Nvidia Chat with RTX hands-on: 35GB installer, Mistral 7B and Llama 2 are 70GB, great at summarizing details and targeted questions, but no follow-up questions
NVIDIA's AI chatbot runs locally on your PC, and it works with the data you provide. — NVIDIA does a lot of interesting things around AI …
Context & Ripple Effects
This hands-on follows Nvidia’s early release of a local RTX chatbot for RTX 30- and 40-series PCs. It adds practical evidence about where the product is useful today: working over user-supplied data rather than acting as a broadly conversational assistant.
The installation and model-package sizes make the hardware cost of local AI tangible. That matters because Nvidia is positioning the GPU-equipped PC as the place where AI workloads can run, not merely as a client for hosted services.
First-order effects
- Users must allocate substantial local storage for the roughly 35GB application and roughly 70GB Mistral 7B or Llama 2 packages before using the chatbot.
- Nvidia Chat is immediately suited to document summarization and targeted retrieval from supplied data, while its inability to handle follow-up questions limits iterative research and conversational workflows.
Second-order effects
- Local-AI tools will be compared not only on answer quality but on installation footprint, model download size, and whether they sustain multi-turn interactions.
- The storage burden makes system configuration part of adoption for RTX PC owners, while the missing follow-up capability gives competing local assistants a clear usability benchmark.
Third-order effects
- If local assistants continue moving onto consumer PCs, endpoint GPU, memory, and storage capacity will increasingly shape which AI features users can practically deploy.
- The pattern points toward a split between compact, task-specific local tools and richer assistants that require more capable hardware or alternative deployment models; the balance will depend on whether usability improves faster than resource demands.
The trend: This is one data point in the shift of generative AI from hosted chat services toward hardware-constrained, privacy-oriented workloads running on the PC.