All LLM Models
Browse 529 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
Qwen3.5 9B Uncensored
LEONW24 · 9B · runs from 4.2 GB
1.8K
8Qwen3.5 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.
Nanowhale 100M
Hugging Face · 110M · runs from 0.5 GB
Nanowhale 100M is a 110M-parameter open language model from Hugging Face. It supports a context window of up to 2,048 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.
Qwen3 0.6B Heretic Abliterated Uncensored
DavidAU · 596M · runs from 0.7 GB
Qwen3 0.6B Heretic Abliterated Uncensored is a 596M-parameter open language model from DavidAU 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.
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.
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.
Qwen3 0.6B
litert-community · 0.6B · runs from 0.3 GB
Qwen3 0.6B is a 0.6B-parameter open language model from litert-community in the Qwen 3 family. See its VRAM requirements by quantization and which GPUs and Macs can run it locally below.
Vicuna 13B V1.3
LMSYS · 13B · runs from 6.1 GB
Vicuna 13B V1.3 is a 13B-parameter open language model from LMSYS in the Vicuna family. It supports a context window of up to 2,048 tokens. 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.
AFM 4.5B
Arcee AI · 4.6B · runs from 2.4 GB
AFM 4.5B is a 4.6B-parameter open language model from Arcee AI. It supports a context window of up to 65,536 tokens. See its VRAM requirements by quantization and which GPUs and Macs can run it locally below.
EuroMoE 2.6B A0.6B 2512
utter-project · 2.6B · runs from 1.5 GB
EuroMoE 2.6B A0.6B 2512 is a 2.6B-parameter open language model from utter-project. 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.
MiniCPM MoE 8x2B
openbmb · 8x2B · runs from 7.8 GB
MiniCPM MoE 8x2B is a 8x2B-parameter open language model from openbmb in the MiniCPM family. 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.
MedPsy 4B
qvac · 4.4B · runs from 2.4 GB
MedPsy 4B is a 4.4B-parameter open language model from qvac. 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.
Turkish Gemma 9B T1
ytu-ce-cosmos · 9.2B · runs from 4.8 GB
Turkish Gemma 9B T1 is a 9.2B-parameter open language model from ytu-ce-cosmos in the Gemma 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.
Param 1 2.9B Instruct
bharatgenai · 2.9B · runs from 6.3 GB
Param 1 2.9B Instruct is a 2.9B-parameter open language model from bharatgenai. 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.
Supra 50M Base
SupraLabs · 52M · runs from 0.3 GB
Supra 50M Base is a 52M-parameter open language model from SupraLabs. 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.
NuExtract 1.5
numind · 3.8B · runs from 2.7 GB
NuExtract 1.5 is a 3.8B-parameter open language model from numind. 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.
Schematron 8B
inference-net · 8B · runs from 4.0 GB
Schematron 8B is a 8B-parameter open language model from inference-net. 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.
GPT X2 125M
AxiomicLabs · 144M · runs from 0.6 GB
GPT X2 125M is a 144M-parameter open language model from AxiomicLabs. 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.
Tiny Aya Water
Cohere · 3.3B · runs from 7.4 GB
Tiny Aya Water is a 3.3B-parameter open language model from Cohere in the Aya family. See its VRAM requirements by quantization and which GPUs and Macs can run it locally below.
Falcon H1 0.5B Instruct
TII UAE · 521M · runs from 0.6 GB
Falcon H1 0.5B Instruct is a 521M-parameter open language model from TII UAE in the Falcon 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.
Penguin VL 2B
tencent · 2.2B · runs from 4.9 GB
Penguin VL 2B is a 2.2B-parameter open language model from tencent. 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.
Soren 1 Small
syntropy-ai · 1.9B · runs from 4.2 GB
Soren 1 Small is a 1.9B-parameter open language model from syntropy-ai. It supports a context window of up to 1,048,576 tokens. See its VRAM requirements by quantization and which GPUs and Macs can run it locally below.
Gemma 3 270M IT
litert-community · 270M · runs from 0.1 GB
Gemma 3 270M IT is a 270M-parameter open language model from litert-community in the Gemma 3 family. See its VRAM requirements by quantization and which GPUs and Macs can run it locally below.
Hunyuan 0.5B Pretrain
tencent · 539M · runs from 0.6 GB
Hunyuan 0.5B Pretrain is a 539M-parameter open language model from tencent in the Hunyuan 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.
Orca Mini 3B
pankajmathur · 3.4B · runs from 1.6 GB
Orca Mini 3B is a 3.4B-parameter open language model from pankajmathur in the Orca family. It supports a context window of up to 2,048 tokens. See its VRAM requirements by quantization and which GPUs and Macs can run it locally below.
Phi 4 Mini Flash Reasoning
Microsoft · 3.9B · runs from 2.3 GB
Phi 4 Mini Flash Reasoning is a 3.9B-parameter open language model from Microsoft in the Phi 4 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.
PicoMistral 23M
PicoKittens · 24M · runs from 0.3 GB
PicoMistral 23M is a 24M-parameter open language model from PicoKittens in the Mistral family. 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.
Kumru 2B
vngrs-ai · 2.4B · runs from 1.4 GB
Kumru 2B is a 2.4B-parameter open language model from vngrs-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.
Kumru 2B Base
vngrs-ai · 2.4B · runs from 1.4 GB
Kumru 2B Base is a 2.4B-parameter open language model from vngrs-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.