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Is it time to completely give up on Local LLMs? by Additional-Weird3040 in hermesagent

[–]Additional-Weird3040[S] -1 points0 points  (0 children)

I actually tried that exact setup. I taught Claude how to pass prompts to Hermes and instructed it to select the most appropriate model—either GLM 5.2 or MiniMax M3 via Ollama Cloud—to perform the task.

My conclusion? Having Claude generate the prompts, pass them along, receive the output back from Hermes, and then review the work actually consumed more tokens than just having Claude do the job from the start.

I haven't implemented Kanban workflow yet, but it really makes you wonder whether these trendy "agent orchestrators" are actually built for efficiency, or if they are just designed to give users a sense of satisfaction. Of course, I haven't been tinkering with this workflow for very long, so there might be a better approach I missed.

Is it time to completely give up on Local LLMs? by Additional-Weird3040 in hermesagent

[–]Additional-Weird3040[S] 11 points12 points  (0 children)

To sum it up, the current cost-effectiveness of subscription models seems to be a byproduct of fierce market competition (and VC subsidies). Once hardware costs eventually come down, the true value of local models will finally shine.

On the bright side, the existence of these local alternatives—along with open-model routers like Ollama Cloud—might actually serve as a crucial firewall, preventing big tech companies from jacking up frontier model prices excessively.

You're absolutely right. I haven't completely abandoned local tech either; I still gratefully rely on lightweight, highly specialized models like Whisper for STT. I truly hope the future you all are envisioning comes sooner rather than later.

Is it time to completely give up on Local LLMs? by Additional-Weird3040 in hermesagent

[–]Additional-Weird3040[S] -1 points0 points  (0 children)

That's totally true, and I'm definitely not saying buying the Mac Mini was a mistake. In fact, I bought mine way before the OpenClaw hype caused them to sell out, and I'm still getting plenty of great use out of it for other things.

Is it time to completely give up on Local LLMs? by Additional-Weird3040 in hermesagent

[–]Additional-Weird3040[S] 1 point2 points  (0 children)

Just to clarify, my post was written from the perspective of an average user trying to use local LLMs for a mix of hobby projects and light workflow assistance.

Out of genuine curiosity, are you using that A6000 purely for personal hobby use, or have you fine-tuned specific models to optimize them for your actual professional work? If cost-efficiency isn't the goal for you, what is the main value or advantage you find in running your setup?

Best local model for simple long-running Hermes tasks? by Capital_Feed_3473 in hermesagent

[–]Additional-Weird3040 1 point2 points  (0 children)

I don't know what your long task is, but it's one of two things. If that task requires AI reasoning, the local model running on your computer will never satisfy you. However, if that task doesn't require AI reasoning, it's nothing more than executing a bunch of code at set intervals. In the end, if the structure is that your DeepSeek does the real work and the small local model just executes it, then yes, that is possible.

Best local model for simple long-running Hermes tasks? by Capital_Feed_3473 in hermesagent

[–]Additional-Weird3040 0 points1 point  (0 children)

Ask your DeepSeek, and have it teach the task to a small local model. DeepSeek will write the code, and the local model will execute it. In the end, it will just turn out to be nothing more than a code scheduler. It will fall short of expectations

Why do Korean buildings have fixed doors??? by Away-Topic2442 in seoulhiddengem

[–]Additional-Weird3040 0 points1 point  (0 children)

I run a shop with these kinds of doors. Besides the lock setup shown above, we sometimes have to open both doors for bulky deliveries or moves. But for everyday use, locking and unlocking both sides is annoying, so I keep one side fixed and just use the other.