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

DeepSeek took off into the world’s awareness this past weekend. It sticks out for 3 powerful factors:

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

2. It’s open source.

3. It utilizes greatly less facilities than the big AI tools we have actually been looking at.

Also: Apple scientists reveal the secret sauce behind DeepSeek AI

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

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

Choose V3 for jobs needing depth and accuracy (e.g., fixing innovative mathematics problems, producing intricate code).

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

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

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

Test 1: Writing a WordPress plugin

This test was actually my first test of ChatGPT’s programs prowess, method back in the day. My wife 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 requirements were fairly basic. It required to take in a list of names, one name per line. It then had to arrange the names, and if there were duplicate names, separate them so they weren’t listed side-by-side.

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

Since then, it’s been my very first test for AIs when examining their shows skills. It requires the AI to understand how to establish code for the WordPress framework and follow triggers plainly sufficient to produce both the user interface and program reasoning.

Only about half of the AIs I’ve checked 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 logic precisely as defined. When It Comes To DeepSeek R1, well that’s an intriguing case. The “reasoning” aspect of R1 caused the AI to spit out 4502 words of analysis before sharing the code.

The UI looked various, with much wider input areas. However, both the UI and logic worked, so R1 also passes this test.

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

Test 2: Rewriting a string function

A user complained that he was unable to go into dollars and cents into a contribution entry field. As composed, my code only allowed dollars. So, the test includes providing the AI the routine that I composed and asking it to reword it to permit both dollars and cents

Also: My preferred ChatGPT function just got method more powerful

Usually, this leads to the AI creating some regular expression recognition code. DeepSeek did create code that works, although there is space for improvement. The code that DeepSeek V2 composed was needlessly long and repetitious while the reasoning before generating the code in R1 was also long.

My greatest issue is that both models of the DeepSeek validation guarantees validation up to 2 decimal locations, but if a large number is entered (like 0.30000000000000004), the usage of parseFloat doesn’t have specific rounding understanding. The R1 model likewise utilized JavaScript’s Number conversion without inspecting for edge case inputs. If bad information 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, since R1 did present an extremely nice list of tests to confirm versus:

So here, we have a split decision. I’m giving 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 expected outcomes. On the other hand, I need to offer a stop working to R1 because if something that’s not a string somehow gets into the Number function, a crash will take place.

And that offers DeepSeek V3 2 triumphes of 4, however R1 only one win out of 4 so far.

Test 3: Finding a bothersome bug

This is a test produced when I had a very bothersome bug that I had trouble locating. Once once again, I decided to see if ChatGPT might manage it, which it did.

The difficulty is that the response isn’t apparent. Actually, the challenge is that there is an obvious answer, based on the mistake message. But the obvious response is the wrong answer. This not only caught me, but it regularly captures a few of the AIs.

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

Solving this bug requires comprehending how particular API calls within WordPress work, having the ability to see beyond the mistake message to the code itself, and then knowing where to find the bug.

Both DeepSeek V3 and R1 passed this one with almost identical responses, bringing us to 3 out of 4 wins for V3 and two out of 4 wins for R1. That currently puts DeepSeek ahead of Gemini, Copilot, Claude, and Meta.

Will DeepSeek score a crowning achievement for V3? Let’s discover.

Test 4: Writing a script

And another one bites the dust. This is a difficult test since it needs the AI to comprehend the interaction in between three environments: AppleScript, the Chrome things model, and a Mac scripting tool called Keyboard Maestro.

I would have called this an unreasonable test because Keyboard Maestro is not a traditional programming tool. But ChatGPT managed the test quickly, understanding precisely what part of the issue is handled by each tool.

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

Unfortunately, neither DeepSeek V3 or R1 had this level of knowledge. Neither model understood that it needed to split the task between instructions to Keyboard Maestro and Chrome. It likewise had fairly weak understanding of AppleScript, writing custom-made regimens for AppleScript that are native to the language.

Weirdly, the R1 design failed as well because it made a bunch of inaccurate presumptions. It presumed that a front window constantly exists, which is certainly not the case. It also made the assumption that the presently front running program would constantly be Chrome, instead of clearly examining to see if Chrome was running.

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

Final ideas

I found that DeepSeek’s persistence on using a public cloud email address like gmail.com (rather than my normal e-mail address with my corporate domain) was annoying. 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 does well and what it doesn’t

I wasn’t sure I ‘d be able to compose this post because, for many of the day, I got this mistake when attempting to register:

DeepSeek’s online services have actually recently faced large-scale harmful attacks. To ensure continued service, registration is temporarily limited to +86 phone numbers. Existing users can log in as usual. Thanks for your understanding and support.

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

DeepSeek appears to be excessively chatty in terms of the code it produces. The AppleScript code in Test 4 was both incorrect and excessively long. The regular expression code in Test 2 was proper in V3, but it might have been written in a manner in which made it far more maintainable. It failed in R1.

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

I’m certainly impressed that DeepSeek V3 beat out Gemini, Copilot, and Meta. But it seems at the old GPT-3.5 level, which indicates there’s definitely room for improvement. I was dissatisfied with the outcomes for the R1 design. Given the choice, I ‘d still select ChatGPT as my programs code assistant.

That stated, for a brand-new tool running on much lower infrastructure than the other tools, this could be an AI to see.

What do you think? Have you attempted DeepSeek? Are you utilizing any AIs for programming support? Let us know in the remarks listed below.

You can follow my everyday task 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.