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 stands out for 3 powerful factors:

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

2. It’s open source.

3. It uses significantly less infrastructure than the huge AI tools we have actually been taking a look at.

Also: Apple researchers expose the secret sauce behind DeepSeek AI

Given the US government’s concerns over TikTok and possible Chinese 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 concerns in her 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 very same set of AI coding tests I have actually tossed at 10 other big language designs. According to DeepSeek itself:

Choose V3 for jobs requiring depth and accuracy (e.g., solving innovative math problems, generating complex code).

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

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

The short answer is this: impressive, 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 programs prowess, method back in the day. My wife required a plugin for WordPress that would assist her run an involvement gadget for her online group.

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Her needs were relatively easy. It required to take in a list of names, one name per line. It then had to sort the names, and if there were names, separate them so they weren’t noted side-by-side.

I didn’t really have time to code it for her, so I chose to provide the AI the obstacle on an impulse. To my huge surprise, it worked.

Since then, it’s been my first test for AIs when evaluating their shows abilities. It needs the AI to know how to set up code for the WordPress framework and follow triggers plainly sufficient to produce both the interface and program reasoning.

Only about half of the AIs I’ve checked can fully pass this test. Now, however, we can add one more to the winner’s circle.

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

The UI looked different, with much larger 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 4 tests.

Test 2: Rewriting a string function

A user complained that he was unable to enter dollars and cents into a donation entry field. As written, my code just enabled dollars. So, the test includes giving the AI the regular that I composed and asking it to reword it to permit for both dollars and cents

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Usually, this results in the AI generating some regular expression recognition code. DeepSeek did produce code that works, although there is room for enhancement. The code that DeepSeek V2 wrote was unnecessarily long and repetitive while the reasoning before creating the code in R1 was also long.

My most significant concern is that both designs of the DeepSeek validation guarantees recognition up to 2 decimal places, however if a large number is gotten in (like 0.30000000000000004), using parseFloat doesn’t have explicit rounding understanding. The R1 design also used JavaScript’s Number conversion without examining 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, due to the fact that R1 did present an extremely good list of tests to validate against:

So here, we have a split decision. I’m providing the point to DeepSeek V3 since neither of these issues its code produced would cause the program to break when run by a user and would produce the expected results. On the other hand, I need to offer a stop working to R1 because if something that’s not a string in some way gets into the Number function, a crash will ensue.

And that offers DeepSeek V3 2 triumphes of 4, however DeepSeek R1 just one triumph of 4 up until now.

Test 3: Finding a frustrating bug

This is a test produced when I had a really irritating bug that I had difficulty finding. Once once again, I chose to see if ChatGPT could handle it, which it did.

The obstacle is that the response isn’t obvious. Actually, the challenge is that there is an apparent answer, based upon the error message. But the obvious answer is the wrong response. This not just caught me, but it routinely catches a few of the AIs.

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Solving this bug needs understanding how particular API calls within WordPress work, having the ability to see beyond the mistake message to the code itself, and then understanding where to discover the bug.

Both DeepSeek V3 and R1 passed this one with nearly identical responses, bringing us to three out of four wins for V3 and 2 out of four wins for R1. That currently puts DeepSeek ahead of Gemini, Copilot, Claude, and Meta.

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

Test 4: Writing a script

And another one bites the dust. This is a challenging test because 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 unreasonable test since Keyboard Maestro is not a mainstream shows tool. But ChatGPT handled the test easily, comprehending exactly what part of the problem is handled by each tool.

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Unfortunately, neither DeepSeek V3 or R1 had this level of knowledge. Neither design knew that it required to split the task between directions to Keyboard Maestro and Chrome. It likewise had relatively weak understanding of AppleScript, writing custom regimens for AppleScript that are belonging to the language.

Weirdly, the R1 design stopped working too because it made a lot of incorrect assumptions. It presumed that a front window always exists, which is definitely not the case. It likewise made the presumption that the currently front running program would constantly be Chrome, rather than explicitly inspecting to see if Chrome was running.

This leaves DeepSeek V3 with three correct tests and one stop working and DeepSeek R1 with two appropriate tests and 2 fails.

Final thoughts

I found that DeepSeek’s persistence on utilizing a public cloud email address like gmail.com (instead of my typical email address with my corporate domain) was irritating. It likewise had a number of responsiveness fails that made doing these tests take longer than I would have liked.

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

I wasn’t sure I ‘d be able to write this short article because, for most of the day, I got this error when trying to sign up:

DeepSeek’s online services have just recently faced massive malicious attacks. To guarantee continued service, registration is briefly restricted to +86 phone numbers. Existing users can visit as normal. Thanks for your understanding and assistance.

Then, I got in and had the ability to run the tests.

DeepSeek seems to be extremely loquacious in terms of the code it creates. The AppleScript code in Test 4 was both incorrect and exceedingly long. The routine expression code in Test 2 was right in V3, however it could have been composed in a manner in which made it a lot more maintainable. It failed in R1.

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I’m absolutely pleased that DeepSeek V3 beat out Gemini, Copilot, and Meta. But it appears to be at the old GPT-3.5 level, which suggests there’s absolutely room for improvement. I was disappointed with the results for the R1 design. Given the choice, I ‘d still pick ChatGPT as my shows code assistant.

That said, for a brand-new tool operating on much lower facilities than the other tools, this might be an AI to view.

What do you believe? Have you tried DeepSeek? Are you utilizing any AIs for shows assistance? Let us know in the remarks below.

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