* feat: add mem-search skill with progressive disclosure architecture Add comprehensive mem-search skill for accessing claude-mem's persistent cross-session memory database. Implements progressive disclosure workflow and token-efficient search patterns. Features: - 12 search operations (observations, sessions, prompts, by-type, by-concept, by-file, timelines, etc.) - Progressive disclosure principles to minimize token usage - Anti-patterns documentation to guide LLM behavior - HTTP API integration for all search functionality - Common workflows with composition examples Structure: - SKILL.md: Entry point with temporal trigger patterns - principles/: Progressive disclosure + anti-patterns - operations/: 12 search operation files 🤖 Generated with [Claude Code](https://claude.com/claude-code) Co-Authored-By: Claude <noreply@anthropic.com> * docs: add CHANGELOG entry for mem-search skill Document mem-search skill addition in Unreleased section with: - 100% effectiveness compliance metrics - Comparison to previous search skill implementation - Progressive disclosure architecture details - Reference to audit report documentation 🤖 Generated with [Claude Code](https://claude.com/claude-code) Co-Authored-By: Claude <noreply@anthropic.com> * docs: add mem-search skill audit report Add comprehensive audit report validating mem-search skill against Anthropic's official skill-creator documentation. Report includes: - Effectiveness metrics comparison (search vs mem-search) - Critical issues analysis for production readiness - Compliance validation across 6 key dimensions - Reference implementation guidance Result: mem-search achieves 100% compliance vs search's 67% 🤖 Generated with [Claude Code](https://claude.com/claude-code) Co-Authored-By: Claude <noreply@anthropic.com> * feat: Add comprehensive search architecture analysis document - Document current state of dual search architectures (HTTP API and MCP) - Analyze HTTP endpoints and MCP search server architectures - Identify DRY violations across search implementations - Evaluate the use of curl as the optimal approach for search - Provide architectural recommendations for immediate and long-term improvements - Outline action plan for cleanup, feature parity, DRY refactoring * refactor: Remove deprecated search skill documentation and operations * refactor: Reorganize documentation into public and context directories Changes: - Created docs/public/ for Mintlify documentation (.mdx files) - Created docs/context/ for internal planning and implementation docs - Moved all .mdx files and assets to docs/public/ - Moved all internal .md files to docs/context/ - Added CLAUDE.md to both directories explaining their purpose - Updated docs.json paths to work with new structure Benefits: - Clear separation between user-facing and internal documentation - Easier to maintain Mintlify docs in dedicated directory - Internal context files organized separately 🤖 Generated with [Claude Code](https://claude.com/claude-code) Co-Authored-By: Claude <noreply@anthropic.com> * Enhance session management and continuity in hooks - Updated new-hook.ts to clarify session_id threading and idempotent session creation. - Modified prompts.ts to require claudeSessionId for continuation prompts, ensuring session context is maintained. - Improved SessionStore.ts documentation on createSDKSession to emphasize idempotent behavior and session connection. - Refined SDKAgent.ts to detail continuation prompt logic and its reliance on session.claudeSessionId for unified session handling. --------- Co-authored-by: Claude <noreply@anthropic.com> Co-authored-by: Alex Newman <thedotmack@gmail.com>
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Models overview
Claude is a family of state-of-the-art large language models developed by Anthropic. This guide introduces our models and compares their performance with legacy models.
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Our best model for complex agents and coding* <Icon icon="inbox-in" iconType="thin" /> Text and image input
* <Icon icon="inbox-out" iconType="thin" /> Text output
* <Icon icon="book" iconType="thin" /> 200k context window (1M context beta available)
* <Icon icon="brain" iconType="thin" /> Highest intelligence across most tasks
Our fastest and most intelligent Haiku model
* <Icon icon="inbox-in" iconType="thin" /> Text and image input
* <Icon icon="inbox-out" iconType="thin" /> Text output
* <Icon icon="book" iconType="thin" /> 200k context window
* <Icon icon="zap" iconType="thin" /> Lightning-fast speed with extended thinking
Exceptional model for specialized complex tasks
* <Icon icon="inbox-in" iconType="thin" /> Text and image input
* <Icon icon="inbox-out" iconType="thin" /> Text output
* <Icon icon="book" iconType="thin" /> 200k context window
* <Icon icon="brain" iconType="thin" /> Superior reasoning capabilities
Model names
| Model | Claude API | AWS Bedrock | GCP Vertex AI |
|---|---|---|---|
| Claude Sonnet 4.5 | claude-sonnet-4-5-20250929 | anthropic.claude-sonnet-4-5-20250929-v1:0 | claude-sonnet-4-5@20250929 |
| Claude Sonnet 4 | claude-sonnet-4-20250514 | anthropic.claude-sonnet-4-20250514-v1:0 | claude-sonnet-4@20250514 |
| Claude Sonnet 3.7 | claude-3-7-sonnet-20250219 (claude-3-7-sonnet-latest) | anthropic.claude-3-7-sonnet-20250219-v1:0 | claude-3-7-sonnet@20250219 |
| Claude Haiku 4.5 | claude-haiku-4-5-20251001 | anthropic.claude-haiku-4-5-20251001-v1:0 | claude-haiku-4-5@20251001 |
| Claude Haiku 3.5 | claude-3-5-haiku-20241022 (claude-3-5-haiku-latest) | anthropic.claude-3-5-haiku-20241022-v1:0 | claude-3-5-haiku@20241022 |
| Claude Haiku 3 | claude-3-haiku-20240307 | anthropic.claude-3-haiku-20240307-v1:0 | claude-3-haiku@20240307 |
| Claude Opus 4.1 | claude-opus-4-1-20250805 | anthropic.claude-opus-4-1-20250805-v1:0 | claude-opus-4-1@20250805 |
| Claude Opus 4 | claude-opus-4-20250514 | anthropic.claude-opus-4-20250514-v1:0 | claude-opus-4@20250514 |
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 future models, 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.
Model aliases
For convenience during development and testing, we offer aliases for our model ids. These aliases automatically point to the most recent snapshot of a given model. When we release new model snapshots, we migrate aliases to point to the newest version of a model, typically within a week of the new release.
While aliases are useful for experimentation, we recommend using specific model versions (e.g., `claude-sonnet-4-5-20250929`) in production applications to ensure consistent behavior.| Model | Alias | Model ID |
|---|---|---|
| Claude Sonnet 4.5 | claude-sonnet-4-5 | claude-sonnet-4-5-20250929 |
| Claude Sonnet 4 | claude-sonnet-4-0 | claude-sonnet-4-20250514 |
| Claude Sonnet 3.7 | claude-3-7-sonnet-latest | claude-3-7-sonnet-20250219 |
| Claude Haiku 4.5 | claude-haiku-4-5 | claude-haiku-4-5-20251001 |
| Claude Haiku 3.5 | claude-3-5-haiku-latest | claude-3-5-haiku-20241022 |
| Claude Opus 4.1 | claude-opus-4-1 | claude-opus-4-1-20250805 |
| Claude Opus 4 | claude-opus-4-0 | claude-opus-4-20250514 |
Model comparison table
To help you choose the right model for your needs, we've compiled a table comparing the key features and capabilities of each model in the Claude family:
| Feature | Claude Sonnet 4.5 | Claude Sonnet 4 | Claude Sonnet 3.7 | Claude Opus 4.1 | Claude Opus 4 | Claude Haiku 4.5 | Claude Haiku 3.5 | Claude Haiku 3 |
|---|---|---|---|---|---|---|---|---|
| Description | Our best model for complex agents and coding | High-performance model | High-performance model with early extended thinking | Exceptional model for specialized complex tasks | Our previous flagship model | Our fastest and most intelligent Haiku model | Our fastest model | Fast and compact model for near-instant responsiveness |
| Strengths | Highest intelligence across most tasks with exceptional agent and coding capabilities | High intelligence and balanced performance | High intelligence with toggleable extended thinking | Very high intelligence and capability for specialized tasks | Very high intelligence and capability | Near-frontier intelligence at blazing speeds with extended thinking and exceptional cost-efficiency | Intelligence at blazing speeds | Quick and accurate targeted performance |
| Multilingual | Yes | Yes | Yes | Yes | Yes | Yes | Yes | Yes |
| Vision | Yes | Yes | Yes | Yes | Yes | Yes | Yes | Yes |
| Extended thinking | Yes | Yes | Yes | Yes | Yes | Yes | No | No |
| Priority Tier | Yes | Yes | Yes | Yes | Yes | Yes | Yes | No |
| API model name | claude-sonnet-4-5-20250929 | claude-sonnet-4-20250514 | claude-3-7-sonnet-20250219 | claude-opus-4-1-20250805 | claude-opus-4-20250514 | claude-haiku-4-5-20251001 | claude-3-5-haiku-20241022 | claude-3-haiku-20240307 |
| Comparative latency | Fast | Fast | Fast | Moderately Fast | Moderately Fast | Fastest | Fastest | Fast |
| Context window | 200K / 1M (beta)1 |
200K / 1M (beta)1 |
200K | 200K | 200K | 200K | 200K | 200K |
| Max output | 64000 tokens | 64000 tokens | 64000 tokens | 32000 tokens | 32000 tokens | 64000 tokens | 8192 tokens | 4096 tokens |
| Reliable knowledge cutoff | Jan 20252 | Jan 20252 | Oct 20242 | Jan 20252 | Jan 20252 | Feb 2025 | 3 | 3 |
| Training data cutoff | Jul 2025 | Mar 2025 | Nov 2024 | Mar 2025 | Mar 2025 | Jul 2025 | Jul 2024 | Aug 2023 |
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. For example, Claude Sonnet 4.5 was trained on publicly available information through July 2025, but its knowledge is most extensive and reliable through January 2025. For more information, see Anthropic's Transparency Hub.
3 - Some Haiku models have a single training data cutoff date.
Include the beta header `output-128k-2025-02-19` in your API request to increase the maximum output token length to 128k tokens for Claude Sonnet 3.7.We strongly suggest using our streaming Messages API to avoid timeouts when generating longer outputs. See our guidance on long requests for more details.
Model pricing
The table below shows the price per million tokens for each model:
| Model | Base Input Tokens | 5m Cache Writes | 1h Cache Writes | Cache Hits & Refreshes | Output Tokens |
|---|---|---|---|---|---|
| Claude Opus 4.1 | $15 / MTok | $18.75 / MTok | $30 / MTok | $1.50 / MTok | $75 / MTok |
| Claude Opus 4 | $15 / MTok | $18.75 / MTok | $30 / MTok | $1.50 / MTok | $75 / MTok |
| Claude Sonnet 4.5 | $3 / MTok | $3.75 / MTok | $6 / MTok | $0.30 / MTok | $15 / MTok |
| Claude Sonnet 4 | $3 / MTok | $3.75 / MTok | $6 / MTok | $0.30 / MTok | $15 / MTok |
| Claude Sonnet 3.7 | $3 / MTok | $3.75 / MTok | $6 / MTok | $0.30 / MTok | $15 / MTok |
| Claude Sonnet 3.5 (deprecated) | $3 / MTok | $3.75 / MTok | $6 / MTok | $0.30 / MTok | $15 / MTok |
| Claude Haiku 4.5 | $1 / MTok | $1.25 / MTok | $2 / MTok | $0.10 / MTok | $5 / MTok |
| Claude Haiku 3.5 | $0.80 / MTok | $1 / MTok | $1.6 / MTok | $0.08 / MTok | $4 / MTok |
| Claude Opus 3 (deprecated) | $15 / MTok | $18.75 / MTok | $30 / MTok | $1.50 / MTok | $75 / MTok |
| Claude Haiku 3 | $0.25 / MTok | $0.30 / MTok | $0.50 / MTok | $0.03 / MTok | $1.25 / MTok |
Prompt and output performance
Claude 4 models excel in:
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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.
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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 our prompt engineering guides for details.
- For specific Claude 4 prompting best practices, see our Claude 4 best practices guide.
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Output quality: When migrating from previous model generations to Claude 4, you may notice larger improvements in overall performance.
Migrating to Claude 4.5
If you're currently using Claude 3 models, we recommend migrating to Claude 4.5 to take advantage of improved intelligence and enhanced capabilities. For detailed migration instructions, see Migrating to Claude 4.5.
Get started with Claude
If you're ready to start exploring what Claude can do for you, let's 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, we've got you covered.
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 our support team or consult the Discord community.