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
Limite 1B Violetto
paradigma-inc · 1.0B · runs from 2.5 GB
1.8K
57Limite 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.
TLive Omni 4B
TaoLiveAIGC · 5.8B · runs from 12.1 GB
TLive Omni 4B is a 5.8B-parameter open language model from TaoLiveAIGC. 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.
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.
Gemma 4 31B IT Control Vectors
gghfez · 31B · runs from 14.5 GB
Gemma 4 31B IT Control Vectors is a 31B-parameter open language model from gghfez in the Gemma 4 family. 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.
Nex N2.5 Mini Uncensored
orcarouter · 35.1B · runs from 16.4 GB
Nex N2.5 Mini Uncensored is a 35.1B-parameter open language model from orcarouter. 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.
FastVLM 7B
Apple · 7.8B · runs from 15.9 GB
FastVLM 7B is a 7.8B-parameter open language model from Apple. 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.
Steerling 8B
guidelabs · 8.4B · runs from 18.5 GB
Steerling 8B is a 8.4B-parameter open language model from guidelabs. 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.
Quasar 10B
silx-ai · 8.6B · runs from 17.8 GB
Quasar 10B is a 8.6B-parameter open language model from silx-ai. It supports a context window of up to 2,097,152 tokens. 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.
Qwen3.6 27B Heretic2 Uncensored Finetune Thinking
DavidAU · 27.4B · runs from 12.4 GB
Qwen3.6 27B Heretic2 Uncensored Finetune Thinking is a 27.4B-parameter open language model from DavidAU in the Qwen 3.6 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.
BananaMind 2 Pro
BananaMind · 160M · runs from 0.7 GB
BananaMind 2 Pro is a 160M-parameter open language model from BananaMind. It supports a context window of up to 3,072 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.
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.
Qwen3.8 27B Obliterated E03
manitcor · 26.9B · runs from 12.2 GB
Qwen3.8 27B Obliterated E03 is a 26.9B-parameter open language model from manitcor 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.
SemanticRepair 270M
Gramscii-IT · 268M · runs from 0.4 GB
SemanticRepair 270M is a 268M-parameter open language model from Gramscii-IT. 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.
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.
MicroLlama v2
ViorikaAI-org · 45M · runs from 0.3 GB
MicroLlama v2 is a 45M-parameter open language model from ViorikaAI-org in the Llama 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.
Pythagoras Prover 4B
Pythagoras-LM · 4.4B · runs from 2.4 GB
Pythagoras Prover 4B is a 4.4B-parameter open language model from Pythagoras-LM. 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 3.2 1B MathCodeInstruct 5k
OliverSundaram · 1.2B · runs from 0.9 GB
Llama 3.2 1B MathCodeInstruct 5k is a 1.2B-parameter open language model from OliverSundaram 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.
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.
Claim Extractor 4B Q 2605
principled-intelligence · 4.7B · runs from 9.8 GB
Claim Extractor 4B Q 2605 is a 4.7B-parameter open language model from principled-intelligence. 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.