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Claude Opus 5.5 vs GPT-6 Astra

Full profiles: Claude Opus 5.5 (Anthropic) and GPT-6 Astra (OpenAI): every benchmark, price and rank.

Updated · Data from 15 sources

As of 9 Nov 2026, Claude Opus 5.5 and GPT-6 Astra are neck and neck on quality (68.9 vs 68.1 on the BenchLeader Index, inside the ±8.1 margin), and Claude Opus 5.5 is 2.5× cheaper at $8.00 vs $20.00 per 1M tokens blended. Choose Claude Opus 5.5 for knowledge (74 vs 56), where it also streams ~2× faster; choose GPT-6 Astra for fast first answers (4.8 s vs 380.6 s) and reasoning (86 vs 72), agents & tools (69 vs 63), and maths (78 vs 74).

Key facts (as of 9 Nov 2026)

  • Claude Opus 5.5 scores 68.9 on the BenchLeader Index and GPT-6 Astra scores 68.1 (BenchLeader, 9 Nov 2026).
  • Claude Opus 5.5 costs $8.00 per 1M tokens blended (list price, 9 Nov 2026).
  • GPT-6 Astra costs $20.00 per 1M tokens blended (list price, 9 Nov 2026).
  • Claude Opus 5.5 streams ~2× faster than GPT-6 Astra (Artificial Analysis, 7-day median, 9 Nov 2026).
  • Of the 5 benchmarks both models have, Claude Opus 5.5 leads 4 (BenchLeader, 9 Nov 2026).
Claude Opus 5.5 benchmarks max Anthropic GPT-6 Astra benchmarks 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 Astra83 vs 80 category scoreMedium
Agents & tool useGPT-6 Astra69 vs 63 category score; APEX-Agents 64.7% vs 73.5%Medium
MathsGPT-6 Astra78 vs 74 category score; ProofBench 99.0% vs 100.0%Medium
ReasoningGPT-6 Astra86 vs 72 category score; LMCA 64.1% vs 68.2%High
KnowledgeClaude Opus 5.574 vs 56 category scoreHigh
Lowest costClaude Opus 5.5$8.00 vs $20.00 per 1M blended; agentic coding session $0.320 vs $0.800–
Fastest first answerGPT-6 Astra4.8 s (GPT-6 Astra) vs 380.6 s (Claude Opus 5.5 (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 5.5 (max) and GPT-6 Astra are neck and neck on quality (68.9 vs 68.1, within the ±8.1 margin).
  • Claude Opus 5.5 (max) is stronger in knowledge, long context, multimodal.
  • GPT-6 Astra is stronger in agents & tools, coding, maths, reasoning, composite.
  • Claude Opus 5.5 (max) is 2.5× cheaper ($8.00 vs $20.00 per 1M blended).
  • Claude Opus 5.5 (max) streams 4.2× faster (115 vs 27 tokens per second).

At a glance

SpecClaude Opus 5.5GPT-6 Astra
DeveloperAnthropicOpenAI
Released22 Sep 20262 Sep 2026
Context window (tokens)1,000,0001,050,000
Max output (tokens)128,000 (up to 300K on the Message Batches API (beta))–
Input typestext, image–
Reasoning effort settingslow, medium, high, xhigh, max–
Compared atClaude Opus 5.5 (max)GPT-6 Astra
Open weightsNoNo
Price in / out / cached input per 1M$4.00 / $20.00 / $0.200$10.00 / $50.00 / $1.00
API model IDclaude-opus-5-5–
Where to use itClaude API, Amazon Bedrock, Google Cloud, Microsoft Foundry–

Limits, availability and announced prices from the vendors' own pages: platform.claude.com (checked 20 Oct 2026). Everything else is from the day's data.

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 5.5 (max)GPT-6 AstraLeader
Reasoning72.385.6GPT-6 Astra
Coding80.483.2GPT-6 Astra
Agents & tools62.769.2GPT-6 Astra
Maths74.077.9GPT-6 Astra
Knowledge73.756.1Claude Opus 5.5
Multimodal70.3–not comparable
Long context67.1–not comparable
Composite–72.6not 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 avg75ReasoningCodingAgents & toolsMathsKnowledgeClaude Opus 5.5, Reasoning: 72.3Claude Opus 5.5, Coding: 80.4Claude Opus 5.5, Agents & tools: 62.7Claude Opus 5.5, Maths: 74.0Claude Opus 5.5, Knowledge: 73.7GPT-6 Astra, Reasoning: 85.6GPT-6 Astra, Coding: 83.2GPT-6 Astra, Agents & tools: 69.2GPT-6 Astra, Maths: 77.9GPT-6 Astra, Knowledge: 56.1

Not drawn, measured for fewer than two of these models: Instruction following, Long context, Multimodal, Human preference.

ModelIndex

Where sources disagree

Across the 5 benchmarks both have, Claude Opus 5.5 leads 4, GPT-6 Astra leads 1. Every overall index that rates both puts Claude Opus 5.5 ahead.

Overall indexClaude Opus 5.5 (max)GPT-6 AstraLeader
BenchLeader Index68.968.1neck and neck
AA Intelligence Index v5.059.143.3†Claude Opus 5.5
Vals Index70.1†65.0Claude Opus 5.5
Arena Text1506†1475Claude Opus 5.5

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 5.5 (max)GPT-6 Astra
Blended price per 1M tokens$8.00$20.00
Input / output per 1M$4.00 / $20.00$10.00 / $50.00
Cached input per 1M$0.200$1.00
Price per task: chat reply$0.0076$0.019
Price per task: summarize a 30-page report$0.060$0.150
Price per task: code edit$0.054$0.135
Price per task: agentic coding session$0.320$0.800
Price per task: structured extraction$0.012$0.030
Agentic coding session, input mostly cached$0.149$0.395
Cost per benchmark task (AA Index)$10.04–
Output tokens per task (AA Index)173k–
Of which reasoning120k–
Time per task (AA Index)25 min–
Output speed115 tok/s27 tok/s
Time to first answer380.6 s4.8 s
Time to a complete answer771.1 s–

Each model is compared at its best-ranked reasoning-effort setting. Claude Opus 5.5 (max) scores 68.9 and takes 381 s to its first answer token; Claude Opus 5.5 (xhigh) scores 65.5 in 84 s, Claude Opus 5.5 (high) scores 65.4 in 28 s. GPT-6 Astra scores 68.1 and takes 5 s to its first answer token; GPT-6 Astra (max) scores 67.4 in 232 s, GPT-6 Astra (high) scores 66.5 in 64 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

149 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 5.5 (max)GPT-6 Astra
BenchLeader IndexBenchLeader68.968.1
Agents & tools scoreBenchLeader62.769.2
Coding scoreBenchLeader80.483.2
Knowledge scoreBenchLeader73.756.1
Long context scoreBenchLeader67.1–
Maths scoreBenchLeader74.077.9
Multimodal scoreBenchLeader70.3–
Reasoning scoreBenchLeader72.385.6
Composite scoreBenchLeader–72.6
Blended price $/MBenchLeader$8.00$20.00
Output speedBenchLeader115 tok/s27 tok/s
Time to first answerBenchLeader380.6 s4.8 s
Context windowBenchLeader1,000,000 tokens1,050,000 tokens
Reasoning
GPQA DiamondEpoch AI Benchmarking Hub90.6%95.8%†
Humanity's Last ExamScale AI / CAIS–54.8%
Arena Hard PromptsArena (LMArena)1530†1500†
LiveBench 2.0 ReasoningLiveBench92.2%†92.7%
LiveBench 1.0 ReasoningLiveBench92.2%92.7%†
GPQA Diamond (AA)Artificial Analysis–96.1%†
Humanity's Last Exam (AA)Artificial Analysis61.4%54.7%†
HLE-Diamond (AA)Artificial Analysis67.9%63.8%†
ARC-AGI-1ARC Prize97.5%97.5%†
ARC-AGI-2ARC Prize91.7%95.0%†
ARC-AGI-3ARC Prize–98.6%†
CritPtArtificial Analysis31.7%31.7%†
CritPt v2 hard subset (AA)Artificial Analysis68.0%70.5%†
MysteryMechanismVals AI49.5%†53.1%†
Chess PuzzlesEpoch AI Benchmarking Hub67.0%74.0%†
Mystery Game PuzzlesEpoch AI Benchmarking Hub71.0%84.0%†
LMCAEpoch AI Benchmarking Hub68.2%64.1%
DTBenchEpoch AI Benchmarking Hub98.9%97.1%
BTF-3Epoch AI Benchmarking Hub–13.5%†
Coding
SciCodeSciCode66.9%56.5%†
WeirdMLWeirdML–93.3%†
FrontierCodeCognition54.6%†53.3%†
GSO-BenchGSO-Bench–79.4%
Arena CodingArena (LMArena)1546†1548†
Arena WebDevArena (LMArena)18181767†
Show all 149 benchmarks
MetricPublisherClaude Opus 5.5 (max)GPT-6 Astra
Coding
LiveBench 2.0 CodingLiveBench87.1%†87.5%
LiveBench 1.0 CodingLiveBench89.3%80.4%†
IOIVals AI95.1%†100.0%†
Code MigrationVals AI66.7%†67.7%†
Code Migration v1.1Vals AI81.0%†80.6%†
ProgramBenchVals AI18.5%†5.5%†
SWE-bench MultimodalVals AI70.2%†43.3%†
Vibe Code Bench 1-100Vals AI30.4%†27.6%†
Vibe Code Bench v1.1Vals AI90.3%†89.6%†
SWE Atlas: Codebase QnAScale AI SEAL–59.1%†
SWE Atlas: RefactoringScale AI SEAL–59.0%†
SWE Atlas: Test WritingScale AI SEAL–50.7%†
MirrorCodeEpoch AI Benchmarking Hub78.9%†46.7%†
DeepSWE v1.1Epoch AI Benchmarking Hub–73.2%†
CursorBenchCursor57.8%–
ALE-BenchEpoch AI Benchmarking Hub2147.4†2951.3†
FrontierSWEEpoch AI Benchmarking Hub62.3%65.5%†
Terminal-Bench 4.0 (AA)Artificial Analysis59.6%59.1%†
Terminal-Bench 2.1 (AA)Artificial Analysis–88.4%†
Startrise FrontendStartrise71.1%†79.9%
GameBench 2 OverallDuelLab GameBench 287.6†88.7
GameBench 2 by reasoning settingDuelLab GameBench 294.8†94.0†
Design Arena WebsiteDesign Arena1325†1333†
FrontierCode 1.1 (AA)Artificial Analysis52.2%47.0%†
FrontierCode 2.0 (AA)Artificial Analysis46.4%42.4%†
Agents & tools
Terminal-BenchTerminal-Bench65.8%60.3%†
Remote Labor IndexScale AI / CAIS21.3%†20.8%
APEX-AgentsMercor73.5%64.7%
Arena AgentArena (LMArena)2014.2†
LiveBench Long AgenticLiveBench72.8%†75.6%
LiveBench BrowserLiveBench88.4%†91.3%
LiveBench Agentic CodingLiveBench71.7%57.3%†
Terminal-Bench 2.1 (Vals)Vals AI87.6%†87.3%†
MCP AtlasScale AI SEAL85.4%†–
HiL-BenchScale AI SEAL59.0%†65.3%
GDPval-AA v2.1, normalised scoreArtificial Analysis68.3%53.7%†
GDPval-AA v2.1Artificial Analysis18661584†
τ³-Banking (AA)Artificial Analysis–41.4%†
ITBench SRE (AA)Artificial Analysis38.2%48.6%†
Analyst Agent (AA)Artificial Analysis56.3%51.3%†
CUA-benchVals AI14.0%19.2%†
CyberBenchVals AI55.4%†41.1%†
Finance Agent v2Vals AI58.6%†53.5%†
Finance Agent v2.1Vals AI67.8%†60.4%†
Harvey's Legal Agent Benchmark v1.1Vals AI9.2%†7.1%†
Harvey's Legal Agent Benchmark v1Vals AI3.8%†5.4%†
Legal Research BenchVals AI50.5%†39.4%†
Robo-benchVals AI14.6%23.3%†
SREBenchVals AI33.6%†56.9%†
Tax Agent BenchVals AI44.5%†20.7%†
Terminal-Bench 4.0 (Vals)Vals AI65.2%†59.6%†
Terminal-Bench ScienceVals AI47.1%†62.9%†
Time Horizon Index: KSPVals AI91.3%†90.5%†
Arena SearchArena (LMArena)1214†1245†
BALROGBALROG–68.3%†
Vending-Bench 2Andon Labs9235.3†15514.7
AutomationBenchArtificial Analysis69.5%68.5%†
GDP.pdf (AA)Artificial Analysis26.2%31.0%†
Harvey LAB-AA v1.1Harvey4.2%8.6%†
AA-Briefcase v1.1Artificial Analysis18001569†
GDPxGDPx by SemiAnalysis12.0%9.6%†
Design Arena AgenticDesign Arena1334†1393†
Terminal-Bench-Science 0.1 (AA)Artificial Analysis59.0%63.3%†
CWE-Bench (AA)Artificial Analysis58.3%63.3%†
DeepSec-Bench (AA)Artificial Analysis26.9%36.9%†
CyberGym end-to-end (AA)Artificial Analysis0.8%0.0%†
FACTS SearchGoogle88.4%†93.3%
Maths
FrontierMath Tiers 1–3Epoch AI Benchmarking Hub91.2%93.7%†
FrontierMath Tier 4Epoch AI Benchmarking Hub95.0%97.6%†
OTIS Mock AIMEEpoch AI Benchmarking Hub100.0%100.0%†
ProofBenchVals AI100.0%99.0%
LiveBench MathematicsLiveBench97.1%96.8%†
Arena MathsArena (LMArena)1518†1481†
Knowledge
SimpleQA VerifiedEpoch AI Benchmarking Hub72.2%75.6%†
LiveBench 2.0 Data AnalysisLiveBench80.3%†83.0%
LiveBench ResearchLiveBench88.9%†90.6%
LiveBench 1.0 Data AnalysisLiveBench80.3%83.0%†
AA-Omniscience v1.1Artificial Analysis48.142.4†
PRBench FinanceScale AI SEAL–47.5%
PRBench LegalScale AI SEAL47.6%†48.4%
BioMysteryBenchVals AI79.3%†79.3%†
ClaimBenchVals AI100.0%†–
Excel Modeling BenchmarkVals AI75.9%†71.7%†
Excel Modeling Benchmark v1.1Vals AI75.8%†72.7%†
MedCodeVals AI49.8%†48.5%†
MedScribeVals AI91.4%†87.9%†
Public Benefits Bench v1.1Vals AI70.6%†–
DrugDiscoveryBenchScale AI SEAL–68.7%†
EBR-benchEpoch AI Benchmarking Hub71.4%76.2%†
GDP.pdfEpoch AI Benchmarking Hub30.6%34.2%†
AA-Omniscience v1.1: accuracyArtificial Analysis65.5%61.6%†
AA-Omniscience v1.1: non-hallucinationArtificial Analysis49.7%50.2%†
HealthBench Professional (AA)OpenAI59.9%66.0%†
Instruction following
LiveBench LanguageLiveBench86.3%89.4%†
LiveBench Instruction FollowingLiveBench65.7%75.6%†
Arena Instruction FollowingArena (LMArena)1519†1473†
Human preference
Arena TextArena (LMArena)1506†1475†
EQ-Bench 4EQ-Bench1340†–
Arena Creative WritingArena (LMArena)1517†1450†
Arena Multi-turnArena (LMArena)1500†1483†
Arena Longer QueriesArena (LMArena)1520†1486†
Multimodal
Arena VisionArena (LMArena)1324†1279†
LiveBench DesignLiveBench83.3%†80.0%
MMMU-ProArtificial Analysis87.7%86.9%†
SAGEVals AI91.3%†–
Blueprint-Bench 2Epoch AI Benchmarking Hub51.2%†49.7%
Code2Video-AAArtificial Analysis15361427†
AA-3DArtificial Analysis12021168†
Long context
AA-LCR v1.1Artificial Analysis84.7%80.7%†
Arena DocumentArena (LMArena)–1473†
MLCRArtificial Analysis27.8%41.7%†
Composite
Epoch Capabilities IndexEpoch AI Benchmarking Hub168.4†169.1
LiveBench 2.0LiveBench83.4%†84.5%
LiveBench 1.0LiveBench83.2%82.2%†
AA Intelligence Index v5.0Artificial Analysis59.156.9†
AA Intelligence Index v4.3.2Artificial Analysis57.652.7†
AA Progress Index v1Artificial Analysis350349.6†
Vals IndexVals AI70.1†65.0†
Vals Finance IndexVals AI65.3%†55.6%†
Vals RSI IndexVals AI37.3%27.1%†
Vals Science IndexVals AI58.6%†65.1%†
Vals Router IndexVals AI64.2%†65.0%
AA Cyber IndexArtificial Analysis28.733.4†
Safety & honesty
FORTRESSScale AI SEAL5.8%12.1%

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

  • Claude Opus 5.5 (max): 2 score revisions.
  • GPT-6 Astra: 5 score revisions.
  • Claude Opus 5.5 (max): 1 score revision.
  • GPT-6 Astra: 1 score revision.
  • Claude Opus 5.5 (max): 1 score revision.
  • GPT-6 Astra: 1 new result (FORTRESS); 1 score revision.
  • Claude Opus 5.5 (max): 2 score revisions.
  • GPT-6 Astra: 1 score revision.
  • Claude Opus 5.5 (max): 2 score revisions.
  • Claude Opus 5.5 (max): 1 score revision.

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

Claude Opus 5.5 vs GPT-6 Astra: questions

Is Claude Opus 5.5 better than GPT-6 Astra?
Claude Opus 5.5 (max) and GPT-6 Astra are neck and neck on quality (68.9 vs 68.1, within the ±8.1 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 5.5 vs GPT-6 Astra: which is cheaper, and will that change?
Claude Opus 5.5 is cheaper today: $8.00 against $20.00 per million tokens, blended at three input tokens per output token. No price change has been announced for either.
Is Claude Opus 5.5 or GPT-6 Astra better for coding?
GPT-6 Astra scores higher in coding (83 vs 80 on the category index, where 50 is average).
Which is faster, Claude Opus 5.5 or GPT-6 Astra?
Claude Opus 5.5 streams ~2× faster (115 vs 27 output tokens per second, Artificial Analysis 7-day median).
Is Claude Opus 5.5 or GPT-6 Astra better for agents and tool use?
GPT-6 Astra scores higher in agentic tasks (69 vs 63 on the category index, where 50 is average). On APEX-Agents, the top shared agents & tools benchmark, it is 73.5% for Claude Opus 5.5 against 64.7% for GPT-6 Astra.
More questions (4)
Which is better for long documents?
Both take about 1.1M tokens: Claude Opus 5.5 1,000,000, GPT-6 Astra 1,050,000.
Which has lower latency?
GPT-6 Astra answers first: 4.8 s against 380.6 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 5.5 vs GPT-6 Astra?
Across the 5 benchmarks both have, Claude Opus 5.5 leads 4, GPT-6 Astra leads 1. Every overall index that rates both puts Claude Opus 5.5 ahead.
When was Claude Opus 5.5 released?
Claude Opus 5.5 was released on 22 Sep 2026.