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Model comparison

Claude Opus 4.7 (Adaptive) vs Qwen3.5 397B

Data verified

Head-to-head evidence from 24 shared benchmark results across 6 categories. Overall scores shown here use the public BenchAlign v5 ranking lane.

66.27/100
Margin
9.3pts
← winning
57.01/100
4 category wins1 category wins

Public leaderboard positions: Claude Opus 4.7 (Adaptive) #27 (Estimated); Qwen3.5 397B #71 (Estimated). Intervals and evidence labels describe ranking uncertainty, not a guarantee for a specific workload.

Evidence parity. Claude Opus 4.7 (Adaptive) and Qwen3.5 397B share 24 comparable benchmark results. 5 of 8 categories are comparable. 14 results are unique to Claude Opus 4.7 (Adaptive); 31 to Qwen3.5 397B.

Updated July 23, 2026
Shared results
24
Claude Opus 4.7 (Adaptive) only
14
Qwen3.5 397B only
31
Comparable categories
5 / 8

Pick Claude Opus 4.7 (Adaptive) if you want the stronger benchmark profile. Qwen3.5 397B only becomes the better choice if multimodal & grounded is the priority or you want the cheaper token bill.

Confidence note. This is a partial-evidence comparison with 24 shared benchmark results across 6 evidence categories; 5 of 8 categories currently have scoreable aggregates for both models. Treat the verdict as directional until coverage is more balanced.

Why this result

Claude Opus 4.7 (Adaptive) is clearly ahead on the BenchAlign aggregate, 66.27 to 57.01. The gap is large enough that you do not need to squint at the spreadsheet to see the difference.

Claude Opus 4.7 (Adaptive)'s sharpest advantage is in agentic, where it averages 75.1 against 56.5. The single biggest benchmark swing on the page is HLE, 54.7% to 28.7%. Qwen3.5 397B does hit back in multimodal & grounded, so the answer changes if that is the part of the workload you care about most.

Claude Opus 4.7 (Adaptive) is also the more expensive model on tokens at $5.00 input / $25.00 output per 1M tokens, versus $0.60 input / $3.60 output per 1M tokens for Qwen3.5 397B. That is roughly 6.9x on output cost alone. Claude Opus 4.7 (Adaptive) is the reasoning model in the pair, while Qwen3.5 397B is not. That usually helps on harder chain-of-thought-heavy tests, but it can also mean more latency and more token spend in real use. Claude Opus 4.7 (Adaptive) gives you the larger context window at 1M, compared with 128K for Qwen3.5 397B.

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 Qwen3.5 397B
CategoryClaude Opus 4.7 (Adaptive)ΔQwen3.5 397B
AgenticClaude Opus 4.7 (Adaptive)75.1Margin← 18.6Qwen3.5 397B56.5
MultimodalClaude Opus 4.7 (Adaptive)65.1Margin→ 14.5Qwen3.5 397B79.6
ReasoningClaude Opus 4.7 (Adaptive)75.8Margin← 12.6Qwen3.5 397B63.2
CodingClaude Opus 4.7 (Adaptive)78.6Margin← 12.1Qwen3.5 397B66.5
KnowledgeClaude Opus 4.7 (Adaptive)60.0Margin← 3.4Qwen3.5 397B56.6
MathClaude Opus 4.7 (Adaptive)Not measuredMarginNo overlapQwen3.5 397B90.6
MultilingualClaude Opus 4.7 (Adaptive)Not measuredMarginNo overlapQwen3.5 397B84.7
Inst. FollowingClaude Opus 4.7 (Adaptive)Not measuredMarginNo overlapQwen3.5 397B92.6

Decisive benchmark drivers

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

More
A · Claude Opus 4.7 (Adaptive)B · Qwen3.5 397B

  1. HLE

    Knowledge
    Source ↗
    A 54.7%B 28.7%
    Winner: Claude Opus 4.7 (Adaptive)Δ 26
    HLE: Claude Opus 4.7 (Adaptive) scored 54.7%; Qwen3.5 397B scored 28.7%. Claude Opus 4.7 (Adaptive) wins this benchmark.

  2. BrowseComp

    Agentic
    Source ↗
    A 79.3%B 62%
    Winner: Claude Opus 4.7 (Adaptive)Δ 17.3
    BrowseComp: Claude Opus 4.7 (Adaptive) scored 79.3%; Qwen3.5 397B scored 62%. Claude Opus 4.7 (Adaptive) wins this benchmark.

  3. Terminal-Bench 2.0

    Agentic
    Source ↗
    A 69.4%B 52.5%
    Winner: Claude Opus 4.7 (Adaptive)Δ 16.9
    Terminal-Bench 2.0: Claude Opus 4.7 (Adaptive) scored 69.4%; Qwen3.5 397B scored 52.5%. Claude Opus 4.7 (Adaptive) wins this benchmark.

  4. SWE-bench Pro

    Coding
    Source ↗
    A 64.3%B 50.9%
    Winner: Claude Opus 4.7 (Adaptive)Δ 13.4
    SWE-bench Pro: Claude Opus 4.7 (Adaptive) scored 64.3%; Qwen3.5 397B scored 50.9%. Claude Opus 4.7 (Adaptive) wins this benchmark.

  5. SWE-bench Verified

    Coding
    Source ↗
    A 87.6%B 76.2%
    Winner: Claude Opus 4.7 (Adaptive)Δ 11.4
    SWE-bench Verified: Claude Opus 4.7 (Adaptive) scored 87.6%; Qwen3.5 397B scored 76.2%. Claude Opus 4.7 (Adaptive) 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)Qwen3.5 397BComparison
Input / output priceUSD per 1M tokensClaude Opus 4.7 (Adaptive)$5 input / $25 outputQwen3.5 397B$0.6 input / $3.6 outputQwen3.5 397B has the lower combined listed price.
Generation speedtokens per secondClaude Opus 4.7 (Adaptive)Not availableQwen3.5 397B96 tok/sA complete speed comparison is not available.
First-answer latencyseconds to first tokenClaude Opus 4.7 (Adaptive)Not availableQwen3.5 397B2.44 sA complete latency comparison is not available.
Context windowmaximum listed tokensClaude Opus 4.7 (Adaptive)1MQwen3.5 397B128KClaude Opus 4.7 (Adaptive) lists the larger context window.

Benchmark Deep Dive

AgenticClaude Opus 4.7 (Adaptive) wins
BenchmarkClaude Opus 4.7 (Adaptive)Qwen3.5 397BResult
Terminal-Bench 2.0Source 69.4%52.5%Claude Opus 4.7 (Adaptive) leads
BrowseCompSource 79.3%62%Claude Opus 4.7 (Adaptive) leads
MCP AtlasSource 77.3%46.1%Claude Opus 4.7 (Adaptive) leads
OSWorld-VerifiedSource 78%—Not comparable
CyberGymSource 73.1%—Not comparable
AA Agentic IndexSource 44.4%19.9%Claude Opus 4.7 (Adaptive) leads
τ²-bench resultsSource 88.6%95.6%Qwen3.5 397B leads
GDPval-AASource 49.8%23.1%Claude Opus 4.7 (Adaptive) leads
GDPval-AASource 1495962Claude Opus 4.7 (Adaptive) leads
OSWorld 2.0Source 18.2%—Not comparable
JobBenchSource 45.9%—Not comparable
AA ITBenchSource 46.7%—Not comparable
Claw-EvalSource —56.8%Not comparable
QwenClawBenchSource —51.8%Not comparable
τ³-bench resultsSource —68.4%Not comparable
VITA-BenchSource —43.7%Not comparable
DeepPlanningSource —37.6%Not comparable
ToolathlonSource —36.3%Not comparable
MCP-TasksSource —74.2%Not comparable
WideResearchSource —74.0%Not comparable
Gert LabsSource —46.76%Not comparable
ResearchClawBenchSource —14.2%Not comparable
APEX-Agents-AASource —15.3%Not comparable
CodingClaude Opus 4.7 (Adaptive) wins
BenchmarkClaude Opus 4.7 (Adaptive)Qwen3.5 397BResult
SWE-bench VerifiedSource 87.6%76.2%Claude Opus 4.7 (Adaptive) leads
SWE-bench ProSource 64.3%50.9%Claude Opus 4.7 (Adaptive) leads
Terminal-Bench 2.0Source 69.4%—Not comparable
AA Coding IndexSource 73.6%48.2%Claude Opus 4.7 (Adaptive) leads
AA-SciCodeSource 54.5%42.0%Claude Opus 4.7 (Adaptive) leads
LiveCodeBench v6Source —83.6%Not comparable
ReasoningClaude Opus 4.7 (Adaptive) wins
BenchmarkClaude Opus 4.7 (Adaptive)Qwen3.5 397BResult
MRCR v2 128K-256KSource 59.2%—Not comparable
ARC-AGI-2Source 75.8%—Not comparable
AA-LCRSource 70.3%65.7%Claude Opus 4.7 (Adaptive) leads
CritPtSource 12.0%1.7%Claude Opus 4.7 (Adaptive) leads
LongBench v2Source —63.2%Not comparable
AI-NeedleSource —68.7%Not comparable
KnowledgeClaude Opus 4.7 (Adaptive) wins
BenchmarkClaude Opus 4.7 (Adaptive)Qwen3.5 397BResult
GPQASource 94.2%88.4%Claude Opus 4.7 (Adaptive) leads
GPQA-DSource 94.2%—Not comparable
HLESource 54.7%28.7%Claude Opus 4.7 (Adaptive) leads
HLE w/o toolsSource 46.9%—Not comparable
Artificial Analysis Intelligence IndexSource 53.5%33.7%Claude Opus 4.7 (Adaptive) leads
AA-GPQA DiamondSource 91.4%89.3%Claude Opus 4.7 (Adaptive) leads
AA-HLESource 39.6%27.3%Claude Opus 4.7 (Adaptive) leads
AA-Omniscience IndexSource 26.2%-29.8%Claude Opus 4.7 (Adaptive) leads
AA-Omniscience AccuracySource 45.8%31.4%Claude Opus 4.7 (Adaptive) leads
AA-Omniscience Hallucination RateSource 36.2%89.1%Claude Opus 4.7 (Adaptive) leads
SuperGPQASource —70.4%Not comparable
MMLU-ProSource —87.8%Not comparable
MMLU-ReduxSource —94.9%Not comparable
C-EvalSource —93%Not comparable
Math
BenchmarkClaude Opus 4.7 (Adaptive)Qwen3.5 397BResult
FrontierMath (legacy)Source 43.8%—Not comparable
AIME26Source —93.3%Not comparable
HMMT Feb 2025Source —94.8%Not comparable
HMMT Nov 2025Source —92.7%Not comparable
HMMT Feb 2026Source —87.9%Not comparable
MMAnswerBenchSource —80.9%Not comparable
Multilingual
BenchmarkClaude Opus 4.7 (Adaptive)Qwen3.5 397BResult
MMLU-ProXSource —84.7%Not comparable
NOVA-63Source —59.1%Not comparable
MultimodalQwen3.5 397B wins
BenchmarkClaude Opus 4.7 (Adaptive)Qwen3.5 397BResult
OfficeQA ProSource 43.6%—Not comparable
CharXivSource 91%80.8%Claude Opus 4.7 (Adaptive) leads
CharXiv w/o toolsSource 82.1%—Not comparable
AA-MMMU-ProSource 78.8%77.3%Claude Opus 4.7 (Adaptive) leads
Design Arena WebsiteSource 1325—Not comparable
MMMU-ProSource —79%Not comparable
MathVisionSource —88.6%Not comparable
VideoMMMUSource —84.7%Not comparable
ScreenSpot ProSource —65.6%Not comparable
V*Source —95.8%Not comparable
Inst. Following
BenchmarkClaude Opus 4.7 (Adaptive)Qwen3.5 397BResult
AA-IFBenchSource 58.6%78.8%Qwen3.5 397B leads
IFEvalSource —92.6%Not comparable
Frequently Asked Questions (6)

Which is better, Claude Opus 4.7 (Adaptive) or Qwen3.5 397B?

Claude Opus 4.7 (Adaptive) is ahead on BenchLM's BenchAlign leaderboard, 66.27 to 57.01. The biggest single separator in this matchup is HLE, where the scores are 54.7% and 28.7%.

Which is better for knowledge tasks, Claude Opus 4.7 (Adaptive) or Qwen3.5 397B?

Claude Opus 4.7 (Adaptive) has the edge for knowledge tasks in this comparison, averaging 60 versus 56.6. Inside this category, AA-Omniscience Index is the benchmark that creates the most daylight between them.

Which is better for coding, Claude Opus 4.7 (Adaptive) or Qwen3.5 397B?

Claude Opus 4.7 (Adaptive) has the edge for coding in this comparison, averaging 78.6 versus 66.5. 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 Qwen3.5 397B?

Claude Opus 4.7 (Adaptive) has the edge for reasoning in this comparison, averaging 75.8 versus 63.2. 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 Qwen3.5 397B?

Claude Opus 4.7 (Adaptive) has the edge for agentic tasks in this comparison, averaging 75.1 versus 56.5. Inside this category, GDPval-AA is the benchmark that creates the most daylight between them.

Which is better for multimodal and grounded tasks, Claude Opus 4.7 (Adaptive) or Qwen3.5 397B?

Qwen3.5 397B has the edge for multimodal and grounded tasks in this comparison, averaging 79.6 versus 65.1. Inside this category, CharXiv is the benchmark that creates the most daylight between them.

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