Skip to page content
SAVRN
Search Plan a project

Open-weight model

fin-laya-multilingual-mlx

by Li ya9919/fin-laya-multilingual-mlx

fin-laya-multilingual-mlx is an open-weight model from Li, released under other. It has 322M parameters. At 16-bit it needs about 0.8 GB of GPU memory, which fits on 1x MI300X from $1.85 an hour, at the lowest prices in the SAVRN Index.

Parameters322M
Context—
Weights—
Licenseother
AccessOpen weights
Monthly Downloads—

Runs On

What it takes to serve fin-laya-multilingual-mlx (322M parameters): the memory its weights need at each precision, and the cheapest way to rent enough data-center GPUs to hold them.

PrecisionWeightsMemory neededCheapest setupPer hourAlso fits
16-bit 0.6 GB 0.8 GB 1x MI300X (192 GB)
Vultr
$1.85 1x H100 $1.99 · 1x MI325X $2.00
8-bit 0.3 GB 0.4 GB 1x MI300X (192 GB)
Vultr
$1.85 1x H100 $1.99 · 1x MI325X $2.00
4-bit 0.2 GB 0.2 GB 1x MI300X (192 GB)
Vultr
$1.85 1x H100 $1.99 · 1x MI325X $2.00

Memory is the weights at that precision plus 20% for the runtime and a short context; a long context needs more. Prices are the lowest on-demand hourly rates in the SAVRN Index, read Oct 20, 2026.

fin-laya-multilingual-mlx on every accelerator the SAVRN Index prices, at every precision

Model Card

Identity and Version

Repository
ya9919/fin-laya-multilingual-mlx
Publisher
Li
Task
Not stated by the source
Modality
Other
Library
Not stated by the source
Parameters
322M parameters
Languages
en, zh
Revision
368e775e74dca3af4f2c3b2ee4e3a771a6918eeb
First published
2026-10-19
Last updated
2026-10-20

License and Download

License
other
Access
Open weights, no gate
Download from Li

Released by Li through its official repository on Hugging Face. Read the license.

Memory Requirements

PrecisionWeights in memory
16-bit0.6 GB
8-bit0.3 GB
4-bit0.2 GB

Weights only, from the published parameter count; the key-value cache and runtime add to this.

Questions About fin-laya-multilingual-mlx

How much GPU memory does fin-laya-multilingual-mlx need?

About 0.8 GB at 16-bit and 0.2 GB at 4-bit: the weights (322M parameters) plus a working margin. A long context needs more.

What is the cheapest GPU to run fin-laya-multilingual-mlx on?

At 16-bit, 1x MI300X from $1.85 an hour; at 4-bit, 1x MI300X from $1.85 an hour, at the lowest on-demand prices the SAVRN Index lists.

What license is fin-laya-multilingual-mlx released under?

other, as its publisher declares it. Read the license text before commercial use.