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Model comparison

Claude Opus 4.7 (Adaptive) vs GPT-5.4

Data verified

Head-to-head evidence from 30 shared benchmark results across 6 categories. Overall scores shown here use the public BenchAlign v5 ranking lane.

66.27/100
Margin
8.0pts
winning →
GPT-5.4
OpenAI
74.24/100
2 category wins2 category wins

Public leaderboard positions: Claude Opus 4.7 (Adaptive) #27 (Estimated); GPT-5.4 #8 (Supported). Intervals and evidence labels describe ranking uncertainty, not a guarantee for a specific workload.

Evidence parity. Claude Opus 4.7 (Adaptive) and GPT-5.4 share 30 comparable benchmark results. 4 of 8 categories are comparable. 8 results are unique to Claude Opus 4.7 (Adaptive); 22 to GPT-5.4.

Updated July 23, 2026
Shared results
30
Claude Opus 4.7 (Adaptive) only
8
GPT-5.4 only
22
Comparable categories
4 / 8

Pick GPT-5.4 if you want the stronger benchmark profile. Claude Opus 4.7 (Adaptive) only becomes the better choice if coding is the priority.

Confidence note. This is a partial-evidence comparison with 30 shared benchmark results across 6 evidence categories; 4 of 8 categories currently have scoreable aggregates for both models. Treat the verdict as directional until coverage is more balanced.

Why this result

GPT-5.4 is clearly ahead on the BenchAlign aggregate, 74.24 to 66.27. The gap is large enough that you do not need to squint at the spreadsheet to see the difference.

GPT-5.4's sharpest advantage is in multimodal & grounded, where it averages 73.2 against 65.1. The single biggest benchmark swing on the page is OfficeQA Pro, 43.6% to 53.2%. Claude Opus 4.7 (Adaptive) does hit back in coding, 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 $2.50 input / $15.00 output per 1M tokens for GPT-5.4. GPT-5.4 gives you the larger context window at 1.05M, compared with 1M for Claude Opus 4.7 (Adaptive).

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-5.4
CategoryClaude Opus 4.7 (Adaptive)ΔGPT-5.4
CodingClaude Opus 4.7 (Adaptive)78.6Margin← 20.9GPT-5.457.7
MultimodalClaude Opus 4.7 (Adaptive)65.1Margin→ 8.1GPT-5.473.2
KnowledgeClaude Opus 4.7 (Adaptive)60.0Margin← 2.4GPT-5.457.6
AgenticClaude Opus 4.7 (Adaptive)75.1Margin→ 2.1GPT-5.477.2
ReasoningClaude Opus 4.7 (Adaptive)75.8MarginNo overlapGPT-5.4Not measured
MathClaude Opus 4.7 (Adaptive)Not measuredMarginNo overlapGPT-5.442.5

Decisive benchmark drivers

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

More
A · Claude Opus 4.7 (Adaptive)B · GPT-5.4

  1. OfficeQA Pro

    Multimodal
    Source ↗
    A 43.6%B 53.2%
    Winner: GPT-5.4Δ 9.6
    OfficeQA Pro: Claude Opus 4.7 (Adaptive) scored 43.6%; GPT-5.4 scored 53.2%. GPT-5.4 wins this benchmark.

  2. CharXiv

    Multimodal
    Source ↗
    A 91%B 82.8%
    Winner: Claude Opus 4.7 (Adaptive)Δ 8.2
    CharXiv: Claude Opus 4.7 (Adaptive) scored 91%; GPT-5.4 scored 82.8%. Claude Opus 4.7 (Adaptive) wins this benchmark.

  3. SWE-bench Pro

    Coding
    Source ↗
    A 64.3%B 57.7%
    Winner: Claude Opus 4.7 (Adaptive)Δ 6.6
    SWE-bench Pro: Claude Opus 4.7 (Adaptive) scored 64.3%; GPT-5.4 scored 57.7%. Claude Opus 4.7 (Adaptive) wins this benchmark.

  4. Terminal-Bench 2.0

    Agentic
    Source ↗
    A 69.4%B 75.1%
    Winner: GPT-5.4Δ 5.7
    Terminal-Bench 2.0: Claude Opus 4.7 (Adaptive) scored 69.4%; GPT-5.4 scored 75.1%. GPT-5.4 wins this benchmark.

  5. BrowseComp

    Agentic
    Source ↗
    A 79.3%B 82.7%
    Winner: GPT-5.4Δ 3.4
    BrowseComp: Claude Opus 4.7 (Adaptive) scored 79.3%; GPT-5.4 scored 82.7%. GPT-5.4 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-5.4Comparison
Input / output priceUSD per 1M tokensClaude Opus 4.7 (Adaptive)$5 input / $25 outputGPT-5.4$2.5 input / $15 outputGPT-5.4 has the lower combined listed price.
Generation speedtokens per secondClaude Opus 4.7 (Adaptive)Not availableGPT-5.474 tok/sA complete speed comparison is not available.
First-answer latencyseconds to first tokenClaude Opus 4.7 (Adaptive)Not availableGPT-5.4151.79 sA complete latency comparison is not available.
Context windowmaximum listed tokensClaude Opus 4.7 (Adaptive)1MGPT-5.41.05MGPT-5.4 lists the larger context window.

Benchmark Deep Dive

AgenticGPT-5.4 wins
BenchmarkClaude Opus 4.7 (Adaptive)GPT-5.4Result
Terminal-Bench 2.0Source 69.4%75.1%GPT-5.4 leads
BrowseCompSource 79.3%82.7%GPT-5.4 leads
MCP AtlasSource 77.3%70.6%Claude Opus 4.7 (Adaptive) leads
OSWorld-VerifiedSource 78%75%Claude Opus 4.7 (Adaptive) leads
CyberGymSource 73.1%79.0%GPT-5.4 leads
AA Agentic IndexSource 44.4%41.1%Claude Opus 4.7 (Adaptive) leads
τ²-bench resultsSource 88.6%87.1%Claude Opus 4.7 (Adaptive) leads
GDPval-AASource 49.8%44.7%Claude Opus 4.7 (Adaptive) leads
GDPval-AASource 14951395Claude Opus 4.7 (Adaptive) leads
OSWorld 2.0Source 18.2%—Not comparable
JobBenchSource 45.9%38.9%Claude Opus 4.7 (Adaptive) leads
AA ITBenchSource 46.7%—Not comparable
ToolathlonSource —54.6%Not comparable
Claw-EvalSource —60.3%Not comparable
DeepSearchQASource —73.6%Not comparable
APEX-Agents-AASource —33.3%Not comparable
Gert LabsSource —64.89%Not comparable
ResearchClawBenchSource —15.3%Not comparable
ExploitGymSource —6.0%Not comparable
CodingClaude Opus 4.7 (Adaptive) wins
BenchmarkClaude Opus 4.7 (Adaptive)GPT-5.4Result
SWE-bench VerifiedSource 87.6%—Not comparable
SWE-bench ProSource 64.3%57.7%Claude Opus 4.7 (Adaptive) leads
Terminal-Bench 2.0Source 69.4%—Not comparable
AA Coding IndexSource 73.6%71.0%Claude Opus 4.7 (Adaptive) leads
AA-SciCodeSource 54.5%56.6%GPT-5.4 leads
LiveCodeBench ProSource —87.5%Not comparable
React Native EvalsSource —85.3%Not comparable
Vibe Code BenchSource —67.42%Not comparable
Reasoning
BenchmarkClaude Opus 4.7 (Adaptive)GPT-5.4Result
MRCR v2 128K-256KSource 59.2%—Not comparable
ARC-AGI-2Source 75.8%—Not comparable
AA-LCRSource 70.3%74.0%GPT-5.4 leads
CritPtSource 12.0%23.4%GPT-5.4 leads
KnowledgeClaude Opus 4.7 (Adaptive) wins
BenchmarkClaude Opus 4.7 (Adaptive)GPT-5.4Result
GPQASource 94.2%92.8%Claude Opus 4.7 (Adaptive) leads
GPQA-DSource 94.2%92.8%Claude Opus 4.7 (Adaptive) leads
HLESource 54.7%52.1%Claude Opus 4.7 (Adaptive) leads
HLE w/o toolsSource 46.9%39.8%Claude Opus 4.7 (Adaptive) leads
Artificial Analysis Intelligence IndexSource 53.5%51.4%Claude Opus 4.7 (Adaptive) leads
AA-GPQA DiamondSource 91.4%92.0%GPT-5.4 leads
AA-HLESource 39.6%41.6%GPT-5.4 leads
AA-Omniscience IndexSource 26.2%5.7%Claude Opus 4.7 (Adaptive) leads
AA-Omniscience AccuracySource 45.8%50.0%GPT-5.4 leads
AA-Omniscience Hallucination RateSource 36.2%88.6%Claude Opus 4.7 (Adaptive) leads
HealthBench HardSource —40.1%Not comparable
MedXpertQA (Text)Source —59.6%Not comparable
HealthBench ProfessionalSource —48.1%Not comparable
Math
BenchmarkClaude Opus 4.7 (Adaptive)GPT-5.4Result
FrontierMath (legacy)Source 43.8%—Not comparable
FrontierMath v2 (Tiers 1-3)Source —47.600%Not comparable
FrontierMath v2 (Tier 4)Source —27.100%Not comparable
MultimodalGPT-5.4 wins
BenchmarkClaude Opus 4.7 (Adaptive)GPT-5.4Result
OfficeQA ProSource 43.6%53.2%GPT-5.4 leads
CharXivSource 91%82.8%Claude Opus 4.7 (Adaptive) leads
CharXiv w/o toolsSource 82.1%—Not comparable
AA-MMMU-ProSource 78.8%78.4%Claude Opus 4.7 (Adaptive) leads
Design Arena WebsiteSource 13251250Claude Opus 4.7 (Adaptive) leads
MMMU-ProSource —81.2%Not comparable
MMMU-Pro w/ PythonSource —82.1%Not comparable
ERQASource —65.4%Not comparable
SimpleVQASource —61.1%Not comparable
ScreenSpot ProSource —85.4%Not comparable
ZeroBenchSource —41.0%Not comparable
MedXpertQA (MM)Source —77.1%Not comparable
Inst. Following
BenchmarkClaude Opus 4.7 (Adaptive)GPT-5.4Result
AA-IFBenchSource 58.6%73.9%GPT-5.4 leads
Frequently Asked Questions (5)

Which is better, Claude Opus 4.7 (Adaptive) or GPT-5.4?

GPT-5.4 is ahead on BenchLM's BenchAlign leaderboard, 74.24 to 66.27. The biggest single separator in this matchup is OfficeQA Pro, where the scores are 43.6% and 53.2%.

Which is better for knowledge tasks, Claude Opus 4.7 (Adaptive) or GPT-5.4?

Claude Opus 4.7 (Adaptive) has the edge for knowledge tasks in this comparison, averaging 60 versus 57.6. 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-5.4?

Claude Opus 4.7 (Adaptive) has the edge for coding in this comparison, averaging 78.6 versus 57.7. Inside this category, SWE-bench Pro is the benchmark that creates the most daylight between them.

Which is better for agentic tasks, Claude Opus 4.7 (Adaptive) or GPT-5.4?

GPT-5.4 has the edge for agentic tasks in this comparison, averaging 77.2 versus 75.1. Inside this category, GDPval-AA 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-5.4?

GPT-5.4 has the edge for multimodal and grounded tasks in this comparison, averaging 73.2 versus 65.1. Inside this category, Design Arena Website is the benchmark that creates the most daylight between them.

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