Claude

Claude Opus 5

ClaudeFlagship
ThinkingTool UseVisionStructured Output

About this model

Claude Opus 5 is Anthropic’s flagship model for demanding reasoning, coding, and long-horizon agentic work. It is particularly strong at end-to-end software tasks, code review and bug finding, visual analysis...

Performance Tier

Flagship

Claude Opus 5 is a flagship model from Claude : the most capable in their lineup.

Best-in-class model from this provider. Highest performance across benchmarks, ideal for demanding tasks.

Pricing

This model is included in Elosia plans
Premium

Highest cost level. A long conversation can quickly consume your monthly cap.

Typeper 1M tokens
Input (prompt)$5.00
Output (completion)$25.00
Cache read$0.500
Cache write$6.25

Capabilities

Context Length1.0M
Max Output Tokens128K
TokenizerClaude
Inputtext, image, file
Outputtext
Release DateJuly 24, 2026

Benchmarks

General Intelligence
MMLU
Not reported
GPQA Diamond
Not reported
Mathematics
MATH-500
Not reported
Programming
HumanEval
Not reported
SWE-bench Verified
96%
SWE-bench Multilingual
89.5%
Reasoning
IFEval
Not reported
ARC-AGI-2
90.4%
Humanity's Last Exam
56.3%

Where does Claude Opus 5 stand?

Compare its performance index against every other model.

View the performance leaderboard

Recommended Use Cases

CodingAnalysisResearchCreative Writing

Strengths

  • Best-in-class real-world software engineering (SWE-bench Verified 96.0%, SWE-bench Multilingual 89.5%)
  • Frontier abstract reasoning and expert knowledge (ARC-AGI-2 90.4%, Humanity's Last Exam 56.3%, 64.7% with tools)
  • Thinking on by default, with a low-to-max effort ladder for the hardest problems
  • Long-horizon agentic work with a 1M-token context, 128K output, and multimodal input (text and image)

Limitations

  • Premium pricing ($5 / $25 per million input / output tokens)
  • Anthropic's Opus 5 system card reports agentic and reasoning evals; the classic academic suite (MMLU, GPQA Diamond, MATH-500, HumanEval, IFEval) is not published
  • Higher time-to-first-token; slower than Sonnet/Haiku for latency-sensitive queries

Frequently asked questions

Resources

This model may use your data for training

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