All LLM Models
Browse 1242 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
Llava Onevision Qwen2 7B Ov
lmms-lab · 8.0B · runs from 3.8 GB
39.7K
64Llava Onevision Qwen2 7B Ov is a 8.0B-parameter open language model from lmms-lab in the Qwen 2 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.
H2ovl Mississippi 800M
h2oai · 826M · runs from 1.8 GB
H2ovl Mississippi 800M is a 826M-parameter open language model from h2oai. See its VRAM requirements by quantization and which GPUs and Macs can run it locally below.
Smollm2 360M Aac Watch
dcostenco · 360M · runs from 0.2 GB
Smollm2 360M Aac Watch is a 360M-parameter open language model from dcostenco in the SmolLM family. See its VRAM requirements by quantization and which GPUs and Macs can run it locally below.
SOLAR 10.7B Instruct v1.0
Upstage · 10.7B · runs from 5.3 GB
SOLAR 10.7B Instruct v1.0 is a 10.7B-parameter open language model from Upstage in the Solar 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.
Deepseek Coder 1.3B Instruct
DeepSeek · 1.3B · runs from 1.3 GB
DeepSeek Coder 1.3B Instruct is an ultra-compact code model designed for environments where hardware resources are extremely limited. Despite having just 1.3 billion parameters, it can handle basic code completion, simple generation tasks, and code Q&A across common programming languages. This is one of the smallest viable code models available, capable of running on integrated graphics or very low-end dedicated GPUs. It is well suited for edge deployment, embedded development environments, or as a fast local autocomplete engine where response speed matters more than handling complex multi-file reasoning tasks.
Deepseek Llm 7B Base
DeepSeek · 7B · runs from 4.3 GB
Deepseek Llm 7B Base is a 7B-parameter open language model from DeepSeek in the DeepSeek 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.
Xing4.0 29B A4B
XingChen-AGI · 31.2B · runs from 14.7 GB
Xing4.0 29B A4B is a 31.2B-parameter open language model from XingChen-AGI. 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.
Kimi K2.6 Eagle3 Mla
lightseekorg · 3.0B · runs from 1.6 GB
Kimi K2.6 Eagle3 Mla is a 3.0B-parameter open language model from lightseekorg 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.
Qwen3Guard Gen 8B
Alibaba · 8.2B · runs from 4.1 GB
Qwen3Guard Gen 8B is a 8.2B-parameter open language model from Alibaba in the Qwen 3 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.
Ling Mini 2.0
Inclusion AI · 16.3B · runs from 7.3 GB
Ling Mini 2.0 is a 16.3B-parameter open language model from Inclusion 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.
Olmo 3 7B Instruct SFT
Allen AI · 7.3B · runs from 4.5 GB
Olmo 3 7B Instruct SFT is a 7.3B-parameter open language model from Allen AI in the OLMo family. 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.
Tofu Ft Phi 1.5
locuslab · 1.4B · runs from 1.3 GB
Tofu Ft Phi 1.5 is a 1.4B-parameter open language model from locuslab in the Phi 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.
Internlm2 5 7B Chat
InternLM · 7B · runs from 3.5 GB
Internlm2 5 7B Chat is a 7B-parameter open language model from InternLM in the InternLM 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.
Ko PlatYi 6B
kyujinpy · 6B · runs from 3.0 GB
Ko PlatYi 6B is a 6B-parameter open language model from kyujinpy. 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.
Granite 3.2 8B Instruct
IBM · 8.2B · runs from 4.1 GB
Granite 3.2 8B Instruct is a 8.2B-parameter open language model from IBM in the Granite 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.
Fanar 1 9B Instruct
QCRI · 8.8B · runs from 4.7 GB
Fanar 1 9B Instruct is a 8.8B-parameter open language model from QCRI. 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.
OLMo 2 1124 7B Instruct
Allen AI · 7.3B · runs from 4.5 GB
OLMo 2 1124 7B Instruct is a 7.3B-parameter open language model from Allen AI in the OLMo 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.
Antares 1B
fdtn-ai · 1.8B · runs from 4.0 GB
Antares 1B is a 1.8B-parameter open language model from fdtn-ai. See its VRAM requirements by quantization and which GPUs and Macs can run it locally below.
Qwen3.5 4B Super Coder
jica98 · 4B · runs from 2.2 GB
Qwen3.5 4B Super Coder is a 4B-parameter open language model from jica98 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.
BioMistral 7B
BioMistral · 7B · runs from 3.5 GB
BioMistral 7B is a 7B-parameter open language model from BioMistral in the Mistral 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.
Lynx Instruct 30B
bineric · 30.5B · runs from 13.4 GB
Lynx Instruct 30B is a 30.5B-parameter open language model from bineric. 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.
Llama3.1 Typhoon2 8B Instruct
typhoon-ai · 8.0B · runs from 4.0 GB
Llama3.1 Typhoon2 8B Instruct is a 8.0B-parameter open language model from typhoon-ai 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.
Ruadapt Qwen2.5 7B Ext U48 Instruct
RefalMachine · 7.6B · runs from 3.6 GB
Ruadapt Qwen2.5 7B Ext U48 Instruct is a 7.6B-parameter open language model from RefalMachine 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.
Qwen1.5 MoE A2.7B Chat
Alibaba · 14.3B · runs from 6.8 GB
Qwen1.5 MoE A2.7B Chat is a 14.3B-parameter open language model from Alibaba in the Qwen 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.
EXAONE 3.5 32B Instruct
LGAI-EXAONE · 32.0B · runs from 15.0 GB
EXAONE 3.5 32B Instruct is a 32.0B-parameter open language model from LGAI-EXAONE in the EXAONE 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.
Deepseek Moe 16B Base
DeepSeek · 16.4B · runs from 7.7 GB
Deepseek Moe 16B Base is a 16.4B-parameter open language model from DeepSeek in the DeepSeek 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.
Gemma 4 E4B IT OBLITERATED
OBLITERATUS · 8.0B · runs from 3.9 GB
Gemma 4 E4B IT OBLITERATED is a 8.0B-parameter open language model from OBLITERATUS 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.
TIPO 500M
KBlueLeaf · 508M · runs from 0.7 GB
TIPO 500M is a 508M-parameter open language model from KBlueLeaf. 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.
Mythos Nano
squ11z1 · 3.1B · runs from 1.7 GB
Mythos Nano is a 3.1B-parameter open language model from squ11z1. 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.
Deepseek Coder 1.3B Base
DeepSeek · 1.3B · runs from 1.3 GB
Deepseek Coder 1.3B Base is a 1.3B-parameter open language model from DeepSeek 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.