Claude Opus 4.1

What is Claude Opus 4.1?

Claude Opus 4.1 is an AI model developed by Anthropic, classified as a large language model (LLM). It is a multimodal model, capable of processing text, images, and potentially other media types. As a proprietary model, it is available via Anthropic's cloud API. With a context window of 200K tokens, it is suitable for processing long documents such as contracts, books, and complete codebases.

Pricing & Costs in 2026

Claude Opus 4.1 is usage-based, priced at $15/1M input tokens and $75/1M output tokens. For context: 1 million tokens is approximately 750,000 words, or about 10 average-length books. The premium pricing reflects the model's frontier capabilities, recommended for complex reasoning, analysis, and generation tasks where quality takes priority over cost.

Benchmarks & Performance

We don't have detailed benchmark results for Claude Opus 4.1 yet. Benchmarks are updated weekly as new data becomes available from sources like Artificial Analysis, LM Arena, and LiveBench.

It's important to note that benchmarks measure specific aspects and don't capture the full user experience. Factors like instruction adherence, behavior in long conversations, and real-world task quality vary significantly between models and aren't always reflected in standard scores.

Recommended Use Cases

Claude Opus 4.1 is suitable for a wide range of AI applications: long document analysis (contracts, legal proceedings, codebases), automation with tool calling (API integration, databases, external systems), image and visual document analysis (OCR, diagrams, screenshots), multimodal processing combining text and images, complex reasoning, math problem solving, and logical analysis, text generation, summarization, translation, and general assistance.

Comparison with Alternatives

In the 2026 AI model ecosystem, Claude Opus 4.1 competes directly with similarly capable models. Key competitors include GPT (OpenAI), Gemini (Google), and open source models like Llama (Meta) and DeepSeek. The choice between models depends on the specific use case, budget, latency requirements, and need for features like multimodality and tool calling.

For a detailed side-by-side comparison, use our comparison tool or check the overall model ranking.