All LLM Models
Browse 880 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
Emo 1b14b 1T
Allen AI · 13.6B · runs from 6.3 GB
Emo 1b14b 1T is a 13.6B-parameter open language model from Allen AI. It supports a context window of up to 4,096 tokens. See its VRAM requirements by quantization and which GPUs and Macs can run it locally below.
Supra 1.5 50M Instruct Exp
SupraLabs · 52M · runs from 0.3 GB
Supra 1.5 50M Instruct Exp is a 52M-parameter open language model from SupraLabs. It supports a context window of up to 5,120 tokens. See its VRAM requirements by quantization and which GPUs and Macs can run it locally below.
Veyra 30M Base
veyra-ai · 35M · runs from 0.3 GB
Veyra 30M Base is a 35M-parameter open language model from veyra-ai. It supports a context window of up to 1,024 tokens. See its VRAM requirements by quantization and which GPUs and Macs can run it locally below.
Kimi K2.6 DFlash
NVIDIA · 3.5B · runs from 1.8 GB
Kimi K2.6 DFlash is a 3.5B-parameter open language model from NVIDIA in the Kimi K2 family. 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.
Qwen2.5 Coder 7B Bird Cot
jk200201 · 7.6B · runs from 3.6 GB
Qwen2.5 Coder 7B Bird Cot is a 7.6B-parameter open language model from jk200201 in the Qwen 2.5 family. It supports a context window of up to 32,768 tokens. See its VRAM requirements by quantization and which GPUs and Macs can run it locally below.
Lumma 0.6B Base
FrontiersMind · 649M · runs from 1.8 GB
Lumma 0.6B Base is a 649M-parameter open language model from FrontiersMind. It supports a context window of up to 12,288 tokens. See its VRAM requirements by quantization and which GPUs and Macs can run it locally below.
Qwen3.8 Flash Next Tq4a Tq2e G64
manjunathshiva · 16.6B · runs from 7.4 GB
Qwen3.8 Flash Next Tq4a Tq2e G64 is a 16.6B-parameter open language model from manjunathshiva in the Qwen 3.8 family. 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.
Finance Llama3 8B
instruction-pretrain · 8.0B · runs from 4.0 GB
Finance Llama3 8B is a 8.0B-parameter open language model from instruction-pretrain in the Llama 3 family. It supports a context window of up to 8,192 tokens. See its VRAM requirements by quantization and which GPUs and Macs can run it locally below.
Huihui Qwen3 4B Abliterated v2
huihui-ai · 4.0B · runs from 2.2 GB
Huihui Qwen3 4B Abliterated v2 is a 4.0B-parameter open language model from huihui-ai 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.
UserLM 8B
Microsoft · 8.0B · runs from 4.0 GB
UserLM 8B is a 8.0B-parameter open language model from Microsoft. It supports a context window of up to 8,192 tokens. See its VRAM requirements by quantization and which GPUs and Macs can run it locally below.
MediPhi Instruct
Microsoft · 3.8B · runs from 2.7 GB
MediPhi Instruct is a 3.8B-parameter open language model from Microsoft in the Phi family. It supports a context window of up to 131,072 tokens. See its VRAM requirements by quantization and which GPUs and Macs can run it locally below.
Carbon 8B
HuggingFaceBio · 8.3B · runs from 4.1 GB
Carbon 8B is a 8.3B-parameter open language model from HuggingFaceBio. It supports a context window of up to 32,768 tokens. See its VRAM requirements by quantization and which GPUs and Macs can run it locally below.
Atom2.7m
UniversalComputingResearch · 3M · runs from 0.3 GB
Atom2.7m is a 3M-parameter open language model from UniversalComputingResearch. It supports a context window of up to 512 tokens. See its VRAM requirements by quantization and which GPUs and Macs can run it locally below.
Smol Llama 101M GQA
BEE-spoke-data · 101M · runs from 0.4 GB
Smol Llama 101M GQA is a 101M-parameter open language model from BEE-spoke-data in the Llama family. It supports a context window of up to 1,024 tokens. See its VRAM requirements by quantization and which GPUs and Macs can run it locally below.
Domyn Small v1.0
domyn · 9.8B · runs from 4.7 GB
Domyn Small v1.0 is a 9.8B-parameter open language model from domyn. It supports a context window of up to 32,768 tokens. See its VRAM requirements by quantization and which GPUs and Macs can run it locally below.
Qwen3.8 9B Distill Uncensored Heretic
petruhonk · 9.4B · runs from 4.6 GB
Qwen3.8 9B Distill Uncensored Heretic is a 9.4B-parameter open language model from petruhonk in the Qwen 3.8 family. 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.
NEXUS Coder
fableforge-ai · 1.5B · runs from 1.0 GB
NEXUS Coder is a 1.5B-parameter open language model from fableforge-ai. It supports a context window of up to 32,768 tokens. See its VRAM requirements by quantization and which GPUs and Macs can run it locally below.
Qwen3.5 9B Uncensored
LEONW24 · 9B · runs from 4.2 GB
Qwen3.5 9B Uncensored is a 9B-parameter open language model from LEONW24 in the Qwen 3.5 family. See its VRAM requirements by quantization and which GPUs and Macs can run it locally below.
Limite 1B Violetto
paradigma-inc · 1.0B · runs from 2.5 GB
Limite 1B Violetto is a 1.0B-parameter open language model from paradigma-inc. It supports a context window of up to 131,072 tokens. See its VRAM requirements by quantization and which GPUs and Macs can run it locally below.
Qwen3 1.7B Abliterated
huihui-ai · 1.7B · runs from 0.8 GB
Qwen3 1.7B Abliterated is a 1.7B-parameter open language model from huihui-ai in the Qwen 3 family. See its VRAM requirements by quantization and which GPUs and Macs can run it locally below.
Llama 3.1 Nemotron Safety Guard 8B v3
NVIDIA · 8.0B · runs from 4.0 GB
Llama 3.1 Nemotron Safety Guard 8B v3 is a 8.0B-parameter open language model from NVIDIA in the Llama 3 family. It supports a context window of up to 131,072 tokens. See its VRAM requirements by quantization and which GPUs and Macs can run it locally below.
Llama 3 Korean Bllossom 8B
MLP-KTLim · 8.0B · runs from 4.0 GB
Llama 3 Korean Bllossom 8B is a 8.0B-parameter open language model from MLP-KTLim in the Llama 3 family. It supports a context window of up to 8,192 tokens. See its VRAM requirements by quantization and which GPUs and Macs can run it locally below.
Arch Router 1.5B
katanemo · 1.5B · runs from 1.0 GB
Arch Router 1.5B is a 1.5B-parameter open language model from katanemo. It supports a context window of up to 32,768 tokens. See its VRAM requirements by quantization and which GPUs and Macs can run it locally below.
Evo2 1B Base
Aquiles-ai · 1.1B · runs from 2.4 GB
Evo2 1B Base is a 1.1B-parameter open language model from Aquiles-ai. It supports a context window of up to 8,192 tokens. See its VRAM requirements by quantization and which GPUs and Macs can run it locally below.
Falcon H1 Tiny 90M Instruct
TII UAE · 91M · runs from 0.4 GB
Falcon H1 Tiny 90M Instruct is a 91M-parameter open language model from TII UAE in the Falcon family. 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.
LFM2.5 230M ONNX
Liquid AI · 230M · runs from 0.5 GB
LFM2.5 230M ONNX is a 230M-parameter open language model from Liquid AI 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.
SupraElegans 500k
SupraLabs · 612391 · runs from 0.0 GB
SupraElegans 500k is a 612391-parameter open language model from SupraLabs. See its VRAM requirements by quantization and which GPUs and Macs can run it locally below.
Instinct Python Coder Gemma4 12B Qwen3.8 27B
projectj · 12B · runs from 5.6 GB
Instinct Python Coder Gemma4 12B Qwen3.8 27B is a 12B-parameter open language model from projectj in the Qwen 3.8 family. See its VRAM requirements by quantization and which GPUs and Macs can run it locally below.
Qwen3 8B Abliterated
huihui-ai · 8.2B · runs from 3.8 GB
Qwen3 8B Abliterated is a 8.2B-parameter open language model from huihui-ai in the Qwen 3 family. See its VRAM requirements by quantization and which GPUs and Macs can run it locally below.
Llama Poro 2 8B Instruct
LumiOpen · 8.0B · runs from 4.0 GB
Llama Poro 2 8B Instruct is a 8.0B-parameter open language model from LumiOpen in the Llama family. It supports a context window of up to 8,192 tokens. See its VRAM requirements by quantization and which GPUs and Macs can run it locally below.