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Model comparison

Claude Sonnet 5 vs GPT-5.6 Luna

Data verified

Head-to-head evidence from 23 shared benchmark results across 5 categories. Overall scores shown here use the public BenchAlign v5 ranking lane.

65.32/100
Margin
1.9pts
winning →
67.17/100
2 category wins2 category wins

Public leaderboard positions: Claude Sonnet 5 #29 (Estimated); GPT-5.6 Luna #22 (Estimated). Intervals and evidence labels describe ranking uncertainty, not a guarantee for a specific workload.

Evidence parity. Claude Sonnet 5 and GPT-5.6 Luna share 23 comparable benchmark results. 4 of 8 categories are comparable. 13 results are unique to Claude Sonnet 5; 18 to GPT-5.6 Luna.

Updated July 23, 2026
Shared results
23
Claude Sonnet 5 only
13
GPT-5.6 Luna only
18
Comparable categories
4 / 8

Pick GPT-5.6 Luna if you want the stronger benchmark profile. Claude Sonnet 5 only becomes the better choice if coding is the priority.

Confidence note. This is a partial-evidence comparison with 23 shared benchmark results across 5 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-5.6 Luna has the cleaner BenchAlign overall profile here, landing at 67.17 versus 65.32. It is a real lead, but still close enough that category-level strengths matter more than the headline number.

GPT-5.6 Luna's sharpest advantage is in knowledge, where it averages 92.3 against 57.4. The single biggest benchmark swing on the page is Terminal-Bench 2.0, 80.4% to 84.7%. Claude Sonnet 5 does hit back in coding, so the answer changes if that is the part of the workload you care about most.

Claude Sonnet 5 is also the more expensive model on tokens at $2.00 input / $10.00 output per 1M tokens, versus $1.00 input / $6.00 output per 1M tokens for GPT-5.6 Luna.

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 Sonnet 5 and GPT-5.6 Luna
CategoryClaude Sonnet 5ΔGPT-5.6 Luna
KnowledgeClaude Sonnet 557.4Margin→ 34.9GPT-5.6 Luna92.3
CodingClaude Sonnet 576.7Margin← 14.0GPT-5.6 Luna62.7
MultimodalClaude Sonnet 588.3Margin← 9.9GPT-5.6 Luna78.4
AgenticClaude Sonnet 581.9Margin→ 2.2GPT-5.6 Luna84.1
MathClaude Sonnet 5Not measuredMarginNo overlapGPT-5.6 Luna73.6

Decisive benchmark drivers

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

More
A · Claude Sonnet 5B · GPT-5.6 Luna

  1. Terminal-Bench 2.0

    Agentic
    Source ↗
    A 80.4%B 84.7%
    Winner: GPT-5.6 LunaΔ 4.3
    Terminal-Bench 2.0: Claude Sonnet 5 scored 80.4%; GPT-5.6 Luna scored 84.7%. GPT-5.6 Luna wins this benchmark.

  2. BrowseComp

    Agentic
    Source ↗
    A 84.7%B 83.3%
    Winner: Claude Sonnet 5Δ 1.4
    BrowseComp: Claude Sonnet 5 scored 84.7%; GPT-5.6 Luna scored 83.3%. Claude Sonnet 5 wins this benchmark.

  3. SWE-bench Pro

    Coding
    Source ↗
    A 63.2%B 62.7%
    Winner: Claude Sonnet 5Δ 0.5
    SWE-bench Pro: Claude Sonnet 5 scored 63.2%; GPT-5.6 Luna scored 62.7%. Claude Sonnet 5 wins this benchmark.

Operational comparison

Runtime and commercial metrics are compared only when both models have a complete sourced value.

MetricClaude Sonnet 5GPT-5.6 LunaComparison
Input / output priceUSD per 1M tokensClaude Sonnet 5$2 input / $10 outputGPT-5.6 Luna$1 input / $6 outputGPT-5.6 Luna has the lower combined listed price.
Generation speedtokens per secondClaude Sonnet 5Not availableGPT-5.6 LunaNot availableA complete speed comparison is not available.
First-answer latencyseconds to first tokenClaude Sonnet 5Not availableGPT-5.6 LunaNot availableA complete latency comparison is not available.
Context windowmaximum listed tokensClaude Sonnet 51MGPT-5.6 Luna1MListed context windows are equal.

Benchmark Deep Dive

AgenticGPT-5.6 Luna wins
BenchmarkClaude Sonnet 5GPT-5.6 LunaResult
Terminal-Bench 2.0Source 80.4%84.7%GPT-5.6 Luna leads
BrowseCompSource 84.7%83.3%Claude Sonnet 5 leads
HLE w/ toolsSource 57.4%—Not comparable
OSWorld-VerifiedSource 81.2%—Not comparable
GDPval-AASource 16071584Claude Sonnet 5 leads
AA Agentic IndexSource 46.7%45.6%Claude Sonnet 5 leads
GDPval-AASource 55.4%54.2%Claude Sonnet 5 leads
AA BriefcaseSource 1388—Not comparable
AA AutomationBenchSource 39.2%42.2%GPT-5.6 Luna leads
AA EnterpriseOps-GymSource 44.7%—Not comparable
AA Harvey LABSource 90.1%87.9%Claude Sonnet 5 leads
AA Tau3 BankingSource 28.2%27.2%Claude Sonnet 5 leads
aaTerminalBench21Source 80.5%80.9%GPT-5.6 Luna leads
OSWorld 2.0Source —45.6%Not comparable
CyberGymSource —77.9%Not comparable
ExploitGymSource —12.4%Not comparable
ToolathlonSource —53.4%Not comparable
AA ITBenchSource —40.3%Not comparable
APEX-Agents-AASource —35.8%Not comparable
CodingClaude Sonnet 5 wins
BenchmarkClaude Sonnet 5GPT-5.6 LunaResult
SWE-bench VerifiedSource 85.2%—Not comparable
SWE-bench ProSource 63.2%62.7%Claude Sonnet 5 leads
SWE MultilingualSource 78.3%—Not comparable
SWE MultimodalSource 28.1%—Not comparable
Terminal-Bench 2.0Source 80.4%84.7%GPT-5.6 Luna leads
FrontierCode 1.1 MainSource 42.7%—Not comparable
cursorBench32Source 61.5%61.1%Claude Sonnet 5 leads
AA Coding IndexSource 71.5%71.5%Claude Sonnet 5 leads
AA-SciCodeSource 53.6%52.5%Claude Sonnet 5 leads
deepSweSource —67.2%Not comparable
FrontierCode 1.1 ExtendedSource —55.1%Not comparable
Reasoning
BenchmarkClaude Sonnet 5GPT-5.6 LunaResult
AA-LCRSource 70.7%74.0%GPT-5.6 Luna leads
CritPtSource 16.9%20.6%GPT-5.6 Luna leads
ARC-AGI-3Source —0.2%Not comparable
KnowledgeGPT-5.6 Luna wins
BenchmarkClaude Sonnet 5GPT-5.6 LunaResult
HLESource 57.4%—Not comparable
HLE w/o toolsSource 43.2%—Not comparable
Artificial Analysis Intelligence IndexSource 53.4%51.2%Claude Sonnet 5 leads
AA-GPQA DiamondSource 91.1%91.1%Tie
AA-HLESource 39.6%37.2%Claude Sonnet 5 leads
AA-Omniscience IndexSource 15.3%-11.2%Claude Sonnet 5 leads
AA-Omniscience AccuracySource 38.3%41.5%GPT-5.6 Luna leads
AA-Omniscience Hallucination RateSource 37.3%90.1%Claude Sonnet 5 leads
GPQASource —92.3%Not comparable
GPQA-DSource —92.3%Not comparable
HealthBench ProfessionalSource —55.7%Not comparable
HealthBench HardSource —32.0%Not comparable
Math
BenchmarkClaude Sonnet 5GPT-5.6 LunaResult
FrontierMath (legacy)Source —78.6%Not comparable
FrontierMath v2 (Tiers 1-3)Source —78.600%Not comparable
FrontierMath v2 (Tier 4)Source —58.500%Not comparable
MultimodalClaude Sonnet 5 wins
BenchmarkClaude Sonnet 5GPT-5.6 LunaResult
CharXivSource 88.3%—Not comparable
CharXiv w/o toolsSource 77%—Not comparable
AA-MMMU-ProSource 77.3%78.6%GPT-5.6 Luna leads
Design Arena WebsiteSource 1314—Not comparable
MMMU-ProSource —78.4%Not comparable
MMMU-Pro w/ PythonSource —79.5%Not comparable
Frequently Asked Questions (5)

Which is better, Claude Sonnet 5 or GPT-5.6 Luna?

GPT-5.6 Luna is ahead on BenchLM's BenchAlign leaderboard, 67.17 to 65.32. The biggest single separator in this matchup is Terminal-Bench 2.0, where the scores are 80.4% and 84.7%.

Which is better for knowledge tasks, Claude Sonnet 5 or GPT-5.6 Luna?

GPT-5.6 Luna has the edge for knowledge tasks in this comparison, averaging 92.3 versus 57.4. Inside this category, AA-Omniscience Hallucination Rate is the benchmark that creates the most daylight between them.

Which is better for coding, Claude Sonnet 5 or GPT-5.6 Luna?

Claude Sonnet 5 has the edge for coding in this comparison, averaging 76.7 versus 62.7. Inside this category, Terminal-Bench 2.0 is the benchmark that creates the most daylight between them.

Which is better for agentic tasks, Claude Sonnet 5 or GPT-5.6 Luna?

GPT-5.6 Luna has the edge for agentic tasks in this comparison, averaging 84.1 versus 81.9. Inside this category, GDPval-AA is the benchmark that creates the most daylight between them.

Which is better for multimodal and grounded tasks, Claude Sonnet 5 or GPT-5.6 Luna?

Claude Sonnet 5 has the edge for multimodal and grounded tasks in this comparison, averaging 88.3 versus 78.4. Inside this category, AA-MMMU-Pro is the benchmark that creates the most daylight between them.

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