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Model comparison

Claude Opus 4.7 (Adaptive) vs GPT-5.5 Pro

Data verified

Head-to-head evidence from 5 shared benchmark results across 4 categories. Overall scores shown here use the public BenchAlign v5 ranking lane.

66.27/100
Margin
2.6pts
← winning
63.69/100
1 category wins1 category wins

Public leaderboard positions: Claude Opus 4.7 (Adaptive) #27 (Estimated); GPT-5.5 Pro #38 (Estimated). Intervals and evidence labels describe ranking uncertainty, not a guarantee for a specific workload.

Evidence parity. Claude Opus 4.7 (Adaptive) and GPT-5.5 Pro share 5 comparable benchmark results. 2 of 8 categories are comparable. 33 results are unique to Claude Opus 4.7 (Adaptive); 2 to GPT-5.5 Pro.

Updated July 23, 2026
Shared results
5
Claude Opus 4.7 (Adaptive) only
33
GPT-5.5 Pro only
2
Comparable categories
2 / 8

Pick Claude Opus 4.7 (Adaptive) if you want the stronger benchmark profile. GPT-5.5 Pro only becomes the better choice if agentic is the priority.

Confidence note. This is a partial-evidence comparison with 5 shared benchmark results across 4 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 4.7 (Adaptive) has the cleaner BenchAlign overall profile here, landing at 66.27 versus 63.69. It is a real lead, but still close enough that category-level strengths matter more than the headline number.

Claude Opus 4.7 (Adaptive)'s sharpest advantage is in knowledge, where it averages 60 against 57.2. The single biggest benchmark swing on the page is BrowseComp, 79.3% to 90.1%. GPT-5.5 Pro does hit back in agentic, so the answer changes if that is the part of the workload you care about most.

GPT-5.5 Pro is also the more expensive model on tokens at $30.00 input / $180.00 output per 1M tokens, versus $5.00 input / $25.00 output per 1M tokens for Claude Opus 4.7 (Adaptive). That is roughly 7.2x 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 GPT-5.5 Pro
CategoryClaude Opus 4.7 (Adaptive)ΔGPT-5.5 Pro
AgenticClaude Opus 4.7 (Adaptive)75.1Margin→ 15.0GPT-5.5 Pro90.1
KnowledgeClaude Opus 4.7 (Adaptive)60.0Margin← 2.8GPT-5.5 Pro57.2
CodingClaude Opus 4.7 (Adaptive)78.6MarginNo overlapGPT-5.5 ProNot measured
ReasoningClaude Opus 4.7 (Adaptive)75.8MarginNo overlapGPT-5.5 ProNot measured
MathClaude Opus 4.7 (Adaptive)Not measuredMarginNo overlapGPT-5.5 Pro48.1
MultimodalClaude Opus 4.7 (Adaptive)65.1MarginNo overlapGPT-5.5 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 · GPT-5.5 Pro

  1. BrowseComp

    Agentic
    Source ↗
    A 79.3%B 90.1%
    Winner: GPT-5.5 ProΔ 10.8
    BrowseComp: Claude Opus 4.7 (Adaptive) scored 79.3%; GPT-5.5 Pro scored 90.1%. GPT-5.5 Pro wins this benchmark.

  2. HLE

    Knowledge
    Source ↗
    A 54.7%B 57.2%
    Winner: GPT-5.5 ProΔ 2.5
    HLE: Claude Opus 4.7 (Adaptive) scored 54.7%; GPT-5.5 Pro scored 57.2%. GPT-5.5 Pro 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)GPT-5.5 ProComparison
Input / output priceUSD per 1M tokensClaude Opus 4.7 (Adaptive)$5 input / $25 outputGPT-5.5 Pro$30 input / $180 outputClaude Opus 4.7 (Adaptive) has the lower combined listed price.
Generation speedtokens per secondClaude Opus 4.7 (Adaptive)Not availableGPT-5.5 ProNot availableA complete speed comparison is not available.
First-answer latencyseconds to first tokenClaude Opus 4.7 (Adaptive)Not availableGPT-5.5 ProNot availableA complete latency comparison is not available.
Context windowmaximum listed tokensClaude Opus 4.7 (Adaptive)1MGPT-5.5 Pro1MListed context windows are equal.

Benchmark Deep Dive

AgenticGPT-5.5 Pro wins
BenchmarkClaude Opus 4.7 (Adaptive)GPT-5.5 ProResult
Terminal-Bench 2.0Source 69.4%—Not comparable
BrowseCompSource 79.3%90.1%GPT-5.5 Pro leads
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 1495—Not 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)GPT-5.5 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)GPT-5.5 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%30.6%GPT-5.5 Pro leads
KnowledgeClaude Opus 4.7 (Adaptive) wins
BenchmarkClaude Opus 4.7 (Adaptive)GPT-5.5 ProResult
GPQASource 94.2%—Not comparable
GPQA-DSource 94.2%—Not comparable
HLESource 54.7%57.2%GPT-5.5 Pro leads
HLE w/o toolsSource 46.9%43.1%Claude Opus 4.7 (Adaptive) leads
Artificial Analysis Intelligence IndexSource 53.5%—Not comparable
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)GPT-5.5 ProResult
FrontierMath (legacy)Source 43.8%52.4%GPT-5.5 Pro leads
FrontierMath v2 (Tiers 1-3)Source —51.000%Not comparable
FrontierMath v2 (Tier 4)Source —39.600%Not comparable
Multimodal
BenchmarkClaude Opus 4.7 (Adaptive)GPT-5.5 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 1325—Not comparable
Inst. Following
BenchmarkClaude Opus 4.7 (Adaptive)GPT-5.5 ProResult
AA-IFBenchSource 58.6%—Not comparable
Frequently Asked Questions (3)

Which is better, Claude Opus 4.7 (Adaptive) or GPT-5.5 Pro?

Claude Opus 4.7 (Adaptive) is ahead on BenchLM's BenchAlign leaderboard, 66.27 to 63.69. The biggest single separator in this matchup is BrowseComp, where the scores are 79.3% and 90.1%.

Which is better for knowledge tasks, Claude Opus 4.7 (Adaptive) or GPT-5.5 Pro?

Claude Opus 4.7 (Adaptive) has the edge for knowledge tasks in this comparison, averaging 60 versus 57.2. Inside this category, HLE w/o tools is the benchmark that creates the most daylight between them.

Which is better for agentic tasks, Claude Opus 4.7 (Adaptive) or GPT-5.5 Pro?

GPT-5.5 Pro has the edge for agentic tasks in this comparison, averaging 90.1 versus 75.1. Inside this category, BrowseComp is the benchmark that creates the most daylight between them.

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