Use-case guide · RAG chatbot

Should you pick RTX 3070 for rag chatbot?

RTX 3070 has 8 GB VRAM. Whether it's the right fit for rag chatbot depends on your model size, expected QPS, and budget. Below is what we're seeing in production.

VRAM + model fit

RTX 3070 fits models up to ~6B parameters in BF16 comfortably with room for KV-cache. For rag chatbot specifically, you'll want to leave headroom for context length growth.

Pricing

Live pricing across all providers for RTX 3070 is on the GPU detail page — click through for the sortable list.

Throughput

On rag chatbot workloads, RTX 3070 typically delivers the throughput published in its FP16 spec, minus the framework overhead (vLLM ≈ 85% MFU, TGI ≈ 70%).

Try the calculator to size the hardware for your specific model, or see all GPUs on the InferenceScore leaderboard.