All LLM Models
Browse 593 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
Qwopus3.5 4B Coder
Jackrong · 4.7B · runs from 9.8 GB
1.4K
11Qwopus3.5 4B Coder is a 4.7B-parameter open language model from Jackrong. 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.
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.
Qwen3.5 4B Claude Opus 4.6 Distilled Heretic
ghost-actual · 4.5B · runs from 9.6 GB
Qwen3.5 4B Claude Opus 4.6 Distilled Heretic is a 4.5B-parameter open language model from ghost-actual in the Qwen 3.5 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.
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.
Qwen35 4B Soyuz Merged
AlexWortega · 4B · runs from 8.5 GB
Qwen35 4B Soyuz Merged is a 4B-parameter open language model from AlexWortega in the Qwen 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.
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.
GPT OSS 20B Heretic Ara v3
p-e-w · 21.5B · runs from 9.5 GB
GPT OSS 20B Heretic Ara v3 is a 21.5B-parameter open language model from p-e-w in the GPT-OSS 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.
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.
Turkish Gemma 9B v0.1
ytu-ce-cosmos · 9.2B · runs from 4.8 GB
Turkish Gemma 9B v0.1 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.
Gemma 3 12B IT Heretic v2
diffusionmodels1254ani · 12.2B · runs from 6.2 GB
Gemma 3 12B IT Heretic v2 is a 12.2B-parameter open language model from diffusionmodels1254ani in the Gemma 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.
T5gemma L L Ul2 IT
Google · 1.2B · runs from 2.7 GB
T5gemma 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.
Supergemma4 E4b Abliterated
Jiunsong · 7.5B · runs from 3.7 GB
Supergemma4 E4b Abliterated is a 7.5B-parameter open language model from Jiunsong in the Gemma 4 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.
Sweep Next Edit v2 7B
sweepai · 7.6B · runs from 3.6 GB
Sweep Next Edit v2 7B is a 7.6B-parameter open language model from sweepai. 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.
Nidum Gemma 2B Uncensored
VibeStudio · 2.5B · runs from 1.4 GB
Nidum Gemma 2B Uncensored is a 2.5B-parameter open language model from VibeStudio in the Gemma 2 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.
VibeThinker 1.5B
WeiboAI · 1.8B · runs from 1.1 GB
VibeThinker 1.5B is a 1.8B-parameter open language model from WeiboAI. 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 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.
CyberSecQwen 4B
lablab-ai-amd-developer-hackathon · 4.0B · runs from 2.2 GB
CyberSecQwen 4B is a 4.0B-parameter open language model from lablab-ai-amd-developer-hackathon in the Qwen 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.
Internlm Chat 20B
InternLM · 20B · runs from 11.3 GB
Internlm Chat 20B is a 20B-parameter open language model from InternLM in the InternLM 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.