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Claude Opus 4.6 vs GPT-6 Sol

Full profiles: Claude Opus 4.6 (Anthropic) and GPT-6 Sol (OpenAI): every benchmark, price and rank.

Updated · Data from 11 sources

As of 9 Nov 2026, Claude Opus 4.6 and GPT-6 Sol are neck and neck on quality (62.7 vs 62.9 on the BenchLeader Index, inside the ±4.0 margin), and GPT-6 Sol is 2.5× cheaper at $4.00 vs $10.00 per 1M tokens blended. Choose Claude Opus 4.6 for multimodal (67 vs 61) and human preference (70 vs 64) and fast first answers (1.1 s vs 72.1 s); choose GPT-6 Sol for maths (69 vs 64), coding (67 vs 63), and reasoning (66 vs 65), where it also streams 3×+ faster.

Key facts (as of 9 Nov 2026)

  • Claude Opus 4.6 scores 62.7 on the BenchLeader Index and GPT-6 Sol scores 62.9 (BenchLeader, 9 Nov 2026).
  • Claude Opus 4.6 costs $10.00 per 1M tokens blended (list price, 9 Nov 2026).
  • GPT-6 Sol costs $4.00 per 1M tokens blended (list price, 9 Nov 2026).
  • GPT-6 Sol streams 3×+ faster than Claude Opus 4.6 (Artificial Analysis, 7-day median, 9 Nov 2026).
  • Of the 19 benchmarks both models have, GPT-6 Sol leads 10 (BenchLeader, 9 Nov 2026).
  • On Arena WebDev, Claude Opus 4.6 is rated 1547 and GPT-6 Sol 1674 (LMArena, as published by 9 Nov 2026).
Claude Opus 4.6 benchmarks high Anthropic GPT-6 Sol benchmarks max OpenAIAdd a third model

Which to pick for…

The pick's numbers come first. Category scores on the BenchLeader scale (50 is the average model, 15 points one standard deviation). High confidence means a lead of half a standard deviation or more; under one point is called either.

Use casePickWhyConfidence
CodingGPT-6 Sol67 vs 63 category score; Arena WebDev 1674 vs 1547Medium
MathsGPT-6 Sol69 vs 64 category score; Arena Maths 1440 vs 1516Medium
ReasoningGPT-6 Sol66 vs 65 category score; ARC-AGI-2 89.6% vs 69.2%Medium
Images and other mediaClaude Opus 4.667 vs 61 category score; Arena Vision 1316 vs 1232Medium
Chat quality (human preference)Claude Opus 4.670 vs 64 on Arena votesMedium
Lowest costGPT-6 Sol$4.00 vs $10.00 per 1M blended; agentic coding session $0.160 vs $0.400–
Fastest first answerClaude Opus 4.61.1 s (Claude Opus 4.6 (high)) vs 72.1 s (GPT-6 Sol (max)) to the first answer token–
High volume on a budgetNeither flagshipA smaller model is usually the better fit: Cheapest good LLMs, Fastest LLMs–

Key differences

  • Claude Opus 4.6 (high) and GPT-6 Sol (max) are neck and neck on quality (62.7 vs 62.9, within the ±4.0 margin).
  • Claude Opus 4.6 (high) is stronger in human preference, multimodal.
  • GPT-6 Sol (max) is stronger in coding, maths, reasoning, agents & tools, knowledge, long context.
  • GPT-6 Sol (max) is 2.5× cheaper ($4.00 vs $10.00 per 1M blended).
  • GPT-6 Sol (max) streams 3.1× faster (121 vs 39 tokens per second).

At a glance

SpecClaude Opus 4.6GPT-6 Sol
DeveloperAnthropicOpenAI
Released5 Feb 202622 Sep 2026
Context window (tokens)1,000,0001,050,000
Compared atClaude Opus 4.6 (high)GPT-6 Sol (max)
Open weightsNoNo
Price in / out / cached input per 1M$5.00 / $25.00 / $0.500$2.00 / $10.00 / $0.200

Category by category

Category scores on the BenchLeader scale: 50 is the average evaluated model, 15 points is one standard deviation. A gap under one point is called level.

CategoryClaude Opus 4.6 (high)GPT-6 Sol (max)Leader
Reasoning65.166.2GPT-6 Sol
Coding62.666.5GPT-6 Sol
Agents & tools–59.6not comparable
Maths63.768.5GPT-6 Sol
Knowledge–61.5not comparable
Human preference69.964.2Claude Opus 4.6
Multimodal66.760.7Claude Opus 4.6
Long context–66.6not comparable

On one chart

Each domain on the index's own scale, where 50 is an average model. Click a domain to see the benchmarks behind it. Pick up to 5 models from the list.

2550 avg75ReasoningCodingMathsMultimodalHumanpreferenceClaude Opus 4.6, Reasoning: 65.1Claude Opus 4.6, Coding: 62.6Claude Opus 4.6, Maths: 63.7Claude Opus 4.6, Multimodal: 66.7Claude Opus 4.6, Human preference: 69.9GPT-6 Sol, Reasoning: 66.2GPT-6 Sol, Coding: 66.5GPT-6 Sol, Maths: 68.5GPT-6 Sol, Multimodal: 60.7GPT-6 Sol, Human preference: 64.2

Not drawn, measured for fewer than two of these models: Agents & tools, Knowledge, Instruction following, Long context.

ModelIndex

Where sources disagree

Across the 19 benchmarks both have, Claude Opus 4.6 leads 9, GPT-6 Sol leads 10. Every overall index that rates both puts Claude Opus 4.6 ahead.

Overall indexClaude Opus 4.6 (high)GPT-6 Sol (max)Leader
BenchLeader Index62.762.9neck and neck
Arena Text15031457Claude Opus 4.6

Each publisher runs its own tasks, harnesses and effort settings, so their overall verdicts can differ; BenchLeader reconciles them on one scale. † measured at another effort setting of the same model (the publisher did not test the one compared here).

Price, speed and latency

List prices blended at three input tokens per output token. Per-task prices use the token counts on the methodology page. Cost, tokens and time per benchmark task are measured: Artificial Analysis’ averages over its whole Intelligence Index run.

MeasureClaude Opus 4.6 (high)GPT-6 Sol (max)
Blended price per 1M tokens$10.00$4.00
Input / output per 1M$5.00 / $25.00$2.00 / $10.00
Cached input per 1M$0.500$0.200
Price per task: chat reply$0.0095$0.0038
Price per task: summarize a 30-page report$0.075$0.030
Price per task: code edit$0.068$0.027
Price per task: agentic coding session$0.400$0.160
Price per task: structured extraction$0.015$0.0060
Agentic coding session, input mostly cached$0.198$0.079
Cost per benchmark task (AA Index)–$2.47
Output tokens per task (AA Index)–54k
Of which reasoning–35k
Time per task (AA Index)–7 min
Output speed39 tok/s121 tok/s
Time to first answer1.1 s72.1 s
Time to a complete answer–130.2 s

Each model is compared at its best-ranked reasoning-effort setting. Claude Opus 4.6 (high) scores 62.7 and takes 1 s to its first answer token; Claude Opus 4.6 (thinking) scores 62.6 in 1 s, Claude Opus 4.6 scores 62.3 in 1 s. GPT-6 Sol (max) scores 62.9 and takes 72 s to its first answer token; GPT-6 Sol (xhigh) scores 58.6 in 24 s, GPT-6 Sol (high) scores 58.2 in 9 s. Higher effort means more thinking before the answer: better scores, longer waits and more tokens billed. How reasoning effort changes scores and cost.

Every benchmark

155 benchmarks, grouped by category; each name links to the board and its leaders. † measured at another effort setting of the same model, shown for reference and not counted as a win.

MetricPublisherClaude Opus 4.6 (high)GPT-6 Sol (max)
BenchLeader IndexBenchLeader62.762.9
Coding scoreBenchLeader62.666.5
Human preference scoreBenchLeader69.964.2
Maths scoreBenchLeader63.768.5
Multimodal scoreBenchLeader66.760.7
Reasoning scoreBenchLeader65.166.2
Agents & tools scoreBenchLeader–59.6
Knowledge scoreBenchLeader–61.5
Long context scoreBenchLeader–66.6
Blended price $/MBenchLeader$10.00$4.00
Output speedBenchLeader39 tok/s121 tok/s
Time to first answerBenchLeader1.1 s72.1 s
Context windowBenchLeader1,000,000 tokens1,050,000 tokens
Reasoning
GPQA DiamondEpoch AI Benchmarking Hub90.5%†94.3%
Humanity's Last ExamScale AI / CAIS19.0%†–
SimpleBenchSimpleBench67.6%†–
Arena Hard PromptsArena (LMArena)15301483
LiveBench 1.0 ReasoningLiveBench88.7%88.7%
GPQA Diamond (AA)Artificial Analysis84.0%†–
Humanity's Last Exam (AA)Artificial Analysis19.1%†47.9%
HLE-Diamond (AA)Artificial Analysis–45.2%
GPQA Diamond (Vals)Vals AI89.7%†–
Kagi LLM BenchmarkKagi LLM Benchmark72.4%†–
ARC-AGI-1ARC Prize94.0%95.5%
ARC-AGI-2ARC Prize69.2%89.6%
ARC-AGI-3ARC Prize0.5%†23.0%
CritPtArtificial Analysis2.8%†30.9%
CritPt v2 hard subset (AA)Artificial Analysis–66.5%
MysteryMechanismVals AI–30.2%
Chess PuzzlesEpoch AI Benchmarking Hub21.0%†56.0%
Mystery Game PuzzlesEpoch AI Benchmarking Hub15.0%†56.0%
CL-benchEpoch AI Benchmarking Hub20.7%†–
CL-bench LifeEpoch AI Benchmarking Hub17.0%–
LMCAEpoch AI Benchmarking Hub55.8%†59.1%
DTBenchEpoch AI Benchmarking Hub91.2%†97.3%
ForecastBenchForecastBench63.4%†–
Coding
SWE-bench Verified (Epoch)Epoch AI Benchmarking Hub78.7%†–
SciCodeSciCode–57.6%
Show all 155 benchmarks
MetricPublisherClaude Opus 4.6 (high)GPT-6 Sol (max)
Coding
WeirdMLWeirdML78.0%–
FrontierCodeCognition26.6%†49.3%
GSO-BenchGSO-Bench41.2%–
Arena CodingArena (LMArena)15471520
Arena WebDevArena (LMArena)15471674
LiveBench 1.0 CodingLiveBench78.2%81.8%
LiveCodeBenchVals AI84.7%†–
IOIVals AI–82.6%
SWE-bench (Vals)Vals AI78.2%†–
SWE-Bench ProScale AI SEAL51.9%†–
SWE-bench Verified (bash only)SWE-bench75.6%†–
SWE-bench Verified (any scaffold)SWE-bench75.6%†–
Code MigrationVals AI–57.2%
ProgramBenchVals AI–2.0%
Vibe Code Bench v1.1Vals AI57.6%†87.8%
SWE-Bench Pro (private)Scale AI SEAL51.9%†–
SWE Atlas: Codebase QnAScale AI SEAL33.3%†–
SWE Atlas: RefactoringScale AI SEAL35.6%†–
SWE Atlas: Test WritingScale AI SEAL36.7%†–
ALE-BenchEpoch AI Benchmarking Hub996.5†2462
AlgoTuneAlgoTune1.5–
Terminal-Bench 4.0 (AA)Artificial Analysis–43.9%
GameBench 2 OverallDuelLab GameBench 2–72.9†
GameBench 2 by reasoning settingDuelLab GameBench 2–79.3†
Design Arena WebsiteDesign Arena1287†1285†
FrontierCode 2.0 (AA)Artificial Analysis–35.6%
Agents & tools
Terminal-BenchTerminal-Bench79.8%†50.3%
CybenchCybench93.0%†–
Remote Labor IndexScale AI / CAIS4.2%†–
APEX-AgentsMercor46.3%†54.3%
Arena AgentArena (LMArena)–7
LiveBench Agentic CodingLiveBench49.0%52.9%
Terminal-Bench HardArtificial Analysis48.5%†–
τ²-Bench Telecom (AA)Artificial Analysis84.8%†–
Terminal-Bench 2.1 (Vals)Vals AI–83.2%
MCP AtlasScale AI SEAL76.8%†–
HiL-BenchScale AI SEAL38.3%†–
τ³-bench Bankingτ²-bench27.3%†–
ITBench SRE (AA)Artificial Analysis–49.4%
APEX-Agents (AA)Artificial Analysis33.0%†–
CyberBenchVals AI–78.0%
Finance Agent v2Vals AI–49.0%
Harvey's Legal Agent Benchmark v1Vals AI–1.7%
Legal Research BenchVals AI–28.9%
SREBenchVals AI–30.5%
Tax Agent BenchVals AI–15.0%
Terminal-Bench 2.0 (Vals)Vals AI58.4%†–
Terminal-Bench 4.0 (Vals)Vals AI–44.4%
Terminal-Bench ScienceVals AI–30.0%
Arena SearchArena (LMArena)1222†1229
DeepResearch BenchDeepResearch Bench55.3%–
METR Time HorizonsMETR78.9%†–
GBAEvalEpoch AI Benchmarking Hub44.1%†–
Vending-Bench 2Andon Labs8017.6†14427.9†
AutomationBenchArtificial Analysis–61.6%
GDP.pdf (AA)Artificial Analysis–25.2%
Harvey LAB-AA v1.1Harvey–3.6%
AA-Briefcase v1.1Artificial Analysis–1476
Design Arena AgenticDesign Arena1192†1212†
Terminal-Bench-Science 0.1 (AA)Artificial Analysis–30.0%
CWE-Bench (AA)Artificial Analysis–64.2%
DeepSec-Bench (AA)Artificial Analysis–46.3%
CyberGym end-to-end (AA)Artificial Analysis–0.0%
Maths
FrontierMath Tiers 1–3Epoch AI Benchmarking Hub66.0%†89.8%
FrontierMath Tier 4Epoch AI Benchmarking Hub26.8%†90.0%
OTIS Mock AIMEEpoch AI Benchmarking Hub94.4%†100.0%
ProofBenchVals AI50.0%†83.0%†
LiveBench MathematicsLiveBench89.3%96.4%
AIME (Vals)Vals AI95.6%†–
AIME 2026MathArena96.7%–
HMMT February 2026MathArena96.2%–
USAMO 2026MathArena47.0%–
MathArena ApexMathArena34.5%–
Arena MathsArena (LMArena)15161440
Knowledge
SimpleQA VerifiedEpoch AI Benchmarking Hub47.0%†60.7%
LiveBench 1.0 Data AnalysisLiveBench69.9%81.2%
AA-Omniscience v1.1Artificial Analysis–21.4
MMLU-ProVals AI89.1%†–
LegalBenchVals AI85.3%†–
CorpFinVals AI67.0%†–
TaxEvalVals AI76.0%†–
MedQAVals AI95.4%†–
PRBench FinanceScale AI SEAL53.3%†–
PRBench LegalScale AI SEAL52.3%†38.6%†
MultiNRCScale AI SEAL48.3%†–
BioMysteryBenchVals AI–74.8%
CaseLaw v2Vals AI62.1%†–
Excel Modeling BenchmarkVals AI–71.5%
MedCodeVals AI48.2%†47.1%
MedScribeVals AI86.7%†82.0%
Public Benefits Bench v1.1Vals AI–56.6%
DrugDiscoveryBenchScale AI SEAL27.7%†–
EBR-benchEpoch AI Benchmarking Hub12.7%†53.3%
GDP.pdfEpoch AI Benchmarking Hub–26.4%
AA-Omniscience v1.1: accuracyArtificial Analysis–51.1%
AA-Omniscience v1.1: non-hallucinationArtificial Analysis–39.1%
Global-MMLU-Lite (AA)Artificial Analysis92.2%†–
HealthBench Professional (AA)OpenAI–62.3%
Instruction following
LiveBench LanguageLiveBench83.3%85.3%
LiveBench Instruction FollowingLiveBench63.3%68.6%
IFBenchArtificial Analysis44.6%†–
MultiChallengeScale AI SEAL56.0%†–
TutorBenchScale AI SEAL53.5%†–
Arena Instruction FollowingArena (LMArena)15111448
Human preference
Arena TextArena (LMArena)15031457
EQ-Bench 4EQ-Bench1210†–
Arena Creative WritingArena (LMArena)14981430
Arena Multi-turnArena (LMArena)15171466
Arena Longer QueriesArena (LMArena)15221466
Multimodal
Arena VisionArena (LMArena)13161232
MMMU-ProArtificial Analysis72.5%†83.0%
VISTAScale AI SEAL45.5%†–
MMMU-Pro (Vals)Vals AI83.9%†–
MortgageTaxVals AI68.5%†–
VTBScale AI SEAL27.5%†–
Blueprint-Bench 2Epoch AI Benchmarking Hub–36.9%†
AA-3DArtificial Analysis–1131
Long context
AA-LCR v1.1Artificial Analysis67.0%†83.7%
Arena DocumentArena (LMArena)1497–
MLCRArtificial Analysis–33.9%
Composite
Epoch Capabilities IndexEpoch AI Benchmarking Hub156.3†164.1†
LiveBench 1.0LiveBench74.5%79.3%
AA Intelligence Index v5.0Artificial Analysis–44.2
AA Intelligence Index v4.3.2Artificial Analysis26.4†47.6
AA Progress Index v1Artificial Analysis274.5†334
Vals RSI IndexVals AI–28.1%
Vals Science IndexVals AI–45.0%
AA Cyber IndexArtificial Analysis–36.8
Safety & honesty
FORTRESSScale AI SEAL20.5%†13.5%†
MASKScale AI SEAL96.3%†–

Data as of 2026-11-09. Best configuration of each model; every score links to its source on the model pages.

DuelLab GameBench 2, release gb2-20261103-eaea31df94e6 (https://benchmarks.duellab.org/releases/gb2-20261103-eaea31df94e6/), CC BY 4.0 (https://creativecommons.org/licenses/by/4.0/). Scores mapped to BenchLeader model names; not endorsed by DuelLab.

What changed

  • GPT-6 Sol (max): BenchLeader Index 63.5 → 62.9.
  • GPT-6 Sol (max): 2 score revisions.
  • GPT-6 Sol (max): 1 score revision.
  • GPT-6 Sol (max): 1 score revision.
  • GPT-6 Sol (max): 6 new results (AA Intelligence Index v5.0, AA-Omniscience v1.1, CritPt v2 hard subset (AA)…).
  • GPT-6 Sol (max): 1 score revision.
  • GPT-6 Sol (max): 1 score revision.
  • GPT-6 Sol (max): BenchLeader Index 64.1 → 63.5.
  • GPT-6 Sol (max): 2 new results (AA Progress Index v1, HLE-Diamond (AA)).
  • GPT-6 Sol (max): 1 score revision.

Rankings: Best LLM overall · Best LLM for agents · Best cheap LLMs

Claude Opus 4.6 vs GPT-6 Sol: questions

Is Claude Opus 4.6 better than GPT-6 Sol?
Claude Opus 4.6 (high) and GPT-6 Sol (max) are neck and neck on quality (62.7 vs 62.9, within the ±4.0 margin). The BenchLeader Index combines every independent quality benchmark; the two are within the margin of error as of 9 Nov 2026, so check the category scores for your use.
Claude Opus 4.6 vs GPT-6 Sol: which is cheaper, and will that change?
GPT-6 Sol is cheaper today: $4.00 against $10.00 per million tokens, blended at three input tokens per output token. No price change has been announced for either.
Is Claude Opus 4.6 or GPT-6 Sol better for coding?
GPT-6 Sol scores higher in coding (67 vs 63 on the category index, where 50 is average). On Arena WebDev, the top shared coding benchmark, it is 1547 for Claude Opus 4.6 against 1674 for GPT-6 Sol.
Which is faster, Claude Opus 4.6 or GPT-6 Sol?
GPT-6 Sol streams 3×+ faster (121 vs 39 output tokens per second, Artificial Analysis 7-day median).
Which is better for long documents?
Both take about 1.1M tokens: Claude Opus 4.6 1,000,000, GPT-6 Sol 1,050,000.
More questions (3)
Which has lower latency?
Claude Opus 4.6 answers first: 1.1 s against 72.1 s to the first answer token, as Artificial Analysis measures it. Reasoning effort drives most of this: a higher setting thinks longer before it answers.
Do independent benchmarks agree on Claude Opus 4.6 vs GPT-6 Sol?
Across the 19 benchmarks both have, Claude Opus 4.6 leads 9, GPT-6 Sol leads 10. Every overall index that rates both puts Claude Opus 4.6 ahead.
When was GPT-6 Sol released?
GPT-6 Sol was released on 22 Sep 2026.