allocate13B class GPU requirements
What it takes to run 13B class locally: memory by quantization, the smallest GPU that fits, and the managed alternative.
Smallest single device that fits: RTX 4090 (24 GB)
How it works
Common questions
How much VRAM does 13B class need?
At 8K context: roughly 30 GB at FP16, 15 GB at 8-bit, and 8 GB at 4-bit, including KV cache and runtime overhead. Longer context adds memory linearly.
Can a single GPU run 13B class?
At 4-bit, yes: a RTX 4090 (24 GB) or larger handles it at 8K context. At FP16 you need a RTX 5090 (32 GB) or larger.
Does quantization hurt 13B class's quality?
Modern 4-bit quantization costs a small amount of quality for a 4x memory saving; 8-bit is near-lossless. Validate on your own tasks before production.
What license is 13B class under?
Varies. Check the license terms for your use case before deployment.
Is there an alternative to buying GPUs for 13B class?
Yes: managed inference. Allocate serves 13B class token-metered inside your own boundary, and if you fine-tune it on your data, the weights belong to you. Idle time costs nothing.
More free tools
Allocate serves 13B class token-metered inside your own boundary. No hardware to buy, and if you fine-tune it on your data, the weights are yours.