by Mistral AI

Mistral Large 2.

text open weights datacenter 123B params 128K ctx Transformer Quality 89.0
Cheapest input
$2.0/M
on Mistral La Plateforme
Cheapest output
$6.0/M
on Mistral La Plateforme
Fastest
26 tok/s
on OpenRouter
Smallest GPU
1× Nvidia RTX PRO 6000 S
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)
384 GB Compare →
FP8
FP8 — 8-bit float (Hopper / Blackwell)
192 GB Compare →
INT4
INT4 — 4-bit integer (~4× VRAM saving)
96 GB Compare →
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