Detailed explanation of Claude Opus 4.7 xhigh mode: A practical guide to 5 effort levels

description: A deep dive into the new Claude Opus 4.7 xhigh effort level, comparing performance across tiers and providing best practices for Agentic coding.

Author's Note: This is a comprehensive guide to the all-new xhigh effort level in Claude Opus 4.7. We'll compare the five tiers—low, medium, high, xhigh, and max—and provide best practices and code examples for programming and Agentic scenarios.

Many developers, after upgrading to Claude Opus 4.7, have noticed a new, unfamiliar value for the effort parameter: xhigh. It’s not the default high, nor is it the ceiling max. So, when should you actually use it? In this article, we’ll dive deep into the design principles, performance curves, and practical configurations of the Claude Opus 4.7 xhigh mode to help you find the sweet spot for "intelligence vs. cost" in Agentic coding and long-running tasks.

Core Value: By the end of this article, you'll understand the differences between xhigh and the other four effort tiers, when to switch, how to enable it in Claude Code and the Messages API, and how to avoid the common pitfalls of "over-reasoning" and "token waste."

Claude Opus 4.7 xhigh Mode: Key Takeaways

Design Motivation for Claude Opus 4.7 xhigh Mode

The introduction of xhigh solves a real pain point: in the Opus 4.6 era, developers running long-running Agentic programming tasks were forced to choose between high and max. high sometimes lacked the "depth" for complex multi-step reasoning, while max caused token usage to skyrocket, leading to uncontrollable costs. Anthropic designed this "long-range-leaning" effort level in 4.7 to ensure high-quality output during multi-turn tool calls, long-context retrieval, and cross-session memory, all while keeping token consumption within an acceptable range.

According to official internal Agentic Coding benchmark curves, Opus 4.7 scores approximately 71% at the xhigh level (consuming ~100k tokens), while the max level only improves that to ~74.5% (but consumes over 200k tokens). In other words, moving from xhigh to max only nets you an average 3% gain while nearly doubling your token costs. This is why xhigh has become the "officially recommended starting point."

Claude Opus 4.7 xhigh Mode: A Five-Level Comparison

The table below compares the official positioning and practical recommendations for all five effort levels of Opus 4.7:

🎯 Pro Tip: For programming tasks, I recommend starting your evaluation directly at xhigh, then deciding whether to scale up to max or down to high based on the results. You can use the APIYI (apiyi.com) platform to invoke the claude-opus-4-7 model directly and quickly compare the performance differences across effort levels. The platform provides a unified OpenAI-compatible interface, making it easy to toggle the effort parameter for testing.

Key Differences: Claude Opus 4.7 xhigh vs. high

Many people ask: If high is already the default, why do we need xhigh? There are three key differences:

First, the depth of reasoning. Under xhigh, Opus 4.7 triggers its adaptive thinking deep mode more frequently. The model will proactively reflect on intermediate results and backtrack on failed tool call paths. In contrast, high leans toward "getting it right the first time," which might skip deep thinking for tasks of moderate complexity.

Second, tool calling strategy. xhigh encourages the model to initiate more exploratory tool calls (e.g., grep, reading multiple files, tracing dependencies), whereas high tends to minimize calls to save tokens. For large-scale code refactoring or cross-file bug localization, the exploratory advantage of xhigh is significant.

Third, performance in long-range tasks. For Agentic tasks that run for over 30 minutes and involve millions of tokens, the stability of xhigh is significantly higher than high. The model is less likely to "lose its way" or terminate prematurely midway through the process.

Getting Started with Claude Opus 4.7 xhigh Mode

Minimal Invocation Example

Here is the minimal code (under 10 lines) to invoke the Opus 4.7 xhigh mode via the OpenAI-compatible interface:

import openai

client = openai.OpenAI(
    api_key="YOUR_API_KEY",
    base_url="https://vip.apiyi.com/v1"
)

response = client.chat.completions.create(
    model="claude-opus-4-7",
    messages=[{"role": "user", "content": "Help me refactor this Python code:..."}],
    extra_body={"effort": "xhigh"}
)
print(response.choices[0].message.content)

import anthropic

client = anthropic.Anthropic(api_key="YOUR_API_KEY")

response = client.messages.create(
    model="claude-opus-4-7",
    max_tokens=64000,
    messages=[
        {
            "role": "user",
            "content": "Please analyze the code structure of this repository and suggest three design pattern improvements."
        }
    ],
    output_config={
        "effort": "xhigh"
    },
    thinking={
        "type": "adaptive",
        "display": "summarized"
    }
)

# 4.7 hides thinking content by default; you need to explicitly opt-in
for block in response.content:
    if block.type == "text":
        print(block.text)
    elif block.type == "thinking":
        print(f"[Thinking Summary]: {block.thinking}")

Recommendation: In xhigh mode, it's best to increase max_tokens to 64k or higher; otherwise, the model might truncate prematurely due to insufficient output space. You can register for a free account at APIYI (apiyi.com) to test the actual performance of Opus 4.7 xhigh. The platform has already pre-configured the effort parameter pass-through to match Anthropic's implementation.

Using Claude Opus 4.7 xhigh Mode in Claude Code

Changes to Claude Code Defaults

With the upgrade to Opus 4.7, Claude Code has adjusted its built-in default effort level from high to xhigh. This means that if you simply run the claude command to enter interactive mode, your requests are already using xhigh by default. Here’s how you’ll notice the difference:

• Significantly higher success rates for complex tasks (especially bug fixes spanning multiple files).
• Token consumption per session is more than double what it was in the 4.6 era.
• Success rates for long-running tasks (like full repository refactoring) have jumped from about 55% to roughly 71%.

Manually Specifying the Effort Level

If you want to explicitly control the effort level in Claude Code, you can adjust it in your configuration file:

{
  "model": "claude-opus-4-7",
  "effort": "xhigh",
  "max_tokens": 96000,
  "thinking_display": "summarized"
}

Recommended effort levels for different task types:

Data Note: The chart above is based on Anthropic's publicly available internal Agentic Coding Eval data, which you can reproduce and verify using the same prompt on the APIYI platform (apiyi.com).

Claude Opus 4.7 xhigh Mode and Supporting Mechanisms

Synergy with Adaptive Thinking

Opus 4.7 has removed the legacy budget_tokens parameter; the only supported thinking mode is adaptive thinking. The effort parameter now effectively acts as the master dial for "depth of thought":

Note: By default, 4.7 hides thinking content (the thinking field in the response stream is empty). If your application needs to display the thinking process to users, you must explicitly set thinking.display = "summarized", otherwise users will experience a long "empty response window."

Working with Task Budgets

Opus 4.7 also introduces the task_budget parameter (in beta), which is particularly useful when paired with xhigh:

response = client.beta.messages.create(
    model="claude-opus-4-7",
    max_tokens=128000,
    output_config={
        "effort": "xhigh",
        "task_budget": {"type": "tokens", "total": 200000}
    },
    messages=[{"role": "user", "content": "Refactor the entire user authentication module"}],
    betas=["task-budgets-2026-03-13"]
)

task_budget is an "advisory" limit—the model sees the remaining budget and prioritizes its work accordingly—whereas max_tokens is a "hard limit" that triggers truncation. Used together, xhigh mode can self-regulate during long-running tasks to prevent token usage from spiraling out of control.

xhigh and the 1M Context Window

Opus 4.7 supports a 1M token context window with no long-context premium. In xhigh mode, the model can perform complex codebase understanding tasks within that 1M context without needing to frequently compress history. This means:

• You can load hundreds of thousands of lines of code at once for holistic analysis.
• Memory tools across sessions can reliably retain context.
• Information loss from context compression is significantly reduced.

Best Practices for Claude Opus 4.7 xhigh Mode

Recommendation 1: Start with xhigh for Coding Tasks

The official Anthropic documentation explicitly states: "Start with xhigh for coding and agentic use cases." This is because coding tasks typically involve multi-file reading, dependency analysis, running tests, and other multi-turn tool invocations. In these scenarios, xhigh offers significantly better exploration capabilities than high.

If you were accustomed to using high as your default for programming on Opus 4.6, I recommend switching directly to xhigh when migrating to 4.7, then adjusting back if the actual results don't require that level of depth.

Recommendation 2: Set max_tokens to at least 64k

Both xhigh and max require ample output space. The official recommendation is to start at 64k and adjust upward based on task complexity. If your max_tokens is still set to 4096, xhigh will frequently truncate during long tasks, leading to a worse experience than high.

Recommendation 3: Enable Thinking Summaries

thinking = {
    "type": "adaptive",
    "display": "summarized"
}

Although 4.7 hides the thinking process by default, enabling summarized display in debugging and production scenarios lets users know the model is actively working, preventing the "it looks like it's frozen" experience.

Recommendation 4: Choose Effort Dynamically Based on Task Complexity

Don't use the same effort level for every request. Here’s a recommended strategy:

def pick_effort(task_type: str, complexity: str) -> str:
    # Select the effort level based on the task type and complexity
    if task_type == "classification" or complexity == "trivial":
        return "low"
    elif task_type == "chat" and complexity == "simple":
        return "medium"
    elif task_type == "coding" and complexity == "moderate":
        return "high"
    elif task_type == "coding" and complexity in ("complex", "agentic"):
        return "xhigh"
    elif task_type == "research" and complexity == "frontier":
        return "max"
    return "high"

Optimization Tip: When accessing Opus 4.7 via APIYI (apiyi.com), you can dynamically switch the effort level at the request layer based on business tags. Use the unified usage dashboard to monitor the cost-benefit ratio across different tiers.

Recommendation 5: Be Aware of Tokenizer Changes

Opus 4.7 uses a new tokenizer, which may consume 1.0 to 1.35 times more tokens than 4.6 for the same text. When estimating costs, remember to reserve a 35% token buffer on top of your 4.6 baseline; otherwise, you might find your billing higher than expected.

Common Misconceptions About Claude Opus 4.7 xhigh Mode

Misconception 1: xhigh is always better than high

Not necessarily. For simple single-turn Q&A or structured output tasks (like JSON extraction), xhigh might trigger "over-reasoning," which slows down response times without improving quality. Use medium or low for these types of tasks.

Misconception 2: max is always the most powerful

While max does score highest in benchmarks, the improvement is marginal (about 3 percentage points) while the cost doubles. Anthropic officially advises: "Reserve max for genuinely frontier problems." For daily programming tasks, xhigh is more than enough; using max blindly is a classic waste of resources.

Misconception 3: You can continue using budget_tokens

Opus 4.7 has removed the thinking.budget_tokens parameter; passing it will return a 400 error. All control over thinking depth must now be handled via the effort parameter.

Misconception 4: xhigh works on Sonnet 4.6

xhigh is exclusive to Opus 4.7. The effort levels for Sonnet 4.6 only support low/medium/high/max; calling xhigh will be rejected.

FAQ

client.chat.completions.create(
    model="claude-opus-4-7",
    messages=[...],
    extra_body={"effort": "xhigh"}
)

Summary

Key takeaways for Claude Opus 4.7 xhigh mode:

1. Precise Positioning: It sits between high and max, specifically designed for long-range programming and Agentic tasks.
2. Sweet Spot for Value: Significantly more powerful than high and much more cost-effective than max; it's the recommended starting point for programming tasks.
3. Comprehensive Support: Works in tandem with adaptive thinking, task budgets, and the 1M context window.
4. Exclusive to 4.7: Only supported by claude-opus-4-7; not available in 4.6 or Sonnet 4.6.
5. Low Barrier to Entry: Simply set output_config.effort to "xhigh" to enable it.

For developers looking to upgrade to Opus 4.7, we recommend starting your evaluation with xhigh, paired with 64k+ max_tokens and adaptive thinking. You'll immediately notice the leap in 4.7's capabilities across most programming tasks.

We recommend using APIYI (apiyi.com) to quickly integrate Claude Opus 4.7 xhigh mode. The platform already supports effort parameter pass-through and 1M context window calls, and it offers free testing credits, making it easy to benchmark the real-world performance of 4.7 versus 4.6 for your specific use cases.

📚 References

1. Anthropic Official effort Parameter Documentation: Detailed definitions and recommended usage for the five effort levels.

   • Link: platform.claude.com/docs/en/build-with-claude/effort
   • Description: Official authoritative definitions and best practices for levels like xhigh.

2. What's new in Claude Opus 4.7: Complete changelog for version 4.7.

   • Link: platform.claude.com/docs/en/about-claude/models/whats-new-claude-4-6
   • Description: Includes the background of the xhigh introduction, breaking changes, and migration advice.

3. Adaptive Thinking Documentation: The only thinking mode supported by 4.7.

   • Link: platform.claude.com/docs/en/build-with-claude/adaptive-thinking
   • Description: Key to understanding how effort and thinking work together.

4. Task Budgets Beta Documentation: Budget control for use with xhigh.

   • Link: platform.claude.com/docs/en/build-with-claude/task-budgets
   • Description: Practical tools for managing token consumption in long-running tasks.

5. APIYI Claude Model Integration Documentation: A quick-start guide for developers in China.

   • Link: help.apiyi.com
   • Description: Includes practical configurations such as effort parameter passthrough and 1M context window model invocation.

Author: APIYI Technical Team
Technical Discussion: Feel free to discuss how the xhigh mode performs in your specific scenarios in the comments. For more Claude Opus 4.7 configuration tips, visit the APIYI documentation center at docs.apiyi.com.