
Whatlurksbeneath
Add a review FollowOverview
-
Founded Date November 21, 1943
-
Posted Jobs 0
-
Viewed 11
Company Description
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 stands out for 3 powerful reasons:
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 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 because code, a brand-new AI emerging from China is bound to generate attention. ZDNET’s Radhika Rajkumar did a deep dive into those problems in her short article Why China’s DeepSeek might burst 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 needing depth and accuracy (e.g., fixing advanced math problems, creating complex code).
Choose R1 for latency-sensitive, high-volume applications (e.g., consumer assistance automation, basic text processing).
You can pick in between R1 and V3 by clicking the little button in the chat interface. If the button is blue, you’re using R1.
The brief response is this: excellent, however clearly not perfect. Let’s dig in.
Test 1: Writing a WordPress plugin
This test was actually my first test of ChatGPT’s programs expertise, way back in the day. My spouse needed a plugin for WordPress that would help her run a participation device for her online group.
Also: The best AI for coding in 2025 (and what not to utilize)
Her needs were fairly easy. It needed to take in a list of names, one name per line. It then had to arrange the names, and if there were replicate names, separate them so they weren’t noted side-by-side.
I didn’t truly have time to code it for her, so I chose to give the AI the challenge on an impulse. To my big surprise, it worked.
Since then, it’s been my very first test for AIs when evaluating their shows abilities. It needs the AI to know how to set up code for the WordPress structure and follow triggers plainly adequate to develop both the user interface and program logic.
Only about half of the AIs I have actually evaluated can fully pass this test. Now, nevertheless, we can include one more to the winner’s circle.
DeepSeek V3 created both the user interface and program logic exactly as specified. 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 different, with much larger input locations. However, both the UI and reasoning 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 grumbled that he was not able to get in dollars and cents into a contribution entry field. As written, my code just permitted dollars. So, the test includes providing the AI the regular that I wrote and asking it to rewrite it to permit for both dollars and cents
Also: My preferred ChatGPT feature just got method more effective
Usually, this results in the AI generating some regular expression validation code. DeepSeek did produce code that works, although there is space for enhancement. The code that DeepSeek V2 wrote was unnecessarily long and repetitive while the thinking before generating the code in R1 was also extremely long.
My biggest concern is that both models of the DeepSeek validation makes sure validation approximately 2 decimal locations, however if a huge number is gotten in (like 0.30000000000000004), the usage of 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 routine expression or a non-string makes it into that conversion, the code would crash.
It’s odd, because R1 did present a really great list of tests to validate versus:
So here, we have a split decision. I’m offering the point to DeepSeek V3 because neither of these problems 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 offer a fail to R1 since if something that’s not a string somehow enters into the Number function, a crash will occur.
Which offers DeepSeek V3 two triumphes of 4, however DeepSeek R1 just one win out of four up until now.
Test 3: Finding a frustrating bug
This is a test developed when I had a really frustrating bug that I had trouble tracking down. Once again, I decided to see if ChatGPT could handle it, which it did.
The difficulty is that the response isn’t apparent. Actually, the challenge is that there is an obvious response, based on the error message. But the obvious response is the incorrect response. This not only caught me, but it regularly catches 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 comprehending how specific 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 nearly similar responses, 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 crowning achievement for V3? Let’s discover out.
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 interplay in between three environments: AppleScript, the Chrome item design, and a Mac scripting tool called Keyboard Maestro.
I would have called this an unreasonable test because Keyboard Maestro is not a mainstream shows tool. But ChatGPT handled the test easily, understanding precisely what part of the problem 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 job in between instructions to Keyboard Maestro and Chrome. It likewise had fairly weak understanding of AppleScript, writing custom regimens for AppleScript that are native to the language.
Weirdly, the R1 model failed also due to the fact that it made a lot of inaccurate assumptions. It presumed that a front window always exists, which is certainly not the case. It also made the presumption that the presently front running program would always be Chrome, rather than clearly inspecting to see if Chrome was running.
This leaves DeepSeek V3 with 3 proper tests and one fail and DeepSeek R1 with 2 correct tests and two stops working.
Final ideas
I discovered that DeepSeek’s insistence on using a public cloud e-mail address like gmail.com (instead of my normal e-mail address with my business domain) was bothersome. It likewise had a of responsiveness stops working that made doing these tests take longer than I would have liked.
Also: How to utilize ChatGPT to compose code: What it does well and what it doesn’t
I wasn’t sure I ‘d have the ability to compose this article because, for the majority of the day, I got this error when attempting to sign up:
DeepSeek’s online services have recently faced large-scale malicious attacks. To guarantee continued service, registration is briefly limited 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 appears to be overly chatty in regards to the code it generates. The AppleScript code in Test 4 was both incorrect and exceedingly long. The routine expression code in Test 2 was proper in V3, but it could have been written in a method that made it much 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 pleased that DeepSeek V3 beat out Gemini, Copilot, and Meta. But it appears to be at the old GPT-3.5 level, which means there’s absolutely room for improvement. I was dissatisfied with the outcomes for the R1 model. Given the option, I ‘d still choose ChatGPT as my shows code helper.
That stated, for a brand-new tool working on much lower infrastructure than the other tools, this might be an AI to enjoy.
What do you think? Have you tried DeepSeek? Are you utilizing any AIs for programs support? Let us know in the comments listed below.
You can follow my daily job updates on social networks. Make sure to sign up for 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.