Text generation · served with vLLM · ↓ 3.5K downloads a month · View on Hugging Face
LGAI-EXAONE/K-EXAONE-2.0-750B-A37B needs about 1670.4 GB of GPU memory for conversations of up to 8,192 tokens. It runs on 8x Nvidia B300 from $133.62/h right now.
Weights
1499 GB
GPU memory needed
about 1670.4 GB
Conversation length
8,192 tokens
Model allows
262,144 tokens
Memory · disk
757.4 GB · 1689 GB
Architecture
ExaoneMoeForCausalLM
Licence
apache-2.0
Hardware and deploy
$133.62/h from your balance while it runs, billed by the hour; stop it from its page. GridPup rents the machine, which downloads the model from Hugging Face (usually ready in 10 to 15 minutes), and gives you an https address, keys and a Playground.
Prices are per hour for the whole machine and its disk, right now. Speed is Vast's DLPerf score of the machine, relative to the cheapest. Best value: the most speed per dollar. Only machines with a Vast reliability above 95% that download at 400 Mbit/s or more are offered: the machine fetches the model itself.
Questions
How much GPU memory does K-EXAONE-2.0-750B-A37B need?
About 1670.4 GB for conversations of up to 8,192 tokens: 1498.72 GB of weights, the cache for one full-length conversation and the runtime's own memory.
What is the cheapest GPU to run K-EXAONE-2.0-750B-A37B?
Right now 8x Nvidia B300 at $133.62 an hour. Prices are live offers from GPU clouds, checked every 15 minutes.
Can K-EXAONE-2.0-750B-A37B run on an RTX 4090?
Not on one: it needs about 1670.4 GB and an RTX 4090 has 24 GB. Use a bigger GPU, or a smaller (quantized) version of the model.
How do I deploy K-EXAONE-2.0-750B-A37B as an API?
Pick a machine on its GridPup page and press Deploy: GridPup rents the GPU, downloads the model from Hugging Face and serves it at an https address with keys and OpenAI's chat API, billed by the hour.