This post is primarily for the people here that are forced to work with AI. But it may be interesting for everyone.

We all here are aware how bad AI is for people and the environment. During some research I found out that this effect is most likely multiplied by pure greed (no even worse then you thought).

A little bit of context: I am currently responsible for a small R&D Team (me and some trainees) for a EU managed Services provider. Because of corpo pressure we need to evaluate AI usage.

I gave multiple models, nearly all run on 150W hardware a shot. And of course I was forced to test Claude also.

And what I found buffled me: the "frontier" top nodge best of the best model by Anthropic was the only one that did not even complete the task.

It constantly violated against clear rules. All of them about code simplicity and maintainability.

For example QWEN solved the task in about 30 minutes, one shot

And this would be the bill we would have paid for Claude without any usable result.

Having a deeper look at what happens if you let different models work on an existing codebase:

Claude will introduce complexity on every change. Wasting compute and energy.

As open source models clearly can do the job, why can those super huge big models not do the job?

And I think the answer is greed:

  • more tokens more money
  • lock the user into your model. Make sure you can not leave anthropic.

And that cost is really high. Not only those absurdly high token prices (factor of 100 higher then open models) it burns the employees out.

Is anyone here forced to work with AI and had made similar observations?

Luckily for me, I have some influence at my job and can minimize the AI impact in every sense. And maybe such experiments and research can convince other employers to not go down this road.

you are viewing a single comment's thread
view the rest of the comments
[–] 5 points 22 hours ago (10 children)

The Anthropic and OpenAI valuations require their models to replace humans. But LLM based AI can't replace humans because LLMs can't make decisions. I only use Chinese models now, they're fast, and they can finish a coding task quicker than I can make an informed decision about the next task.

  • source
  • hideshow 10 child comments
  • [–] 2 points 14 hours ago (6 children)

    Chinese models like Qwen? Can those be run on local hardware (like a 4090) with good results? I thought the appeal of services like Claude was that you needed bazillions of memory for good results. I’m very out of the loop.

  • source
  • parent
  • hideshow 6 child comments
  • [–] 2 points 9 hours ago (1 child)

    I have a RTX4090 (24GB VRAM) plus 128GB DDR4 system RAM on Ubuntu 24.04 and I am running these models locally

    | Model | Speed | Context window | |


    |


    |


    | | Qwen3.8-Flash-Next UD-Q4_K_XL — 125B/6B-active hybrid MoE, 104 GB | ~16.7 tok/s | 128k tokens | | GLM-5.3-Flash UD-IQ3_XXS — 320B/18B-active MoE, 120 GB | ~9 tok/s | 128k tokens | | Qwen3.8-27B UD-Q4_K_M — dense hybrid, 16 GB, fully on the 4090 | ~49 tok/s | 262k tokens |

    The larger models don't fit on the GPU alone but they're mixture-of-experts and their active weights easily fit on the 24GB. The bottleneck is my system RAM as llama.cpp has to constantly move the experts between RAM and VRAM. I'm running older hardware, AM4 CPU, DDR4 RAM, etc. so 128GB is my limit on system memory and it's relatively slow compared to DDR5. With DDR5 I would expect a good bump in speed for Qwen 3.8 Flash Next and GLM 5.3 Flash.

    I also have a Kimi subscription which I use as my daily agentic driver and use DeepSeek for random tasks (DeepSeek Flash 4.1 is really fast and cheap).

  • source
  • parent
  • hideshow 1 child comment
  • [–] [S] 2 points 12 hours ago (2 children)

    It depends. If you have enough host memory, those models are pretty efficient and work well with MTP.

    AMD Strix is good for it. Slower memory but a lot of it, no CPU Fallback.

    And the results are not worse then Claude at least

  • source
  • parent
  • hideshow 2 child comments
  • [–] 1 point 8 hours ago (1 child)

    That’s nice, I might give it a go. I thought Claude would be way better than those models.

  • source
  • parent
  • hideshow 1 child comment
  • [–] [S] 2 points 7 hours ago

    Standing rule in my projects:

    • never read code from imported libraries/modules
    • read all of our design and code style rules before even responding to a question.

    Claude never followed those rules. Or the design guides or the style guides.

    Qwen adheres to every fucking single word.

  • source
  • parent
  • [–] [S] 3 points 21 hours ago (2 children)

    We have a big pitch coming. And I am happy that I could convince our uppers to try a stund.

    We have a hackathon with a customer. One of our teams will work on strix workstations. We local, custom tuned models, run directly from a small solar installation.

    We will reveal this at the end. Our power consumption and the 0bits into USA metric

  • source
  • parent
  • hideshow 2 child comments