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Model comparison

Claude Opus 4.7 (Adaptive) vs GPT-5.2

Data verified

Head-to-head evidence from 20 shared benchmark results across 6 categories. Overall scores shown here use the public BenchAlign v5 ranking lane.

66.27/100
Margin
7.8pts
← winning
GPT-5.2
OpenAI
58.43/100
3 category wins2 category wins

Public leaderboard positions: Claude Opus 4.7 (Adaptive) #27 (Estimated); GPT-5.2 #64 (Estimated). Intervals and evidence labels describe ranking uncertainty, not a guarantee for a specific workload.

Evidence parity. Claude Opus 4.7 (Adaptive) and GPT-5.2 share 20 comparable benchmark results. 5 of 8 categories are comparable. 18 results are unique to Claude Opus 4.7 (Adaptive); 8 to GPT-5.2.

Updated July 23, 2026
Shared results
20
Claude Opus 4.7 (Adaptive) only
18
GPT-5.2 only
8
Comparable categories
5 / 8

Pick Claude Opus 4.7 (Adaptive) if you want the stronger benchmark profile. GPT-5.2 only becomes the better choice if knowledge is the priority or you want the cheaper token bill.

Confidence note. This is a partial-evidence comparison with 20 shared benchmark results across 6 evidence categories; 5 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 58.43. The gap is large enough that you do not need to squint at the spreadsheet to see the difference.

Claude Opus 4.7 (Adaptive)'s sharpest advantage is in reasoning, where it averages 75.8 against 52.9. The single biggest benchmark swing on the page is OSWorld-Verified, 78% to 47.3%. GPT-5.2 does hit back in knowledge, so the answer changes if that is the part of the workload you care about most.

Claude Opus 4.7 (Adaptive) is also the more expensive model on tokens at $5.00 input / $25.00 output per 1M tokens, versus $1.75 input / $14.00 output per 1M tokens for GPT-5.2. Claude Opus 4.7 (Adaptive) gives you the larger context window at 1M, compared with 400K for GPT-5.2.

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 4.7 (Adaptive) and GPT-5.2
CategoryClaude Opus 4.7 (Adaptive)ΔGPT-5.2
KnowledgeClaude Opus 4.7 (Adaptive)60.0Margin→ 32.4GPT-5.292.4
ReasoningClaude Opus 4.7 (Adaptive)75.8Margin← 22.9GPT-5.252.9
AgenticClaude Opus 4.7 (Adaptive)75.1Margin← 19.4GPT-5.255.7
MultimodalClaude Opus 4.7 (Adaptive)65.1Margin→ 15.3GPT-5.280.4
CodingClaude Opus 4.7 (Adaptive)78.6Margin← 8.0GPT-5.270.6
MathClaude Opus 4.7 (Adaptive)Not measuredMarginNo overlapGPT-5.235.2

Decisive benchmark drivers

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

More
A · Claude Opus 4.7 (Adaptive)B · GPT-5.2

  1. OSWorld-Verified

    Agentic
    Source ↗
    A 78%B 47.3%
    Winner: Claude Opus 4.7 (Adaptive)Δ 30.7
    OSWorld-Verified: Claude Opus 4.7 (Adaptive) scored 78%; GPT-5.2 scored 47.3%. Claude Opus 4.7 (Adaptive) wins this benchmark.

  2. ARC-AGI-2

    Reasoning
    Source ↗
    A 75.8%B 52.9%
    Winner: Claude Opus 4.7 (Adaptive)Δ 22.9
    ARC-AGI-2: Claude Opus 4.7 (Adaptive) scored 75.8%; GPT-5.2 scored 52.9%. Claude Opus 4.7 (Adaptive) wins this benchmark.

  3. BrowseComp

    Agentic
    Source ↗
    A 79.3%B 65.8%
    Winner: Claude Opus 4.7 (Adaptive)Δ 13.5
    BrowseComp: Claude Opus 4.7 (Adaptive) scored 79.3%; GPT-5.2 scored 65.8%. Claude Opus 4.7 (Adaptive) wins this benchmark.

  4. CharXiv

    Multimodal
    Source ↗
    A 91%B 82.1%
    Winner: Claude Opus 4.7 (Adaptive)Δ 8.9
    CharXiv: Claude Opus 4.7 (Adaptive) scored 91%; GPT-5.2 scored 82.1%. Claude Opus 4.7 (Adaptive) wins this benchmark.

  5. SWE-bench Pro

    Coding
    Source ↗
    A 64.3%B 55.6%
    Winner: Claude Opus 4.7 (Adaptive)Δ 8.7
    SWE-bench Pro: Claude Opus 4.7 (Adaptive) scored 64.3%; GPT-5.2 scored 55.6%. 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)GPT-5.2Comparison
Input / output priceUSD per 1M tokensClaude Opus 4.7 (Adaptive)$5 input / $25 outputGPT-5.2$1.75 input / $14 outputGPT-5.2 has the lower combined listed price.
Generation speedtokens per secondClaude Opus 4.7 (Adaptive)Not availableGPT-5.273 tok/sA complete speed comparison is not available.
First-answer latencyseconds to first tokenClaude Opus 4.7 (Adaptive)Not availableGPT-5.2130.34 sA complete latency comparison is not available.
Context windowmaximum listed tokensClaude Opus 4.7 (Adaptive)1MGPT-5.2400KClaude Opus 4.7 (Adaptive) lists the larger context window.

Benchmark Deep Dive

AgenticClaude Opus 4.7 (Adaptive) wins
BenchmarkClaude Opus 4.7 (Adaptive)GPT-5.2Result
Terminal-Bench 2.0Source 69.4%—Not comparable
BrowseCompSource 79.3%65.8%Claude Opus 4.7 (Adaptive) leads
MCP AtlasSource 77.3%—Not comparable
OSWorld-VerifiedSource 78%47.3%Claude Opus 4.7 (Adaptive) leads
CyberGymSource 73.1%—Not comparable
AA Agentic IndexSource 44.4%—Not comparable
τ²-bench resultsSource 88.6%84.8%Claude Opus 4.7 (Adaptive) leads
GDPval-AASource 49.8%—Not comparable
GDPval-AASource 1495—Not comparable
OSWorld 2.0Source 18.2%—Not comparable
JobBenchSource 45.9%34.3%Claude Opus 4.7 (Adaptive) leads
AA ITBenchSource 46.7%—Not comparable
Gert LabsSource —46.54%Not comparable
CodingClaude Opus 4.7 (Adaptive) wins
BenchmarkClaude Opus 4.7 (Adaptive)GPT-5.2Result
SWE-bench VerifiedSource 87.6%80%Claude Opus 4.7 (Adaptive) leads
SWE-bench ProSource 64.3%55.6%Claude Opus 4.7 (Adaptive) leads
Terminal-Bench 2.0Source 69.4%—Not comparable
AA Coding IndexSource 73.6%—Not comparable
AA-SciCodeSource 54.5%52.1%Claude Opus 4.7 (Adaptive) leads
Vibe Code BenchSource —53.50%Not comparable
ReasoningClaude Opus 4.7 (Adaptive) wins
BenchmarkClaude Opus 4.7 (Adaptive)GPT-5.2Result
MRCR v2 128K-256KSource 59.2%—Not comparable
ARC-AGI-2Source 75.8%52.9%Claude Opus 4.7 (Adaptive) leads
AA-LCRSource 70.3%72.7%GPT-5.2 leads
CritPtSource 12.0%11.6%Claude Opus 4.7 (Adaptive) leads
KnowledgeGPT-5.2 wins
BenchmarkClaude Opus 4.7 (Adaptive)GPT-5.2Result
GPQASource 94.2%92.4%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%42.2%Claude Opus 4.7 (Adaptive) leads
AA-GPQA DiamondSource 91.4%90.3%Claude Opus 4.7 (Adaptive) leads
AA-HLESource 39.6%35.4%Claude Opus 4.7 (Adaptive) leads
AA-Omniscience IndexSource 26.2%-1.0%Claude Opus 4.7 (Adaptive) leads
AA-Omniscience AccuracySource 45.8%43.8%Claude Opus 4.7 (Adaptive) leads
AA-Omniscience Hallucination RateSource 36.2%79.7%Claude Opus 4.7 (Adaptive) leads
Math
BenchmarkClaude Opus 4.7 (Adaptive)GPT-5.2Result
FrontierMath (legacy)Source 43.8%—Not comparable
AA AIME 2025Source —99.0%Not comparable
FrontierMath v2 (Tiers 1-3)Source —40.700%Not comparable
FrontierMath v2 (Tier 4)Source —18.800%Not comparable
MultimodalGPT-5.2 wins
BenchmarkClaude Opus 4.7 (Adaptive)GPT-5.2Result
OfficeQA ProSource 43.6%—Not comparable
CharXivSource 91%82.1%Claude Opus 4.7 (Adaptive) leads
CharXiv w/o toolsSource 82.1%—Not comparable
AA-MMMU-ProSource 78.8%—Not comparable
Design Arena WebsiteSource 13251224Claude Opus 4.7 (Adaptive) leads
MMMU-ProSource —79.5%Not comparable
MathVisionSource —83.0%Not comparable
V*Source —75.9%Not comparable
Inst. Following
BenchmarkClaude Opus 4.7 (Adaptive)GPT-5.2Result
AA-IFBenchSource 58.6%75.4%GPT-5.2 leads
Frequently Asked Questions (6)

Which is better, Claude Opus 4.7 (Adaptive) or GPT-5.2?

Claude Opus 4.7 (Adaptive) is ahead on BenchLM's BenchAlign leaderboard, 66.27 to 58.43. The biggest single separator in this matchup is OSWorld-Verified, where the scores are 78% and 47.3%.

Which is better for knowledge tasks, Claude Opus 4.7 (Adaptive) or GPT-5.2?

GPT-5.2 has the edge for knowledge tasks in this comparison, averaging 92.4 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 GPT-5.2?

Claude Opus 4.7 (Adaptive) has the edge for coding in this comparison, averaging 78.6 versus 70.6. Inside this category, SWE-bench Pro is the benchmark that creates the most daylight between them.

Which is better for reasoning, Claude Opus 4.7 (Adaptive) or GPT-5.2?

Claude Opus 4.7 (Adaptive) has the edge for reasoning in this comparison, averaging 75.8 versus 52.9. Inside this category, ARC-AGI-2 is the benchmark that creates the most daylight between them.

Which is better for agentic tasks, Claude Opus 4.7 (Adaptive) or GPT-5.2?

Claude Opus 4.7 (Adaptive) has the edge for agentic tasks in this comparison, averaging 75.1 versus 55.7. Inside this category, OSWorld-Verified is the benchmark that creates the most daylight between them.

Which is better for multimodal and grounded tasks, Claude Opus 4.7 (Adaptive) or GPT-5.2?

GPT-5.2 has the edge for multimodal and grounded tasks in this comparison, averaging 80.4 versus 65.1. Inside this category, Design Arena Website is the benchmark that creates the most daylight between them.

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