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Claude Opus 4.7 vs Kimi K3.1 Pro Together

Full profiles: Claude Opus 4.7 (Anthropic) and Kimi K3.1 Pro Together (Moonshot AI): every benchmark, price and rank.

Updated · Data from 9 sources

As of 9 Nov 2026, Claude Opus 4.7 and Kimi K3.1 Pro Together are neck and neck on quality (63.2 vs 60.5 on the BenchLeader Index, inside the ±3.5 margin). Kimi K3.1 Pro Together leads in every category we measure both in.

Key facts (as of 9 Nov 2026)

  • Claude Opus 4.7 scores 63.2 on the BenchLeader Index and Kimi K3.1 Pro Together scores 60.5 (BenchLeader, 9 Nov 2026).
  • Claude Opus 4.7 costs $10.00 per 1M tokens blended (list price, 9 Nov 2026).
  • Of the 1 benchmarks both models have, Kimi K3.1 Pro Together leads 1 (BenchLeader, 9 Nov 2026).
Claude Opus 4.7 benchmarks Anthropic Kimi K3.1 Pro Together benchmarks max Moonshot AIAdd 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
MathsEither67 vs 66 category scoreEither
ReasoningKimi K3.1 Pro Together67 vs 65 category score; Mystery Game Puzzles 42.0% vs 13.0%Medium
KnowledgeKimi K3.1 Pro Together68 vs 62 category scoreMedium
Chat quality (human preference)–Only Claude Opus 4.7 has an Arena rating (67 category score)Not comparable
High volume on a budgetNeither flagshipA smaller model is usually the better fit: Cheapest good LLMs, Fastest LLMs–

Key differences

  • Claude Opus 4.7 and Kimi K3.1 Pro Together (max) are neck and neck on quality (63.2 vs 60.5, within the ±3.5 margin).
  • Claude Opus 4.7 is stronger in agents & tools, coding, human preference, maths, multimodal.
  • Kimi K3.1 Pro Together (max) is stronger in knowledge, reasoning.

At a glance

SpecClaude Opus 4.7Kimi K3.1 Pro Together
DeveloperAnthropicMoonshot AI
Released16 Apr 202623 Oct 2026
Context window (tokens)1,000,000–
Compared atClaude Opus 4.7Kimi K3.1 Pro Together (max)
Open weightsNoNo
Price in / out / cached input per 1M$5.00 / $25.00 / $0.500–

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 4.7Kimi K3.1 Pro Together (max)Leader
Reasoning65.067.1Kimi K3.1 Pro Together
Coding61.3–not comparable
Agents & tools65.1–not comparable
Maths66.765.8level
Knowledge62.467.6Kimi K3.1 Pro Together
Human preference67.4–not comparable
Multimodal67.1–not 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 avg75ReasoningMathsKnowledgeClaude Opus 4.7, Reasoning: 65.0Claude Opus 4.7, Maths: 66.7Claude Opus 4.7, Knowledge: 62.4Kimi K3.1 Pro Together, Reasoning: 67.1Kimi K3.1 Pro Together, Maths: 65.8Kimi K3.1 Pro Together, Knowledge: 67.6

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

ModelIndex

Where sources disagree

Across the 1 benchmarks both have, Claude Opus 4.7 leads 0, Kimi K3.1 Pro Together leads 1.

Overall indexClaude Opus 4.7Kimi K3.1 Pro Together (max)Leader
BenchLeader Index63.260.5neck and neck

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 4.7Kimi K3.1 Pro Together (max)
Blended price per 1M tokens$10.00–
Input / output per 1M$5.00 / $25.00– / –
Cached input per 1M$0.500–
Price per task: chat reply$0.0095–
Price per task: summarize a 30-page report$0.075–
Price per task: code edit$0.068–
Price per task: agentic coding session$0.400–
Price per task: structured extraction$0.015–
Agentic coding session, input mostly cached$0.198–
Output speed48 tok/s–
Time to first answer1.0 s–

Each model is compared at its best-ranked reasoning-effort setting. Claude Opus 4.7 scores 63.2 and takes 1 s to its first answer token; Claude Opus 4.7 (high) scores 60.9 in 1 s, Claude Opus 4.7 (max) scores 59.5 in 25 s. Kimi K3.1 Pro Together (max) scores 60.5. 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

102 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 4.7Kimi K3.1 Pro Together (max)
BenchLeader IndexBenchLeader63.260.5
Agents & tools scoreBenchLeader65.1–
Coding scoreBenchLeader61.3–
Human preference scoreBenchLeader67.4–
Knowledge scoreBenchLeader62.467.6
Maths scoreBenchLeader66.765.8
Multimodal scoreBenchLeader67.1–
Reasoning scoreBenchLeader65.067.1
Blended price $/MBenchLeader$10.00–
Output speedBenchLeader48 tok/s–
Time to first answerBenchLeader1.0 s–
Context windowBenchLeader1,000,000 tokens–
Reasoning
GPQA DiamondEpoch AI Benchmarking Hub86.4%†94.2%
Humanity's Last ExamScale AI / CAIS36.2%–
SimpleBenchSimpleBench61.7%–
Arena Hard PromptsArena (LMArena)1519–
LiveBench 1.0 ReasoningLiveBench87.2%†–
GPQA Diamond (AA)Artificial Analysis91.4%†–
Humanity's Last Exam (AA)Artificial Analysis42.3%†–
GPQA Diamond (Vals)Vals AI90.2%–
Kagi LLM BenchmarkKagi LLM Benchmark73.3%–
ARC-AGI-3ARC Prize0.2%†–
CritPtArtificial Analysis12.0%†–
Chess PuzzlesEpoch AI Benchmarking Hub41.0%†45.0%
Mystery Game PuzzlesEpoch AI Benchmarking Hub13.0%42.0%
LMCAEpoch AI Benchmarking Hub52.2%†–
DTBenchEpoch AI Benchmarking Hub94.7%†–
ForecastBenchForecastBench63.1%–
Coding
SWE-bench Verified (Epoch)Epoch AI Benchmarking Hub83.5%†–
SciCodeSciCode54.5%†–
WeirdMLWeirdML76.4%–
FrontierCodeCognition38.5%–
GSO-BenchGSO-Bench44.1%–
Arena CodingArena (LMArena)1546–
Arena WebDevArena (LMArena)1555–
LiveBench 1.0 CodingLiveBench82.1%†–
LiveCodeBenchVals AI85.1%–
Show all 102 benchmarks
MetricPublisherClaude Opus 4.7Kimi K3.1 Pro Together (max)
Coding
SWE-bench (Vals)Vals AI82.0%–
Code MigrationVals AI43.9%–
ProgramBenchVals AI0.0%–
Vibe Code Bench v1.1Vals AI71.0%–
SWE Atlas: Codebase QnAScale AI SEAL40.3%–
SWE Atlas: RefactoringScale AI SEAL48.6%–
SWE Atlas: Test WritingScale AI SEAL38.5%–
MirrorCodeEpoch AI Benchmarking Hub31.1%†–
ALE-BenchEpoch AI Benchmarking Hub1323.0–
Terminal-Bench 2.1 (AA)Artificial Analysis83.2%†–
Agents & tools
Terminal-BenchTerminal-Bench80.2%–
OSWorld-Verified 2.0OSWorld18.2%†–
APEX-AgentsMercor49.2%†–
LiveBench Agentic CodingLiveBench50.7%†–
Terminal-Bench HardArtificial Analysis51.5%†–
τ²-Bench Telecom (AA)Artificial Analysis88.6%†–
Terminal-Bench 2.1 (Vals)Vals AI68.5%–
MCP AtlasScale AI SEAL79.1%†–
HiL-BenchScale AI SEAL41.7%–
τ³-bench Bankingτ²-bench40.2%†–
τ³-Banking (AA)Artificial Analysis34.6%†–
ITBench SRE (AA)Artificial Analysis46.7%†–
Analyst Agent (AA)Artificial Analysis43.8%†–
Finance Agent v2Vals AI51.5%–
Harvey's Legal Agent Benchmark v1Vals AI6.7%–
Legal Research BenchVals AI38.5%–
Tax Agent BenchVals AI23.7%–
Terminal-Bench 2.0 (Vals)Vals AI68.5%–
Arena SearchArena (LMArena)1210–
PostTrainBenchEpoch AI Benchmarking Hub28.6%†–
ExploitBenchEpoch AI Benchmarking Hub26.5%–
GBAEvalEpoch AI Benchmarking Hub43.8%–
Vending-Bench 2Andon Labs10936.8–
Maths
FrontierMath Tiers 1–3Epoch AI Benchmarking Hub70.2%†78.3%
FrontierMath Tier 4Epoch AI Benchmarking Hub31.7%†65.8%
OTIS Mock AIMEEpoch AI Benchmarking Hub86.7%†100.0%
ProofBenchVals AI54.0%†–
LiveBench MathematicsLiveBench92.8%†–
AIME (Vals)Vals AI96.3%–
AIME 2026MathArena95.8%†–
HMMT February 2026MathArena93.9%†–
MathArena ApexMathArena40.6%†–
Arena MathsArena (LMArena)1490–
Knowledge
SimpleQA VerifiedEpoch AI Benchmarking Hub51.7%†62.2%
LiveBench 1.0 Data AnalysisLiveBench78.3%†–
MMLU-ProVals AI89.9%–
LegalBenchVals AI85.3%–
CorpFinVals AI66.1%–
TaxEvalVals AI75.3%–
CaseLaw v2Vals AI68.4%–
Excel Modeling BenchmarkVals AI63.7%–
MedCodeVals AI54.9%–
MedScribeVals AI83.0%–
EBR-benchEpoch AI Benchmarking Hub19.1%†–
GDP.pdfEpoch AI Benchmarking Hub21.0%†–
Instruction following
LiveBench LanguageLiveBench77.9%†–
LiveBench Instruction FollowingLiveBench66.7%†–
IFBenchArtificial Analysis58.6%†–
Arena Instruction FollowingArena (LMArena)1493–
Human preference
Arena TextArena (LMArena)1494–
EQ-Bench 4EQ-Bench1293–
Arena Creative WritingArena (LMArena)1482–
Arena Multi-turnArena (LMArena)1514–
Arena Longer QueriesArena (LMArena)1507–
Multimodal
Arena VisionArena (LMArena)1319–
MMMU-ProArtificial Analysis78.8%†–
MMMU-Pro (Vals)Vals AI85.5%–
MortgageTaxVals AI70.3%–
Blueprint-Bench 2Epoch AI Benchmarking Hub24.5%–
Long context
AA-LCR v1.1Artificial Analysis78.7%†–
Arena DocumentArena (LMArena)1494–
Composite
Epoch Capabilities IndexEpoch AI Benchmarking Hub157.6–
LiveBench 1.0LiveBench76.5%†–
AA Intelligence Index v4.3.2Artificial Analysis40.7†–
AA Progress Index v1Artificial Analysis312.5†–
Vals RSI IndexVals AI19.1%†–
Vals Multimodal IndexVals AI67.4%–

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

What changed

  • Kimi K3.1 Pro Together (max): first results.
  • Claude Opus 4.7: 1 score revision.
  • Claude Opus 4.7: 1 score revision.
  • Claude Opus 4.7: 1 new result (Harvey's Legal Agent Benchmark v1).
  • Claude Opus 4.7: 1 score revision.
  • Claude Opus 4.7: 1 score revision.
  • Claude Opus 4.7: 1 score revision.
  • Claude Opus 4.7: BenchLeader Index 63.9 → 63.4.
  • Claude Opus 4.7: 1 new result (SWE Atlas: Codebase QnA).

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

Claude Opus 4.7 vs Kimi K3.1 Pro Together: questions

Is Claude Opus 4.7 better than Kimi K3.1 Pro Together?
Claude Opus 4.7 and Kimi K3.1 Pro Together (max) are neck and neck on quality (63.2 vs 60.5, within the ±3.5 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.
Do independent benchmarks agree on Claude Opus 4.7 vs Kimi K3.1 Pro Together?
Across the 1 benchmarks both have, Claude Opus 4.7 leads 0, Kimi K3.1 Pro Together leads 1.
When was Kimi K3.1 Pro Together released?
Kimi K3.1 Pro Together was released on 23 Oct 2026.