**Efficient Use of Large System RAM**
A user on r/LocalLLaMA inquired about the limitations when dealing with large amounts of system RAM but limited VRAM, specifically 128 GB of system RAM and only 16 GB of GPU memory. The question revolves around whether such setups are still constrained to models that fit within the GPU’s memory (aside from CPU offloading techniques like Mix & Match) and if there are methods to leverage system RAM for increasing context size with acceptable token generation speed.
**Takeaways:**
– **Limited Models**: Users may face limitations in using larger language models due to the constraint of available GPU VRAM.
– **System RAM Utilization**: There is potential for utilizing system RAM alongside GPU memory, but this would require specific techniques and optimizations.
– **Research Needed**: More investigation into how best to leverage both system and GPU resources is needed to fully realize these benefits.
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