Comment by segmondy
11 hours ago
The entire point of this post is that it's open weights, you can run it yourself and don't have to deal with the API issues. You really do have that choice.
11 hours ago
The entire point of this post is that it's open weights, you can run it yourself and don't have to deal with the API issues. You really do have that choice.
You could subscribe to Anthropic/OpenAI for the rest of your life for the cost it would take to host GLM5.2 locally - you need 1.5TB of VRAM just for the weights
You don't need that much VRAM unless you're targeting a high-performance deployment that's intended to scale far beyond local use. For a lower-throughput case, you can keep the model weights on SSD at very low cost and stream them in for inference. This could actually scale reasonably well if you have something as simple as a previous-gen HEDT with a decent amount of PCIe lanes to host fast storage from.