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Model comparison

Claude Opus 4.7 (Adaptive) vs o1-pro

Data verified

Head-to-head evidence from 2 shared benchmark results across 1 category. Overall scores shown here use the public BenchAlign v5 ranking lane.

66.27/100
Margin
20.3pts
← winning
OpenAI
45.94/100
0 category wins1 category wins

Public leaderboard positions: Claude Opus 4.7 (Adaptive) #27 (Estimated); o1-pro #141 (Estimated). Intervals and evidence labels describe ranking uncertainty, not a guarantee for a specific workload.

Evidence parity. Claude Opus 4.7 (Adaptive) and o1-pro share 2 comparable benchmark results. 1 of 8 categories are comparable. 36 results are unique to Claude Opus 4.7 (Adaptive); 0 to o1-pro.

Updated July 23, 2026
Shared results
2
Claude Opus 4.7 (Adaptive) only
36
o1-pro only
0
Comparable categories
1 / 8

Pick Claude Opus 4.7 (Adaptive) if you want the stronger benchmark profile. o1-pro only becomes the better choice if knowledge is the priority.

Confidence note. This is a partial-evidence comparison with 2 shared benchmark results across 1 evidence category; 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 Opus 4.7 (Adaptive) is clearly ahead on the BenchAlign aggregate, 66.27 to 45.94. The gap is large enough that you do not need to squint at the spreadsheet to see the difference.

o1-pro is also the more expensive model on tokens at $150.00 input / $600.00 output per 1M tokens, versus $5.00 input / $25.00 output per 1M tokens for Claude Opus 4.7 (Adaptive). That is roughly 24.0x on output cost alone. Claude Opus 4.7 (Adaptive) gives you the larger context window at 1M, compared with 200K for o1-pro.

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 o1-pro
CategoryClaude Opus 4.7 (Adaptive)Δo1-pro
KnowledgeClaude Opus 4.7 (Adaptive)60.0Margin 19.0o1-pro79.0
AgenticClaude Opus 4.7 (Adaptive)75.1MarginNo overlapo1-proNot measured
CodingClaude Opus 4.7 (Adaptive)78.6MarginNo overlapo1-proNot measured
ReasoningClaude Opus 4.7 (Adaptive)75.8MarginNo overlapo1-proNot measured
MultimodalClaude Opus 4.7 (Adaptive)65.1MarginNo overlapo1-proNot measured

Decisive benchmark drivers

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

More
A · Claude Opus 4.7 (Adaptive)B · o1-pro
  1. GPQA

    Knowledge
    Source ↗
    A 94.2%B 79%
    Winner: Claude Opus 4.7 (Adaptive)Δ 15.2
    GPQA: Claude Opus 4.7 (Adaptive) scored 94.2%; o1-pro scored 79%. 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)o1-proComparison
Input / output priceUSD per 1M tokensClaude Opus 4.7 (Adaptive)$5 input / $25 outputo1-pro$150 input / $600 outputClaude Opus 4.7 (Adaptive) has the lower combined listed price.
Generation speedtokens per secondClaude Opus 4.7 (Adaptive)Not availableo1-proNot availableA complete speed comparison is not available.
First-answer latencyseconds to first tokenClaude Opus 4.7 (Adaptive)Not availableo1-proNot availableA complete latency comparison is not available.
Context windowmaximum listed tokensClaude Opus 4.7 (Adaptive)1Mo1-pro200KClaude Opus 4.7 (Adaptive) lists the larger context window.

Benchmark Deep Dive

Agentic
BenchmarkClaude Opus 4.7 (Adaptive)o1-proResult
Terminal-Bench 2.0Source 69.4%Not comparable
BrowseCompSource 79.3%Not comparable
MCP AtlasSource 77.3%Not comparable
OSWorld-VerifiedSource 78%Not comparable
CyberGymSource 73.1%Not comparable
AA Agentic IndexSource 44.4%Not comparable
τ²-bench resultsSource 88.6%Not comparable
GDPval-AASource 49.8%Not comparable
GDPval-AASource 1495Not comparable
OSWorld 2.0Source 18.2%Not comparable
JobBenchSource 45.9%Not comparable
AA ITBenchSource 46.7%Not comparable
Coding
BenchmarkClaude Opus 4.7 (Adaptive)o1-proResult
SWE-bench VerifiedSource 87.6%Not comparable
SWE-bench ProSource 64.3%Not comparable
Terminal-Bench 2.0Source 69.4%Not comparable
AA Coding IndexSource 73.6%Not comparable
AA-SciCodeSource 54.5%Not comparable
Reasoning
BenchmarkClaude Opus 4.7 (Adaptive)o1-proResult
MRCR v2 128K-256KSource 59.2%Not comparable
ARC-AGI-2Source 75.8%Not comparable
AA-LCRSource 70.3%Not comparable
CritPtSource 12.0%Not comparable
Knowledgeo1-pro wins
BenchmarkClaude Opus 4.7 (Adaptive)o1-proResult
GPQASource 94.2%79%Claude Opus 4.7 (Adaptive) leads
GPQA-DSource 94.2%Not comparable
HLESource 54.7%Not comparable
HLE w/o toolsSource 46.9%Not comparable
Artificial Analysis Intelligence IndexSource 53.5%18.9%Claude Opus 4.7 (Adaptive) leads
AA-GPQA DiamondSource 91.4%Not comparable
AA-HLESource 39.6%Not comparable
AA-Omniscience IndexSource 26.2%Not comparable
AA-Omniscience AccuracySource 45.8%Not comparable
AA-Omniscience Hallucination RateSource 36.2%Not comparable
Math
BenchmarkClaude Opus 4.7 (Adaptive)o1-proResult
FrontierMath (legacy)Source 43.8%Not comparable
Multimodal
BenchmarkClaude Opus 4.7 (Adaptive)o1-proResult
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 1325Not comparable
Inst. Following
BenchmarkClaude Opus 4.7 (Adaptive)o1-proResult
AA-IFBenchSource 58.6%Not comparable
Frequently Asked Questions (2)

Which is better, Claude Opus 4.7 (Adaptive) or o1-pro?

Claude Opus 4.7 (Adaptive) is ahead on BenchLM's BenchAlign leaderboard, 66.27 to 45.94. The biggest single separator in this matchup is GPQA, where the scores are 94.2% and 79%.

Which is better for knowledge tasks, Claude Opus 4.7 (Adaptive) or o1-pro?

o1-pro has the edge for knowledge tasks in this comparison, averaging 79 versus 60. Inside this category, Artificial Analysis Intelligence Index is the benchmark that creates the most daylight between them.

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Last updated: July 23, 2026

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