The arrival of the Claude 4 family in May 2025 introduced a key question for any professional using AI: should I use Sonnet or Opus? Unlike other comparisons, the answer here isn’t simply “the good one vs. the best one.” Anthropic has engineered two distinct tools for very different purposes.
This is not a deep-dive analysis of each model individually. For that, we have our dedicated guides. This is a battleground: a direct, head-to-head comparison designed to answer a single question: which model is right for your job? We will analyze their differences in performance, speed, and practical use cases so you can make a strategic, informed decision.
The Core Difference: Speed & Scale vs. Depth & Complexity
If you only take one thing away from this article, let it be this:
- Claude 4 Sonnet is the workhorse, optimized for speed, cost-efficiency, and at-scale execution.
- Claude 4 Opus is the specialist, engineered for unparalleled reasoning depth and high-complexity tasks.
Your choice will depend on whether your priority is volume productivity or excellence on the toughest problems.
At a Glance: Sonnet vs. Opus Head-to-Head
This table summarizes the most critical differences that will guide your decision.
| Key Feature | Claude 4 Sonnet | Claude 4 Opus | The Quick Verdict |
|---|---|---|---|
| Primary Role | At-Scale Productivity | Complex Specialist | Sonnet for 90% of tasks, Opus for the toughest 10%. |
| Speed (TPS) | Faster (~55-63) | Slower (~39-40) | Sonnet is the undisputed winner for interactive apps. |
| Cost Differential | Baseline (1x) | ~5x More Expensive | The economic factor makes Sonnet the default choice. |
| Coding Performance | Surprisingly Superior | Excellent | Sonnet is more practical and efficient for daily coding tasks. |
| Complex Reasoning | Good | Exceptional | Opus is unmatched when logic and ambiguity are high. |
| Risk & Governance | Standard (ASL-2) | Elevated (ASL-3) | Using Opus requires greater risk consideration. |
The Performance Battleground: Where Each Model Wins
Real-world benchmarks and tests reveal a clear picture: each model is tuned to dominate a different kind of task.
Coding: The Surprising Victory of Sonnet
In what has been the most discussed result, Sonnet consistently outperforms Opus on practical coding benchmarks like SWE-bench. It resolves real-world GitHub issues more efficiently. Developers confirm this experience: Sonnet is more direct, faster, and often produces more pragmatic solutions for everyday tasks like generating components, debugging snippets, or writing tests. It is the ideal daily coding assistant.
Reasoning and Math: The Territory of Opus
When complexity rises, Opus shows why it carries a premium price. Opus dominates in advanced reasoning (GPQA) and competition math (AIME) benchmarks. It is significantly better at solving problems with multiple logical steps, navigating ambiguous specifications, or synthesizing information from multiple dense sources. If your task looks more like a research problem or designing a complex algorithm, Opus is the right tool.
Speed and User Experience: Sonnet’s Undeniable Advantage
For any user-facing application, speed is king. And here, there is no debate. Sonnet is roughly 30% faster than Opus and has lower latency (Time to First Token). This translates to a much smoother experience in chatbots, real-time assistants, and any interactive workflow. Sonnet’s immediacy makes it the superior choice for these applications.
The Practical Dilemma: Which Model for Which Task?
Based on performance, the choice of model becomes a clear strategic decision. We’ve created a matrix to help you decide quickly.
| If Your Task Is… | Use… | Why? |
|---|---|---|
| Developing a customer service chatbot | Sonnet | Its speed and low cost are essential for a good user experience at scale. |
| Generating and debugging code day-to-day | Sonnet | It’s faster, cheaper, and its performance is equal or superior for well-defined tasks. |
| Refactoring an entire codebase | Opus | Its superior long-context reasoning is needed to handle complex dependencies. |
| Powering a high-stakes financial analysis tool | Opus | Mission-critical reasoning and accuracy justify the cost and power. |
| Automating high-volume content creation | Sonnet | It provides the best balance of quality, speed, and cost-efficiency for production workflows. |
This leads to a simple and effective workflow for most users: use Sonnet by default, and only escalate to Opus by exception.
The Decisive Factors: Cost and Risk in Brief
Beyond pure performance, two factors make the choice between Sonnet and Opus very clear.
Cost: The 5x Price Multiplier
The most significant difference is the price. Claude 4 Opus is approximately five times more expensive than Claude 4 Sonnet. This isn’t a small gap; it’s a strategic chasm that makes Sonnet the only logical choice for high-volume or cost-sensitive applications. The decision to use Opus must be justified by a clear and significant return on investment that Sonnet cannot provide.
Risk: The ASL-3 Safety Designation
The models have different AI Safety Level (ASL) ratings. Sonnet is rated ASL-2 (Standard), while Opus is the first model rated ASL-3 (Elevated). This designation is for systems that pose a heightened risk and require stricter deployment safeguards. This reflects Opus’s immense power and agentic capabilities. For enterprises, this means using Opus, especially when connected to sensitive systems, requires a more robust governance and risk management framework than Sonnet.
The Final Verdict
The choice between Claude 4 Sonnet and Opus isn’t about which model is “better,” but which is the “right tool for the job.” Sonnet is the fast, efficient, and cost-effective engine for the majority of business and development tasks. Opus is the high-precision instrument you reserve for your most complex, high-stakes challenges where its profound reasoning capabilities can deliver a decisive advantage.
FREQUENTLY ASKED QUESTIONS (FAQ)
QUESTION: Is Claude Opus 4 worth the extra cost?
ANSWER: For most everyday tasks, no. Sonnet provides the vast majority of the quality at 20% of the cost. Opus is only worth the 5x price increase for highly specialized tasks requiring deep reasoning (like advanced scientific or legal analysis) or when building complex autonomous agents where its superior planning is critical.
QUESTION: Which model is better for coding, Sonnet or Opus?
ANSWER: Surprisingly, Sonnet is the better choice for most practical, day-to-day coding. It scores higher on the key SWE-bench benchmark, is faster, and provides more direct, pragmatic solutions. Only choose Opus for extremely complex architectural design or refactoring an entire codebase.
QUESTION: How does “Extended Thinking” affect the Sonnet vs. Opus comparison?
ANSWER: “Extended Thinking” is a mode that allows both models more time to “think” before answering, dramatically improving performance on complex tasks. It affects the comparison by widening the performance gap: when enabled, Opus’s lead in complex reasoning becomes even more pronounced. However, it also significantly increases the cost for both models, making the economic argument in favor of Sonnet for standard tasks even stronger.
QUESTION: Has anyone found a problem Opus can solve that Sonnet can’t?
ANSWER: Yes. The clearest examples are in domains requiring deep, multi-step logical inference. Opus can solve high-level competition math problems (AIME benchmark) that Sonnet struggles with. It can also successfully execute long-horizon agentic tasks that require planning and maintaining context over hours, where Sonnet is more likely to fail.
QUESTION: Why do they have different max output token limits?
ANSWER: Sonnet has a larger maximum output of 64,000 tokens compared to Opus’s 32,000. This reinforces their intended roles. Sonnet is better suited for tasks that require generating long-form content at scale. Opus is optimized for complex reasoning and agentic control, where the final answer or action is often more concise than the intricate thought process behind it.