Compare models

If you're unsure which model to use, start with Claude Opus 5.5 for most workloads. Use Claude Fable 5.1 for demanding reasoning and long-horizon agentic work, or when your evals on Claude Opus 5.5 at higher effort still fall short. All current models support text and image input, text output, multilingual capabilities, vision, and tool use. Each model's page lists the platforms it's available on.

Once you've picked a model, learn how to make your first API call. To understand how model IDs, aliases, and snapshots work, see Model IDs and versioning; for the reliable-knowledge and training-data cutoffs behind each model, see Anthropic's Transparency Hub.

Using the Models API

You can query model capabilities and token limits programmatically with the Models API. The response includes max_input_tokens, max_tokens, and a capabilities object for every available model.

Each model in the response also has a line field, which names the model line it belongs to. Claude Opus 4.5 and Claude Opus 4.6 both report opus. Use line to group models, for example, in a model picker. line is null when a model belongs to no line. Read line instead of inferring it from the model's id. Anthropic might add more lines, so don't treat the set of values as fixed.

Each model's capabilities object includes thinking.types.disabled, which reports whether the model accepts thinking: {type: "disabled"}, the setting that turns thinking off. supported is false when the model rejects "disabled" with a 400 error, and true on a model that doesn't support thinking. Even when supported is true, the API can still reject a "disabled" request for another reason. One such reason is an effort level that the model doesn't allow with thinking off.

Each model's capabilities object also includes server_tools, which reports whether the model accepts the web search and code execution tools. It doesn't cover other server tools, such as web fetch. server_tools.web_search.supported and server_tools.code_execution.supported are true when the model accepts at least one version of that tool, not necessarily every version. server_tools.supported is true when the model accepts at least one of the two tools. Even when a tool is supported, your organization's settings can still cause a request that uses it to fail. For example, an administrator can disable web search.

The top-level code_execution capability is a different check. It reports whether code that Claude runs in the code execution tool can call the request's other tools, as in programmatic tool calling. For Claude Haiku 4.5, for example, the Models API reports server_tools.code_execution.supported as true and code_execution.supported as false.

Prompt and output performance

Current Claude models excel in:

• Performance: Top-tier results in reasoning, coding, multilingual tasks, long-context handling, honesty, and image processing. See Prompting best practices for general and model-specific prompting guidance.
• Engaging responses: Claude models are ideal for applications that require rich, human-like interactions. If you prefer more concise responses, adjust your prompts to guide the model toward the desired output length. Refer to the prompt engineering guides for details.
• Output quality: When migrating from a previous model generation, you may notice larger improvements in overall performance. If you're on Claude Opus 5 or earlier, see the Claude Opus 5.5 migration guide.

Get started with Claude

If you're ready to start exploring what Claude can do for you, dive in! Whether you're a developer looking to integrate Claude into your applications or a user wanting to experience the power of AI firsthand, the following resources can help.

Looking to chat with Claude? Visit claude.ai. If you have questions, reach out to the support team or the Discord community.