7 (Adaptive) scored 54.7%; Qwen3.7 Max scored 41.4%. Claude Opus 4.7 (Adaptive) wins this benchmark.

  2. SWE-bench Verified

    Coding
    Source ↗
    A 87.6%B 80.4%
    Winner: Claude Opus 4.7 (Adaptive)Δ 7.2
    SWE-bench Verified: Claude Opus 4.7 (Adaptive) scored 87.6%; Qwen3.7 Max scored 80.4%. Claude Opus 4.7 (Adaptive) wins this benchmark.

  3. SWE-bench Pro

    Coding
    Source ↗
    A 64.3%B 60.6%
    Winner: Claude Opus 4.7 (Adaptive)Δ 3.7
    SWE-bench Pro: Claude Opus 4.7 (Adaptive) scored 64.3%; Qwen3.7 Max scored 60.6%. Claude Opus 4.7 (Adaptive) wins this benchmark.

  4. GPQA

    Knowledge
    Source ↗
    A 94.2%B 92.4%
    Winner: Claude Opus 4.7 (Adaptive)Δ 1.8
    GPQA: Claude Opus 4.7 (Adaptive) scored 94.2%; Qwen3.7 Max scored 92.4%. Claude Opus 4.7 (Adaptive) wins this benchmark.

  5. Terminal-Bench 2.0

    Agentic
    Source ↗
    A 69.4%B 69.7%
    Winner: Qwen3.7 MaxΔ 0.3
    Terminal-Bench 2.0: Claude Opus 4.7 (Adaptive) scored 69.4%; Qwen3.7 Max scored 69.7%. Qwen3.7 Max wins this benchmark.

Operational comparison

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

MetricClaude Opus 4.7 (Adaptive)Qwen3.7 MaxComparison
Input / output priceUSD per 1M tokensClaude Opus 4.7 (Adaptive)$5 input / $25 outputQwen3.7 MaxNot availableA complete price comparison is not available.
Generation speedtokens per secondClaude Opus 4.7 (Adaptive)Not availableQwen3.7 MaxNot availableA complete speed comparison is not available.
First-answer latencyseconds to first tokenClaude Opus 4.7 (Adaptive)Not availableQwen3.7 MaxNot availableA complete latency comparison is not available.
Context windowmaximum listed tokensClaude Opus 4.7 (Adaptive)1MQwen3.7 Max1MListed context windows are equal.

Benchmark Deep Dive

AgenticClaude Opus 4.7 (Adaptive) wins
BenchmarkClaude Opus 4.7 (Adaptive)Qwen3.7 MaxResult
Terminal-Bench 2.0Source 69.4%69.7%Qwen3.7 Max leads
BrowseCompSource 79.3%—Not comparable
MCP AtlasSource 77.3%76.4%Claude Opus 4.7 (Adaptive) leads
OSWorld-VerifiedSource 78%—Not comparable
CyberGymSource 73.1%—Not comparable
AA Agentic IndexSource 44.4%30.6%Claude Opus 4.7 (Adaptive) leads
τ²-bench resultsSource 88.6%94.7%Qwen3.7 Max leads
GDPval-AASource 49.8%38.7%Claude Opus 4.7 (Adaptive) leads
GDPval-AASource 14951273Claude Opus 4.7 (Adaptive) leads
OSWorld 2.0Source 18.2%—Not comparable
JobBenchSource 45.9%—Not comparable
AA ITBenchSource 46.7%42.5%Claude Opus 4.7 (Adaptive) leads
QwenClawBenchSource —64.3%Not comparable
QwenWebBenchSource —1568Not comparable
Claw-EvalSource —65.2%Not comparable
BFCL v4Source —75.0%Not comparable
VITA-BenchSource —47.9%Not comparable
HLE w/ toolsSource —53.5%Not comparable
Gert LabsSource —64.27%Not comparable
ResearchClawBenchSource —18.7%Not comparable
AA BriefcaseSource —908Not comparable
AA AutomationBenchSource —25.6%Not comparable
AA EnterpriseOps-GymSource —45.0%Not comparable
terminalBenchHardSource —50.8%Not comparable
aaTerminalBench21Source —74.5%Not comparable
AA Harvey LABSource —83.4%Not comparable
CodingClaude Opus 4.7 (Adaptive) wins
BenchmarkClaude Opus 4.7 (Adaptive)Qwen3.7 MaxResult
SWE-bench VerifiedSource 87.6%80.4%Claude Opus 4.7 (Adaptive) leads
SWE-bench ProSource 64.3%60.6%Claude Opus 4.7 (Adaptive) leads
Terminal-Bench 2.0Source 69.4%69.7%Qwen3.7 Max leads
AA Coding IndexSource 73.6%66.0%Claude Opus 4.7 (Adaptive) leads
AA-SciCodeSource 54.5%48.8%Claude Opus 4.7 (Adaptive) leads
SWE MultilingualSource —78.3%Not comparable
NL2RepoSource —47.2%Not comparable
SciCodeSource —53.5%Not comparable
LiveCodeBenchSource —91.6%Not comparable
ReasoningQwen3.7 Max wins
BenchmarkClaude Opus 4.7 (Adaptive)Qwen3.7 MaxResult
MRCR v2 128K-256KSource 59.2%—Not comparable
ARC-AGI-2Source 75.8%—Not comparable
AA-LCRSource 70.3%69.0%Claude Opus 4.7 (Adaptive) leads
CritPtSource 12.0%13.4%Qwen3.7 Max leads
MRCRv2Source —90.4%Not comparable
KnowledgeQwen3.7 Max wins
BenchmarkClaude Opus 4.7 (Adaptive)Qwen3.7 MaxResult
GPQASource 94.2%92.4%Claude Opus 4.7 (Adaptive) leads
GPQA-DSource 94.2%92.4%Claude Opus 4.7 (Adaptive) leads
HLESource 54.7%41.4%Claude Opus 4.7 (Adaptive) leads
HLE w/o toolsSource 46.9%—Not comparable
Artificial Analysis Intelligence IndexSource 53.5%46.0%Claude Opus 4.7 (Adaptive) leads
AA-GPQA DiamondSource 91.4%92.3%Qwen3.7 Max leads
AA-HLESource 39.6%38.1%Claude Opus 4.7 (Adaptive) leads
AA-Omniscience IndexSource 26.2%14.1%Claude Opus 4.7 (Adaptive) leads
AA-Omniscience AccuracySource 45.8%30.1%Claude Opus 4.7 (Adaptive) leads
AA-Omniscience Hallucination RateSource 36.2%22.9%Qwen3.7 Max leads
MMLU-ProSource —89.6%Not comparable
MMLU-ReduxSource —95%Not comparable
SuperGPQASource —73.6%Not comparable
MMMLUSource —90.3%Not comparable
Math
BenchmarkClaude Opus 4.7 (Adaptive)Qwen3.7 MaxResult
FrontierMath (legacy)Source 43.8%—Not comparable
HMMT Feb 2026Source —97.1%Not comparable
IMOAnswerBenchSource —90.0%Not comparable
ApexSource —44.5%Not comparable
Multilingual
BenchmarkClaude Opus 4.7 (Adaptive)Qwen3.7 MaxResult
MMLU-ProXSource —87%Not comparable
NOVA-63Source —59.0%Not comparable
INCLUDESource —86.2%Not comparable
MAXIFESource —89.2%Not comparable
PolyMathSource —86.5%Not comparable
Multimodal
BenchmarkClaude Opus 4.7 (Adaptive)Qwen3.7 MaxResult
OfficeQA ProSource 43.6%—Not comparable
CharXivSource 91%—Not comparable
CharXiv w/o toolsSource 82.1%—Not comparable
AA-MMMU-ProSource 78.8%—Not comparable
Design Arena WebsiteSource 13251293Claude Opus 4.7 (Adaptive) leads
Inst. Following
BenchmarkClaude Opus 4.7 (Adaptive)Qwen3.7 MaxResult
AA-IFBenchSource 58.6%80.5%Qwen3.7 Max leads
IFEvalSource —94.3%Not comparable
IFBenchSource —79.1%Not comparable
Frequently Asked Questions (5)

Which is better, Claude Opus 4.7 (Adaptive) or Qwen3.7 Max?

Qwen3.7 Max is ahead on BenchLM's BenchAlign leaderboard, 72.84 to 66.27. The biggest single separator in this matchup is HLE, where the scores are 54.7% and 41.4%.

Which is better for knowledge tasks, Claude Opus 4.7 (Adaptive) or Qwen3.7 Max?

Qwen3.7 Max has the edge for knowledge tasks in this comparison, averaging 64.2 versus 60. Inside this category, AA-Omniscience Accuracy is the benchmark that creates the most daylight between them.

Which is better for coding, Claude Opus 4.7 (Adaptive) or Qwen3.7 Max?

Claude Opus 4.7 (Adaptive) has the edge for coding in this comparison, averaging 78.6 versus 77.9. Inside this category, AA Coding Index is the benchmark that creates the most daylight between them.

Which is better for reasoning, Claude Opus 4.7 (Adaptive) or Qwen3.7 Max?

Qwen3.7 Max has the edge for reasoning in this comparison, averaging 90.4 versus 75.8. Inside this category, CritPt is the benchmark that creates the most daylight between them.

Which is better for agentic tasks, Claude Opus 4.7 (Adaptive) or Qwen3.7 Max?

Claude Opus 4.7 (Adaptive) has the edge for agentic tasks in this comparison, averaging 75.1 versus 69.7. Inside this category, GDPval-AA is the benchmark that creates the most daylight between them.

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