Overview ↗
yesEditorial Notes
This is the essential reference for understanding the Claude model family and should be one of the first pages you read before building anything with the Anthropic API. Focus on the capability differences between model tiers (Haiku, Sonnet, Opus) as this directly impacts your cost, latency, and quality tradeoffs in production. Pay attention to context window sizes and maximum output token limits, since these constraints will shape your prompt design and chunking strategies. When comparing with OpenAI’s model lineup, note that Anthropic’s naming convention signals capability tier rather than generation number.
Original Documentation
Claude is a family of state-of-the-art large language models developed by Anthropic. This guide introduces the available models and compares their performance.
Choosing a model#
If you’re unsure which model to use, consider starting with Claude Opus 4.6 for the most complex tasks. It is the latest generation model with exceptional performance in coding and reasoning.
All current Claude models support text and image input, text output, multilingual capabilities, and vision. Models are available via the Claude API, AWS Bedrock, and Google Vertex AI.
Once you’ve picked a model, learn how to make your first API call.
Latest models comparison#
| Feature | Claude Opus 4.6 | Claude Sonnet 4.6 | Claude Haiku 4.5 |
|---|---|---|---|
| Description | The most intelligent model for building agents and coding | The best combination of speed and intelligence | The fastest model with near-frontier intelligence |
| Claude API ID | claude-opus-4-6 | claude-sonnet-4-6 | claude-haiku-4-5-20251001 |
| Claude API alias | claude-opus-4-6 | claude-sonnet-4-6 | claude-haiku-4-5 |
| AWS Bedrock ID | anthropic.claude-opus-4-6-v1 | anthropic.claude-sonnet-4-6 | anthropic.claude-haiku-4-5-20251001-v1:0 |
| GCP Vertex AI ID | claude-opus-4-6 | claude-sonnet-4-6 | claude-haiku-4-5@20251001 |
| Pricing1 | $5 / input MTok $25 / output MTok | $3 / input MTok $15 / output MTok | $1 / input MTok $5 / output MTok |
| Extended thinking | Yes | Yes | Yes |
| Adaptive thinking | Yes | Yes | No |
| Priority Tier | Yes | Yes | Yes |
| Comparative latency | Moderate | Fast | Fastest |
| Context window | 200K tokens / 1M tokens (beta)3 | 200K tokens / 1M tokens (beta)3 | 200K tokens |
| Max output | 128K tokens | 64K tokens | 64K tokens |
| Reliable knowledge cutoff | May 20252 | Aug 20252 | Feb 2025 |
| Training data cutoff | Aug 2025 | Jan 2026 | Jul 2025 |
1 - See the pricing page for complete pricing information including batch API discounts, prompt caching rates, extended thinking costs, and vision processing fees.
2 - Reliable knowledge cutoff indicates the date through which a model’s knowledge is most extensive and reliable. Training data cutoff is the broader date range of training data used. For more information, see Anthropic’s Transparency Hub.
3 - Claude Opus 4.6 and Sonnet 4.6 support a 1M token context window when using the context-1m-2025-08-07 beta header. Long context pricing applies to requests exceeding 200K tokens.
Models with the same snapshot date (e.g., 20240620) are identical across all platforms and do not change. The snapshot date in the model name ensures consistency and allows developers to rely on stable performance across different environments.
Starting with Claude Sonnet 4.5 and all subsequent models (including Claude Sonnet 4.6), AWS Bedrock and Google Vertex AI offer two endpoint types: global endpoints (dynamic routing for maximum availability) and regional endpoints (guaranteed data routing through specific geographic regions). For more information, see the third-party platform pricing section.
Legacy models
The following models are still available. Consider migrating to current models for improved performance:
| Feature | Claude Sonnet 4.5 | Claude Opus 4.5 | Claude Opus 4.1 | Claude Sonnet 4 | Claude Opus 4 | Claude Haiku 3 (deprecated) |
|---|---|---|---|---|---|---|
| Claude API ID | claude-sonnet-4-5-20250929 | claude-opus-4-5-20251101 | claude-opus-4-1-20250805 | claude-sonnet-4-20250514 | claude-opus-4-20250514 | claude-3-haiku-20240307 |
| Claude API alias | claude-sonnet-4-5 | claude-opus-4-5 | claude-opus-4-1 | claude-sonnet-4-0 | claude-opus-4-0 | — |
| AWS Bedrock ID | anthropic.claude-sonnet-4-5-20250929-v1:0 | anthropic.claude-opus-4-5-20251101-v1:0 | anthropic.claude-opus-4-1-20250805-v1:0 | anthropic.claude-sonnet-4-20250514-v1:0 | anthropic.claude-opus-4-20250514-v1:0 | anthropic.claude-3-haiku-20240307-v1:0 |
| GCP Vertex AI ID | claude-sonnet-4-5@20250929 | claude-opus-4-5@20251101 | claude-opus-4-1@20250805 | claude-sonnet-4@20250514 | claude-opus-4@20250514 | claude-3-haiku@20240307 |
| Pricing | $3 / input MTok $15 / output MTok | $5 / input MTok $25 / output MTok | $15 / input MTok $75 / output MTok | $3 / input MTok $15 / output MTok | $15 / input MTok $75 / output MTok | $0.25 / input MTok $1.25 / output MTok |
| Extended thinking | Yes | Yes | Yes | Yes | Yes | No |
| Priority Tier | Yes | Yes | Yes | Yes | Yes | No |
| Comparative latency | Fast | Moderate | Moderate | Fast | Moderate | Fast |
| Context window | 200K tokens / 1M tokens (beta)1 | 200K tokens | 200K tokens | 200K tokens / 1M tokens (beta)1 | 200K tokens | 200K tokens |
| Max output | 64K tokens | 64K tokens | 32K tokens | 64K tokens | 32K tokens | 4K tokens |
| Reliable knowledge cutoff | Jan 20252 | May 20252 | Jan 20252 | Jan 20252 | Jan 20252 | 3 |
| Training data cutoff | Jul 2025 | Aug 2025 | Mar 2025 | Mar 2025 | Mar 2025 | Aug 2023 |
Claude Haiku 3 (claude-3-haiku-20240307) is deprecated and will be retired on April 19, 2026. Migrate to Claude Haiku 4.5 before the retirement date. See model deprecations for details.
1 - Claude Sonnet 4.5 and Claude Sonnet 4 support a 1M token context window when using the context-1m-2025-08-07 beta header. Long context pricing applies to requests exceeding 200K tokens.
2 - Reliable knowledge cutoff indicates the date through which a model’s knowledge is most extensive and reliable. Training data cutoff is the broader date range of training data used.
3 - Some Haiku models have a single training data cutoff date.
Prompt and output performance#
Claude 4 models excel in:
Performance: Top-tier results in reasoning, coding, multilingual tasks, long-context handling, honesty, and image processing. See the Claude 4 blog post for more information.
Engaging responses: Claude models are ideal for applications that require rich, human-like interactions.
If you prefer more concise responses, you can adjust your prompts to guide the model toward the desired output length. Refer to the prompt engineering guides for details.
For prompting best practices, see the prompting best practices guide.
Output quality: When migrating from previous model generations to Claude 4, you may notice larger improvements in overall performance.
Migrating to Claude 4.6#
If you’re currently using older Claude models, consider migrating to Claude Opus 4.6 to take advantage of improved intelligence and enhanced capabilities. For detailed migration instructions, see Migrating to Claude 4.6.
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!
Explore Claude’s capabilities and development flow. Learn how to make your first API call in minutes. Craft and test powerful prompts directly in your browser.
If you have any questions or need assistance, don’t hesitate to reach out to the support team or consult the Discord community.