An Evaluation of the Best Anthropic Code Model

Anthropic has been buzzing as of late. It recently caused a drop in stock markets with its release of the Claude Cowork tool that included shares of the world’s largest SaaS providers. And now they’re about to change thinking models with their latest release, Claude Opus 4.6, which they claim is their best coding model yet.

Whether it lives up to the claims or not, we’ll find out in this article where we put it to the test to see how well it performs in all coding and consulting tasks.

Claude Opus 4.6!

The Opus line is the top tier of Anthropic’s Claude family, built for critical thinking and advanced coding. These models are designed to handle long, multi-step tasks that require planning, contextualization, and systematic problem solving.

Claude Opus 4.6 is the newest entry in this list and the most capable Anthropic code model to date. It focuses on making thinking clearer, cleaning up code generation, and long-term workflows easier to manage.

What Opus 4.6 brings to the table:

• Multi-step robust reasoning: Better planning and case management for complex cases.
• Improved code performance: Reliable code generation, debugging, and consistency across major codes.
• To handle long context: It supports context for all extended tasks and large documents. Token window of up to 1 million tokens (128k withdrawal tokens).
• Workflow awareness: Designed for multi-phase projects such as software development and analysis work. This is extended to all projects with multiple files, where the entire project can be imported to work on.
• Adaptive thinking: Opus 4.6 can consider different effort levels. You can tell Opus how hard to think: low, medium, high, or maximum, and it decides when to spend more computation on difficult problems.

How to access Claude Opus 4.6?

Claude Opus 4.6 is premium, paid a model aimed at users who need high-level functionality for coding and complex workflows. It is available within Claude and through the Anthropic developer platform.

• Access to the Claude app: Available at Pro, Max, Team, and Enterprise subscribers to Claude.

• Developer access: Available via Claude Developer Platform with Anthropic API for usage-based payments.

• Cloud Platform: Offered by major cloud providers such as Cursor, Windsurf integrates Anthropic models for business and developer applications.

The price is the same as Claude Opus 4.5. But here it is hold on! The tokens used are almost 5 times what they were in its Opus 4.5. So although the cost is the same, if using the Claude Opus 4.6 API it will be more expensive.

Putting it to the test

All the good name of Opus will not help, if its performance falls down in real-world use cases. To test it, I will be analyzing how well it answers 4 types of questions. The questions are designed to test:

1. Multi-step scheduling and agent-style workflows
2. Major code refactoring and feature engineering
3. Algorithmic reasoning under real-world constraints
4. System level maintenance and troubleshooting

Multi-step agent workflow

This test measures planning ability and long-term thinking.

Build a small SaaS analytics dashboard. Take the following things into consideration.
Break this into phases:
• Requirements gathering
• System design
• Database schema
• Backend API design
• Frontend architecture
• Deployment plan
For each phase:
1. Produce concrete deliverables
2. Identify risks
3. Propose mitigation strategies
At the end, summarize the full execution roadmap.

Answer:

Color me impressed! In the time it took us to create one, this is a really high quality dashboard. It is functional and has a responsive design. For concepts and prototypes, this functionality may prove useful.

Code refactor and feature expansion

This experiment tests whether Opus can understand dirty legacy code, redesign it, and extend it with production-grade features. I have attached some dirty code with lots of errors to see how many of them can be fixed by the model.

Refactor this project into a clean, production-ready architecture and add the following features:
1. JWT-based authentication
2. Password hashing and validation
3. Structured logging
4. Persistent database storage (replace the current file system logic)
5. REST API interface
6. Unit tests for core functionality
Constraints:
• Follow clean architecture principles
• Eliminate global state
• Add proper error handling and input validation
• Document your architectural decisions
Use the attached code. 

This took very far away. Long enough to tell me about:

But the wait was perfect it’s worth it. The code was comprehensive, functional and satisfied each of the criteria I had established in the notification. It provided a number of files each serving a purpose. The code was modular, well written and the architecture file defined the project in an understandable way.

Algorithmic reasoning under constraints

This test evaluates critical thinking, tradeoff analysis, and implementation quality.

Design and implement an efficient system to detect duplicate files across millions of records.
Requirements:
• Files may be partially corrupted
• Memory is limited to 2GB
• The system must scale horizontally
• Provide time and space complexity analysis
• Include a working Python prototype
• Explain your design step by step and justify tradeoffs.
Explain your design step by step and justify tradeoffs. 

Answer:

Opus rendered an article in the time it would take one to open a word processor. The design prototype was sound and the sections clearly covered the individual parts. Reasons for different parts of the program are welcome.

Windows system debugging

This test tests structured problem solving and real-world diagnostic reasoning.

My Windows PC has been experiencing intermittent freezes and crashes for about a month.
Symptoms:
• Random system freezes during normal use
• Occasional Blue Screen of Death (BSOD)
• Chrome tabs frequently crash with memory errors
• The system suddenly stopped booting entirely
• After removing one RAM stick, the PC boots again
• With the remaining RAM stick installed, instability still occurs
I suspect a hardware or memory-related issue.
Provide a structured troubleshooting plan that includes:
1. Likely root causes ranked by probability
2. Step-by-step diagnostic tests to isolate the issue
3. Recommended Windows tools and third-party utilities
4. Hardware checks and stress tests
5. A clear decision tree for repair or replacement
Explain your reasoning at each stage. 

Answer:

It’s amazing! This is one of the problems I’ve been having for the past few weeks and I haven’t been able to fix it no matter what I’ve tried. Checking the Reddit forums and LTT threads didn’t help. The feedback provided by Claude Opus was very helpful. Not only did it summarize almost everything I had gone through in the past few weeks, but it also laid it out based on the most likely cause of the problem. The answer was based on truth and the instructions that followed were really helpful.

For the Neds!

If you are interested in working on all AI benchmarks the following may help:

High numbers in all cognitive and genetic measurements compared to other state-of-the-art models. Not only is it a clear advantage over its predecessor, but a huge difference in capabilities compared to its contemporaries. It is continuously strengthening its position in the seat of coding and consulting.

If you are interested in more benchmarks or want to know about its performance in a specific benchmark, read the official test page of the model.

The conclusion

Was it worth the effort? In terms of coding and thinking, Claude also showed that he has a clear track record. Opus 4.6 just helped extend that lead even further. With sandbox-style coding, the ability to work on all projects at once and the ability to think flexibly to optimize the use of tokens based on activity, Claude offers more than Great code!

The entire Claude ecosystem has been upgraded to accommodate this newcomer, and the latest model is able to do more with these additional functions.

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