Meta AI Fails to Compete with Llama, Gemini, and ChatGPT in Coding Test
How Well Do AI Tools Write Code?
Over the past year or so, I've put several large language models through their paces to see how effectively they tackle basic programming challenges. The idea behind these tests is straightforward: if they can't handle the basics, it's unlikely they'll be much help with more complex tasks. But if they do well on these foundational challenges, they might just become valuable allies for developers looking to save time.
To establish a baseline, I've been using four distinct tests. These range from straightforward coding assignments to debugging exercises that require deeper insight into frameworks like WordPress. Let’s dive into each test and compare how Meta's new AI tool stacks up against others.
Test 1: Writing a WordPress Plugin
Creating a WordPress plugin involves web development using PHP within the WordPress ecosystem. It also demands some UI design. If an AI chatbot can pull this off, it could serve as a helpful assistant for web developers.
Results:
- Meta AI: Adequate interface but failed functionality.
- Meta Code Llama: Complete failure.
- Google Gemini Advanced: Good interface, failed functionality.
- ChatGPT: Clean interface and functional output.
Here’s a visual comparison:
(Note: Replace "/path-to-image/" with the actual path to the image file.)
ChatGPT delivered a neater interface and positioned the "Randomize" button more logically. When it came to actually running the plugin, however, Meta AI crashed, presenting the dreaded "White Screen of Death."
Test 2: Rewriting a String Function
This test assesses an AI's ability to improve utility functions. Success here suggests potential assistance for developers, while failure implies room for improvement.
Results:
- Meta AI: Failed due to incorrect value corrections, poor handling of multi-decimal numbers, and formatting issues.
- Meta Code Llama: Succeeded.
- Google Gemini Advanced: Failed.
- ChatGPT: Succeeded.
While Meta AI stumbled on this seemingly simple task, Meta Code Llama managed to shine, showcasing its capability. ChatGPT also performed admirably.
Test 3: Finding an Annoying Bug
This isn’t about writing code—it’s about diagnosing issues. Success requires deep knowledge of WordPress APIs and the interactions between different parts of the codebase.
Results:
- Meta AI: Passed with flying colors, identifying the issue and suggesting an efficiency-enhancing tweak.
- Meta Code Llama: Failed.
- Google Gemini Advanced: Failed.
- ChatGPT: Passed.
Surprisingly, despite its earlier struggles, Meta AI excelled here, proving its potential but also highlighting inconsistencies in its responses.
Test 4: Writing a Script
This test evaluates knowledge of specialized tools like Keyboard Maestro and AppleScript. Both are relatively niche but represent a broader spectrum of programming skills.
Results:
- Meta AI: Failed to retrieve data from Keyboard Maestro.
- Meta Code Llama: Same failure.
- Google Gemini Advanced: Succeeded.
- ChatGPT: Succeeded.
Gemini and ChatGPT demonstrated proficiency with these tools, whereas Meta’s offerings fell short.
Overall Results
Model Success Rate Meta AI 1/4 Meta Code Llama 1/4 Google Gemini 1/4 ChatGPT 4/4
Based on my six-month experience using ChatGPT for coding projects, I remain confident in its reliability. Other models have yet to match its consistency and effectiveness. While Meta AI showed flashes of brilliance, its overall performance leaves much to be desired.
Have you experimented with these tools? Share your thoughts in the comments below!
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Comments (6)
0/500
Interesting test! I've been using ChatGPT for coding help and it's been decent, but honestly I'm more curious about the open-source alternatives like Llama. Meta's AI being behind isn't a huge shock, but it makes you wonder if they're focusing on different strengths. Maybe coding isn't their main goal? 🤔 Still, competition is good for us users!
Meta AI 코딩 테스트 결과는 참 실망스럽네요 😅 다른 경쟁사들보다 확실히 뒤처지는 모습인데... 그래도 아직 초기 단계니까 차차 나아지지 않을까요? 물론 빠르게 따라잡아야 하지만 말이죠!
¡Qué decepción con Meta AI! No me esperaba que fallara tan estrepitosamente en las pruebas de programación. Si no puede con lo básico, ¿cómo va a competir con los grandes como Gemini o ChatGPT? 🤔
Meta AI's coding skills are lagging behind? Ouch, that’s a rough one! 😅 Llama and Gemini are eating its lunch. Maybe it’s time for Meta to rethink their AI game plan.
Meta AI's coding skills seem underwhelming compared to Llama and others. 😕 I was hoping for a stronger contender in the AI coding space, but it looks like they’ve got some catching up to do. Anyone else tried using it for coding yet?
How Well Do AI Tools Write Code?
Over the past year or so, I've put several large language models through their paces to see how effectively they tackle basic programming challenges. The idea behind these tests is straightforward: if they can't handle the basics, it's unlikely they'll be much help with more complex tasks. But if they do well on these foundational challenges, they might just become valuable allies for developers looking to save time.
To establish a baseline, I've been using four distinct tests. These range from straightforward coding assignments to debugging exercises that require deeper insight into frameworks like WordPress. Let’s dive into each test and compare how Meta's new AI tool stacks up against others.
Test 1: Writing a WordPress Plugin
Creating a WordPress plugin involves web development using PHP within the WordPress ecosystem. It also demands some UI design. If an AI chatbot can pull this off, it could serve as a helpful assistant for web developers.
Results:
- Meta AI: Adequate interface but failed functionality.
- Meta Code Llama: Complete failure.
- Google Gemini Advanced: Good interface, failed functionality.
- ChatGPT: Clean interface and functional output.
Here’s a visual comparison:
(Note: Replace "/path-to-image/" with the actual path to the image file.)
ChatGPT delivered a neater interface and positioned the "Randomize" button more logically. When it came to actually running the plugin, however, Meta AI crashed, presenting the dreaded "White Screen of Death."
Test 2: Rewriting a String Function
This test assesses an AI's ability to improve utility functions. Success here suggests potential assistance for developers, while failure implies room for improvement.
Results:
- Meta AI: Failed due to incorrect value corrections, poor handling of multi-decimal numbers, and formatting issues.
- Meta Code Llama: Succeeded.
- Google Gemini Advanced: Failed.
- ChatGPT: Succeeded.
While Meta AI stumbled on this seemingly simple task, Meta Code Llama managed to shine, showcasing its capability. ChatGPT also performed admirably.
Test 3: Finding an Annoying Bug
This isn’t about writing code—it’s about diagnosing issues. Success requires deep knowledge of WordPress APIs and the interactions between different parts of the codebase.
Results:
- Meta AI: Passed with flying colors, identifying the issue and suggesting an efficiency-enhancing tweak.
- Meta Code Llama: Failed.
- Google Gemini Advanced: Failed.
- ChatGPT: Passed.
Surprisingly, despite its earlier struggles, Meta AI excelled here, proving its potential but also highlighting inconsistencies in its responses.
Test 4: Writing a Script
This test evaluates knowledge of specialized tools like Keyboard Maestro and AppleScript. Both are relatively niche but represent a broader spectrum of programming skills.
Results:
- Meta AI: Failed to retrieve data from Keyboard Maestro.
- Meta Code Llama: Same failure.
- Google Gemini Advanced: Succeeded.
- ChatGPT: Succeeded.
Gemini and ChatGPT demonstrated proficiency with these tools, whereas Meta’s offerings fell short.
Overall Results
| Model | Success Rate |
|---|---|
| Meta AI | 1/4 |
| Meta Code Llama | 1/4 |
| Google Gemini | 1/4 |
| ChatGPT | 4/4 |
Based on my six-month experience using ChatGPT for coding projects, I remain confident in its reliability. Other models have yet to match its consistency and effectiveness. While Meta AI showed flashes of brilliance, its overall performance leaves much to be desired.
Have you experimented with these tools? Share your thoughts in the comments below!
DeepMind CEO Hassabis: I sleep six hours a day, usually feel energetic around 1 a.m.
Fortune recently featured an interview with Demis Hassabis, CEO of Google DeepMind, revealing his unconventional approach to rest and productivity. Hassabis disclosed that he sleeps very little, structuring his waking hours into two distinct work blo
OpenAI, Anthropic Vie for Market Share Despite Revenue Shortfalls
Despite recent reports suggesting OpenAI missed revenue targets, creating pressure on tech stocks this Tuesday, private AI lab investors remain resilient. Seasoned backers have confirmed they will not reduce investment despite negative media coverage
Interesting test! I've been using ChatGPT for coding help and it's been decent, but honestly I'm more curious about the open-source alternatives like Llama. Meta's AI being behind isn't a huge shock, but it makes you wonder if they're focusing on different strengths. Maybe coding isn't their main goal? 🤔 Still, competition is good for us users!
Meta AI 코딩 테스트 결과는 참 실망스럽네요 😅 다른 경쟁사들보다 확실히 뒤처지는 모습인데... 그래도 아직 초기 단계니까 차차 나아지지 않을까요? 물론 빠르게 따라잡아야 하지만 말이죠!
¡Qué decepción con Meta AI! No me esperaba que fallara tan estrepitosamente en las pruebas de programación. Si no puede con lo básico, ¿cómo va a competir con los grandes como Gemini o ChatGPT? 🤔
Meta AI's coding skills are lagging behind? Ouch, that’s a rough one! 😅 Llama and Gemini are eating its lunch. Maybe it’s time for Meta to rethink their AI game plan.
Meta AI's coding skills seem underwhelming compared to Llama and others. 😕 I was hoping for a stronger contender in the AI coding space, but it looks like they’ve got some catching up to do. Anyone else tried using it for coding yet?





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