promptfoo--promptfoo/site/docs/providers/anthropic.md

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2	Deploy Anthropic's Claude models including Opus, Sonnet, and Haiku for advanced reasoning and conversational AI applications

Anthropic

This provider supports the Anthropic Claude series of models.

Note: Anthropic models can also be accessed through Azure AI Foundry, AWS Bedrock, and Google Vertex.

:::tip Agentic Evals For agentic evaluations that need built-in file access and skill plugins on top of the Messages API, see the Claude Agent SDK provider. The Messages provider documented here speaks directly to MCP servers via the mcp config so you can plug in your own tools without changing providers. :::

Setup

To use Anthropic, you need to set the ANTHROPIC_API_KEY environment variable or specify the apiKey in the provider configuration.

Create Anthropic API keys here.

Example of setting the environment variable:

export ANTHROPIC_API_KEY=your_api_key_here

Authenticating via a Claude Code session

If you already have an active Claude Code session (for example as a Claude Pro or Max subscriber), you can reuse its OAuth credential instead of creating a separate Anthropic Console API key. Set apiKeyRequired: false on the provider config:

providers:
  - id: anthropic:messages:claude-sonnet-4-6
    config:
      apiKeyRequired: false

When apiKeyRequired is false and no ANTHROPIC_API_KEY is available, Promptfoo loads the Claude Code OAuth credential from:

1. The macOS keychain entry Claude Code-credentials (darwin only), then
2. $HOME/.claude/.credentials.json on Linux and macOS, or %USERPROFILE%\.claude\.credentials.json on Windows.

Set CLAUDE_CONFIG_DIR to read the credential from a different Claude Code profile — the same environment variable the Claude Code CLI itself uses to relocate ~/.claude. It can be set in your shell, in the config's top-level env: block, or in a provider's env: block (the provider-scoped value wins). On macOS, where Claude Code stores credentials in the system keychain, Promptfoo mirrors the CLI's profile-specific keychain entry: when CLAUDE_CONFIG_DIR is set, the credential is looked up under that profile's keychain service (derived from the configured directory) rather than the default one, so evals authenticate as the profile you selected.

Promptfoo authenticates requests with a Bearer token, sends the claude-code-20250219,oauth-2025-04-20 beta headers, and prepends the required Claude Code identity system block ("You are Claude Code, Anthropic's official CLI for Claude.") to every Messages request. Your own system prompt is still forwarded as the next system block.

If you haven't logged in yet, run claude /login to create a credential. Re-run it if Promptfoo warns that the credential has expired. Requests made this way are expected to count against your Claude subscription the same way calls from the Claude Code CLI do — check Anthropic's documentation for current billing behavior.

This also enables model-graded assertions such as llm-rubric to run without a separate Anthropic Console key — see the example below.

Models

The anthropic provider supports the following models via the messages API:

Model ID	Description
anthropic:messages:claude-fable-5	Claude Fable 5
anthropic:messages:claude-mythos-5	Claude Mythos 5
anthropic:messages:claude-opus-4-8	Claude 4.8 Opus
anthropic:messages:claude-opus-4-7	Claude 4.7 Opus
anthropic:messages:claude-sonnet-5	Claude Sonnet 5
anthropic:messages:claude-sonnet-4-6	Claude 4.6 Sonnet
anthropic:messages:claude-opus-4-6	Claude 4.6 Opus
anthropic:messages:claude-opus-4-5-20251101 (claude-opus-4-5-latest)	Claude 4.5 Opus
anthropic:messages:claude-opus-4-1-20250805 (claude-opus-4-1-latest)	Claude 4.1 Opus
anthropic:messages:claude-opus-4-20250514 (claude-opus-4-latest)	Claude 4 Opus
anthropic:messages:claude-sonnet-4-5-20250929 (claude-sonnet-4-5-latest)	Claude 4.5 Sonnet
anthropic:messages:claude-sonnet-4-20250514 (claude-sonnet-4-latest)	Claude 4 Sonnet
anthropic:messages:claude-haiku-4-5-20251001 (claude-haiku-4-5-latest)	Claude 4.5 Haiku
anthropic:messages:claude-3-7-sonnet-20250219 (claude-3-7-sonnet-latest)	Claude 3.7 Sonnet
anthropic:messages:claude-3-5-sonnet-20241022 (claude-3-5-sonnet-latest)	Claude 3.5 Sonnet (v2)
anthropic:messages:claude-3-5-sonnet-20240620	Claude 3.5 Sonnet (v1)
anthropic:messages:claude-3-5-haiku-20241022 (claude-3-5-haiku-latest)	Claude 3.5 Haiku
anthropic:messages:claude-3-opus-20240229 (claude-3-opus-latest)	Claude 3 Opus
anthropic:messages:claude-3-haiku-20240307	Claude 3 Haiku

Cross-Platform Model Availability

Claude models are available across multiple platforms. Here's how the model names map across different providers:

Model	Anthropic API	Azure AI Foundry (docs)	AWS Bedrock (docs)	GCP Vertex AI (docs)
Claude Fable 5	claude-fable-5	claude-fable-5	anthropic.claude-fable-5	claude-fable-5
Claude Mythos 5	claude-mythos-5	Not available	anthropic.claude-mythos-5 (limited)	Limited availability; ID not public
Claude 4.8 Opus	claude-opus-4-8	claude-opus-4-8	anthropic.claude-opus-4-8	claude-opus-4-8
Claude 4.7 Opus	claude-opus-4-7	claude-opus-4-7	anthropic.claude-opus-4-7	claude-opus-4-7
Claude Sonnet 5	claude-sonnet-5	claude-sonnet-5	anthropic.claude-sonnet-5	claude-sonnet-5
Claude 4.6 Sonnet	claude-sonnet-4-6	claude-sonnet-4-6	anthropic.claude-sonnet-4-6	claude-sonnet-4-6
Claude 4.6 Opus	claude-opus-4-6	claude-opus-4-6-20260205	anthropic.claude-opus-4-6-v1	claude-opus-4-6
Claude 4.5 Opus	claude-opus-4-5-20251101 (claude-opus-4-5-latest)	claude-opus-4-5-20251101	anthropic.claude-opus-4-5-20251101-v1:0	claude-opus-4-5@20251101
Claude 4.5 Sonnet	claude-sonnet-4-5-20250929 (claude-sonnet-4-5-latest)	claude-sonnet-4-5-20250929	anthropic.claude-sonnet-4-5-20250929-v1:0	claude-sonnet-4-5@20250929
Claude 4.5 Haiku	claude-haiku-4-5-20251001 (claude-haiku-4-5-latest)	claude-haiku-4-5-20251001	anthropic.claude-haiku-4-5-20251001-v1:0	claude-haiku-4-5@20251001
Claude 4.1 Opus	claude-opus-4-1-20250805	claude-opus-4-1-20250805	anthropic.claude-opus-4-1-20250805-v1:0	claude-opus-4-1@20250805
Claude 4 Opus	claude-opus-4-20250514 (claude-opus-4-latest)	claude-opus-4-20250514	anthropic.claude-opus-4-20250514-v1:0	claude-opus-4@20250514
Claude 4 Sonnet	claude-sonnet-4-20250514 (claude-sonnet-4-latest)	claude-sonnet-4-20250514	anthropic.claude-sonnet-4-20250514-v1:0	claude-sonnet-4@20250514
Claude 3.7 Sonnet	claude-3-7-sonnet-20250219 (claude-3-7-sonnet-latest)	claude-3-7-sonnet-20250219	anthropic.claude-3-7-sonnet-20250219-v1:0	claude-3-7-sonnet@20250219
Claude 3.5 Sonnet	claude-3-5-sonnet-20241022 (claude-3-5-sonnet-latest)	claude-3-5-sonnet-20241022	anthropic.claude-3-5-sonnet-20241022-v2:0	claude-3-5-sonnet-v2@20241022
Claude 3.5 Haiku	claude-3-5-haiku-20241022 (claude-3-5-haiku-latest)	claude-3-5-haiku-20241022	anthropic.claude-3-5-haiku-20241022-v1:0	claude-3-5-haiku@20241022
Claude 3 Opus	claude-3-opus-20240229 (claude-3-opus-latest)	claude-3-opus-20240229	anthropic.claude-3-opus-20240229-v1:0	claude-3-opus@20240229
Claude 3 Haiku	claude-3-haiku-20240307	claude-3-haiku-20240307	anthropic.claude-3-haiku-20240307-v1:0	claude-3-haiku@20240307

Supported Parameters

Config Property	Environment Variable	Description
apiKey	ANTHROPIC_API_KEY	Your API key from Anthropic
apiKeyRequired	-	Skip the API key preflight and authenticate via a local Claude Code session
apiBaseUrl	ANTHROPIC_BASE_URL	The base URL for requests to the Anthropic API
temperature	ANTHROPIC_TEMPERATURE	Controls the randomness of the output (default: 0). Omitted when top_p is set.
max_tokens	ANTHROPIC_MAX_TOKENS	The maximum length of the generated text (default: 1024)
cost	-	Legacy per-token override applied to both input and output pricing
inputCost	-	Override input token pricing in promptfoo cost estimates
outputCost	-	Override output token pricing in promptfoo cost estimates
top_p	-	Controls nucleus sampling. Mutually exclusive with temperature.
top_k	-	Only sample from the top K options for each subsequent token
stop_sequences	-	Array of strings that will stop generation when encountered
stream	-	Enable streaming (required when max_tokens > 21,333)
tools	-	An array of tool or function definitions for the model to call
tool_choice	-	An object specifying the tool to call
effort	-	Output effort level: low, medium, high, xhigh, or max
output_format	-	JSON schema configuration for structured outputs
thinking	-	Configuration for Claude's extended thinking (enabled, adaptive, or disabled)
showThinking	-	Whether to include thinking content in the output (default: true)
cache_control	-	Auto-apply cache_control to the last cacheable block in the request
metadata	-	Request metadata such as user_id for tracking purposes
service_tier	-	Priority tier: auto (default) or standard_only
headers	-	Additional headers to be sent with the API request
extra_body	-	Additional parameters to be included in the API request body

Prompt Template

To allow for compatibility with the OpenAI prompt template, the following format is supported:

[
  {
    "role": "system",
    "content": "{{ system_message }}"
  },
  {
    "role": "user",
    "content": "{{ question }}"
  }
]

If the role system is specified, it will be automatically added to the API request. All user or assistant roles will be automatically converted into the right format for the API request. Currently, only type text is supported.

The system_message and question are example variables that can be set with the var directive.

Options

The Anthropic provider supports several options to customize the behavior of the model. These include:

• temperature: Controls the randomness of the output.
• max_tokens: The maximum length of the generated text.
• top_p: Controls nucleus sampling, affecting the randomness of the output.
• top_k: Only sample from the top K options for each subsequent token.
• tools: An array of tool or function definitions for the model to call.
• tool_choice: An object specifying the tool to call.
• stop_sequences: An array of strings that stop generation when encountered.
• metadata: Request metadata (e.g., user_id) passed to the API.
• extra_body: Additional parameters to pass directly to the Anthropic API request body.
• mcp: Connect to one or more Model Context Protocol servers. Tools exposed by the server become callable by Claude.
• max_tool_calls: Maximum number of MCP tool executions promptfoo will perform per request before aborting the loop. Defaults to 8 and is only relevant when mcp.enabled is true.

Example configuration with options and prompts:

providers:
  - id: anthropic:messages:claude-sonnet-4-5-20250929
    config:
      temperature: 0.0
      max_tokens: 512
      extra_body:
        custom_param: 'test_value'
prompts:
  - file://prompt.json

Stop Sequences

Use stop_sequences to halt generation when Claude encounters specific strings:

providers:
  - id: anthropic:messages:claude-sonnet-4-5-20250929
    config:
      stop_sequences:
        - "\n\nHuman:"
        - 'STOP'

Metadata

Pass request metadata to the API for tracking or auditing purposes:

providers:
  - id: anthropic:messages:claude-sonnet-4-5-20250929
    config:
      metadata:
        user_id: 'user-123'

Tool Calling

The Anthropic provider supports tool calling (function calling). Here's an example configuration for defining tools.

providers:
  - id: anthropic:messages:claude-sonnet-4-5-20250929
    config:
      tools:
        - name: get_weather
          description: Get the current weather in a given location
          input_schema:
            type: object
            properties:
              location:
                type: string
                description: The city and state, e.g., San Francisco, CA
              unit:
                type: string
                enum:
                  - celsius
                  - fahrenheit
            required:
              - location

Web Search and Web Fetch Tools

Anthropic provides specialized tools for web search and web fetching capabilities:

Web Fetch Tool

The web fetch tool allows Claude to retrieve full content from web pages and PDF documents. This is useful when you want Claude to access and analyze specific web content.

providers:
  - id: anthropic:messages:claude-sonnet-4-5-20250929
    config:
      tools:
        - type: web_fetch_20250910
          name: web_fetch
          max_uses: 5
          allowed_domains:
            - docs.example.com
            - help.example.com
          citations:
            enabled: true
          max_content_tokens: 50000

Promptfoo also supports the stable web_fetch_20260209 variant. A newer version web_fetch_20260309 adds use_cache support for controlling whether cached content is used:

providers:
  - id: anthropic:messages:claude-sonnet-4-5-20250929
    config:
      tools:
        - type: web_fetch_20260209
          name: web_fetch
          max_uses: 3
          defer_loading: true
        - type: web_fetch_20260309
          name: web_fetch
          max_uses: 3
          use_cache: false # Bypass cache for fresh content

Web Fetch Tool Configuration Options:

Parameter	Type	Description
type	string	web_fetch_20250910 (beta), web_fetch_20260209, or web_fetch_20260309 (adds use_cache)
name	string	Must be web_fetch
max_uses	number	Maximum number of web fetches per request (optional)
allowed_callers	string[]	Restrict which tool callers may invoke the server tool (optional)
allowed_domains	string[]	List of domains to allow fetching from (optional, mutually exclusive with blocked_domains)
blocked_domains	string[]	List of domains to block fetching from (optional, mutually exclusive with allowed_domains)
defer_loading	boolean	Load the tool lazily instead of including it in the initial system prompt (optional)
citations	object	Enable citations with { enabled: true } (optional)
max_content_tokens	number	Maximum tokens for web content (optional)
cache_control	object	Apply Anthropic cache control to the tool definition (optional)
strict	boolean	Enable strict schema validation for tool names and inputs (optional)
use_cache	boolean	Whether to use cached content (web_fetch_20260309 only, optional)

Web Search Tool

The web search tool allows Claude to search the internet for information:

providers:
  - id: anthropic:messages:claude-sonnet-4-5-20250929
    config:
      tools:
        - type: web_search_20260209
          name: web_search
          max_uses: 3

Web Search Tool Configuration Options:

Parameter	Type	Description
type	string	web_search_20250305 (beta) or web_search_20260209
name	string	Must be web_search
max_uses	number	Maximum number of searches per request (optional)
allowed_callers	string[]	Restrict which tool callers may invoke the server tool (optional)
allowed_domains	string[]	Restrict results to specific domains (optional, mutually exclusive with blocked_domains)
blocked_domains	string[]	Exclude domains from results (optional, mutually exclusive with allowed_domains)
cache_control	object	Apply Anthropic cache control to the tool definition (optional)
defer_loading	boolean	Load the tool lazily instead of including it in the initial system prompt (optional)
strict	boolean	Enable strict schema validation for tool names and inputs (optional)
user_location	object	Approximate user location to improve search relevance (optional)

Combined Web Search and Web Fetch

You can use both tools together for comprehensive web information gathering:

providers:
  - id: anthropic:messages:claude-sonnet-4-5-20250929
    config:
      tools:
        - type: web_search_20260209
          name: web_search
          max_uses: 3
        - type: web_fetch_20260309
          name: web_fetch
          max_uses: 5
          citations:
            enabled: true

This configuration allows the model to first search for relevant information, then fetch full content from the most promising results.

Memory Tool

Anthropic's memory_20250818 tool can be included in tools. Promptfoo passes this native tool definition through unchanged, which is useful for evaluating whether a model requests memory operations. Promptfoo does not manage Anthropic memory stores or run local memory handlers for you.

providers:
  - id: anthropic:messages:claude-sonnet-4-6
    config:
      tools:
        - type: memory_20250818
          name: memory
          allowed_callers:
            - direct

Memory Tool Configuration Options:

Parameter	Type	Description
type	string	Must be memory_20250818
name	string	Must be memory
allowed_callers	string[]	Restrict which tool callers may invoke the memory tool (optional)
cache_control	object	Apply Anthropic cache control to the tool definition (optional)
defer_loading	boolean	Load the tool lazily instead of including it in the initial prompt
input_examples	object[]	Example memory commands to include in the tool definition (optional)
strict	boolean	Enable strict schema validation for tool names and inputs (optional)

Important Security Notes:

• The web fetch tool requires trusted environments due to potential data exfiltration risks
• The model cannot dynamically construct URLs - only URLs provided by users or from search results can be fetched
• Use domain filtering to restrict access to specific sites:
  • Use allowed_domains to whitelist trusted domains (recommended)
  • Use blocked_domains to blacklist specific domains
  • Note: Only one of allowed_domains or blocked_domains can be specified, not both

Model Context Protocol (MCP)

The Anthropic Messages provider can connect to any MCP server — stdio, SSE, or streamable HTTP — and execute the model's tool_use blocks against that server, feeding the tool_result back into the conversation until Claude produces a final reply.

providers:
  - id: anthropic:messages:claude-sonnet-4-6
    config:
      mcp:
        enabled: true
        # Inline command-based stdio server, or `path` to a local script
        server:
          command: npx
          args: ['-y', '@modelcontextprotocol/server-filesystem', '/tmp/workspace']
        # Or use a remote SSE / streamable HTTP server
        # servers:
        #   - name: deepwiki
        #     url: https://mcp.deepwiki.com/mcp
      # Optional cap on MCP rounds per request (default 8). Enforced locally;
      # not sent to Anthropic.
      max_tool_calls: 5

How it works:

• Tools discovered on the MCP server are passed to Claude alongside any inline tools.
• When Claude returns a tool_use block whose name matches an MCP tool, promptfoo calls the tool with the model's arguments and appends a matching tool_result block on the user turn.
• The loop repeats until Claude returns text (no more tool_use) or max_tool_calls is hit. Tool errors are forwarded as tool_result blocks with is_error: true so the model can recover.
• Non-MCP tool_use blocks (regular function tools, or built-ins like web_search) are passed through to the existing output and not auto-executed.

:::note Response caching with MCP The disk response cache is skipped while mcp.enabled is true, because tool results can be non-deterministic between runs. Use max_tool_calls to bound spend. :::

See the MCP integration guide for full server configuration options (auth, timeouts, multiple servers, etc.) and the Anthropic MCP example.

See the Anthropic Tool Use Guide for more information on how to define tools and the tool use example here.

Images / Vision

You can include images in the prompts in Claude 3 models.

See the Claude vision example.

One important note: The Claude API only supports base64 representations of images. This is different from how OpenAI's vision works, as it supports grabbing images from a URL. As a result, if you are trying to compare Claude 3 and OpenAI vision capabilities, you will need to have separate prompts for each.

See the OpenAI vision example to understand the differences.

Prompt Caching

Claude supports prompt caching to optimize API usage and reduce costs for repetitive tasks. This feature caches portions of your prompts to avoid reprocessing identical content in subsequent requests.

Supported on all Claude 3, 3.5, and 4 models. Basic example:

providers:
  - id: anthropic:messages:claude-sonnet-4-5-20250929
prompts:
  - file://prompts.yaml

- role: system
  content:
    - type: text
      text: 'System message'
      cache_control:
        type: ephemeral
    - type: text
      text: '{{context}}'
      cache_control:
        type: ephemeral
- role: user
  content: '{{question}}'

As a simpler alternative, use the top-level cache_control parameter to automatically apply a cache marker to the last cacheable block in the request, without annotating each block individually:

providers:
  - id: anthropic:messages:claude-sonnet-4-5-20250929
    config:
      cache_control:
        type: ephemeral

Common use cases for caching:

• System messages and instructions
• Tool/function definitions
• Large context documents
• Frequently used images

Cache read and creation token counts are tracked in the response's token usage details.

See Anthropic's Prompt Caching Guide for more details on requirements, pricing, and best practices.

Citations

Claude can provide detailed citations when answering questions about documents. Basic example:

providers:
  - id: anthropic:messages:claude-sonnet-4-5-20250929
prompts:
  - file://prompts.yaml

- role: user
  content:
    - type: document
      source:
        type: text
        media_type: text/plain
        data: 'Your document text here'
      citations:
        enabled: true
    - type: text
      text: 'Your question here'

See Anthropic's Citations Guide for more details.

PDF Documents

Claude can process PDF files using document content blocks. Pass the PDF as base64-encoded data:

- role: user
  content:
    - type: document
      source:
        type: base64
        media_type: application/pdf
        data: '{{pdf_base64}}'
    - type: text
      text: 'Summarize this document'

Use a test var to supply the base64-encoded PDF content:

tests:
  - vars:
      pdf_base64: file://document.pdf

Claude Fable 5 and Mythos 5 notes

Fable 5 and Mythos 5 use always-on adaptive thinking. Promptfoo omits unsupported temperature, top_p, and top_k values, converts legacy thinking: { type: 'enabled', budget_tokens: N } configs to adaptive thinking, and omits thinking: { type: 'disabled' } because thinking cannot be disabled. Set thinking: { type: 'adaptive', display: 'summarized' } to include a readable thinking summary; the default display: 'omitted' returns an empty thinking block, which Promptfoo excludes from the output.

Both models use a 1M-token context window, support up to 128K output tokens, and are priced at $10 per million input tokens and $50 per million output tokens. Mythos 5 access is limited through Project Glasswing and may require provider approval. Both model IDs are pinned; Anthropic does not publish -latest aliases for them.

Claude Sonnet 5 notes

Sonnet 5 is the most agentic Sonnet model, with a 1M-token context window and support for effort levels (low through xhigh). Unlike Sonnet 4.5/4.6 — but like the Opus 4.7/4.8 and Fable 5 generation — it deprecates manual sampling controls at the model level:

• Sampling controls are managed for you. Sonnet 5 rejects temperature, top_p, and top_k with a 400; promptfoo omits all three from every request (including its built-in temperature: 0 default). Setting any of them in config or ANTHROPIC_TEMPERATURE logs a one-time heads-up. This suppression also applies when you reach Sonnet 5 through AWS Bedrock, GCP Vertex, or Azure AI Foundry.
• Manual thinking budgets convert to adaptive. A legacy thinking: { type: 'enabled', budget_tokens: N } config is converted to thinking: { type: 'adaptive' }; use effort to control reasoning depth.

Sonnet 5 uses a 1M-token context window billed at a flat $3 per million input / $15 per million output — the full context window bills at the standard rate, with no long-context surcharge above 200K tokens (a 900K-token request bills at the same per-token rate as a 9K-token request). Anthropic's launch introductory pricing ($2 / $10 through Aug 31, 2026) is not encoded in promptfoo's cost calculation; set an explicit cost in your provider config if you want to track the introductory rate.

Claude Opus 4.8 notes

Opus 4.8 is Anthropic's most capable model and builds directly on Opus 4.7 — it supports the same feature set, so the Opus 4.7 guidance below applies unchanged. Promptfoo handles the model-level differences automatically:

• Sampling controls are managed for you. Like Opus 4.7, Opus 4.8 samples adaptively and rejects temperature, top_p, and top_k (any of them returns a 400); promptfoo omits all three from every request. Setting any of them in config or ANTHROPIC_TEMPERATURE logs a one-time heads-up so you can clean the values out of your eval.
• Adaptive thinking is opt-in. Set thinking: { type: 'adaptive' } to let the model decide how much to reason per request. Without an explicit thinking block the model runs without extended thinking, even at high effort. Manual budget-based thinking (thinking: { type: 'enabled', budget_tokens: N }) is rejected with a 400.
• effort defaults to high and xhigh is available. Setting effort: high behaves the same as omitting it. Start with xhigh for coding and agentic work. See the Effort Level section.

The same suppression applies when you reach Opus 4.8 through AWS Bedrock, GCP Vertex, or Azure AI Foundry — promptfoo omits the unsupported sampling parameters on each of those paths too (silently; the one-time warning above is specific to the Anthropic Messages provider).

Claude Opus 4.7 notes

Opus 4.7 is designed around adaptive thinking and runs with the reasoning stack always on. Promptfoo handles the key differences from earlier Opus models automatically:

• Temperature is managed for you. Opus 4.7 samples adaptively and does not accept temperature; promptfoo omits the field from every request. Passing temperature in config or ANTHROPIC_TEMPERATURE logs a one-time heads-up so you can clean the value out of your eval.
• Adaptive thinking is the default. Use thinking: { type: 'adaptive' } (or leave thinking unset) to let the model choose how much to reason per request. Budget-based modes from older models aren't used on 4.7.
• xhigh effort level is available. It sits between high and max and is a good starting point for coding and agentic tasks. See the Effort Level section.
• Updated tokenizer. The same input can map to 1.0–1.35× more tokens than Opus 4.6, so measure real traffic if you're comparing costs.

The same guidance applies when you reach Opus 4.7 through AWS Bedrock, GCP Vertex, or Azure AI Foundry — promptfoo suppresses temperature on each of those paths as well.

Extended Thinking

Claude supports an extended thinking capability that allows you to see the model's internal reasoning process before it provides the final answer. This can be configured using the thinking parameter:

providers:
  # Adaptive thinking (recommended for Claude Opus 4.7)
  - id: anthropic:messages:claude-opus-4-7
    config:
      max_tokens: 20000
      thinking:
        type: 'adaptive'

  # Enabled thinking with explicit budget
  - id: anthropic:messages:claude-sonnet-4-5-20250929
    config:
      max_tokens: 20000
      thinking:
        type: 'enabled'
        budget_tokens: 16000 # Must be ≥1024 and less than max_tokens

The thinking configuration has three possible values:

1. Adaptive thinking (recommended for Claude Opus 4.7):

thinking:
  type: 'adaptive'

In adaptive mode, Claude decides when and how much to think based on the complexity of the request. This is the recommended mode for claude-opus-4-7.

2. Enabled thinking:

thinking:
  type: 'enabled'
  budget_tokens: number # Must be ≥1024 and less than max_tokens

3. Disabled thinking:

thinking:
  type: 'disabled'

The display field controls how thinking content is returned:

• 'summarized' (default) - thinking content is included in the response
• 'omitted' - thinking content is redacted but a signature is returned for multi-turn continuity (saves tokens)

thinking:
  type: enabled
  budget_tokens: 10000
  display: omitted

When thinking is enabled or adaptive:

• Responses will include thinking content blocks showing Claude's reasoning process
• Requires a minimum budget of 1,024 tokens
• The budget_tokens value must be less than the max_tokens parameter
• The tokens used for thinking count towards your max_tokens limit
• A specialized 28 or 29 token system prompt is automatically included
• Previous turn thinking blocks are ignored and not counted as input tokens
• temperature and top_k are incompatible with thinking and will be omitted with a warning
• top_p is clamped to the range [0.95, 1.0] when thinking is enabled
• Forced tool use (tool_choice type any or tool) is incompatible with thinking and will be omitted with a warning; use auto instead

Example response with thinking enabled:

{
  "content": [
    {
      "type": "thinking",
      "thinking": "Let me analyze this step by step...",
      "signature": "WaUjzkypQ2mUEVM36O2TxuC06KN8xyfbJwyem2dw3URve/op91XWHOEBLLqIOMfFG/UvLEczmEsUjavL...."
    },
    {
      "type": "text",
      "text": "Based on my analysis, here is the answer..."
    }
  ]
}

Controlling Thinking Output

By default, thinking content is included in the response output. You can control this behavior using the showThinking parameter:

providers:
  - id: anthropic:messages:claude-sonnet-4-5-20250929
    config:
      thinking:
        type: 'enabled'
        budget_tokens: 16000
      showThinking: false # Exclude thinking content from the output

When showThinking is set to false, the thinking content will be excluded from the output, and only the final response will be returned. This is useful when you want to use thinking for better reasoning but don't want to expose the thinking process to end users.

Redacted Thinking

Sometimes Claude's internal reasoning may be flagged by safety systems. When this occurs, the thinking block will be encrypted and returned as a redacted_thinking block:

{
  "content": [
    {
      "type": "redacted_thinking",
      "data": "EmwKAhgBEgy3va3pzix/LafPsn4aDFIT2Xlxh0L5L8rLVyIwxtE3rAFBa8cr3qpP..."
    },
    {
      "type": "text",
      "text": "Based on my analysis..."
    }
  ]
}

Redacted thinking blocks are automatically decrypted when passed back to the API, allowing Claude to maintain context without compromising safety guardrails.

Extended Output with Thinking

Claude 4 models provide enhanced output capabilities and extended thinking support:

providers:
  - id: anthropic:messages:claude-sonnet-4-5-20250929
    config:
      max_tokens: 64000 # Claude 4 Sonnet supports up to 64K output tokens
      thinking:
        type: 'enabled'
        budget_tokens: 32000

Note: The output-128k-2025-02-19 beta feature is specific to Claude 3.7 Sonnet and is not needed for Claude 4 models, which have improved output capabilities built-in.

When using extended output:

• Streaming is required when max_tokens is greater than 21,333
• For thinking budgets above 32K, batch processing is recommended
• The model may not use the entire allocated thinking budget

See Anthropic's Extended Thinking Guide for more details on requirements and best practices.

Effort Level

The effort parameter controls the output quality/speed tradeoff. Higher effort levels may produce more thorough responses but take longer:

providers:
  - id: anthropic:messages:claude-opus-4-7
    config:
      effort: xhigh # Options: low, medium, high, xhigh, max

Claude Opus 4.7 introduces the xhigh level between high and max, giving finer control over reasoning/latency on hard problems. For coding and agentic use cases, Anthropic recommends starting with high or xhigh.

This can be combined with other features like structured outputs:

providers:
  - id: anthropic:messages:claude-opus-4-7
    config:
      effort: high
      output_format:
        type: json_schema
        schema:
          type: object
          properties:
            analysis:
              type: string
          required:
            - analysis
          additionalProperties: false

Structured Outputs

Structured outputs constrain Claude's responses to a JSON schema. Supported on Claude Opus 4.7, Opus 4.6, Sonnet 4.6, and Sonnet 4.5+ / Opus 4.1+.

JSON Outputs

Add output_format to get structured responses:

providers:
  - id: anthropic:messages:claude-sonnet-4-5-20250929
    config:
      output_format:
        type: json_schema
        schema:
          type: object
          properties:
            name:
              type: string
            email:
              type: string
          required:
            - name
            - email
          additionalProperties: false

You can also load the entire output_format from an external file:

config:
  output_format: file://./schemas/analysis-format.json

Nested file references are supported for the schema:

{
  "type": "json_schema",
  "schema": "file://./schemas/analysis-schema.json"
}

Variable rendering is supported in file paths:

config:
  output_format: file://./schemas/{{ schema_name }}.json

Strict Tool Use

Add strict: true to tool definitions for schema-validated parameters:

providers:
  - id: anthropic:messages:claude-sonnet-4-5-20250929
    config:
      tools:
        - name: get_weather
          strict: true
          input_schema:
            type: object
            properties:
              location:
                type: string
            required:
              - location
            additionalProperties: false

Limitations

Supported: object, array, string, integer, number, boolean, null, enum, required, additionalProperties: false

Not supported: recursive schemas, minimum/maximum, minLength/maxLength

Incompatible with: citations, message prefilling

See Anthropic's guide and the structured outputs example.

Model-Graded Tests

Model-graded assertions such as factuality or llm-rubric will automatically use Anthropic as the grading provider if ANTHROPIC_API_KEY is set and OPENAI_API_KEY is not set.

If both API keys are present, OpenAI will be used by default. You can explicitly override the grading provider in your configuration.

Claude Pro/Max subscribers without a separate Anthropic Console key can wire up llm-rubric through a local Claude Code session by pointing the grader at anthropic:messages:<model> with apiKeyRequired: false:

defaultTest:
  options:
    provider:
      id: anthropic:messages:claude-sonnet-4-6
      config:
        apiKeyRequired: false

See Authenticating via a Claude Code session above for how the credential is loaded and what beta headers Promptfoo sets.

Because of how model-graded evals are implemented, the model must support chat-formatted prompts (except for embedding or classification models).

You can override the grading provider in several ways:

1. For all test cases using defaultTest:

defaultTest:
  options:
    provider: anthropic:messages:claude-sonnet-4-5-20250929

2. For individual assertions:

assert:
  - type: llm-rubric
    value: Do not mention that you are an AI or chat assistant
    provider:
      id: anthropic:messages:claude-sonnet-4-5-20250929
      config:
        temperature: 0.0

3. For specific tests:

tests:
  - vars:
      question: What is the capital of France?
    options:
      provider:
        id: anthropic:messages:claude-sonnet-4-5-20250929
    assert:
      - type: llm-rubric
        value: Answer should mention Paris

Additional Capabilities

• Caching: Promptfoo caches previous LLM requests by default.
• Token Usage Tracking: Provides detailed information on the number of tokens used in each request, aiding in usage monitoring and optimization.
• Cost Calculation: Calculates the cost of each request based on the number of tokens generated and the specific model used.

See Also

Examples

We provide several example implementations demonstrating Claude's capabilities:

Core Features

• Tool Use Example - Shows how to use Claude's tool calling capabilities
• MCP Example - Connect Claude to a Model Context Protocol server and let it execute the discovered tools
• Structured Outputs Example - Demonstrates JSON outputs and strict tool use for guaranteed schema compliance
• Vision Example - Demonstrates using Claude's vision capabilities

Model Comparisons & Evaluations

• Claude vs GPT - Compares Claude with GPT-5.4 on various tasks
• Claude vs GPT Image Analysis - Compares Claude's and GPT's image analysis capabilities

Cloud Platform Integrations

• Azure AI Foundry - Using Claude through Azure AI Foundry
• AWS Bedrock - Using Claude through AWS Bedrock
• Google Vertex AI - Using Claude through Google Vertex AI

Agentic Evaluations

• Claude Agent SDK - For agentic evals with file access, tool use, and MCP servers

For more examples and general usage patterns, visit our examples directory on GitHub.