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Model comparison

Claude Opus 4.6 vs DeepSeek V3.2

Data verified

Head-to-head evidence from 18 shared benchmark results across 7 categories. Overall scores shown here use the public BenchAlign v5 ranking lane.

68.59/100
Margin
13.2pts
← winning
55.4/100
2 category wins0 category wins

Public leaderboard positions: Claude Opus 4.6 #16 (Supported); DeepSeek V3.2 #82 (Supported). Intervals and evidence labels describe ranking uncertainty, not a guarantee for a specific workload.

Evidence parity. Claude Opus 4.6 and DeepSeek V3.2 share 18 comparable benchmark results. 2 of 8 categories are comparable. 28 results are unique to Claude Opus 4.6; 1 to DeepSeek V3.2.

Updated July 20, 2026
Shared results
18
Claude Opus 4.6 only
28
DeepSeek V3.2 only
1
Comparable categories
2 / 8

Pick Claude Opus 4.6 if you want the stronger benchmark profile. DeepSeek V3.2 only becomes the better choice if you want the cheaper token bill.

Confidence note. This is a partial-evidence comparison with 18 shared benchmark results across 7 evidence categories; 2 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 55.4. 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 mathematics, where it averages 36.3 against 17.1. The single biggest benchmark swing on the page is FrontierMath v2 (Tier 4), 22.900% to 2.100%.

Claude Opus 4.6 is also the more expensive model on tokens at $5.00 input / $25.00 output per 1M tokens, versus $0.28 input / $0.42 output per 1M tokens for DeepSeek V3.2. That is roughly 59.5x on output cost alone. Claude Opus 4.6 gives you the larger context window at 1M, compared with 128K for DeepSeek V3.2.

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 DeepSeek V3.2
CategoryClaude Opus 4.6ΔDeepSeek V3.2
MathClaude Opus 4.636.3Margin← 19.2DeepSeek V3.217.1
CodingClaude Opus 4.668.1Margin← 7.2DeepSeek V3.260.9
AgenticClaude Opus 4.673.0MarginNo overlapDeepSeek V3.2Not measured
KnowledgeClaude Opus 4.669.1MarginNo overlapDeepSeek V3.2Not measured
MultimodalClaude Opus 4.677.3MarginNo overlapDeepSeek V3.2Not measured

Decisive benchmark drivers

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

More
A · Claude Opus 4.6B · DeepSeek V3.2

  1. FrontierMath v2 (Tier 4)

    Math
    Source ↗
    A 22.900%B 2.100%
    Winner: Claude Opus 4.6Δ 20.8
    FrontierMath v2 (Tier 4): Claude Opus 4.6 scored 22.900%; DeepSeek V3.2 scored 2.100%. Claude Opus 4.6 wins this benchmark.

  2. FrontierMath v2 (Tiers 1-3)

    Math
    Source ↗
    A 40.700%B 22.100%
    Winner: Claude Opus 4.6Δ 18.6
    FrontierMath v2 (Tiers 1-3): Claude Opus 4.6 scored 40.700%; DeepSeek V3.2 scored 22.100%. Claude Opus 4.6 wins this benchmark.

  3. SWE-Rebench

    Coding
    Source ↗
    A 65.3%B 60.9%
    Winner: Claude Opus 4.6Δ 4.4
    SWE-Rebench: Claude Opus 4.6 scored 65.3%; DeepSeek V3.2 scored 60.9%. 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 4.6DeepSeek V3.2Comparison
Input / output priceUSD per 1M tokensClaude Opus 4.6$5 input / $25 outputDeepSeek V3.2$0.28 input / $0.42 outputDeepSeek V3.2 has the lower combined listed price.
Generation speedtokens per secondClaude Opus 4.640 tok/sDeepSeek V3.235 tok/sClaude Opus 4.6 has the higher measured throughput.
First-answer latencyseconds to first tokenClaude Opus 4.61.78 sDeepSeek V3.23.75 sClaude Opus 4.6 reaches the first token sooner.
Context windowmaximum listed tokensClaude Opus 4.61MDeepSeek V3.2128KClaude Opus 4.6 lists the larger context window.

Benchmark Deep Dive

Agentic
BenchmarkClaude Opus 4.6DeepSeek V3.2Result
Terminal-Bench 2.0Source 65.4%—Not comparable
BrowseCompSource 83.7%—Not comparable
OSWorld-VerifiedSource 72.7%—Not comparable
τ²-bench resultsSource 84.8%78.9%Claude Opus 4.6 leads
Claw-EvalSource 70.4%40.2%Claude Opus 4.6 leads
DeepSearchQASource 73.7%—Not comparable
CyberGymSource 66.6%—Not comparable
Gert LabsSource 61.85%29.57%Claude Opus 4.6 leads
ResearchClawBenchSource 19.9%—Not comparable
JobBenchSource 36.7%—Not comparable
VITA-BenchSource —18.5%Not comparable
CodingClaude Opus 4.6 wins
BenchmarkClaude Opus 4.6DeepSeek V3.2Result
SWE-bench VerifiedSource 80.8%—Not comparable
SWE-bench Verified*Source 75.6%—Not comparable
LiveCodeBench ProSource 70.7%—Not comparable
SWE-bench ProSource 53.4%—Not comparable
SWE-RebenchSource 65.3%60.9%Claude Opus 4.6 leads
React Native EvalsSource 84.1%71.5%Claude Opus 4.6 leads
Vibe Code BenchSource 57.57%—Not comparable
AA-SciCodeSource 45.7%38.7%Claude Opus 4.6 leads
FrontierCode 1.1 MainSource 26.9%—Not comparable
Reasoning
BenchmarkClaude Opus 4.6DeepSeek V3.2Result
AA-LCRSource 58.3%39.0%Claude Opus 4.6 leads
CritPtSource 2.8%0.9%Claude Opus 4.6 leads
Knowledge
BenchmarkClaude Opus 4.6DeepSeek V3.2Result
GPQASource 91.3%—Not comparable
GPQA-DSource 89.2%—Not comparable
SuperGPQASource 95%—Not comparable
MMLU-ProSource 82%—Not comparable
MMLU-Pro (Arcee)Source 89.1%—Not comparable
HLESource 53%—Not comparable
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%24.7%Claude Opus 4.6 leads
AA-GPQA DiamondSource 84.0%75.1%Claude Opus 4.6 leads
AA-HLESource 18.6%10.5%Claude Opus 4.6 leads
AA-Omniscience IndexSource 3.5%-46.7%Claude Opus 4.6 leads
AA-Omniscience AccuracySource 45.2%24.2%Claude Opus 4.6 leads
AA-Omniscience Hallucination RateSource 76.0%93.5%Claude Opus 4.6 leads
MathClaude Opus 4.6 wins
BenchmarkClaude Opus 4.6DeepSeek V3.2Result
AIME25 (Arcee)Source 99.8%—Not comparable
FrontierMath v2 (Tiers 1-3)Source 40.700%22.100%Claude Opus 4.6 leads
FrontierMath v2 (Tier 4)Source 22.900%2.100%Claude Opus 4.6 leads
Multimodal
BenchmarkClaude Opus 4.6DeepSeek V3.2Result
MMMU-ProSource 77.3%—Not comparable
ERQASource 51.6%—Not comparable
ScreenSpot ProSource 83.1%—Not comparable
MedXpertQA (MM)Source 64.8%—Not comparable
AA-MMMU-ProSource 72.5%—Not comparable
Design Arena WebsiteSource 13281206Claude Opus 4.6 leads
Inst. Following
BenchmarkClaude Opus 4.6DeepSeek V3.2Result
AA-IFBenchSource 44.6%49.0%DeepSeek V3.2 leads
Frequently Asked Questions (3)

Which is better, Claude Opus 4.6 or DeepSeek V3.2?

Claude Opus 4.6 is ahead on BenchLM's BenchAlign leaderboard, 68.59 to 55.4. The biggest single separator in this matchup is FrontierMath v2 (Tier 4), where the scores are 22.900% and 2.100%.

Which is better for coding, Claude Opus 4.6 or DeepSeek V3.2?

Claude Opus 4.6 has the edge for coding in this comparison, averaging 68.1 versus 60.9. Inside this category, React Native Evals is the benchmark that creates the most daylight between them.

Which is better for math, Claude Opus 4.6 or DeepSeek V3.2?

Claude Opus 4.6 has the edge for math in this comparison, averaging 36.3 versus 17.1. Inside this category, FrontierMath v2 (Tier 4) is the benchmark that creates the most daylight between them.

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