hermes-agent depends heavily on the local model and setup
can be fun and useful for learning, but they can take a lot of time before they produce real work. Image-to-video, text-to-image, coding, , and LoRA training can all turn into long setup work around the right workflow, , settings, and hardware. They can help with simple code debugging or with making a rough first version of something new.
For many other tasks, free web models or may be faster and better. can also get stuck when paired with , depending on which model is used. A machine with two GPUs, one with 16GB VRAM and one with 8GB VRAM, may still struggle.
Qwen 27B looks usable, but it may need Q8 and a 256k context to be practical. For medium-size tasks, a or free web tool limits may be more efficient than spending time tuning .
Key points
- may get stuck with some .
- can cost more time in workflow, , and settings than they save.
- They may still be useful for simple code debugging or rough first drafts.
- Two GPUs with 16GB and 8GB VRAM may not be enough for smooth medium-size agent work.
- Qwen 27B may need Q8 and a 256k context to be practical.