MiniMax 2.5 vs Llama 3.1 vs DeepSeek-R1 Comparison

MiniMax 2.5 vs Llama 3.1 vs DeepSeek-R1 Comparison

Sitepoint did a comparison of local coding models to see which ones are best for coding. They run the models through 4 coding tasks:

  1. Generating a complete, correct python function from a one-shot prompt.
  2. Given a code block with a deliberate bug, let the LLM find it, explain it, and fix it.
  3. Given a poorly structured block of code with key code smells, produce a refactored version that preserves correct behavior but fixed readability and performance
  4. Provide three related files, answer questions about the cross-file dependencies

Almost all of them require a NVidia Blackwell 6000 or better to run since more require at least 50gb of RAM to run. Here were their results:

DimensionMiniMax 2.5Llama 3.1 405BDeepSeek-R1
Best Task CategoryCode refactoringFunction generation & multi-file contextBug detection & debugging
Avg Tokens/sec (dual RTX 3090)17.57.89.8
Min VRAM Requirement~46 GB (dual GPU + partial CPU offload)~48 GB+ (dual GPU + heavy CPU offload)~44 GB (dual GPU + heavy CPU offload)
Composite Rank Across 4 Tasks1st or 2nd on 3 of 4 tasks1st on 2 of 4 tasks; highest peak quality1st on debugging; competitive elsewhere

Meta on track to spend $2.5 billion in AI tokens

Meta on track to spend $2.5 billion in AI tokens

You read right, $2.5 billion in AI usage for a single year. This averages out to about $35,000-$55,000 per developer (depending on how you count their employees), or about $3000-$5000 per dev per month.

This is a staggering expense for a company; and if this is part of the core strategy, an extremely dangerous one. This spending may even be justified today – until the AI companies double or triple or more what they are charging. Which they often do without warning. Overnight you could find this number become twice as much.

Game industry is changing and embracing AI slowly

Game industry is changing and embracing AI slowly

2026 Unity Game Development Report reports a lot of things many already know. The game industry – after massive hiring during Covid when people had nothing to do but play games – is now going through one of the worst layoff periods since the video game collapse of the 1980’s. This is causing major shifts in how and what game development teams are building. The report tells us the practical effects.

  • The majority of developers making their games with Unity (62%) use AI tools for coding assistance, with the second most popular use, writing and narrative design, at 44%. Only 5% of those surveyed responded with “I do not use AI.”
    • This is in line with GDC’s State of the Game Industry report
    • Larger teams are the ones adopting AI tools into their workflow at the highest rate with “79% of polled devs with over 150 team members say that AI tools have helped them improve efficiency.”

The activist elements of the game development industry have been staunchly anti-AI. As the survey shows, however, it’s probably already a losing position. This is especially true in the hyper-competitive environment that is game development where speed is critical.

It’s not just game developers. I recently read the lament of one seasoned programmer that interviewed really well at nVidia until they got to a set of AI experience questions. The tone changed when he said he didn’t use AI and had little experience coding with it. He went further and said he’d prefer not to use it. He didn’t get the offer and was complaining on the forum as to why that mattered since he was an excellent coder with over a decade of experience. An nVidia employee responded and said it clearly: the poster wouldn’t be successful at nvidia. Reason? Because everyone else would be coding circles around him. You simply cannot write the volume that is expected from you without it. Sticking your head in the sand and just doing everything by hand means you’ll soon be driving 40 on the freeway when everyone else is driving by at 65.

AI models that could only churn out slop 12 months ago started getting ‘good enough’ for testing and other menial tasks about 6 months ago. Now, in mid 2026, they’re good enough to create entire software stacks.

As a software engineer myself, the reality is it’s not a question of if you are using AI or not. If you are not, you simply cannot keep up with those that have learned how to use AI. AI has it’s problems, but it’s also a profound force multiplier.

Are jobs being lost to AI – almost certainly. But it doesn’t have to be the end of your career. What it does mean is you have to learn to use the tools and demonstrate you are more proficient than your competition at generating quality output.

Artices:

100 Days unemployed as a former Big Tech Software Engineer

100 Days unemployed as a former Big Tech Software Engineer

Asian Dad Energy is one of the literally 10,000’s of highly skilled software engineers that have been laid off in the last 2 years. Here’s his video of reaching 100 days of continued unemployment (published 3 months ago). His channel covers what a LOT of former software engineers are going through as the industry undergoes a massive reset due to the end of Covid era and the rise of AI.

37 Majors Have Unemployment Rates Higher Than non-college majors and college now doesn’t pay off in work for majority of men

37 Majors Have Unemployment Rates Higher Than non-college majors and college now doesn’t pay off in work for majority of men

As I posted before, the unemployment rate for recent college graduates has been significantly higher than the labor market taken as a whole across all workers, according to Federal Reserve Bank of New York data.

Even worse, Gen Z men with college degrees (taken as a whole across all majors) now have the same unemployment rate as non-grads. Meaning higher education no longer pays off for men when it comes to unemployment – though college grads make more than their non-college counterparts over their life.

In other data, these particular majors have the worst unemployment rates. Interesting new ones on the list? Computer Science and Computer Engineering – almost at the top.

Anyone that doesn’t think that rampant over hiring during Covid and AI is actively reshaping the entire programming industry is fooling themselves. Especially since so many people are calling software a ‘cooked’ field now.

College MajorUnemployment Rate
Anthropology7.90%
Computer Engineering7.80%
Fine Arts7.70%
Performing Arts7.00%
Computer Science7.00%
Architecture6.80%
Art History6.70%
Physics6.60%
Early Childhood Education6.60%
Environmental Studies6.30%
Medical Technicians6.20%
International Affairs6.10%
English Language6.10%
Information Systems & Management6.00%
Mathematics5.80%
Commercial Art & Graphic Design5.70%
Advertising and Public Relations5.70%
Pharmacy5.60%
Mass Media5.20%
Philosophy5.10%
Psychology5.00%
Business Analytics5.00%
Ethnic Studies4.90%
Chemical Engineering4.70%
Sociology4.60%
Political Science4.50%
Nutrition Sciences4.50%
General Engineering4.50%
Miscellaneous Biological Science4.40%
Mechanical Engineering4.40%
Marketing4.40%
History4.30%
General Business4.30%
Family and Consumer Sciences4.30%
Chemistry4.30%
Biology4.30%
Industrial Engineering4.20%
Mathnet takes on Agatha Christie

Mathnet takes on Agatha Christie

Square One TV was a math oriented education show during the late 80’s and early 90’s on PBS. I loved catching the show whenever I could after school. It was a show full of short sketches – one of the regular ones was Mathnet – a mathematical parody of Dragnet.

In one episode – they hit 2 of my favorite things: math and spooky mysteries. They parodied Agatha Christie’s “And Then There Were None” in the episode “The Case of the Mystery Weekend“.