Claude 3.5 Sonnet vs. Opus: the fastest sprinter or the deepest thinker?

The AI Paradox of Today

Anthropic has presented us with an interesting choice. With Claude 3.5 Sonnet, we have a model that is faster than ever, while Opus holds the crown as the most advanced. For developers, this means a fundamental consideration: speed or depth?

Speed or Depth?

The key differences between Sonnet and Opus at a glance.

Speed & Cost

The latest Claude 3.5 Sonnet is a game changer. It operates up to twice as fast as Opus, making it significantly more cost-effective for daily tasks, rapid iterations, and customer-facing applications where response time is crucial.

Code Generation

For us as developers, this is a big deal. Internal tests from Anthropic show that 3.5 Sonnet solves 64% of programming problems, compared to 38% for Opus. In practice, we notice this immediately: cleaner code, faster results.

Complex Analysis

Here, Opus remains king. For tasks that require in-depth, nuanced reasoning – think strategic market analysis, R&D reports, or deciphering complex legal texts – Opus’s superior "thinking power" is indispensable.

Visual Tasks

Surprisingly, 3.5 Sonnet takes the lead here. The model is significantly better at interpreting graphs, diagrams, and even imperfect images. For data analysis or processing visual input, this is an enormous practical advantage.

The Developer’s Choice: Why 3.5 Sonnet is the New Favourite

A look at code, speed, and practical applicability in our daily workflow.

Have you ever had that feeling? That you’re using a tool so good that you can hardly imagine how you managed without it before? That feeling has been creeping up on us more often since we fully adopted Claude 3.5 Sonnet in our development sprints. Recently, we faced a challenge: refactoring a legacy codebase into a modern PHP framework. A task that usually takes weeks, full of hidden "gotchas" and outdated logic.

We threw a complex, old file at both Opus and 3.5 Sonnet, asking them to modernise it, optimise the logic, and provide unit tests. The result was fascinating.

Opus provided a theoretically brilliant, academically perfect solution. The code was elegant, but also so abstract that it was almost a work of art in itself. It took a while to receive the output, and it required some thought to implement.

Then came 3.5 Sonnet. Within seconds, we received a solution that was perhaps 95% as "elegant," but 100% practical and immediately usable. The code was robust, easy to read, and the tests were spot-on. It felt as though we had partnered with a senior developer who not only knows the theory but also understands what works in practice. This is precisely the feedback we also see online, such as on Reddit, where programmers praise Sonnet for producing "nearly bug-free code on the first try."

The 64% benchmark is not just a hollow claim

Anthropic claims that 3.5 Sonnet solves 64% of coding problems in their internal benchmarks, well above Opus’s 38%. This is not marketing talk; this is a game changer. For developers, this means that Sonnet is not just an assistant but a full-fledged sparring partner. The model is better at understanding the context of an entire codebase, identifying bugs, and suggesting efficient solutions. The speed at which this happens makes the iterative process of coding, testing, and refactoring much more dynamic.

Interestingly, "somewhat less intelligent" actually works in Sonnet’s favour here. The model is less prone to over-analysis and comes up with a pragmatic, "good enough" solution that helps you as a developer move forward immediately. In the world of software development, speed and momentum are often more valuable than striving for an unattainable ideal.

When is Opus worth the investment?

Strategy, R&D, and the pursuit of deep insights where pure thinking power makes the difference.

Does the rise of the impressive 3.5 Sonnet mean that Opus has become redundant? Absolutely not. It is crucial to understand that this is not a competition with one winner, but a matter of choosing the right tool for the job. Opus is not an all-round screwdriver; it is a precision instrument for the most demanding tasks.

Imagine you’re not refactoring code, but entering a completely new market. You need an in-depth analysis of competitors, technological trends, potential legal pitfalls, and socio-economic factors. You feed the model hundreds of pages of reports, news articles, and academic papers. This is where Opus excels.

The Power of Nuanced Reasoning

What strikes me in practice is that Opus has an almost eerie ability to make connections between seemingly unrelated information. While Sonnet would provide an excellent summary of each document, Opus can identify the underlying, unspoken thread. The model can reason at a level we call "graduate level expert reasoning" (GPQA), as Anthropic describes it in their launch article.

A concrete example from our experience: we investigated the feasibility of a complex platform that needed to combine machine learning with real-time data processing. We fed Opus technical documentation, market research, and user feedback. The output was not a simple list of pros and cons. It was a strategic document that identified potential friction points we had overlooked, including a prediction of how user needs might evolve based on the identified trends.

Think of Opus as your most brilliant, yet also most expensive, strategist. You don’t use it for daily minutes, but for that one crucial board meeting that determines the company’s direction for the next five years. The investment in Opus lies not in speed, but in the depth and quality of the insights it can generate. For high-stakes R&D, groundbreaking research, or formulating a watertight business strategy, Opus remains the undisputed champion.

How do you choose the right Claude model in practice?

A simple 4-step plan to select the best tool for your task.

The choice between Sonnet and Opus can seem paralyzing. But with a structured approach, it becomes much simpler. This is how we at Spartner make the consideration for each new project or complex task.

Step 1: Analyse the nature of your workflow

Is the task part of a fast, iterative cycle? Think of generating code, fixing bugs, creating content for social media, or handling customer inquiries. Here, speed and cost-effectiveness reign supreme. In 9 out of 10 cases, Claude 3.5 Sonnet is the obvious winner. Is the task a one-off, in-depth research project? Such as a strategic analysis, a scientific literature review, or drafting a complex legal document. Then you lean towards Opus.

Step 2: Define the "intelligence threshold"

Ask yourself: is "extremely smart and fast" good enough, or do I need "the absolute, most nuanced maximum of thinking power," regardless of cost and time? For most business and development tasks, Sonnet’s intelligence is more than sufficient. In fact, its pragmatism is often an advantage. Only when the slightest nuance or the deepest insight can make the difference between success and failure is Opus the right choice.

Step 3: Conduct a "head-to-head" test

Our pro tip: still in doubt? Take one representative, complex prompt that is characteristic of your challenge. Enter exactly the same prompt into both 3.5 Sonnet and Opus. This is the most honest way to compare performance for your specific use case. It will cost you a bit extra upfront, but that investment pays off handsomely.

Step 4: Evaluate the output on more than just correctness

Look beyond whether the answer is "good." Assess the output based on the following criteria:

• Speed: How long did it take to generate the answer?

• Usability: How quickly could you practically use the output? Did you have to adjust it a lot?

• Style and Tone: Does the writing style fit your purpose? Does it feel natural?

• Cost: What was the final cost for the generated output?

Often, you will find that Sonnet is the "overall" winner based on a combination of these factors, even if Opus scores slightly better on pure intelligence.

The Toolbox of the Modern Developer

Sonnet is your favourite all-rounder, Opus your specialist precision tool.

Choosing an AI model increasingly feels like assembling the perfect toolbox. You don’t have one hammer that works for everything. You have a reliable claw hammer for most jobs, and a heavy mallet for the heavy breaking work. In the world of Anthropic's Claude, 3.5 Sonnet has become that indispensable, versatile claw hammer. It’s fast, smart, reliable, and surprisingly good at tasks we thought we needed a specialist for, such as coding and visual analysis. It’s the tool we reach for first 90% of the time.

Claude 3 Opus is that precision mallet. You don’t use it every day, but when you need it, there’s no alternative. For that 10% of tasks where absolute depth, strategic insight, and nuanced reasoning make the difference, Opus is worth its weight in gold.

The real art lies not in determining which model is "better," but in recognising which task requires which tool.

• For daily development, rapid iterations, and content creation: Choose Claude 3.5 Sonnet. You gain speed, cost-effectiveness, and practical usability.

• For complex, high-stakes analyses and strategic planning: Invest in Claude 3 Opus. The depth and nuance of the insights are invaluable.

• When in doubt: Always start with Sonnet. There’s a good chance you’ll be pleasantly surprised by the quality and that you won’t even need the extra power of Opus.

• The key lesson: The introduction of Claude 3.5 Sonnet shows that the "best" AI is not always the "most intelligent," but the most balanced for the task.

Frequently Asked Questions about Claude Sonnet vs. Opus