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I’m biased [0], but I think we should be scripting around LLM-agnostic open source agents. This technology is changing software development at its foundations—-
by rbren 1y ago
I’m biased [0], but I think we should be scripting around LLM-agnostic open source agents. This technology is changing software development at its foundations—-we need to ensure we continue to control how we work.
[0] https://github.com/all-hands-ai/openhands https://github.com/all-hands-ai/openhands
- ProofHouse 1y agoThis 10000%
- handfuloflight 1y agoBut what do we do if the closed models are just better?
- davidmurdoch 1y agoWait?
- handfuloflight 1y agoAnd get superseded by competitors willing to spend on those models?
- bluefirebrand 1y agoSteal from them shamelessly, the same way they stole from everyone else?
- rkangel 1y agoThe agents are separate from the models. Claude Code only allows you to use Claude, but Aider allows you to use any model.
- handfuloflight 1y agoHow does that solve the problem of closed models being better than open models?
- hn8726 1y agoThere is no problem. OP said we should be using open _agents_, not open _models_. You can use an open agent with any model, open or closed, while using something like Claude Code locks you in to one model vendor
- handfuloflight 1y agoI know what OP said and I asked a question in turn.
- robotbikes 1y agoThis looks like a good resource. There are some pretty powerful models that will run on a Nvidia 4090 w/ 24gb of RAM. Devstral and Queen 3. Ollama makes it simple to run them on your own hardware, but the cost of the GPU is a significant investment. But if you are paying $250 a month for a proprietary tool it would pay for itself pretty quickly.
- seanmcdirmid 1y agoA Max M3 with 64 GB works well for a wider range of models although it fairs worse on stable diffusion jobs. Plus you can get it as a laptop.
- NitpickLawyer 1y ago> There are some pretty powerful models that will run on a Nvidia 4090 w/ 24gb of RAM. Devstral and Queen 3. I'd caution against using devstral on a 24 gb vram budget. Heavy quantisation (the only way to make it fit into 24gb) will affect it a lot. Lots of reports on locallama about subpar results, especially from kv cache quant. We've had good experiences with running it fp8 and full cache, but going lower than that will impact the quality a lot.