| ▲ | parsimo2010 8 hours ago | |
Tl;dr: think hard about what you’d use this much RAM for in a desktop setting and do some research about how people like the 395 for your use case. Not all use cases work well. Anyone who thinks they are going to serve some 100+ GB LLM locally, remember that memory bandwidth becomes a key limitation for large models. While you might be able to load a model, token generation can be very slow. MoE models like Qwen3.5-122B-A10B work decently fast, but dense models of a decent size are slow and you won’t want to use them. I’ve got a 395 system, and found that I’m quite happy with Qwen3.6-35B-A3B, generating at around 50 t/s, but the dense 27B model is 20-25 t/s and that’s the lower limit I’m willing to tolerate. So a 70b dense model is just not going to happen. That means you can’t really use that much RAM. A reasonable use case is to have multiple smaller models loaded- you can have an image generation model loaded along with the text model. Or you can use this computer for development simultaneously with serving LLMs. Those ideas work okay. But trying to load up a single giant model is going to test your patience. | ||
| ▲ | esseph 7 hours ago | parent [-] | |
> A reasonable use case is to have multiple smaller models loaded- you can have an image generation model loaded along with the text model. Lemonade server updated yesterday for an Arena model / ai routing. --- The Lemonade local AI server allows easily deploying LLM workloads across Ryzen AI NPUs, Radeon GPUs, and CPUs with ease under both Windows and Linux. The most significant change with Lemonade 11.5 is the completion of the Lemonade Router that can be used for automatically routing queries to relevant models based on defined policies -- or even LLM-as-a-router for using a small LLM to in turn determine which model to route a particular request. The Lemonade Router allows steering requests based on rule, classifier, semantic similarity, or LLM-as-router policies. The policies are defined in JSON files or can also be authored via the Lemonade GUI. More details on these router capabilities can be found via this commit. Lemonade 11.5 also introduces a server-side job engine to let clients post multi-step recipes and managing them via /jobs endpoints. From these endpoints the muilti-step recipes can be paused / interrupted / resumed / deleted. And another one is that the lemond daemon can now act as an MCP client host to connect external stdio MCP servers. | ||