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Model comparison

Claude Sonnet 5 vs DeepSeek V3.2

Data verified

Head-to-head evidence from 10 shared benchmark results across 4 categories. Overall scores shown here use the public BenchAlign v5 ranking lane.

65.32/100
Margin
9.9pts
← winning
55.4/100
1 category wins0 category wins

Public leaderboard positions: Claude Sonnet 5 #29 (Estimated); DeepSeek V3.2 #82 (Supported). Intervals and evidence labels describe ranking uncertainty, not a guarantee for a specific workload.

Evidence parity. Claude Sonnet 5 and DeepSeek V3.2 share 10 comparable benchmark results. 1 of 8 categories are comparable. 26 results are unique to Claude Sonnet 5; 9 to DeepSeek V3.2.

Updated July 23, 2026
Shared results
10
Claude Sonnet 5 only
26
DeepSeek V3.2 only
9
Comparable categories
1 / 8

Pick Claude Sonnet 5 if you want the stronger benchmark profile. DeepSeek V3.2 only becomes the better choice if you want the cheaper token bill or you would rather avoid the extra latency and token burn of a reasoning model.

Confidence note. This is a partial-evidence comparison with 10 shared benchmark results across 4 evidence categories; 1 of 8 categories currently have scoreable aggregates for both models. Treat the verdict as directional until coverage is more balanced.

Why this result

Claude Sonnet 5 is clearly ahead on the BenchAlign aggregate, 65.32 to 55.4. The gap is large enough that you do not need to squint at the spreadsheet to see the difference.

Claude Sonnet 5's sharpest advantage is in coding, where it averages 76.7 against 60.9.

Claude Sonnet 5 is also the more expensive model on tokens at $2.00 input / $10.00 output per 1M tokens, versus $0.28 input / $0.42 output per 1M tokens for DeepSeek V3.2. That is roughly 23.8x on output cost alone. Claude Sonnet 5 is the reasoning model in the pair, while DeepSeek V3.2 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 Sonnet 5 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 Sonnet 5 and DeepSeek V3.2
CategoryClaude Sonnet 5ΔDeepSeek V3.2
CodingClaude Sonnet 576.7Margin 15.8DeepSeek V3.260.9
AgenticClaude Sonnet 581.9MarginNo overlapDeepSeek V3.2Not measured
KnowledgeClaude Sonnet 557.4MarginNo overlapDeepSeek V3.2Not measured
MathClaude Sonnet 5Not measuredMarginNo overlapDeepSeek V3.217.1
MultimodalClaude Sonnet 588.3MarginNo overlapDeepSeek V3.2Not measured

Operational comparison

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

MetricClaude Sonnet 5DeepSeek V3.2Comparison
Input / output priceUSD per 1M tokensClaude Sonnet 5$2 input / $10 outputDeepSeek V3.2$0.28 input / $0.42 outputDeepSeek V3.2 has the lower combined listed price.
Generation speedtokens per secondClaude Sonnet 5Not availableDeepSeek V3.235 tok/sA complete speed comparison is not available.
First-answer latencyseconds to first tokenClaude Sonnet 5Not availableDeepSeek V3.23.75 sA complete latency comparison is not available.
Context windowmaximum listed tokensClaude Sonnet 51MDeepSeek V3.2128KClaude Sonnet 5 lists the larger context window.

Benchmark Deep Dive

Agentic
BenchmarkClaude Sonnet 5DeepSeek V3.2Result
Terminal-Bench 2.0Source 80.4%Not comparable
BrowseCompSource 84.7%Not comparable
HLE w/ toolsSource 57.4%Not comparable
OSWorld-VerifiedSource 81.2%Not comparable
GDPval-AASource 1607Not comparable
AA Agentic IndexSource 46.7%Not comparable
GDPval-AASource 55.4%Not comparable
AA BriefcaseSource 1388Not comparable
AA AutomationBenchSource 39.2%Not comparable
AA EnterpriseOps-GymSource 44.7%Not comparable
AA Harvey LABSource 90.1%Not comparable
AA Tau3 BankingSource 28.2%Not comparable
aaTerminalBench21Source 80.5%Not comparable
Claw-EvalSource 40.2%Not comparable
VITA-BenchSource 18.5%Not comparable
τ²-bench resultsSource 78.9%Not comparable
Gert LabsSource 29.57%Not comparable
CodingClaude Sonnet 5 wins
BenchmarkClaude Sonnet 5DeepSeek V3.2Result
SWE-bench VerifiedSource 85.2%Not comparable
SWE-bench ProSource 63.2%Not comparable
SWE MultilingualSource 78.3%Not comparable
SWE MultimodalSource 28.1%Not comparable
Terminal-Bench 2.0Source 80.4%Not comparable
FrontierCode 1.1 MainSource 42.7%Not comparable
cursorBench32Source 61.5%Not comparable
AA Coding IndexSource 71.5%Not comparable
AA-SciCodeSource 53.6%38.7%Claude Sonnet 5 leads
SWE-RebenchSource 60.9%Not comparable
React Native EvalsSource 71.5%Not comparable
Reasoning
BenchmarkClaude Sonnet 5DeepSeek V3.2Result
AA-LCRSource 70.7%39.0%Claude Sonnet 5 leads
CritPtSource 16.9%0.9%Claude Sonnet 5 leads
Knowledge
BenchmarkClaude Sonnet 5DeepSeek V3.2Result
HLESource 57.4%Not comparable
HLE w/o toolsSource 43.2%Not comparable
Artificial Analysis Intelligence IndexSource 53.4%24.7%Claude Sonnet 5 leads
AA-GPQA DiamondSource 91.1%75.1%Claude Sonnet 5 leads
AA-HLESource 39.6%10.5%Claude Sonnet 5 leads
AA-Omniscience IndexSource 15.3%-46.7%Claude Sonnet 5 leads
AA-Omniscience AccuracySource 38.3%24.2%Claude Sonnet 5 leads
AA-Omniscience Hallucination RateSource 37.3%93.5%Claude Sonnet 5 leads
Math
BenchmarkClaude Sonnet 5DeepSeek V3.2Result
FrontierMath v2 (Tiers 1-3)Source 22.100%Not comparable
FrontierMath v2 (Tier 4)Source 2.100%Not comparable
Multimodal
BenchmarkClaude Sonnet 5DeepSeek V3.2Result
CharXivSource 88.3%Not comparable
CharXiv w/o toolsSource 77%Not comparable
AA-MMMU-ProSource 77.3%Not comparable
Design Arena WebsiteSource 13141204Claude Sonnet 5 leads
Inst. Following
BenchmarkClaude Sonnet 5DeepSeek V3.2Result
AA-IFBenchSource 49.0%Not comparable
Frequently Asked Questions (2)

Which is better, Claude Sonnet 5 or DeepSeek V3.2?

Claude Sonnet 5 is ahead on BenchLM's BenchAlign leaderboard, 65.32 to 55.4.

Which is better for coding, Claude Sonnet 5 or DeepSeek V3.2?

Claude Sonnet 5 has the edge for coding in this comparison, averaging 76.7 versus 60.9. Inside this category, AA-SciCode is the benchmark that creates the most daylight between them.

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Last updated: July 23, 2026

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