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Model comparison

Claude Opus 4.7 (Adaptive) vs DeepSeek V4 Pro (Max)

Data verified

Head-to-head evidence from 26 shared benchmark results across 6 categories. Overall scores shown here use the public BenchAlign v5 ranking lane.

66.27/100
No comparison
N/A
2 category wins1 category wins

Public leaderboard positions: Claude Opus 4.7 (Adaptive) #27 (Estimated); DeepSeek V4 Pro (Max) unranked (Not scored). Intervals and evidence labels describe ranking uncertainty, not a guarantee for a specific workload.

Evidence parity. Claude Opus 4.7 (Adaptive) and DeepSeek V4 Pro (Max) share 26 comparable benchmark results. 3 of 8 categories are comparable. 12 results are unique to Claude Opus 4.7 (Adaptive); 22 to DeepSeek V4 Pro (Max).

Updated July 23, 2026
Shared results
26
Claude Opus 4.7 (Adaptive) only
12
DeepSeek V4 Pro (Max) only
22
Comparable categories
3 / 8

Treat this as a split decision. Claude Opus 4.7 (Adaptive) makes more sense if coding is the priority; DeepSeek V4 Pro (Max) is the better fit if knowledge is the priority or you want the cheaper token bill.

Confidence note. This is a partial-evidence comparison with 26 shared benchmark results across 6 evidence categories; 3 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) and DeepSeek V4 Pro (Max) finish on the same BenchAlign overall score, so this is less about a single winner and more about where the edge shows up. The BenchAlign headline says tie; the benchmark table is where the real choice happens.

Claude Opus 4.7 (Adaptive) is also the more expensive model on tokens at $5.00 input / $25.00 output per 1M tokens, versus $0.43 input / $0.87 output per 1M tokens for DeepSeek V4 Pro (Max). That is roughly 28.7x on output cost alone.

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 DeepSeek V4 Pro (Max)
CategoryClaude Opus 4.7 (Adaptive)ΔDeepSeek V4 Pro (Max)
CodingClaude Opus 4.7 (Adaptive)78.6Margin← 7.7DeepSeek V4 Pro (Max)70.9
AgenticClaude Opus 4.7 (Adaptive)75.1Margin← 0.6DeepSeek V4 Pro (Max)74.5
KnowledgeClaude Opus 4.7 (Adaptive)60.0Margin→ 0.1DeepSeek V4 Pro (Max)60.1
ReasoningClaude Opus 4.7 (Adaptive)75.8MarginNo overlapDeepSeek V4 Pro (Max)Not measured
MathClaude Opus 4.7 (Adaptive)Not measuredMarginNo overlapDeepSeek V4 Pro (Max)95.2
MultimodalClaude Opus 4.7 (Adaptive)65.1MarginNo overlapDeepSeek V4 Pro (Max)Not measured

Decisive benchmark drivers

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

More
A · Claude Opus 4.7 (Adaptive)B · DeepSeek V4 Pro (Max)

  1. HLE

    Knowledge
    Source ↗
    A 54.7%B 37.7%
    Winner: Claude Opus 4.7 (Adaptive)Δ 17
    HLE: Claude Opus 4.7 (Adaptive) scored 54.7%; DeepSeek V4 Pro (Max) scored 37.7%. Claude Opus 4.7 (Adaptive) wins this benchmark.

  2. SWE-bench Pro

    Coding
    Source ↗
    A 64.3%B 55.4%
    Winner: Claude Opus 4.7 (Adaptive)Δ 8.9
    SWE-bench Pro: Claude Opus 4.7 (Adaptive) scored 64.3%; DeepSeek V4 Pro (Max) scored 55.4%. Claude Opus 4.7 (Adaptive) wins this benchmark.

  3. SWE-bench Verified

    Coding
    Source ↗
    A 87.6%B 80.6%
    Winner: Claude Opus 4.7 (Adaptive)Δ 7
    SWE-bench Verified: Claude Opus 4.7 (Adaptive) scored 87.6%; DeepSeek V4 Pro (Max) scored 80.6%. Claude Opus 4.7 (Adaptive) wins this benchmark.

  4. BrowseComp

    Agentic
    Source ↗
    A 79.3%B 83.4%
    Winner: DeepSeek V4 Pro (Max)Δ 4.1
    BrowseComp: Claude Opus 4.7 (Adaptive) scored 79.3%; DeepSeek V4 Pro (Max) scored 83.4%. DeepSeek V4 Pro (Max) wins this benchmark.

  5. GPQA

    Knowledge
    Source ↗
    A 94.2%B 90.1%
    Winner: Claude Opus 4.7 (Adaptive)Δ 4.1
    GPQA: Claude Opus 4.7 (Adaptive) scored 94.2%; DeepSeek V4 Pro (Max) scored 90.1%. 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)DeepSeek V4 Pro (Max)Comparison
Input / output priceUSD per 1M tokensClaude Opus 4.7 (Adaptive)$5 input / $25 outputDeepSeek V4 Pro (Max)$0.435 input / $0.87 outputDeepSeek V4 Pro (Max) has the lower combined listed price.
Generation speedtokens per secondClaude Opus 4.7 (Adaptive)Not availableDeepSeek V4 Pro (Max)Not availableA complete speed comparison is not available.
First-answer latencyseconds to first tokenClaude Opus 4.7 (Adaptive)Not availableDeepSeek V4 Pro (Max)Not availableA complete latency comparison is not available.
Context windowmaximum listed tokensClaude Opus 4.7 (Adaptive)1MDeepSeek V4 Pro (Max)1MListed context windows are equal.

Benchmark Deep Dive

AgenticClaude Opus 4.7 (Adaptive) wins
BenchmarkClaude Opus 4.7 (Adaptive)DeepSeek V4 Pro (Max)Result
Terminal-Bench 2.0Source 69.4%67.9%Claude Opus 4.7 (Adaptive) leads
BrowseCompSource 79.3%83.4%DeepSeek V4 Pro (Max) leads
MCP AtlasSource 77.3%73.6%Claude Opus 4.7 (Adaptive) leads
OSWorld-VerifiedSource 78%—Not comparable
CyberGymSource 73.1%—Not comparable
AA Agentic IndexSource 44.4%36.4%Claude Opus 4.7 (Adaptive) leads
τ²-bench resultsSource 88.6%96.2%DeepSeek V4 Pro (Max) leads
GDPval-AASource 49.8%40.4%Claude Opus 4.7 (Adaptive) leads
GDPval-AASource 14951307Claude Opus 4.7 (Adaptive) leads
OSWorld 2.0Source 18.2%—Not comparable
JobBenchSource 45.9%—Not comparable
AA ITBenchSource 46.7%38.3%Claude Opus 4.7 (Adaptive) leads
HLE w/ toolsSource —48.2%Not comparable
ToolathlonSource —51.8%Not comparable
APEX-Agents-AASource —24.3%Not comparable
AA BriefcaseSource —932Not comparable
AA EnterpriseOps-GymSource —40.4%Not comparable
AA Harvey LABSource —84.4%Not comparable
AA Tau3 BankingSource —25.8%Not comparable
terminalBenchHardSource —46.2%Not comparable
aaTerminalBench21Source —64%Not comparable
CodingClaude Opus 4.7 (Adaptive) wins
BenchmarkClaude Opus 4.7 (Adaptive)DeepSeek V4 Pro (Max)Result
SWE-bench VerifiedSource 87.6%80.6%Claude Opus 4.7 (Adaptive) leads
SWE-bench ProSource 64.3%55.4%Claude Opus 4.7 (Adaptive) leads
Terminal-Bench 2.0Source 69.4%67.9%Claude Opus 4.7 (Adaptive) leads
AA Coding IndexSource 73.6%59.4%Claude Opus 4.7 (Adaptive) leads
AA-SciCodeSource 54.5%50.0%Claude Opus 4.7 (Adaptive) leads
CodeforcesSource —3206.0Not comparable
SWE MultilingualSource —76.2%Not comparable
Vibe Code BenchSource —49.93%Not comparable
Reasoning
BenchmarkClaude Opus 4.7 (Adaptive)DeepSeek V4 Pro (Max)Result
MRCR v2 128K-256KSource 59.2%—Not comparable
ARC-AGI-2Source 75.8%—Not comparable
AA-LCRSource 70.3%66.3%Claude Opus 4.7 (Adaptive) leads
CritPtSource 12.0%12.9%DeepSeek V4 Pro (Max) leads
MRCR 1MSource —83.5%Not comparable
CorpusQA 1MSource —62.0%Not comparable
KnowledgeDeepSeek V4 Pro (Max) wins
BenchmarkClaude Opus 4.7 (Adaptive)DeepSeek V4 Pro (Max)Result
GPQASource 94.2%90.1%Claude Opus 4.7 (Adaptive) leads
GPQA-DSource 94.2%90.1%Claude Opus 4.7 (Adaptive) leads
HLESource 54.7%37.7%Claude Opus 4.7 (Adaptive) leads
HLE w/o toolsSource 46.9%—Not comparable
Artificial Analysis Intelligence IndexSource 53.5%44.3%Claude Opus 4.7 (Adaptive) leads
AA-GPQA DiamondSource 91.4%88.8%Claude Opus 4.7 (Adaptive) leads
AA-HLESource 39.6%35.9%Claude Opus 4.7 (Adaptive) leads
AA-Omniscience IndexSource 26.2%-10.0%Claude Opus 4.7 (Adaptive) leads
AA-Omniscience AccuracySource 45.8%43.3%Claude Opus 4.7 (Adaptive) leads
AA-Omniscience Hallucination RateSource 36.2%94.0%Claude Opus 4.7 (Adaptive) leads
MMLU-ProSource —87.5%Not comparable
SimpleQASource —57.9%Not comparable
Chinese-SimpleQASource —84.4%Not comparable
AA Openness IndexSource —50.0%Not comparable
Math
BenchmarkClaude Opus 4.7 (Adaptive)DeepSeek V4 Pro (Max)Result
FrontierMath (legacy)Source 43.8%—Not comparable
HMMT Feb 2026Source —95.2%Not comparable
IMOAnswerBenchSource —89.8%Not comparable
ApexSource —38.3%Not comparable
Apex ShortlistSource —90.2%Not comparable
Multimodal
BenchmarkClaude Opus 4.7 (Adaptive)DeepSeek V4 Pro (Max)Result
OfficeQA ProSource 43.6%—Not comparable
CharXivSource 91%—Not comparable
CharXiv w/o toolsSource 82.1%—Not comparable
AA-MMMU-ProSource 78.8%—Not comparable
Design Arena WebsiteSource 13251264Claude Opus 4.7 (Adaptive) leads
Inst. Following
BenchmarkClaude Opus 4.7 (Adaptive)DeepSeek V4 Pro (Max)Result
AA-IFBenchSource 58.6%76.5%DeepSeek V4 Pro (Max) leads
Frequently Asked Questions (4)

Which is better, Claude Opus 4.7 (Adaptive) or DeepSeek V4 Pro (Max)?

Claude Opus 4.7 (Adaptive) and DeepSeek V4 Pro (Max) are tied on the BenchAlign overall score, so the right pick depends on which category matters most for your use case.

Which is better for knowledge tasks, Claude Opus 4.7 (Adaptive) or DeepSeek V4 Pro (Max)?

DeepSeek V4 Pro (Max) has the edge for knowledge tasks in this comparison, averaging 60.1 versus 60. Inside this category, AA-Omniscience Hallucination Rate is the benchmark that creates the most daylight between them.

Which is better for coding, Claude Opus 4.7 (Adaptive) or DeepSeek V4 Pro (Max)?

Claude Opus 4.7 (Adaptive) has the edge for coding in this comparison, averaging 78.6 versus 70.9. Inside this category, AA Coding Index is the benchmark that creates the most daylight between them.

Which is better for agentic tasks, Claude Opus 4.7 (Adaptive) or DeepSeek V4 Pro (Max)?

Claude Opus 4.7 (Adaptive) has the edge for agentic tasks in this comparison, averaging 75.1 versus 74.5. Inside this category, GDPval-AA is the benchmark that creates the most daylight between them.

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