by Nvidia

NVIDIA: Llama 3.3 Nemotron Super 49B V1.5.

text open weights workstation 49B params 131K ctx
Cheapest input
$0.1/M
on DeepInfra
Cheapest output
$0.4/M
on DeepInfra
Fastest
52 tok/s
on OpenRouter
Smallest GPU
1× Nvidia RTX 5090 Laptop GPU
Run it yourself

Cheapest hardware per quantisation.

Each row is one quantisation tier (the same weights compressed differently). Lower precision → lower VRAM → cheaper hardware, at the cost of small accuracy loss. $/hr refreshed hourly from each provider's API.

Quantisation Cheapest GPU config Total VRAM Live $/hr tokens/sec
FP16
FP16 — half precision (default)
141 GB Compare →
FP8
FP8 — 8-bit float (Hopper / Blackwell)
64 GB Compare →
INT4
INT4 — 4-bit integer (~4× VRAM saving)
32 GB Compare →
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