Embeddings (features) · served with Text Embeddings Inference · ↓ 1.7K downloads a month · View on Hugging Face
codefuse-ai/F2LLM-0.6B needs about 3 GB of GPU memory. It runs on one GTX 1650 from $0.06/h right now; best value: RTX 5090 at $0.67/h.
Weights
1.2 GB
GPU memory needed
about 3 GB
Model allows
40,960 tokens
Memory · disk
8 GB · 22 GB
Architecture
Qwen3Model
Licence
apache-2.0
Hardware and deploy
Deploying ONNX models from the catalog is coming soon. Today, download the files from Hugging Face and upload them in Inference.
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 F2LLM-0.6B need?
About 3 GB: 1.19 GB of weights and the runtime's own memory.
What is the cheapest GPU to run F2LLM-0.6B?
Right now one GTX 1650 at $0.06 an hour; RTX 5090 at $0.67 an hour is the best value for its speed. Prices are live offers from GPU clouds, checked every 15 minutes.
Can F2LLM-0.6B run on an RTX 4090?
Yes: it needs about 3 GB and an RTX 4090 has 24 GB.