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  • Founded Date March 2, 1907
  • Sectors Sales & Marketing
  • Posted Jobs 0
  • Viewed 10
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I Tested DeepSeek’s R1 and V3 Coding Skills – and we’re not All Doomed (Yet).

DeepSeek exploded into the world’s awareness this past weekend. It stands apart for three effective factors:

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

2. It’s open source.

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

Also: Apple researchers reveal the secret sauce behind DeepSeek AI

Given the US federal government’s concerns over TikTok and possible Chinese federal government participation 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 concerns in her short article Why China’s DeepSeek might rupture our AI bubble.

In this post, we’re preventing politics. Instead, I’m putting both DeepSeek V3 and DeekSeek R1 through the same set of AI coding tests I’ve thrown at 10 other large language models. According to DeepSeek itself:

Choose V3 for tasks requiring depth and accuracy (e.g., resolving sophisticated mathematics problems, producing intricate code).

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

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

The brief response is this: remarkable, however clearly not ideal. Let’s dig in.

Test 1: Writing a WordPress plugin

This test was really my very first test of ChatGPT’s shows prowess, way 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 use)

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

I didn’t actually have time to code it for her, so I chose to provide the AI the difficulty on a whim. To my substantial surprise, it worked.

Ever since, it’s been my first test for AIs when evaluating their programming skills. It needs the AI to know how to establish code for the WordPress structure and follow triggers clearly sufficient to develop both the interface and program reasoning.

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

DeepSeek V3 produced both the user interface and program reasoning precisely as specified. As for 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 various, with much broader input locations. However, both the UI and logic worked, so R1 likewise passes this test.

Up until now, DeepSeek V3 and R1 both passed among 4 tests.

Test 2: Rewriting a string function

A user complained that he was not able to enter dollars and cents into a donation entry field. As composed, my code only enabled dollars. So, the test includes offering the AI the regular that I composed and asking it to rewrite it to allow for both dollars and cents

Also: My favorite ChatGPT feature just got method more effective

Usually, this leads to the AI producing some regular expression validation code. DeepSeek did create code that works, although there is room for enhancement. The code that DeepSeek V2 wrote was needlessly long and repetitive while the reasoning before producing the code in R1 was also long.

My most significant concern is that both models of the DeepSeek validation ensures validation as much as 2 decimal places, but if a huge number is entered (like 0.30000000000000004), using parseFloat doesn’t have explicit rounding understanding. The R1 design also utilized JavaScript’s Number conversion without inspecting for edge case inputs. If bad information returns from an earlier part of the regular expression or a non-string makes it into that conversion, the code would crash.

It’s odd, since R1 did present a really nice list of tests to verify versus:

So here, we have a split decision. I’m offering the indicate DeepSeek V3 because neither of these concerns its code produced would trigger the program to break when run by a user and would create the anticipated outcomes. On the other hand, I have to provide a stop working to R1 due to the fact that if something that’s not a string somehow enters into the Number function, a crash will occur.

Which gives DeepSeek V3 2 triumphes of 4, however DeepSeek R1 only one win out of four so far.

Test 3: Finding an annoying bug

This is a test developed when I had an extremely annoying bug that I had trouble tracking down. Once again, I decided to see if ChatGPT might manage it, which it did.

The obstacle is that the response isn’t apparent. Actually, the challenge is that there is an apparent response, based on the mistake message. But the apparent answer is the wrong response. This not just caught me, however it routinely captures some of the AIs.

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

Solving this bug requires understanding how particular API calls within WordPress work, having the ability to see beyond the error message to the code itself, and after that understanding where to find the bug.

Both DeepSeek V3 and R1 passed this one with almost identical responses, bringing us to 3 out of four wins for V3 and two out of four wins for R1. That currently puts DeepSeek ahead of Gemini, Copilot, Claude, and Meta.

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

Test 4: Writing a script

And another one bites the dust. This is a challenging test due to the fact that it needs the AI to comprehend the interplay between 3 environments: AppleScript, the Chrome object design, and a Mac scripting tool called Keyboard Maestro.

I would have called this an unfair test since Keyboard Maestro is not a mainstream shows tool. But ChatGPT dealt with the test quickly, comprehending precisely 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 knew that it needed to split the task between directions to Keyboard Maestro and Chrome. It also had fairly weak knowledge of AppleScript, writing custom-made regimens for AppleScript that are native to the language.

Weirdly, the R1 design stopped working as well because it made a bunch of inaccurate assumptions. It presumed that a front window always exists, which is definitely not the case. It also made the presumption that the currently front running program would always be Chrome, instead of explicitly examining to see if Chrome was running.

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

Final thoughts

I discovered that DeepSeek’s persistence on using a public cloud email address like gmail.com (instead of my typical email address with my business domain) was frustrating. It likewise had a variety of responsiveness stops working that made doing these tests take longer than I would have liked.

Also: How to use ChatGPT to compose code: What it succeeds and what it does not

I wasn’t sure I ‘d be able to write this post since, for the majority of the day, I got this mistake when attempting to sign up:

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

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

DeepSeek seems to be extremely loquacious in regards to the code it produces. The AppleScript code in Test 4 was both incorrect and exceedingly long. The routine expression code in Test 2 was appropriate in V3, but it might have been composed in a manner in which made it far more maintainable. It stopped working in R1.

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

I’m absolutely impressed that DeepSeek V3 beat out Gemini, Copilot, and Meta. But it seems at the old GPT-3.5 level, which suggests there’s certainly room for enhancement. I was dissatisfied with the results for the R1 model. Given the option, I ‘d still pick ChatGPT as my programs code assistant.

That stated, for a new tool working on much lower infrastructure than the other tools, this might be an AI to enjoy.

What do you believe? Have you tried DeepSeek? Are you utilizing any AIs for programming support? Let us understand in the comments below.

You can follow my day-to-day job updates on social media. Make sure to sign up for my weekly upgrade 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.

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