RTX 50 and DIGITS: What Does It Mean for Local AI?
Fine-tuning a 2-bit Llama 4 70B with a single consumer GPU
NVIDIA has officially unveiled the RTX 50 GPUs at CES 2025, and it’s big news for the AI community. NVIDIA GPUs have long been the go-to choice for running and fine-tuning large language models (LLMs), so every new release of GPUs is watched closely by AI enthusiasts and professionals alike.
What makes the RTX 50 series particularly exciting is their potential as "consumer" GPUs. They’re powerful, relatively affordable, and perfectly suited for local AI setups.
In a previous article, we benchmarked several NVIDIA GPUs and found the RTX 3090 and 4090 to be the most cost-effective for tasks like parameter-efficient fine-tuning (LoRA) and small-batch inference, especially for LLMs that fit within 24 GB of VRAM.
Will the RTX 5090 be even more cost-effective? And what new possibilities for local LLM applications could it unlock?
In this article, we’ll break down everything we know so far about the RTX 50 series, including what they make possible for local AI. We’ll also take a look at DIGITS, NVIDIA’s upcoming device designed for local LLM applications, featuring a massive 128 GB of memory.