by Meta AI

Muse Spark Open.

multimodal open weights datacenter 822B params 1M ctx
Cheapest input
$1.25/M
on Together AI
Cheapest output
$4.25/M
on Together AI
Smallest GPU
8× Nvidia A100 SXM4
$5.73/hr
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. $/小时为当前最低报价。多卡配置在有同规格实例出租时使用真实实例价格,否则为单卡价格乘以卡数。

Quantisation Cheapest GPU config Total VRAM Live $/hr tokens/sec
FP16
FP16 — half precision (default)
2048 GB $24.57/hr
Cyfuture AI · 按需
— Compare →
FP8
FP8 — 8-bit float (Hopper / Blackwell)
1024 GB $12.41/hr
Cyfuture AI · 按需
— Compare →
INT4
INT4 — 4-bit integer (~4× VRAM saving)
640 GB $5.73/hr
估算:8 × 单卡价格
Nosana · 按需
— Compare →
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