Claude Opus 5

Claude Opus 5 is Anthropic’s current Opus model for complex agentic coding and enterprise work.

Verified model facts

Anthropic lists a 1M-token context window, 128K maximum output, May 2026 knowledge cutoff, adaptive thinking and text/image input.

Current status

It is active across the Claude API and major cloud platforms at $5/M input and $25/M output.

Best fit

It is best for difficult software engineering, enterprise agents, research and large-context professional analysis.

Limitations

It is still a premium proprietary model and can be unnecessarily expensive for routine workloads that Sonnet 5 can handle.

Claude Opus 5 capabilities and use cases

In addition, its main capabilities include 1M context, 128K output, Adaptive thinking, Coding, Agents and Vision. For example, common use cases include Software engineering, Enterprise agents, Deep research, Professional analysis and Long documents.

Who should consider Claude Opus 5?

In practice, this model may suit Complex coding, Enterprise agents, Deep reasoning, Long-context research and Professional workflows. Also, notable strengths include Strong current Opus model, 1M context, Large output limit and Broad cloud availability. However, review trade-offs such as May 2026 static cutoff without tools, Can still make reasoning or tool-use errors and Premium cost for high-volume workloads before adopting it.

Claude Opus 5 pricing and access

Meanwhile, $5.00 per 1M input tokens and $25.00 per 1M output tokens. Prompt cache reads cost $0.50/M and Batch API offers a 50% input/output discount. Current Claude API pricing is $5/M input and $25/M output, half the standard Fable 5.1 rate.

Official resources and verification

Use the official model website, official documentation and pricing or release source to confirm current availability, limits and pricing. Product details can change after publication, so rely on primary documentation for final decisions.

Compare with other AI models

Next, continue your research in the AI models directory, Anthropic models and General Purpose Language Model models. Compare providers, pricing, modalities and practical limitations side by side to choose the right model for your workflow.

How to evaluate Claude Opus 5 responsibly

First, test the model with a small set of realistic tasks before relying on it for production work. Also, check response quality, consistency, latency, supported file types, context limits and the effort required to review its output. For sensitive or regulated work, examine the provider’s privacy, data-retention, regional-processing and security documentation before submitting private information.

However, AI systems sometimes return incomplete, outdated or confidently incorrect information. Therefore, check important claims against trusted sources and test generated code before deployment. Pricing, quotas and model availability can also change without notice. Finally, revisit the official documentation before you plan a long-term integration or a large-volume workload.