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Claude Opus 4.7 (Adaptive)

AnthropicSupersededReleased Apr 16, 2026
Overall Score
84Prov. #17 of 124Verified #10 of 33
Arena Elo
1502
Categories Ranked
4of 8
Price (1M tokens)
$5 in / $25 out
Speed
N/A
Context
1M
ProprietaryReasoning
Confidence
reasoning

According to BenchLM.ai, Claude Opus 4.7 (Adaptive) ranks #17 out of 124 models on the provisional leaderboard with an overall score of 84/100. It also ranks #10 out of 33 on the verified leaderboard. This places it in the mid-tier of AI models, with strengths in specific benchmark categories.

Claude Opus 4.7 (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 4.7 (Adaptive) sits inside the Claude Opus 4.7 family alongside Claude Opus 4.7. BenchLM links it directly to Claude Opus 4.6 as the earlier related model in that lineage. This profile currently has 36 of 249 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 Knowledge (#1), while its weakest is Multimodal & Grounded (#73). This performance profile makes it particularly effective for knowledge-intensive tasks like research, analysis, and factual Q&A.

Ranking Distribution

Category rank across 6 benchmark categories — sorted by best rank

Category Performance

Scores across all benchmark categories (0-100 scale)

Category Breakdown

Agentic

#8
85.7/ 100
Weight: 22%9 benchmarks
Terminal-Bench 2.0BrowseCompOSWorld-VerifiedGAIATAU-benchWebArena

Coding

#4
93.5/ 100
Weight: 20%6 benchmarks
SWE-bench VerifiedLiveCodeBenchSWE-bench ProSWE-RebenchSciCode

Reasoning

90.7/ 100
Weight: 17%4 benchmarks
MuSRLongBench v2MRCRv2ARC-AGI-2

Knowledge

#1
99.6/ 100
Weight: 12%10 benchmarks
GPQASuperGPQAMMLU-ProHLEFrontierScienceSimpleQA

Math

71.2/ 100
Weight: 5%1 benchmark
AIME 2025BRUMO 2025MATH-500FrontierMath

Multilingual

0.0/ 100
Weight: 7%0 benchmarks
MGSMMMLU-ProX

Multimodal

#73
45.0/ 100
Weight: 12%5 benchmarks
MMMU-ProOfficeQA ProCharXivCharXiv w/o tools

Inst. Following

0.0/ 100
Weight: 5%1 benchmark
IFEvalIFBench

Chatbot Arena Performance

Text Overall1502CI: ±4.632,629 votes
Coding1553CI: ±7.49,252 votes
Math1504CI: ±14.41,779 votes
Instruction Following1504CI: ±6.911,075 votes
Creative Writing1486CI: ±9.15,500 votes
Multi-turn1517CI: ±8.95,605 votes
Hard Prompts1524CI: ±5.521,557 votes
Hard Prompts (English)1527CI: ±6.910,929 votes
Longer Query1514CI: ±6.614,253 votes

Benchmark Details

Only benchmark rows with an attached exact-source record are shown here. Source-unverified manual rows and generated rows are hidden from model pages.

Claude Opus 4.7 Family

reasoning · adaptive

Canonical Entry

Claude Opus 4.7

Related Earlier Model

Claude Opus 4.6
Claude Opus 4.7

Compare This Model

See how Claude Opus 4.7 (Adaptive) stacks up against similar models

Claude Opus 4.7Anthropic
—
Claude Mythos 5Anthropic
Prov. 99
Claude Fable 5Anthropic
Prov. 95
Claude Opus 4.8Anthropic
Prov. 93
GLM-5.2Z.AI
Prov. 91

Frequently Asked Questions

How does Claude Opus 4.7 (Adaptive) perform overall in AI benchmarks?

Claude Opus 4.7 (Adaptive) currently ranks #17 out of 124 models on BenchLM's provisional leaderboard with an overall score of 84. It also ranks #10 out of 33 on the verified leaderboard. It is created by Anthropic and features a 1M context window.

Is Claude Opus 4.7 (Adaptive) good for knowledge and understanding?

Claude Opus 4.7 (Adaptive) ranks #1 out of 124 models in knowledge and understanding benchmarks with an average score of 99.6. It is among the top performers in this category.

Is Claude Opus 4.7 (Adaptive) good for coding and programming?

Claude Opus 4.7 (Adaptive) ranks #4 out of 124 models in coding and programming benchmarks with an average score of 93.5. It is among the top performers in this category.

Is Claude Opus 4.7 (Adaptive) good for mathematics?

Claude Opus 4.7 (Adaptive) has visible benchmark coverage in mathematics, but BenchLM does not currently assign it a global category rank there.

Is Claude Opus 4.7 (Adaptive) good for reasoning and logic?

Claude Opus 4.7 (Adaptive) has visible benchmark coverage in reasoning and logic, but BenchLM does not currently assign it a global category rank there.

Is Claude Opus 4.7 (Adaptive) good for agentic tool use and computer tasks?

Claude Opus 4.7 (Adaptive) ranks #8 out of 124 models in agentic tool use and computer tasks benchmarks with an average score of 85.7. It is among the top performers in this category.

Is Claude Opus 4.7 (Adaptive) good for multimodal and grounded tasks?

Claude Opus 4.7 (Adaptive) ranks #73 out of 124 models in multimodal and grounded tasks benchmarks with an average score of 45. There are stronger options in this category.

Is Claude Opus 4.7 (Adaptive) good for instruction following?

Claude Opus 4.7 (Adaptive) has visible benchmark coverage in instruction following, but BenchLM does not currently assign it a global category rank there.

Which sibling models are related to Claude Opus 4.7 (Adaptive)?

Claude Opus 4.7 (Adaptive) belongs to the Claude Opus 4.7 family. Related variants on BenchLM include Claude Opus 4.7.

Does Claude Opus 4.7 (Adaptive) have full benchmark coverage on BenchLM?

Not yet. Claude Opus 4.7 (Adaptive) currently has 36 published benchmark scores out of the 249 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 4.7 (Adaptive)?

Claude Opus 4.7 (Adaptive) has a context window of 1M, which determines how much text it can process in a single interaction.

Related Resources

More from Anthropic LLM Pricing Comparison BenchLM Methodology The AI Race Which LLM Should I Use? Benchmark Explainers
Last updated: June 18, 2026 · Runtime metrics stay blank until BenchLM has a sourced snapshot.

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