I've been on the Claude Max plan for quite a while now but I also run my own local models and every week there are new local models that are slowly but very surely closing the gap to frontier-level quality and so, pretty soon, I won't use APIs at all. Can't wait!
In order to have an efficient use of tokens, I created proper documentation from the start of the project:
- What component is where, what it does and how it does it
- Kept a history of all the architectural decisions
- How a new component (of a known type) should be added to the system
- Instructed the agent to keep this information valid and up to date as part of the PR prerequisites.
Claude subscription (the cheapest $20/month one) -- I very rarely hit the limits, particularly the weekly ones. But then again, the largest codebase I ever work on is 50k lines.
I'd prefer local models massively for both work and "pleasure" (I love LLMs as random cognitive sparring partners), but then again, my bank account massively disagrees :/
I am using a tool I built which gives me a pre-flight estimate about token usage for different models, for a given task. It looks like this https://caspian.md/assets/feature-4-ai-models.mp4
I've been on the Claude Max plan for quite a while now but I also run my own local models and every week there are new local models that are slowly but very surely closing the gap to frontier-level quality and so, pretty soon, I won't use APIs at all. Can't wait!
Out of interest, what does your local setup look like? Is this a spare GPU you’re using or have you got something more designed for local LLMs?
In order to have an efficient use of tokens, I created proper documentation from the start of the project: - What component is where, what it does and how it does it - Kept a history of all the architectural decisions - How a new component (of a known type) should be added to the system - Instructed the agent to keep this information valid and up to date as part of the PR prerequisites.
Claude subscription (the cheapest $20/month one) -- I very rarely hit the limits, particularly the weekly ones. But then again, the largest codebase I ever work on is 50k lines.
I'd prefer local models massively for both work and "pleasure" (I love LLMs as random cognitive sparring partners), but then again, my bank account massively disagrees :/
I have a Proxmox machine with dual P40 gpus that pass thru to a vm with ollama running for local inference. Been working great for over 2 years.