All LLM Models
Browse 1475 LLM models with VRAM requirements, quantization options, and hardware compatibility.
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.
Model List
LFM2.5 1.2B Instruct Uncensored
zaakirio · 1.2B · runs from 0.9 GB
100
2LFM2.5 1.2B Instruct Uncensored is a 1.2B-parameter open language model from zaakirio in the LFM2.5 family. It supports a context window of up to 128,000 tokens. See its VRAM requirements by quantization and which GPUs and Macs can run it locally below.
Qwen3 4B Domino B16
Huang2020 · 588M · runs from 0.6 GB
Qwen3 4B Domino B16 is a 588M-parameter open language model from Huang2020 in the Qwen 3 family. It supports a context window of up to 40,960 tokens. See its VRAM requirements by quantization and which GPUs and Macs can run it locally below.
MobileLLM R1.5 950M
Meta · 950M · runs from 2.1 GB
MobileLLM R1.5 950M is a 950M-parameter open language model from Meta. See its VRAM requirements by quantization and which GPUs and Macs can run it locally below.
WorldSim Opus 3.6 35B A3B
Gryphe · 35.1B · runs from 70.6 GB
WorldSim Opus 3.6 35B A3B is a 35.1B-parameter open language model from Gryphe. It supports a context window of up to 262,144 tokens. See its VRAM requirements by quantization and which GPUs and Macs can run it locally below.
Deepseek Coder 1.3B Kexer
JetBrains · 1.3B · runs from 1.3 GB
Deepseek Coder 1.3B Kexer is a 1.3B-parameter open language model from JetBrains in the DeepSeek Coder family. It supports a context window of up to 16,384 tokens. See its VRAM requirements by quantization and which GPUs and Macs can run it locally below.