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Replaced $40/month in AI API subscriptions with self-hosted Ollama + n8n (discuss.tchncs.de)

submitted 2 months ago by quickbitesdev@discuss.tchncs.de to c/selfhosted@lemmy.world

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Quick post about a change I made that's worked out well.

I was using OpenAI API for automations in n8n — email summaries, content drafts, that kind of thing. Was spending ~$40/month.

Switched everything to Ollama running locally. The migration was pretty straightforward since n8n just hits an HTTP endpoint. Changed the URL from api.openai.com to localhost:11434 and updated the request format.

For most tasks (summarization, classification, drafting) the local models are good enough. Complex reasoning is worse but I don't need that for automation workflows.

Hardware: i7 with 16GB RAM, running Llama 3 8B. Plenty fast for async tasks.

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[–] suicidaleggroll@lemmy.world 4 points 2 months ago* (last edited 2 months ago)

In general, you take the model size in billions of parameters (eg: 397B), divide it by 2 and add a bit for overhead, and that’s how much RAM/VRAM it takes to run it at a “normal” quantization level. For Qwen3.5-397B, that’s about 220 GB. Ideally that would be all VRAM for speed, but you can offload some or all of that to normal RAM on the CPU, you’ll just take a speed hit.

So for something like Qwen3.5-397B, it takes a pretty serious system, especially if you’re trying to do it all in VRAM.