All LLM Models
Browse 982 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
Carbon 8B
HuggingFaceBio · 8.3B · runs from 4.1 GB
1.9K
45Carbon 8B is a 8.3B-parameter open language model from HuggingFaceBio. 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.
Atom2.7m
UniversalComputingResearch · 3M · runs from 0.3 GB
Atom2.7m is a 3M-parameter open language model from UniversalComputingResearch. 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.
Smol Llama 101M GQA
BEE-spoke-data · 101M · runs from 0.4 GB
Smol Llama 101M GQA is a 101M-parameter open language model from BEE-spoke-data in the Llama family. 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.
Qwen3.8 Flash Next VQ 2.1bpw
TheDrainFlorist · 24.6B · runs from 10.8 GB
Qwen3.8 Flash Next VQ 2.1bpw is a 24.6B-parameter open language model from TheDrainFlorist 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.
Domyn Small v1.0
domyn · 9.8B · runs from 4.7 GB
Domyn Small v1.0 is a 9.8B-parameter open language model from domyn. 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.
Qwen3.8 9B Distill Uncensored Heretic
petruhonk · 9.4B · runs from 4.6 GB
Qwen3.8 9B Distill Uncensored Heretic is a 9.4B-parameter open language model from petruhonk 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.
NEXUS Coder
fableforge-ai · 1.5B · runs from 1.0 GB
NEXUS Coder is a 1.5B-parameter open language model from fableforge-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.
Qwen3.5 9B Uncensored
LEONW24 · 9B · runs from 4.2 GB
Qwen3.5 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.
Limite 1B Violetto
paradigma-inc · 1.0B · runs from 2.5 GB
Limite 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.
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.
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.
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.
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.
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.
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.
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.
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.