This is an MoE model with 1.6T-A49B
The weights were up briefly then taken down due to some issues in the repo files apparently, now they’re back up:
GGUFs are out as well:
DeepSeek published benchmarks for reference:
Are these free to use, or do you have to pay?
free to use if you have the hardware. For this model because of its size, the main problem is the hardware availability/cost. But in general there are 3 ways to run an open weights model:
- pay a provider like DeepSeek/OpenRouter per usage
- buy hardware that can run it locally: actually not a bad investment for a business
- rent hardware that can run it from a cloud provider, hardware can be rented dedicated or time-shared (so called serverless).
Is there some sort of calculator to help one determine the best model to run?
LM Studio will let you know what models you can run on your hardware and has a browser that can point you at the most popular models. It only supports Nvidia cards though. Use Kobol.cpp’s nocuda releases if you have an AMD card.
I’m actually curious as to what’s the most I can run on an Apple M4 Max system.
How much RAM do you have?
96gb
If I understand the nature of your hardware correctly, you should be able to run the MoE models like Gemma4 26B-A4B or Qwen3.6 35B-A3B at a high quantization fairly performantly.
You could try running some of the dense models (like today’s Qwen 3.8 27B) as well, but I expect they’ll be pretty slow (judging by my own experience with a unified RAM system that has a Strix Halo APU). Might still be useful for tasks that you can leave running on their own for a long time instead of for interactive chat style interaction though.
You’ve got enough RAM to load larger models, but there hasn’t been much released in between the “it fits on a 24GB or 32GB GPU that a gamer might own” and the “oh god you need HOW MUCH RAM!?” scales lately…
