Use-case guide · Long context

Should you pick RTX 3080 for long context?

RTX 3080 has 10 GB VRAM. Whether it's the right fit for long context depends on your model size, expected QPS, and budget. Below is what we're seeing in production.

VRAM + model fit

RTX 3080 fits models up to ~7B parameters in BF16 comfortably with room for KV-cache. For long context specifically, you'll want to leave headroom for context length growth.

Pricing

Live pricing across all providers for RTX 3080 is on the GPU detail page — click through for the sortable list.

Throughput

On long context workloads, RTX 3080 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.