BenchLeader
Menu
Best LLMsChoose a modelLeaderboardsModelsBenchmarksProvidersReleases9

Claude Opus 5 vs GPT-6.1 Terra

Full profiles: Claude Opus 5 (Anthropic) and GPT-6.1 Terra (OpenAI): every benchmark, price and rank.

Updated · Data from 11 sources

As of 27 Oct 2026, Claude Opus 5 (max) and GPT-6.1 Terra (max) are neck and neck on quality (68.7 vs 65.9 on the BenchLeader Index, inside the ±7.5 margin of error), and GPT-6.1 Terra (max) costs 5.0× less, which makes it the better buy for most workloads. GPT-6.1 Terra leads in every category we measure both in.

Claude Opus 5 benchmarks max Anthropic GPT-6.1 Terra benchmarks max OpenAIOpen in the comparison tool

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
ReasoningGPT-6.1 Terra86 vs 74 category score; CritPt 28.0% vs 29.1%High
KnowledgeGPT-6.1 Terra75 vs 71 category score; AA-Omniscience 29.8 vs 37.1Medium
Long documentsGPT-6.1 Terra66 vs 65 category score; AA-LCR 82.7% vs 79.3%Medium
Images and other mediaEither68 vs 68 category score; MMMU-Pro 84.7% vs 84.7%Either
Chat quality (human preference)–Only Claude Opus 5 has an Arena rating (69 category score)Not comparable
Lowest costGPT-6.1 Terra$2.00 vs $10.00 per 1M blended; agentic coding session $0.080 vs $0.400–
Fastest first answerClaude Opus 576.3 s (Claude Opus 5 (max)) vs 131.8 s (GPT-6.1 Terra (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 (max) and GPT-6.1 Terra (max) are neck and neck on quality (68.7 vs 65.9, within the ±7.5 margin).
  • Claude Opus 5 (max) is stronger in agents & tools, coding, composite, human preference, maths, multimodal.
  • GPT-6.1 Terra (max) is stronger in knowledge, long context, reasoning.
  • GPT-6.1 Terra (max) is 5.0× cheaper ($2.00 vs $10.00 per 1M blended).
  • GPT-6.1 Terra (max) streams 1.7× faster (91 vs 52 tokens per second).

At a glance

SpecClaude Opus 5GPT-6.1 Terra
DeveloperAnthropicOpenAI
Released24 Jul 202626 Oct 2026
Context window (tokens)1,000,0001,050,000
Compared atClaude Opus 5 (max)GPT-6.1 Terra (max)
Open weightsNoNo
Price in / out / cached input per 1M$5.00 / $25.00 / $0.500$1.00 / $5.00 / $0.050

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 (max)GPT-6.1 Terra (max)Leader
Reasoning74.086.2GPT-6.1 Terra
Coding70.2–not comparable
Agents & tools64.3–not comparable
Maths70.6–not comparable
Knowledge71.474.5GPT-6.1 Terra
Human preference68.5–not comparable
Multimodal67.667.5level
Long context64.566.3GPT-6.1 Terra
Composite85.782.8Claude Opus 5

Where sources disagree

Across the 13 benchmarks both have, Claude Opus 5 leads 7, GPT-6.1 Terra leads 6. Every overall index that rates both puts Claude Opus 5 ahead.

Overall indexClaude Opus 5 (max)GPT-6.1 Terra (max)Leader
BenchLeader Index68.765.9neck and neck
AA Intelligence Index v4.3.250.848.1Claude Opus 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; suite cost is what Artificial Analysis paid to run its whole Intelligence Index.

MeasureClaude Opus 5 (max)GPT-6.1 Terra (max)
Blended price per 1M tokens$10.00$2.00
Input / output per 1M$5.00 / $25.00$1.00 / $5.00
Cached input per 1M$0.500$0.050
Price per task: chat reply$0.0095$0.0019
Price per task: summarize a 30-page report$0.075$0.015
Price per task: code edit$0.068$0.013
Price per task: agentic coding session$0.400$0.080
Price per task: structured extraction$0.015$0.0030
Cost to run a full benchmark suite$5.86$0.403
Output speed52 tok/s91 tok/s
Time to first answer76.3 s131.8 s
Time to a complete answer85.9 s137.3 s

Per token is not per task: on Artificial Analysis' full suite Claude Opus 5 (max) cost $5.86 and GPT-6.1 Terra (max) $0.403, because Claude Opus 5 (max) used about 2.9× as many tokens for the same work, which a per-token price hides.

Each model is compared at its best-ranked reasoning-effort setting. Claude Opus 5 (max) scores 68.7 and takes 76 s to its first answer token; Claude Opus 5 (high) scores 67.7 in 19 s, Claude Opus 5 (xhigh) scores 67.2 in 27 s. GPT-6.1 Terra (max) scores 65.9 and takes 132 s to its first answer token; GPT-6.1 Terra (xhigh) scores 65.0 in 18 s, GPT-6.1 Terra (high) scores 64.7 in 7 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

131 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 (max)GPT-6.1 Terra (max)
BenchLeader IndexBenchLeader68.765.9
Agents & tools scoreBenchLeader64.3–
Coding scoreBenchLeader70.2–
Composite scoreBenchLeader85.782.8
Human preference scoreBenchLeader68.5–
Knowledge scoreBenchLeader71.474.5
Long context scoreBenchLeader64.566.3
Maths scoreBenchLeader70.6–
Multimodal scoreBenchLeader67.667.5
Reasoning scoreBenchLeader74.086.2
Blended price $/MBenchLeader$10.00$2.00
Output speedBenchLeader52 tok/s91 tok/s
Time to first answerBenchLeader76.3 s131.8 s
Context windowBenchLeader1,000,000 tokens1,050,000 tokens
Reasoning
GPQA DiamondEpoch AI Benchmarking Hub93.9%–
SimpleBenchSimpleBench80.6%†–
Arena Hard PromptsArena (LMArena)1515–
LiveBench 2.0 ReasoningLiveBench–88.7%†
LiveBench 1.0 ReasoningLiveBench91.2%–
GPQA Diamond (AA)Artificial Analysis93.2%–
Humanity's Last Exam (AA)Artificial Analysis54.9%46.3%
GPQA Diamond (Vals)Vals AI93.4%†–
ARC-AGI-1ARC Prize97.5%–
ARC-AGI-2ARC Prize90.4%–
ARC-AGI-3ARC Prize30.2%†–
CritPtArtificial Analysis29.1%28.0%
MysteryMechanismVals AI37.4%†–
Chess PuzzlesEpoch AI Benchmarking Hub43.0%–
Mystery Game PuzzlesEpoch AI Benchmarking Hub59.0%–
LMCAEpoch AI Benchmarking Hub63.3%–
DTBenchEpoch AI Benchmarking Hub97.6%–
ForecastBenchForecastBench66.5%–
BTF-3Epoch AI Benchmarking Hub12.0%†–
Coding
SciCodeSciCode56.4%–
WeirdMLWeirdML91.8%–
FrontierCodeCognition53.4%–
Arena CodingArena (LMArena)1528–
Arena WebDevArena (LMArena)1691–
LiveBench 2.0 CodingLiveBench–90.8%†
Show all 131 benchmarks
MetricPublisherClaude Opus 5 (max)GPT-6.1 Terra (max)
Coding
LiveBench 1.0 CodingLiveBench81.5%–
SciCode (AA)Artificial Analysis56.4%55.1%
LiveCodeBenchVals AI89.0%†–
IOIVals AI84.3%†–
SWE-bench (Vals)Vals AI97.0%†–
Code MigrationVals AI57.5%†–
ProgramBenchVals AI3.0%†–
Vibe Code Bench 1-100Vals AI28.5%†–
Vibe Code Bench v1.1Vals AI88.4%†–
SWE Atlas: Codebase QnAScale AI SEAL63.2%†–
SWE Atlas: Test WritingScale AI SEAL62.2%†–
DeepSWE v1.1Epoch AI Benchmarking Hub73.7%–
CursorBenchCursor46.6%–
ALE-BenchEpoch AI Benchmarking Hub2164.6†–
FrontierSWEEpoch AI Benchmarking Hub52.0%–
Terminal-Bench 4.0 (AA)Artificial Analysis49.0%55.6%
Terminal-Bench 2.1 (AA)Artificial Analysis89.1%–
Startrise FrontendStartrise82.3%†–
FrontierCode 1.1 (AA)Artificial Analysis–36.0%
Agents & tools
Terminal-BenchTerminal-Bench51.8%–
OSWorld-Verified 2.0OSWorld31.4%–
APEX-AgentsMercor65.8%–
Arena AgentArena (LMArena)8.2–
LiveBench Long AgenticLiveBench–48.6%†
LiveBench BrowserLiveBench–93.1%†
LiveBench Agentic CodingLiveBench65.2%–
Terminal-Bench 2.1 (Vals)Vals AI84.6%†–
MCP AtlasScale AI SEAL85.8%†–
HiL-BenchScale AI SEAL57.0%†–
τ³-bench Bankingτ²-bench48.7%–
τ³-Banking (AA)Artificial Analysis42.1%–
Analyst Agent (AA)Artificial Analysis53.8%–
CUA-benchVals AI9.0%–
CyberBenchVals AI65.4%†–
Finance Agent v2Vals AI58.6%†–
Harvey's Legal Agent Benchmark v1Vals AI6.7%†–
Legal Research BenchVals AI55.3%†–
SkillsBenchVals AI60.4%†–
SREBenchVals AI12.2%†–
Tax Agent BenchVals AI45.5%†–
Terminal-Bench 4.0 (Vals)Vals AI53.5%†–
Terminal-Bench ScienceVals AI27.1%†–
Time Horizon Index: KSPVals AI18.8%†–
Arena SearchArena (LMArena)1214†–
BALROGBALROG63.4%–
PostTrainBenchEpoch AI Benchmarking Hub35.0%†–
GBAEvalEpoch AI Benchmarking Hub79.6%†–
Vending-Bench 2Andon Labs11181.9†–
AutomationBenchArtificial Analysis56.6%60.2%
GDP.pdf (AA)Artificial Analysis21.6%28.6%
EnterpriseOps-GymArtificial Analysis47.5%–
AA-Briefcase v1.1Artificial Analysis16571402
Terminal-Bench-Science 0.1 (AA)Artificial Analysis28.6%57.6%
DeepSec-Bench (AA)Artificial Analysis25.9%–
FACTS SearchGoogle85.3%†–
Maths
FrontierMath Tiers 1–3Epoch AI Benchmarking Hub85.6%–
FrontierMath Tier 4Epoch AI Benchmarking Hub73.2%–
OTIS Mock AIMEEpoch AI Benchmarking Hub98.9%–
ProofBenchVals AI99.0%–
LiveBench MathematicsLiveBench95.7%–
Arena MathsArena (LMArena)1517–
Knowledge
SimpleQA VerifiedEpoch AI Benchmarking Hub59.9%–
LiveBench 2.0 Data AnalysisLiveBench–82.3%†
LiveBench ResearchLiveBench–73.9%†
LiveBench 1.0 Data AnalysisLiveBench74.5%–
AA-OmniscienceArtificial Analysis37.129.8
MMLU-ProVals AI91.6%†–
LegalBenchVals AI87.0%†–
CorpFinVals AI73.2%†–
TaxEvalVals AI75.1%†–
BioMysteryBenchVals AI79.3%†–
Excel Modeling BenchmarkVals AI73.6%†–
MedCodeVals AI63.6%†–
MedScribeVals AI91.0%†–
Public Benefits Bench v1.1Vals AI76.9%†–
DrugDiscoveryBenchScale AI SEAL53.7%–
EBR-benchEpoch AI Benchmarking Hub45.7%–
GDP.pdfEpoch AI Benchmarking Hub24.0%–
AA-Omniscience: accuracyArtificial Analysis60.9%49.1%
AA-Omniscience: non-hallucinationArtificial Analysis39.2%62.0%
Instruction following
LiveBench LanguageLiveBench88.7%–
LiveBench Instruction FollowingLiveBench63.8%–
Arena Instruction FollowingArena (LMArena)1495–
Human preference
Arena TextArena (LMArena)1491–
EQ-Bench 4EQ-Bench1360†–
Arena Creative WritingArena (LMArena)1474–
Arena Multi-turnArena (LMArena)1487–
Arena Longer QueriesArena (LMArena)1503–
Multimodal
Arena VisionArena (LMArena)1320†–
LiveBench DesignLiveBench–82.3%†
MMMU-ProArtificial Analysis84.7%84.7%
MMMU-Pro (Vals)Vals AI89.9%†–
MortgageTaxVals AI72.1%†–
SAGEVals AI49.4%†–
Blueprint-Bench 2Epoch AI Benchmarking Hub30.4%†–
Long context
AA-LCRArtificial Analysis79.3%82.7%
Arena DocumentArena (LMArena)1490†–
MLCRArtificial Analysis11.1%–
Composite
Epoch Capabilities IndexEpoch AI Benchmarking Hub163.9†–
LiveBench 2.0LiveBench–77.2%†
LiveBench 1.0LiveBench80.1%–
AA Intelligence Index v4.3.2Artificial Analysis50.848.1
Vals RSI IndexVals AI33.0%–
Vals Science IndexVals AI47.9%†–
Vals Multimodal IndexVals AI73.9%†–
Safety & honesty
FORTRESSScale AI SEAL16.8%†18.2%†

Data as of 2026-10-27. Best configuration of each model; every score links to its source on the model pages.

What changed

  • Claude Opus 5 (max): 1 new result (Vals RSI Index).
  • Claude Opus 5 (max): 1 score revision.
  • Claude Opus 5 (max): 1 new result (ForecastBench); 1 score revision.
  • Claude Opus 5 (max): BenchLeader Index 68.3 → 68.9.
  • Claude Opus 5 (max): 4 new results (GDPval-AA v2.1, AA-Omniscience: accuracy, AA-Omniscience: non-hallucination…).
  • Claude Opus 5 (max): 1 score revision.
  • Claude Opus 5 (max): 2 score revisions.
  • Claude Opus 5 (max): 2 new results (Terminal-Bench-Science 0.1 (AA), DeepSec-Bench (AA)).
  • Claude Opus 5 (max): 1 new result (DrugDiscoveryBench).
  • Claude Opus 5 (max): 1 score revision.

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

Claude Opus 5 vs GPT-6.1 Terra: questions

Is Claude Opus 5 better than GPT-6.1 Terra?
Claude Opus 5 (max) and GPT-6.1 Terra (max) are neck and neck on quality (68.7 vs 65.9, within the ±7.5 margin). The BenchLeader Index combines every independent quality benchmark; the two are within the margin of error as of 2026-10-27, so check the category scores for your use.
Which is cheaper, Claude Opus 5 or GPT-6.1 Terra, and will that change?
GPT-6.1 Terra is cheaper today: $2.00 against $10.00 per million tokens, blended at three input tokens per output token. No price change has been announced for either.
Which is better for long documents?
GPT-6.1 Terra scores higher on long-context benchmarks (66 vs 65). Both take about 1.1M tokens: Claude Opus 5 1,000,000, GPT-6.1 Terra 1,050,000.
Which has lower latency?
Claude Opus 5 (max) answers first: 76.3 s against 131.8 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.
Which is faster, Claude Opus 5 or GPT-6.1 Terra?
GPT-6.1 Terra streams faster: 91 against 52 output tokens per second.
Do independent benchmarks agree on Claude Opus 5 vs GPT-6.1 Terra?
Across the 13 benchmarks both have, Claude Opus 5 leads 7, GPT-6.1 Terra leads 6. Every overall index that rates both puts Claude Opus 5 ahead.
When was GPT-6.1 Terra released?
GPT-6.1 Terra was released on 26 Oct 2026.