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Model profile

Claude Opus 4.6 (Adaptive)

AnthropicCurrentReleased February 2026
Data verified
Overall Score
64.18Public #35 of 200
Arena Elo
1504
Eligible category ranks
2of 8
Price (1M tokens)
Not listedAPI pricing
Speed
Not listed
Context
1M

Evidence coverage

16 of 323 tracked benchmarks are published. 1 is verified and 15 provisional. 7 of 8 categories are measured.

Updated July 23, 2026Methodology
Published / tracked
16 / 323
Verified
1
Provisional
15
Categories with evidence
7 / 8

Evidence by category

  • Agentic2 benchmarks
    Reported
  • Coding2 benchmarks
    Mixed evidence
  • Reasoning2 benchmarks
    Reported
  • Knowledge6 benchmarks
    Reported
  • Math0 benchmarks
    Not measured
  • Multilingual1 benchmark
    Reported
  • Multimodal2 benchmarks
    Reported
  • Inst. Following1 benchmark
    Reported
ProprietaryReasoning
Confidence:
Low
reasoning

Claude Opus 4.6 (Adaptive) ranks #35 out of 200 models on the public leaderboard with an overall score of 64.18/100. It does not yet have enough sourced coverage for BenchLM's verified leaderboard. While not a frontier model, it offers specific advantages depending on the use case.

Claude Opus 4.6 (Adaptive) is a proprietary model with a 1M token context window. It uses explicit chain-of-thought reasoning, which typically improves performance on math and complex reasoning tasks at the cost of higher latency and token usage.

Claude Opus 4.6 (Adaptive) sits inside the Claude Opus 4.6 family alongside Claude Opus 4.6. This profile currently has 16 of 323 tracked benchmarks. BenchLM only exposes non-generated benchmark rows publicly, so missing categories stay blank until a sourced evaluation is available.

Its strongest category is Agentic (#20), while its weakest is Coding (#21). This performance profile makes it particularly useful for coding agents, browser research, and computer-use workflows.

Peer position

Exact provisional scores and ranks for the closest listed peers. A score can appear before a model clears the evidence threshold for a rank, so equal scores can have different rank states.

Range 63.564.75

  1. Gemini 3.5 Flash
    Google
    #3364.75
    Gemini 3.5 Flash is #33 with a score of 64.75.
    Compare
  2. Claude Opus 4.5
    Anthropic
    #3464.22
    Claude Opus 4.5 is #34 with a score of 64.22.
    Compare
  3. Claude Opus 4.6 (Adaptive)Current model
    Anthropic
    #3564.18
    Claude Opus 4.6 (Adaptive) is #35 with a score of 64.18.
  4. MiniMax M2.7
    MiniMax
    #3664.11
    MiniMax M2.7 is #36 with a score of 64.11.
    Compare
  5. GLM-5.2
    Z.AI
    #3763.96
    GLM-5.2 is #37 with a score of 63.96.
    Compare
  6. GPT-5.5 Pro
    OpenAI
    #3863.69
    GPT-5.5 Pro is #38 with a score of 63.69.
    Compare
  7. GLM-5V-Turbo
    Z.AI
    #3963.5
    GLM-5V-Turbo is #39 with a score of 63.5.
    Compare

Category percentile

More

Relative position among models eligible for each sourced category. A higher percentile means a stronger position within that category's ranked cohort; 100 is highest.

  1. Agentic84%
    Eligible cohort rank #20 of 119Category score 55.4
  2. Coding83%
    Eligible cohort rank #21 of 122Category score 60.7

Category evidence

Scores and ranks appear only where this model has published benchmark evidence. Categories without displayable source records remain not measured.

Category scores, ranks, weighting, benchmark coverage, and evidence status
CategoryScore
AgenticRank #20 of 119Percentile 84thWeight 22%2 benchmarksReported55.4
CodingRank #21 of 122Percentile 83rdWeight 20%2 benchmarksMixed sources60.7
ReasoningWeight 17%2 benchmarksReportedScore pending
KnowledgeWeight 12%6 benchmarksReportedScore pending
MathWeight 5%0 benchmarksNot measuredNot measured
MultilingualWeight 7%1 benchmarkReportedScore pending
MultimodalWeight 12%2 benchmarksReportedScore pending
Inst. FollowingWeight 5%1 benchmarkReportedScore pending

Chatbot Arena performance

Scroll horizontally to inspect confidence intervals and vote counts.

Chatbot Arena Elo, confidence interval, and vote count by evaluation view
ViewEloConfidence intervalVotes
Text Overall1504±3.762,355
Coding1550±6.116,120
Math1519±11.03,231
Instruction Following1513±5.719,376
Creative Writing1499±7.210,627
Multi-turn1518±6.910,654
Hard Prompts1532±4.638,977
Hard Prompts (English)1538±5.818,751
Longer Query1524±5.524,855

Benchmark Details

Rows below have a displayable published verification record. Each source link and provenance note remains in the page HTML while its category is closed. Source-unverified manual rows and generated rows stay hidden.

Agentic2 benchmarks
APEX-Agents-AAReported
33.0%Display only
Source: Artificial Analysis model benchmarksProvenance: Display-only row synced from the current Artificial Analysis model payload. It is excluded from BenchLM weighted scoring.
τ²-bench resultsReported

τ²-Bench Tool-Agent-User Evaluation

92.1%Display only
Source: Artificial Analysis model benchmarksProvenance: Display-only row synced from the current Artificial Analysis model payload. It is excluded from BenchLM weighted scoring.
Coding2 benchmarks
Vibe Code BenchBenchmark exact

Vibe Code Bench v1.1

53.50%Display only
Source: Vals AI: Vibe Code Bench v1.1Provenance: Vals Vibe Code Bench v1.1 reports this exact row under anthropic/claude-opus-4-6-thinking; BenchLM stores it on the local vibeCodeBench key.
AA-SciCodeReported

Artificial Analysis SciCode

51.9%Display only
Source: Artificial Analysis model benchmarksProvenance: Display-only row synced from the current Artificial Analysis model payload. It is excluded from BenchLM weighted scoring.
Reasoning2 benchmarks
AA-LCRReported

Artificial Analysis Long Context Reasoning

70.7%Display only
Source: Artificial Analysis model benchmarksProvenance: Display-only row synced from the current Artificial Analysis model payload. It is excluded from BenchLM weighted scoring.
CritPtReported

Critical Physics Tasks

12.6%Display only
Source: Artificial Analysis model benchmarksProvenance: Display-only row synced from the current Artificial Analysis model payload. It is excluded from BenchLM weighted scoring.
Knowledge6 benchmarks
Artificial Analysis Intelligence IndexReported
43.7%Display only
Source: Artificial Analysis model benchmarksProvenance: Display-only row synced from the current Artificial Analysis model payload. It is excluded from BenchLM weighted scoring.
AA-GPQA DiamondReported

Artificial Analysis GPQA Diamond

89.6%Display only
Source: Artificial Analysis model benchmarksProvenance: Display-only row synced from the current Artificial Analysis model payload. It is excluded from BenchLM weighted scoring.
AA-HLEReported

Artificial Analysis Humanity's Last Exam

36.7%Display only
Source: Artificial Analysis model benchmarksProvenance: Display-only row synced from the current Artificial Analysis model payload. It is excluded from BenchLM weighted scoring.
AA-Omniscience IndexReported

Artificial Analysis Omniscience Index

13.5%Display only
Source: Artificial Analysis model benchmarksProvenance: Display-only row synced from the current Artificial Analysis model payload. It is excluded from BenchLM weighted scoring.
AA-Omniscience AccuracyReported

Artificial Analysis Omniscience Accuracy

46.4%Display only
Source: Artificial Analysis model benchmarksProvenance: Display-only row synced from the current Artificial Analysis model payload. It is excluded from BenchLM weighted scoring.
AA-Omniscience Hallucination RateReported

Artificial Analysis Omniscience Hallucination Rate

61.3%Display only
Source: Artificial Analysis model benchmarksProvenance: Display-only row synced from the current Artificial Analysis model payload. It is excluded from BenchLM weighted scoring.
Multilingual1 benchmark
AA Global-MMLU-LiteReported

Artificial Analysis Global-MMLU-Lite

92.2%Display only
Source: Artificial Analysis: global-mmlu-lite leaderboardProvenance: Display-only row synced from the current Artificial Analysis evaluation leaderboard. It is excluded from BenchLM weighted scoring.
Multimodal2 benchmarks
AA-MMMU-ProReported

Artificial Analysis MMMU-Pro

75.4%Display only
Source: Artificial Analysis model benchmarksProvenance: Display-only row synced from the current Artificial Analysis model payload. It is excluded from BenchLM weighted scoring.
Design Arena WebsiteReported

Design Arena Website Elo

1325Display only
Source: OpenRouter model benchmarksProvenance: Display-only Design Arena Website Elo synced from OpenRouter model benchmark metadata. It is excluded from BenchLM weighted scoring.
Inst. Following1 benchmark
AA-IFBenchReported

Artificial Analysis IFBench

53.1%Display only
Source: Artificial Analysis model benchmarksProvenance: Display-only row synced from the current Artificial Analysis model payload. It is excluded from BenchLM weighted scoring.

Claude Opus 4.6 Family

reasoning · adaptive

Canonical Entry

Claude Opus 4.6

Frequently Asked Questions

How does Claude Opus 4.6 (Adaptive) perform overall in AI benchmarks?

Claude Opus 4.6 (Adaptive) has 16 published benchmark scores on BenchLM, but it does not yet have enough non-generated coverage to receive a global overall rank.

Is Claude Opus 4.6 (Adaptive) good for knowledge and understanding?

Claude Opus 4.6 (Adaptive) has visible benchmark coverage in knowledge and understanding, but BenchLM does not currently assign it a global category rank there.

Is Claude Opus 4.6 (Adaptive) good for coding and programming?

Claude Opus 4.6 (Adaptive) ranks #21 out of 122 models in coding and programming benchmarks with an average score of 60.7. There are stronger options in this category.

Is Claude Opus 4.6 (Adaptive) good for reasoning and logic?

Claude Opus 4.6 (Adaptive) has visible benchmark coverage in reasoning and logic, but BenchLM does not currently assign it a global category rank there.

Is Claude Opus 4.6 (Adaptive) good for agentic tool use and computer tasks?

Claude Opus 4.6 (Adaptive) ranks #20 out of 119 models in agentic tool use and computer tasks benchmarks with an average score of 55.4. There are stronger options in this category.

Is Claude Opus 4.6 (Adaptive) good for multimodal and grounded tasks?

Claude Opus 4.6 (Adaptive) has visible benchmark coverage in multimodal and grounded tasks, but BenchLM does not currently assign it a global category rank there.

Is Claude Opus 4.6 (Adaptive) good for instruction following?

Claude Opus 4.6 (Adaptive) has visible benchmark coverage in instruction following, but BenchLM does not currently assign it a global category rank there.

Is Claude Opus 4.6 (Adaptive) good for multilingual tasks?

Claude Opus 4.6 (Adaptive) has visible benchmark coverage in multilingual tasks, but BenchLM does not currently assign it a global category rank there.

Which sibling models are related to Claude Opus 4.6 (Adaptive)?

Claude Opus 4.6 (Adaptive) belongs to the Claude Opus 4.6 family. Related variants on BenchLM include Claude Opus 4.6.

Does Claude Opus 4.6 (Adaptive) have full benchmark coverage on BenchLM?

Not yet. Claude Opus 4.6 (Adaptive) currently has 16 published benchmark scores out of the 323 benchmarks BenchLM tracks. BenchLM only exposes non-generated public benchmark rows, so missing categories stay blank until a sourced evaluation is available.

What is the context window size of Claude Opus 4.6 (Adaptive)?

Claude Opus 4.6 (Adaptive) has a published context window of 1M, which determines how much text it can process in a single interaction.

Last updated: July 23, 2026 · Runtime metrics stay blank until BenchLM has a sourced snapshot.

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