I Tested DeepSeek’s R1 and V3 Coding Skills – and we’re not All Doomed (Yet).

DeepSeek exploded into the world’s consciousness this past weekend. It sticks out for 3 effective reasons:

1. It’s an AI chatbot from China, rather than the US

2. It’s open source.

3. It utilizes vastly less facilities than the big AI tools we’ve been looking at.

Also: Apple scientists expose the secret sauce behind DeepSeek AI

Given the US federal government’s issues over TikTok and possible Chinese federal government involvement in that code, a brand-new AI emerging from China is bound to create attention. ZDNET’s Radhika Rajkumar did a deep dive into those problems in her article Why China’s DeepSeek might rupture our AI bubble.

In this article, we’re avoiding politics. Instead, I’m putting both DeepSeek V3 and DeekSeek R1 through the very same set of AI coding tests I have actually thrown at 10 other big language designs. According to DeepSeek itself:

Choose V3 for tasks needing depth and accuracy (e.g., solving advanced math issues, creating complex code).

Choose R1 for latency-sensitive, high-volume applications (e.g., customer assistance automation, standard text processing).

You can choose between R1 and V3 by clicking the little button in the chat interface. If the button is blue, you’re utilizing R1.

The short response is this: impressive, but clearly not perfect. Let’s dig in.

Test 1: Writing a WordPress plugin

This test was really my very first test of ChatGPT’s programming prowess, method back in the day. My partner required a plugin for WordPress that would assist her run a participation device for her online group.

Also: The very best AI for coding in 2025 (and what not to utilize)

Her needs were fairly simple. It needed to take in a list of names, one name per line. It then needed to sort the names, and if there were replicate names, different them so they weren’t noted side-by-side.

I didn’t really have time to code it for her, so I decided to give the AI the obstacle on a whim. To my substantial surprise, it worked.

Since then, it’s been my very first test for AIs when assessing their programming abilities. It needs the AI to know how to set up code for the WordPress structure and follow prompts plainly adequate to develop both the interface and program logic.

Only about half of the AIs I have actually evaluated can totally pass this test. Now, nevertheless, we can include one more to the winner’s circle.

DeepSeek V3 developed both the interface and program logic exactly as defined. When It Comes To DeepSeek R1, well that’s an intriguing case. The “thinking” aspect of R1 triggered the AI to spit out 4502 words of analysis before sharing the code.

The UI looked different, with much broader input areas. However, both the UI and logic worked, so R1 likewise passes this test.

So far, DeepSeek V3 and R1 both passed one of four tests.

Test 2: Rewriting a string function

A user grumbled that he was not able to get in dollars and cents into a donation entry field. As written, my code only enabled dollars. So, the test involves providing the AI the routine that I wrote and asking it to reword it to permit for both dollars and cents

Also: My preferred ChatGPT function simply got method more effective

Usually, this results in the AI creating some routine expression validation code. DeepSeek did create code that works, although there is space for enhancement. The code that DeepSeek V2 composed was needlessly long and repetitious while the reasoning before creating the code in R1 was also really long.

My greatest issue is that both models of the DeepSeek recognition ensures validation up to 2 decimal locations, however if a huge number is gotten in (like 0.30000000000000004), using parseFloat doesn’t have specific rounding knowledge. The R1 design likewise utilized JavaScript’s Number conversion without looking for edge case inputs. If bad data comes back from an earlier part of the regular expression or a non-string makes it into that conversion, the code would crash.

It’s odd, because R1 did present a really good list of tests to verify against:

So here, we have a split choice. I’m offering the point to DeepSeek V3 because neither of these problems its code produced would cause the program to break when run by a user and would generate the anticipated outcomes. On the other hand, I need to offer a stop working to R1 since if something that’s not a string somehow enters the Number function, a crash will ensue.

And that offers DeepSeek V3 two triumphes of 4, but DeepSeek R1 just one win out of 4 up until now.

Test 3: Finding a frustrating bug

This is a test created when I had a very bothersome bug that I had difficulty tracking down. Once again, I chose to see if ChatGPT might handle it, which it did.

The difficulty is that the response isn’t apparent. Actually, the obstacle is that there is an obvious response, based on the error message. But the obvious response is the wrong response. This not only captured me, however it regularly captures a few of the AIs.

Also: Are ChatGPT Plus or Pro worth it? Here’s how they compare to the complimentary version

Solving this bug needs comprehending how particular API calls within WordPress work, being able to see beyond the mistake message to the code itself, and then understanding where to find the bug.

Both DeepSeek V3 and R1 passed this one with nearly identical answers, bringing us to 3 out of 4 wins for V3 and 2 out of 4 wins for R1. That already puts DeepSeek ahead of Gemini, Copilot, Claude, and Meta.

Will DeepSeek score a home run for V3? Let’s learn.

Test 4: Writing a script

And another one bites the dust. This is a tough test due to the fact that it requires the AI to understand the interaction between three environments: AppleScript, the Chrome things design, and a Mac scripting tool called Keyboard Maestro.

I would have called this an unfair test because Keyboard Maestro is not a traditional programs tool. But ChatGPT handled the test quickly, understanding exactly what part of the issue is dealt with by each tool.

Also: How ChatGPT scanned 170k lines of code in seconds, conserving me hours of work

Unfortunately, neither DeepSeek V3 or R1 had this level of understanding. Neither design understood that it required to split the task in between directions to Keyboard Maestro and Chrome. It also had fairly weak understanding of AppleScript, writing customized regimens for AppleScript that are belonging to the language.

Weirdly, the R1 model failed as well since it made a lot of inaccurate . It presumed that a front window constantly exists, which is absolutely not the case. It likewise made the assumption that the currently front running program would always be Chrome, instead of clearly inspecting to see if Chrome was running.

This leaves DeepSeek V3 with 3 right tests and one fail and DeepSeek R1 with 2 correct tests and two stops working.

Final ideas

I found that DeepSeek’s persistence on utilizing a public cloud e-mail address like gmail.com (instead of my regular e-mail address with my corporate domain) was annoying. It also had a number of responsiveness stops working that made doing these tests take longer than I would have liked.

Also: How to use ChatGPT to write code: What it does well and what it doesn’t

I wasn’t sure I ‘d have the ability to write this post due to the fact that, for many of the day, I got this mistake when attempting to sign up:

DeepSeek’s online services have actually just recently faced large-scale malicious attacks. To guarantee continued service, registration is temporarily restricted to +86 telephone number. Existing users can log in as normal. Thanks for your understanding and assistance.

Then, I got in and was able to run the tests.

DeepSeek seems to be extremely loquacious in terms of the code it generates. The AppleScript code in Test 4 was both wrong and exceedingly long. The regular expression code in Test 2 was appropriate in V3, but it could have been written in a way that made it a lot more maintainable. It failed in R1.

Also: If ChatGPT produces AI-generated code for your app, who does it truly belong to?

I’m definitely satisfied that DeepSeek V3 vanquished Gemini, Copilot, and Meta. But it seems at the old GPT-3.5 level, which implies there’s absolutely room for improvement. I was dissatisfied with the results for the R1 design. Given the option, I ‘d still select ChatGPT as my programming code assistant.

That stated, for a new tool running on much lower facilities than the other tools, this might be an AI to view.

What do you believe? Have you attempted DeepSeek? Are you using any AIs for programs assistance? Let us understand in the remarks listed below.

You can follow my everyday task updates on social media. Make sure to subscribe to my weekly update newsletter, and follow me on Twitter/X at @DavidGewirtz, on Facebook at Facebook.com/ DavidGewirtz, on Instagram at Instagram.com/ DavidGewirtz, on Bluesky at @DavidGewirtz. com, and on YouTube at YouTube.com/ DavidGewirtzTV.