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Model comparison

Claude Opus 4.6 vs Qwen3.6-27B

Data verified

Head-to-head evidence from 23 shared benchmark results across 6 categories. Overall scores shown here use the public BenchAlign v5 ranking lane.

68.59/100
Margin
14.8pts
← winning
53.82/100
3 category wins2 category wins

Public leaderboard positions: Claude Opus 4.6 #16 (Supported); Qwen3.6-27B #93 (Estimated). Intervals and evidence labels describe ranking uncertainty, not a guarantee for a specific workload.

Evidence parity. Claude Opus 4.6 and Qwen3.6-27B share 23 comparable benchmark results. 5 of 8 categories are comparable. 23 results are unique to Claude Opus 4.6; 31 to Qwen3.6-27B.

Updated July 21, 2026
Shared results
23
Claude Opus 4.6 only
23
Qwen3.6-27B only
31
Comparable categories
5 / 8

Pick Claude Opus 4.6 if you want the stronger benchmark profile. Qwen3.6-27B 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 23 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 53.82. 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 knowledge, where it averages 69.1 against 53.3. The single biggest benchmark swing on the page is SuperGPQA, 95% to 66%. Qwen3.6-27B 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 $0.00 input / $0.00 output per 1M tokens for Qwen3.6-27B. That is roughly Infinityx on output cost alone. Qwen3.6-27B is the reasoning model in the pair, while Claude Opus 4.6 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 4.6 gives you the larger context window at 1M, compared with 262K for Qwen3.6-27B.

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 4.6 and Qwen3.6-27B
CategoryClaude Opus 4.6ΔQwen3.6-27B
MathClaude Opus 4.636.3Margin 52.9Qwen3.6-27B89.2
KnowledgeClaude Opus 4.669.1Margin 15.8Qwen3.6-27B53.3
AgenticClaude Opus 4.673.0Margin 13.7Qwen3.6-27B59.3
CodingClaude Opus 4.668.1Margin 9.4Qwen3.6-27B77.5
MultimodalClaude Opus 4.677.3Margin 0.6Qwen3.6-27B76.7

Decisive benchmark drivers

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

More
A · Claude Opus 4.6B · Qwen3.6-27B
  1. SuperGPQA

    Knowledge
    Source ↗
    A 95%B 66%
    Winner: Claude Opus 4.6Δ 29
    SuperGPQA: Claude Opus 4.6 scored 95%; Qwen3.6-27B scored 66%. Claude Opus 4.6 wins this benchmark.
  2. HLE

    Knowledge
    Source ↗
    A 53%B 24%
    Winner: Claude Opus 4.6Δ 29
    HLE: Claude Opus 4.6 scored 53%; Qwen3.6-27B scored 24%. Claude Opus 4.6 wins this benchmark.
  3. Terminal-Bench 2.0

    Agentic
    Source ↗
    A 65.4%B 59.3%
    Winner: Claude Opus 4.6Δ 6.1
    Terminal-Bench 2.0: Claude Opus 4.6 scored 65.4%; Qwen3.6-27B scored 59.3%. Claude Opus 4.6 wins this benchmark.
  4. MMLU-Pro

    Knowledge
    Source ↗
    A 82%B 86.2%
    Winner: Qwen3.6-27BΔ 4.2
    MMLU-Pro: Claude Opus 4.6 scored 82%; Qwen3.6-27B scored 86.2%. Qwen3.6-27B wins this benchmark.
  5. SWE-bench Verified

    Coding
    Source ↗
    A 80.8%B 77.2%
    Winner: Claude Opus 4.6Δ 3.6
    SWE-bench Verified: Claude Opus 4.6 scored 80.8%; Qwen3.6-27B scored 77.2%. Claude Opus 4.6 wins this benchmark.

Operational comparison

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

MetricClaude Opus 4.6Qwen3.6-27BComparison
Input / output priceUSD per 1M tokensClaude Opus 4.6$5 input / $25 outputQwen3.6-27B$0 input / $0 outputQwen3.6-27B has the lower combined listed price.
Generation speedtokens per secondClaude Opus 4.640 tok/sQwen3.6-27BNot availableA complete speed comparison is not available.
First-answer latencyseconds to first tokenClaude Opus 4.61.78 sQwen3.6-27BNot availableA complete latency comparison is not available.
Context windowmaximum listed tokensClaude Opus 4.61MQwen3.6-27B262KClaude Opus 4.6 lists the larger context window.

Benchmark Deep Dive

AgenticClaude Opus 4.6 wins
BenchmarkClaude Opus 4.6Qwen3.6-27BResult
Terminal-Bench 2.0Source 65.4%59.3%Claude Opus 4.6 leads
BrowseCompSource 83.7%Not comparable
OSWorld-VerifiedSource 72.7%Not comparable
τ²-bench resultsSource 84.8%94.2%Qwen3.6-27B leads
Claw-EvalSource 70.4%72.4%Qwen3.6-27B leads
DeepSearchQASource 73.7%Not comparable
CyberGymSource 66.6%Not comparable
Gert LabsSource 61.85%54.84%Claude Opus 4.6 leads
ResearchClawBenchSource 19.9%Not comparable
JobBenchSource 36.7%Not comparable
QwenClawBenchSource 53.4%Not comparable
QwenWebBenchSource 1487Not comparable
AndroidWorldSource 70.3%Not comparable
AA Agentic IndexSource 27.0%Not comparable
GDPval-AASource 32.0%Not comparable
GDPval-AASource 1140Not comparable
CodingQwen3.6-27B wins
BenchmarkClaude Opus 4.6Qwen3.6-27BResult
SWE-bench VerifiedSource 80.8%77.2%Claude Opus 4.6 leads
SWE-bench Verified*Source 75.6%Not comparable
LiveCodeBench ProSource 70.7%Not comparable
SWE-bench ProSource 53.4%53.5%Qwen3.6-27B 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%39.8%Claude Opus 4.6 leads
FrontierCode 1.1 MainSource 26.9%Not comparable
SWE MultilingualSource 71.3%Not comparable
Terminal-Bench 2.0Source 59.3%Not comparable
LiveCodeBenchSource 83.9%Not comparable
NL2RepoSource 36.2%Not comparable
AA Coding IndexSource 53.7%Not comparable
Reasoning
BenchmarkClaude Opus 4.6Qwen3.6-27BResult
AA-LCRSource 58.3%68.7%Qwen3.6-27B leads
CritPtSource 2.8%1.1%Claude Opus 4.6 leads
KnowledgeClaude Opus 4.6 wins
BenchmarkClaude Opus 4.6Qwen3.6-27BResult
GPQASource 91.3%87.8%Claude Opus 4.6 leads
GPQA-DSource 89.2%Not comparable
SuperGPQASource 95%66%Claude Opus 4.6 leads
MMLU-ProSource 82%86.2%Qwen3.6-27B leads
MMLU-Pro (Arcee)Source 89.1%Not comparable
HLESource 53%24%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%37.0%Claude Opus 4.6 leads
AA-GPQA DiamondSource 84.0%84.2%Qwen3.6-27B leads
AA-HLESource 18.6%21.6%Qwen3.6-27B leads
AA-Omniscience IndexSource 3.5%-19.8%Claude Opus 4.6 leads
AA-Omniscience AccuracySource 45.2%19.2%Claude Opus 4.6 leads
AA-Omniscience Hallucination RateSource 76.0%48.3%Qwen3.6-27B leads
MMLU-ReduxSource 93.5%Not comparable
C-EvalSource 91.4%Not comparable
MathQwen3.6-27B wins
BenchmarkClaude Opus 4.6Qwen3.6-27BResult
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
HMMT Feb 2025Source 93.8%Not comparable
HMMT Nov 2025Source 90.7%Not comparable
HMMT Feb 2026Source 84.3%Not comparable
MMAnswerBenchSource 80.8%Not comparable
AIME26Source 94.1%Not comparable
MultimodalClaude Opus 4.6 wins
BenchmarkClaude Opus 4.6Qwen3.6-27BResult
MMMU-ProSource 77.3%75.8%Claude Opus 4.6 leads
ERQASource 51.6%62.5%Qwen3.6-27B leads
ScreenSpot ProSource 83.1%Not comparable
MedXpertQA (MM)Source 64.8%Not comparable
AA-MMMU-ProSource 72.5%74.6%Qwen3.6-27B leads
Design Arena WebsiteSource 1325Not comparable
MMMUSource 82.9%Not comparable
RealWorldQASource 84.1%Not comparable
DynaMathSource 85.6%Not comparable
MStarSource 81.4%Not comparable
SimpleVQASource 56.1%Not comparable
CharXivSource 78.4%Not comparable
CC-OCRSource 81.2%Not comparable
CountBenchSource 97.8%Not comparable
RefCOCO (avg)Source 92.5%Not comparable
Video-MME (with subtitle)Source 87.7%Not comparable
VideoMMMUSource 84.4%Not comparable
MLVU (M-Avg)Source 86.6%Not comparable
V*Source 94.7%Not comparable
Inst. Following
BenchmarkClaude Opus 4.6Qwen3.6-27BResult
AA-IFBenchSource 44.6%67.6%Qwen3.6-27B leads
Frequently Asked Questions (6)

Which is better, Claude Opus 4.6 or Qwen3.6-27B?

Claude Opus 4.6 is ahead on BenchLM's BenchAlign leaderboard, 68.59 to 53.82. The biggest single separator in this matchup is SuperGPQA, where the scores are 95% and 66%.

Which is better for knowledge tasks, Claude Opus 4.6 or Qwen3.6-27B?

Claude Opus 4.6 has the edge for knowledge tasks in this comparison, averaging 69.1 versus 53.3. Inside this category, SuperGPQA is the benchmark that creates the most daylight between them.

Which is better for coding, Claude Opus 4.6 or Qwen3.6-27B?

Qwen3.6-27B has the edge for coding in this comparison, averaging 77.5 versus 68.1. Inside this category, AA-SciCode is the benchmark that creates the most daylight between them.

Which is better for math, Claude Opus 4.6 or Qwen3.6-27B?

Qwen3.6-27B has the edge for math in this comparison, averaging 89.2 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 Qwen3.6-27B?

Claude Opus 4.6 has the edge for agentic tasks in this comparison, averaging 73 versus 59.3. Inside this category, τ²-bench results is the benchmark that creates the most daylight between them.

Which is better for multimodal and grounded tasks, Claude Opus 4.6 or Qwen3.6-27B?

Claude Opus 4.6 has the edge for multimodal and grounded tasks in this comparison, averaging 77.3 versus 76.7. Inside this category, ERQA is the benchmark that creates the most daylight between them.

Self-host vs API cost

Estimates at 50,000 req/day · 1000 tokens/req average.

Claude Opus 4.6
API / mo$22,500
Self-host / moNot listed
Break-even
Proprietary model — self-hosting not applicable.
Qwen3.6-27B
API / mo$0
Self-host / mo$429
Break-even
Model the full break-even

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Last updated: July 21, 2026

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