I don't quite understand how people use these kind of local models that are specifically trained for agentic use cases. Like, what do they actually do with them? Do you use them as an assistant like with OpenClaw?
When used for coding, how do you divide the work between agents? Use a relatively fast model, like this one, as the main agent that calls out to other subagents that write the actual code? But then you'd need multiple models loaded, and why not just use the coding model to do everything? Do you use hosted cloud models for coding and code review, and this local one for orchestration? I don't see the benefit of that workflow either.
I've used local models to write some scripts etc, I like the idea of local computation instead of buying tokens from the cloud, but I don't know what the various agentic models are for, if not code generation.
When used for coding, how do you divide the work between agents? Use a relatively fast model, like this one, as the main agent that calls out to other subagents that write the actual code? But then you'd need multiple models loaded, and why not just use the coding model to do everything? Do you use hosted cloud models for coding and code review, and this local one for orchestration? I don't see the benefit of that workflow either.
I've used local models to write some scripts etc, I like the idea of local computation instead of buying tokens from the cloud, but I don't know what the various agentic models are for, if not code generation.