Claude Opus 4.6

Claude Opus 4.6 is an AI model verified from first-party Anthropic sources.

Claude Opus 4.6 verified specifications

Claude Opus 4.6 is Anthropic’s February 2026 Opus model for complex agentic tasks and long-horizon work, supporting 1M context and adaptive thinking. Its verified context or usage limit is 1000000 tokens, with 128000 tokens maximum output.

Claude Opus 4.6 pricing and access

Claude Opus 4.6 costs $5 per 1M input tokens and $25 per 1M output tokens, with separate prompt-cache rates and 50% Batch API discounts.

Claude Opus 4.6 best uses

Complex agents, Coding, Research, Long-context analysis, Professional reasoning.

Claude Opus 4.6 limitations

Anthropic recommends newer Opus versions, Extended-thinking controls are deprecated, Critical outputs need validation.

Claude Opus 4.6 capabilities and use cases

In addition, its main capabilities include 1M context, 128K output, Adaptive thinking, Vision, Tool use and Compaction support. For example, common use cases include Agentic workflows, Coding, Research, Enterprise analysis and Long conversations.

Who should consider Claude Opus 4.6?

In practice, this model may suit Complex agents, Coding, Research, Long-context analysis and Professional reasoning. Also, notable strengths include Large context, Strong agent capabilities and Mature ecosystem. However, review trade-offs such as Anthropic recommends newer Opus versions, Extended-thinking controls are deprecated and Critical outputs need validation before adopting it.

Claude Opus 4.6 pricing and access

Meanwhile, Claude Opus 4.6 costs $5 per 1M input tokens and $25 per 1M output tokens, with separate prompt-cache rates and 50% Batch API discounts. The API costs $5/M input and $25/M output; newer Opus releases use the same base token rates.

Official resources and verification

Use the official model website, official documentation, pricing or release source and additional primary 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 Reasoning 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 4.6 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.