Skip to main content

Claude Opus 4.7

AnthropicCurrentReleased Apr 16, 2026
Overall Score
93Prov. #4 of 109Verified #2 of 13
Arena Elo
N/A
Categories Ranked
3of 8
Price (1M tokens)
$5 in / $25 out
Speed
N/A
Context
1M
ProprietaryNon-Reasoning
Confidence
base

According to BenchLM.ai, Claude Opus 4.7 ranks #4 out of 109 models on the provisional leaderboard with an overall score of 93/100. It also ranks #2 out of 13 on the verified leaderboard. This places it among the top tier of AI models available in 2026, competing directly with the strongest models from leading AI labs.

Claude Opus 4.7 is a proprietary model with a 1M token context window. It processes queries without explicit chain-of-thought reasoning, offering faster response times and lower token usage.

BenchLM links it directly to Claude Opus 4.6 as the earlier related model in that lineage. This profile currently has 13 of 152 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 Agentic (#5). This performance profile makes it particularly effective for knowledge-intensive tasks like research, analysis, and factual Q&A.

Ranking Distribution

Category rank across 3 benchmark categories — sorted by best rank

Category Performance

Scores across all benchmark categories (0-100 scale)

Category Breakdown

Agentic

#5
90.0/ 100
Weight: 22%4 benchmarks
Terminal-Bench 2.0BrowseCompOSWorld-VerifiedGAIATAU-benchWebArena

Coding

#3
92.6/ 100
Weight: 20%3 benchmarks
SWE-bench VerifiedLiveCodeBenchSWE-bench ProSWE-RebenchSciCode

Reasoning

0.0/ 100
Weight: 17%0 benchmarks
MuSRLongBench v2MRCRv2ARC-AGI-2

Knowledge

#1
98.6/ 100
Weight: 12%4 benchmarks
GPQASuperGPQAMMLU-ProHLEFrontierScienceSimpleQA

Math

0.0/ 100
Weight: 5%0 benchmarks
AIME 2025BRUMO 2025MATH-500FrontierMath

Multilingual

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

Multimodal

0.0/ 100
Weight: 12%2 benchmarks
MMMU-ProOfficeQA Pro

Inst. Following

0.0/ 100
Weight: 5%0 benchmarks
IFEvalIFBench

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

Base entry

Related Earlier Model

Claude Opus 4.6

Frequently Asked Questions

How does Claude Opus 4.7 perform overall in AI benchmarks?

Claude Opus 4.7 currently ranks #4 out of 109 models on BenchLM's provisional leaderboard with an overall score of 93. It also ranks #2 out of 13 on the verified leaderboard. It is created by Anthropic and features a 1M context window.

Is Claude Opus 4.7 good for knowledge and understanding?

Claude Opus 4.7 ranks #1 out of 109 models in knowledge and understanding benchmarks with an average score of 98.6. It is among the top performers in this category.

Is Claude Opus 4.7 good for coding and programming?

Claude Opus 4.7 ranks #3 out of 109 models in coding and programming benchmarks with an average score of 92.6. It is among the top performers in this category.

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

Claude Opus 4.7 ranks #5 out of 109 models in agentic tool use and computer tasks benchmarks with an average score of 90. It is among the top performers in this category.

Is Claude Opus 4.7 good for multimodal and grounded tasks?

Claude Opus 4.7 has visible benchmark coverage in multimodal and grounded tasks, but BenchLM does not currently assign it a global category rank there.

Does Claude Opus 4.7 have full benchmark coverage on BenchLM?

Not yet. Claude Opus 4.7 currently has 13 published benchmark scores out of the 152 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?

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

Last updated: April 16, 2026 · Runtime metrics stay blank until BenchLM has a sourced snapshot.

Don't miss the next GPT moment

Which models moved up, what’s new, and what it costs. One email a week, 3-min read.

Free. One email per week.