All LLM Models
Browse 62 LLM models with VRAM requirements, quantization options, and hardware compatibility.
Model List
T5gemma L L Ul2 IT
Google · 1.2B · runs from 2.3 GB at Q4
1.0K
6T5gemma L L Ul2 IT is a 1.2B-parameter open language model from Google in the Gemma family. See its VRAM requirements by quantization and which GPUs and Macs can run it locally below.
T5gemma B B Ul2 IT
Google · 591M · runs from 1.6 GB at Q4
T5gemma B B Ul2 IT is a 591M-parameter open language model from Google in the Gemma family. See its VRAM requirements by quantization and which GPUs and Macs can run it locally below.
Understanding LLM VRAM Requirements
How much VRAM you need depends on the model size and quantization level. Quantization reduces the precision of model weights, trading small quality losses for significantly lower VRAM usage. For example, a 7B parameter model needs ~14 GB at FP16 but only ~4 GB at Q4_K_M quantization.