All LLM Models
Browse 1214 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
Qwen3.8 27B Uncensored
orcarouter · 27.8B · runs from 13.0 GB
67.0K
232Qwen3.8 27B Uncensored is a 27.8B-parameter open language model from orcarouter in the Qwen 3.8 family. See its VRAM requirements by quantization and which GPUs and Macs can run it locally below.
Falcon Mamba Tiny Dev
TII UAE · 9M · runs from 0.0 GB
Falcon Mamba Tiny Dev is a 9M-parameter open language model from TII UAE in the Falcon family. See its VRAM requirements by quantization and which GPUs and Macs can run it locally below.
Nemotron H 8B Base 8K
NVIDIA · 8.1B · runs from 17.8 GB
Nemotron H 8B Base 8K is a 8.1B-parameter open language model from NVIDIA in the Nemotron family. See its VRAM requirements by quantization and which GPUs and Macs can run it locally below.
Opt 6.7B
Meta · 6.7B · runs from 14.7 GB
Opt 6.7B is a 6.7B-parameter open language model from Meta. 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.
K2 Horizon 7B Uno
IFM · 7B · runs from 3.3 GB
K2 Horizon 7B Uno is a 7B-parameter open language model from IFM. See its VRAM requirements by quantization and which GPUs and Macs can run it locally below.
Distil Lfm25 Shellper
distil-labs · 354M · runs from 0.5 GB
Distil Lfm25 Shellper is a 354M-parameter open language model from distil-labs. 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.
XCurOS0.1 8B Instruct
XCurOS · 7.6B · runs from 15.7 GB
XCurOS0.1 8B Instruct is a 7.6B-parameter open language model from XCurOS. 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.
NVIDIA Nemotron 3 Nano 30B A3B Base BF16
NVIDIA · 31.6B · runs from 14.8 GB
NVIDIA Nemotron 3 Nano 30B A3B Base BF16 is the foundation model version of the Nemotron 3 Nano 30B, offered in full BF16 precision. Unlike the chat-tuned variants, this base model hasn't been instruction-tuned, making it suitable for fine-tuning, research, or custom alignment workflows. At 31.6 billion total parameters with a mixture-of-experts architecture, the base model gives developers and researchers a strong starting point for building specialized applications. It retains all the architectural benefits of the MoE design while leaving the behavioral layer open for customization.
Qwen3.8 27B EfficientThink Uncensored K3 Opus5 Grok4.6 GPT5.6Sol SFT SimPO DFlash2
nerkyor · 27B · runs from 12.6 GB
Qwen3.8 27B EfficientThink Uncensored K3 Opus5 Grok4.6 GPT5.6Sol SFT SimPO DFlash2 is a 27B-parameter open language model from nerkyor in the Qwen 3.8 family. See its VRAM requirements by quantization and which GPUs and Macs can run it locally below.
Granite 4.2 3B
IBM · 3.7B · runs from 2.0 GB
Granite 4.2 3B is a 3.7B-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.
DialoGPT Small
Microsoft · 176M · runs from 0.1 GB
DialoGPT Small is a 176M-parameter open language model from Microsoft. 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.
GLM 5.3 Flash DFlash2
incoai · 1.2B · runs from 0.8 GB
GLM 5.3 Flash DFlash2 is a 1.2B-parameter open language model from incoai in the GLM 5 family. 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.
GPT Neo 1.3B
EleutherAI · 1.4B · runs from 3 GB
GPT Neo 1.3B is a 1.4B-parameter open language model from EleutherAI. 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.
ERNIE 4.5 21B A3B Thinking
Baidu · 21.8B · runs from 9.7 GB
ERNIE 4.5 21B A3B Thinking is a 21.8B-parameter open language model from Baidu in the ERNIE 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 Guard 3 8B
Meta · 8.0B · runs from 17.7 GB
Meta Llama Guard 3 8B is an 8-billion parameter safety classifier model built on the Llama 3.1 architecture. Unlike general-purpose chat models, Llama Guard is specifically designed to classify whether prompts or responses contain unsafe content across categories such as violence, sexual content, criminal planning, and other policy violations. The model is intended to be used as a moderation layer in LLM-based applications, providing input and output safety filtering. It follows a taxonomy-based classification approach and can be customized for different safety policies. Released under the Llama 3.1 Community License.
Mistral NeMo Minitron 8B Instruct
NVIDIA · 8.4B · runs from 4.2 GB
Mistral NeMo Minitron 8B Instruct is a 8.4B-parameter open language model from NVIDIA in the Mistral 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.
GPT Bigcode Santacoder
BigCode · 1.1B · runs from 0.5 GB
GPT Bigcode Santacoder is a 1.1B-parameter open language model from BigCode. 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.
Beetle Monolingual Fineweb3 Eng
Beetle-FineWeb3-24B · 194M · runs from 0.4 GB
Beetle Monolingual Fineweb3 Eng is a 194M-parameter open language model from Beetle-FineWeb3-24B. 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.
PowerLM 3B
ibm-research · 3.5B · runs from 2.5 GB
PowerLM 3B is a 3.5B-parameter open language model from ibm-research. 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.
Opt 2.7B
Meta · 2.7B · runs from 5.9 GB
Opt 2.7B is a 2.7B-parameter open language model from Meta. 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.
Stablelm 3B 4e1t
Stability AI · 2.8B · runs from 2.2 GB
Stablelm 3B 4e1t is a 2.8B-parameter open language model from Stability AI in the StableLM 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.
Tiny LLM
arnir0 · 13M · runs from 0.3 GB
Tiny LLM is a 13M-parameter open language model from arnir0. 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.
Llama 3 8B Instruct Gradient 1048k
gradientai · 8.0B · runs from 4.0 GB
Llama 3 8B Instruct Gradient 1048k is a 8.0B-parameter open language model from gradientai in the Llama 3 family. 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.
Granite 3.1 8B Instruct
IBM · 8.2B · runs from 4.1 GB
Granite 3.1 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.
Beetle Monolingual Humanscale Eng
Beetle-HumanScale · 194M · runs from 0.4 GB
Beetle Monolingual Humanscale Eng is a 194M-parameter open language model from Beetle-HumanScale. 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.
Typhoon2.5 Qwen3 4B
typhoon-ai · 4.0B · runs from 2.2 GB
Typhoon2.5 Qwen3 4B is a 4.0B-parameter open language model from typhoon-ai in the Qwen 3 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.
GPT OSS Safeguard 20B
OpenAI · 21.5B · runs from 9.5 GB
GPT OSS Safeguard 20B is a 21.5B-parameter open language model from OpenAI 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.
Granite 3.0 8B Instruct
IBM · 8.2B · runs from 4.1 GB
Granite 3.0 8B Instruct is a 8.2B-parameter open language model from IBM in the Granite 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.
SedibaLM
Sedibaai · 1.5B · runs from 1.0 GB
SedibaLM is a 1.5B-parameter open language model from Sedibaai. 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 3.0 7.8B Instruct
LGAI-EXAONE · 7.8B · runs from 17.2 GB
EXAONE 3.0 7.8B Instruct is a 7.8B-parameter open language model from LGAI-EXAONE in the EXAONE family. See its VRAM requirements by quantization and which GPUs and Macs can run it locally below.