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Model comparison

Claude Opus 4.6 vs Qwen3.5 397B

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.

68.59/100
Margin
11.6pts
← winning
57.01/100
3 category wins2 category wins

Public leaderboard positions: Claude Opus 4.6 #16 (Supported); Qwen3.5 397B #71 (Estimated). Intervals and evidence labels describe ranking uncertainty, not a guarantee for a specific workload.

Evidence parity. Claude Opus 4.6 and Qwen3.5 397B share 25 comparable benchmark results. 5 of 8 categories are comparable. 21 results are unique to Claude Opus 4.6; 30 to Qwen3.5 397B.

Updated July 20, 2026
Shared results
25
Claude Opus 4.6 only
21
Qwen3.5 397B only
30
Comparable categories
5 / 8

Pick Claude Opus 4.6 if you want the stronger benchmark profile. Qwen3.5 397B only becomes the better choice if mathematics is the priority or you want the cheaper token bill.

Confidence note. This is a partial-evidence comparison with 25 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 4.6 is clearly ahead on the BenchAlign aggregate, 68.59 to 57.01. The gap is large enough that you do not need to squint at the spreadsheet to see the difference.

Claude Opus 4.6's sharpest advantage is in agentic, where it averages 73 against 56.5. The single biggest benchmark swing on the page is SuperGPQA, 95% to 70.4%. Qwen3.5 397B does hit back in mathematics, so the answer changes if that is the part of the workload you care about most.

Claude Opus 4.6 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 4.6 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 4.6 and Qwen3.5 397B
CategoryClaude Opus 4.6ΔQwen3.5 397B
MathClaude Opus 4.636.3Margin→ 54.3Qwen3.5 397B90.6
AgenticClaude Opus 4.673.0Margin← 16.5Qwen3.5 397B56.5
KnowledgeClaude Opus 4.669.1Margin← 12.5Qwen3.5 397B56.6
MultimodalClaude Opus 4.677.3Margin→ 2.3Qwen3.5 397B79.6
CodingClaude Opus 4.668.1Margin← 1.6Qwen3.5 397B66.5
ReasoningClaude Opus 4.6Not measuredMarginNo overlapQwen3.5 397B63.2
MultilingualClaude Opus 4.6Not measuredMarginNo overlapQwen3.5 397B84.7
Inst. FollowingClaude Opus 4.6Not measuredMarginNo overlapQwen3.5 397B92.6

Decisive benchmark drivers

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

More
A · Claude Opus 4.6B · Qwen3.5 397B

  1. SuperGPQA

    Knowledge
    Source ↗
    A 95%B 70.4%
    Winner: Claude Opus 4.6Δ 24.6
    SuperGPQA: Claude Opus 4.6 scored 95%; Qwen3.5 397B scored 70.4%. Claude Opus 4.6 wins this benchmark.

  2. HLE

    Knowledge
    Source ↗
    A 53%B 28.7%
    Winner: Claude Opus 4.6Δ 24.3
    HLE: Claude Opus 4.6 scored 53%; Qwen3.5 397B scored 28.7%. Claude Opus 4.6 wins this benchmark.

  3. BrowseComp

    Agentic
    Source ↗
    A 83.7%B 62%
    Winner: Claude Opus 4.6Δ 21.7
    BrowseComp: Claude Opus 4.6 scored 83.7%; Qwen3.5 397B scored 62%. Claude Opus 4.6 wins this benchmark.

  4. Terminal-Bench 2.0

    Agentic
    Source ↗
    A 65.4%B 52.5%
    Winner: Claude Opus 4.6Δ 12.9
    Terminal-Bench 2.0: Claude Opus 4.6 scored 65.4%; Qwen3.5 397B scored 52.5%. Claude Opus 4.6 wins this benchmark.

  5. MMLU-Pro

    Knowledge
    Source ↗
    A 82%B 87.8%
    Winner: Qwen3.5 397BΔ 5.8
    MMLU-Pro: Claude Opus 4.6 scored 82%; Qwen3.5 397B scored 87.8%. Qwen3.5 397B wins this benchmark.

Operational comparison

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

MetricClaude Opus 4.6Qwen3.5 397BComparison
Input / output priceUSD per 1M tokensClaude Opus 4.6$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 4.640 tok/sQwen3.5 397B96 tok/sQwen3.5 397B has the higher measured throughput.
First-answer latencyseconds to first tokenClaude Opus 4.61.78 sQwen3.5 397B2.44 sClaude Opus 4.6 reaches the first token sooner.
Context windowmaximum listed tokensClaude Opus 4.61MQwen3.5 397B128KClaude Opus 4.6 lists the larger context window.

Benchmark Deep Dive

AgenticClaude Opus 4.6 wins
BenchmarkClaude Opus 4.6Qwen3.5 397BResult
Terminal-Bench 2.0Source 65.4%52.5%Claude Opus 4.6 leads
BrowseCompSource 83.7%62%Claude Opus 4.6 leads
OSWorld-VerifiedSource 72.7%—Not comparable
τ²-bench resultsSource 84.8%95.6%Qwen3.5 397B leads
Claw-EvalSource 70.4%56.8%Claude Opus 4.6 leads
DeepSearchQASource 73.7%—Not comparable
CyberGymSource 66.6%—Not comparable
Gert LabsSource 61.85%46.76%Claude Opus 4.6 leads
ResearchClawBenchSource 19.9%14.2%Claude Opus 4.6 leads
JobBenchSource 36.7%—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 AtlasSource —46.1%Not comparable
MCP-TasksSource —74.2%Not comparable
WideResearchSource —74.0%Not comparable
AA Agentic IndexSource —19.9%Not comparable
APEX-Agents-AASource —15.3%Not comparable
GDPval-AASource —23.1%Not comparable
GDPval-AASource —962Not comparable
CodingClaude Opus 4.6 wins
BenchmarkClaude Opus 4.6Qwen3.5 397BResult
SWE-bench VerifiedSource 80.8%76.2%Claude Opus 4.6 leads
SWE-bench Verified*Source 75.6%—Not comparable
LiveCodeBench ProSource 70.7%—Not comparable
SWE-bench ProSource 53.4%50.9%Claude Opus 4.6 leads
SWE-RebenchSource 65.3%—Not comparable
React Native EvalsSource 84.1%—Not comparable
Vibe Code BenchSource 57.57%—Not comparable
AA-SciCodeSource 45.7%42.0%Claude Opus 4.6 leads
FrontierCode 1.1 MainSource 26.9%—Not comparable
LiveCodeBench v6Source —83.6%Not comparable
AA Coding IndexSource —48.2%Not comparable
Reasoning
BenchmarkClaude Opus 4.6Qwen3.5 397BResult
AA-LCRSource 58.3%65.7%Qwen3.5 397B leads
CritPtSource 2.8%1.7%Claude Opus 4.6 leads
LongBench v2Source —63.2%Not comparable
AI-NeedleSource —68.7%Not comparable
KnowledgeClaude Opus 4.6 wins
BenchmarkClaude Opus 4.6Qwen3.5 397BResult
GPQASource 91.3%88.4%Claude Opus 4.6 leads
GPQA-DSource 89.2%—Not comparable
SuperGPQASource 95%70.4%Claude Opus 4.6 leads
MMLU-ProSource 82%87.8%Qwen3.5 397B leads
MMLU-Pro (Arcee)Source 89.1%—Not comparable
HLESource 53%28.7%Claude Opus 4.6 leads
HLE w/o toolsSource 40%—Not comparable
HealthBench HardSource 14.8%—Not comparable
MedXpertQA (Text)Source 52.1%—Not comparable
Artificial Analysis Intelligence IndexSource 37.8%33.7%Claude Opus 4.6 leads
AA-GPQA DiamondSource 84.0%89.3%Qwen3.5 397B leads
AA-HLESource 18.6%27.3%Qwen3.5 397B leads
AA-Omniscience IndexSource 3.5%-29.8%Claude Opus 4.6 leads
AA-Omniscience AccuracySource 45.2%31.4%Claude Opus 4.6 leads
AA-Omniscience Hallucination RateSource 76.0%89.1%Claude Opus 4.6 leads
MMLU-ReduxSource —94.9%Not comparable
C-EvalSource —93%Not comparable
MathQwen3.5 397B wins
BenchmarkClaude Opus 4.6Qwen3.5 397BResult
AIME25 (Arcee)Source 99.8%—Not comparable
FrontierMath v2 (Tiers 1-3)Source 40.700%—Not comparable
FrontierMath v2 (Tier 4)Source 22.900%—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 4.6Qwen3.5 397BResult
MMLU-ProXSource —84.7%Not comparable
NOVA-63Source —59.1%Not comparable
MultimodalQwen3.5 397B wins
BenchmarkClaude Opus 4.6Qwen3.5 397BResult
MMMU-ProSource 77.3%79%Qwen3.5 397B leads
ERQASource 51.6%—Not comparable
ScreenSpot ProSource 83.1%65.6%Claude Opus 4.6 leads
MedXpertQA (MM)Source 64.8%—Not comparable
AA-MMMU-ProSource 72.5%77.3%Qwen3.5 397B leads
Design Arena WebsiteSource 1328—Not comparable
MathVisionSource —88.6%Not comparable
CharXivSource —80.8%Not comparable
VideoMMMUSource —84.7%Not comparable
V*Source —95.8%Not comparable
Inst. Following
BenchmarkClaude Opus 4.6Qwen3.5 397BResult
AA-IFBenchSource 44.6%78.8%Qwen3.5 397B leads
IFEvalSource —92.6%Not comparable
Frequently Asked Questions (6)

Which is better, Claude Opus 4.6 or Qwen3.5 397B?

Claude Opus 4.6 is ahead on BenchLM's BenchAlign leaderboard, 68.59 to 57.01. The biggest single separator in this matchup is SuperGPQA, where the scores are 95% and 70.4%.

Which is better for knowledge tasks, Claude Opus 4.6 or Qwen3.5 397B?

Claude Opus 4.6 has the edge for knowledge tasks in this comparison, averaging 69.1 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 4.6 or Qwen3.5 397B?

Claude Opus 4.6 has the edge for coding in this comparison, averaging 68.1 versus 66.5. Inside this category, SWE-bench Verified is the benchmark that creates the most daylight between them.

Which is better for math, Claude Opus 4.6 or Qwen3.5 397B?

Qwen3.5 397B has the edge for math in this comparison, averaging 90.6 versus 36.3. Claude Opus 4.6 stays close enough that the answer can still flip depending on your workload.

Which is better for agentic tasks, Claude Opus 4.6 or Qwen3.5 397B?

Claude Opus 4.6 has the edge for agentic tasks in this comparison, averaging 73 versus 56.5. Inside this category, BrowseComp is the benchmark that creates the most daylight between them.

Which is better for multimodal and grounded tasks, Claude Opus 4.6 or Qwen3.5 397B?

Qwen3.5 397B has the edge for multimodal and grounded tasks in this comparison, averaging 79.6 versus 77.3. Inside this category, ScreenSpot Pro is the benchmark that creates the most daylight between them.

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