Kimi K3’s 2.8T open weights need data-center hardware to run locally

ArtificialAnlys · x · 2026-07-29

Running Kimi K3 locally needs data-center scale hardware

Artificial Analysis argues that Kimi K3 is far harder to host locally than recent open-weight flagships like GLM-5.2. It says Kimi K3 is the first open-weights model that does not fit on a single Hopper node even at 4-bit precision.

Key points

Practical hardware targets

The post lists realistic configurations that can fit the model and leave room for cache: 8× B300 or GB300, 16× B200 or GB200, or AMD 8× MI355X / MI455X.

Artificial Analysis says it will publish day-one inference benchmarks soon and track how serving performance improves as inference stacks mature.

Related event: Kimi K3 Open Weights Demand Data Center Hardware(3 posts)→

Original post →

More from Infra

Infra channel →