All LLM Models
Browse 1475 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
Nemotron Terminal 14B
NVIDIA · 14.8B · runs from 6.9 GB
336
8Nemotron Terminal 14B is a 14.8B-parameter open language model from NVIDIA in the Nemotron family. 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.
FlexOlmo 7x7B 1T
Allen AI · 33.3B · runs from 67.9 GB
FlexOlmo 7x7B 1T is a 33.3B-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.
GLM 4.7 Flash Heretic 1.2.0
darkc0de · 29.9B · runs from 13.8 GB
GLM 4.7 Flash Heretic 1.2.0 is a 29.9B-parameter open language model from darkc0de in the GLM 4 family. It supports a context window of up to 202,752 tokens. See its VRAM requirements by quantization and which GPUs and Macs can run it locally below.
Darkidol Ballad 27B
aifeifei798 · 26.9B · runs from 54.5 GB
Darkidol Ballad 27B is a 26.9B-parameter open language model from aifeifei798. 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.
Aryabhata 2.0
PhysicsWallahAI · 20.9B · runs from 9.3 GB
Aryabhata 2.0 is a 20.9B-parameter open language model from PhysicsWallahAI. 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.
IFlow ROME
FutureLivingLab · 30.5B · runs from 13.4 GB
IFlow ROME is a 30.5B-parameter open language model from FutureLivingLab. 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.
Gemma4 E4B MiniFantasy V1
Nubinu · 8.0B · runs from 16.5 GB
Gemma4 E4B MiniFantasy V1 is a 8.0B-parameter open language model from Nubinu 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.
T5gemma B B Ul2 IT
Google · 591M · runs from 1.3 GB
T5gemma B B Ul2 IT is a 591M-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.
Archaea 74M
GODELEV · 74M · runs from 0.3 GB
Archaea 74M is a 74M-parameter open language model from GODELEV. 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.
Penguin VL 8B
Tencent · 8.7B · runs from 17.9 GB
Penguin VL 8B is a 8.7B-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.
Nerdsking Python Coder 7B I
Nerdsking · 7B · runs from 3.3 GB
Nerdsking Python Coder 7B I is a 7B-parameter open language model from Nerdsking. See its VRAM requirements by quantization and which GPUs and Macs can run it locally below.
Covenant 72B
1Covenant · 72.7B · runs from 31.9 GB
Covenant 72B is a 72.7B-parameter open language model from 1Covenant. 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.
Datarus R1 14B Preview
DatarusAI · 14.8B · runs from 7.0 GB
Datarus R1 14B Preview is a 14.8B-parameter open language model from DatarusAI. 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 Code Reasoning 4B
GetSoloTech · 4B · runs from 2.2 GB
Qwen3 Code Reasoning 4B is a 4B-parameter open language model from GetSoloTech 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.
Qwen3 Nemotron 235B A22B GenRM 2603
NVIDIA · 235.1B · runs from 100.4 GB
Qwen3 Nemotron 235B A22B GenRM 2603 is a 235.1B-parameter open language model from NVIDIA 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.
JOSIE 1.1 4B Instruct
Goekdeniz-Guelmez · 4.0B · runs from 2.2 GB
JOSIE 1.1 4B Instruct is a 4.0B-parameter open language model from Goekdeniz-Guelmez. 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.
Browsesafe
perplexity-ai · 30.5B · runs from 13.4 GB
Browsesafe is a 30.5B-parameter open language model from perplexity-ai. 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.
MN VelvetCafe RP 12B
IggyLux · 12.2B · runs from 5.9 GB
MN VelvetCafe RP 12B is a 12.2B-parameter open language model from IggyLux. 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.
SmolLM3 3B ONNX
Hugging Face · 3B · runs from 1.7 GB
SmolLM3 3B ONNX is a 3B-parameter open language model from Hugging Face in the SmolLM 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.
Gemma 3 270M IT Heretic
p-e-w · 268M · runs from 0.4 GB
Gemma 3 270M IT Heretic is a 268M-parameter open language model from p-e-w in the Gemma 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.
Mellum2 12B A2.5B Base Pretrain
JetBrains · 12.1B · runs from 24.7 GB
Mellum2 12B A2.5B Base Pretrain is a 12.1B-parameter open language model from JetBrains in the Mellum 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.
Scout 4B
vanta-research · 4.3B · runs from 2.5 GB
Scout 4B is a 4.3B-parameter open language model from vanta-research. 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.
GLM 5 Abliterated
skyblanket · 753.9B · runs from 324.6 GB
GLM 5 Abliterated is a 753.9B-parameter open language model from skyblanket in the GLM 5 family. It supports a context window of up to 202,752 tokens. See its VRAM requirements by quantization and which GPUs and Macs can run it locally below.
Protocol Phantom 12B
DarkArtsForge · 12.2B · runs from 5.9 GB
Protocol Phantom 12B is a 12.2B-parameter open language model from DarkArtsForge. 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.
GhostFace 24B V1
Naphula · 23.6B · runs from 10.7 GB
GhostFace 24B V1 is a 23.6B-parameter open language model from Naphula. 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.
Nandi Mini V1.1 600M Intermediate Checkpoint 400GT
FrontiersMind · 649M · runs from 1.8 GB
Nandi Mini V1.1 600M Intermediate Checkpoint 400GT is a 649M-parameter open language model from FrontiersMind. 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.
Huihui MoE 23B A4B Abliterated
huihui-ai · 23.2B · runs from 10.4 GB
Huihui MoE 23B A4B Abliterated is a 23.2B-parameter open language model from huihui-ai. 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.
Turkish Gemma 4B T1 Scout
ytu-ce-cosmos · 4.3B · runs from 2.5 GB
Turkish Gemma 4B T1 Scout is a 4.3B-parameter open language model from ytu-ce-cosmos 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.
LensVLM 9B
Apple · 9.4B · runs from 3.2 GB
LensVLM-9B is Apple's research vision-language model for efficient long-document understanding, built on a 9.4-billion-parameter Qwen3.5-9B backbone. Rather than feeding a document's full text into the context window, it scans compressed images of the text and uses learned tools to selectively expand only the pages relevant to a query back into their uncompressed form, at configurable 5x, 10x, or 15x compression ratios, letting it reason over long documents while processing far less raw context per query. It is a research model released alongside its arXiv paper and reference code, not a product, and is not described as instruction-tuned for general chat. At 9.4 billion parameters it fits on a single consumer GPU, especially once quantized. Context length is 262,144 tokens. It is released under the Apple Machine Learning Research Model License, a custom license restricted strictly to non-commercial research purposes, with no commercial exploitation permitted. It was published in September 2026.
BharatGPT 3B Indic
CoRover · 3.2B · runs from 7.1 GB
BharatGPT 3B Indic is a 3.2B-parameter open language model from CoRover. See its VRAM requirements by quantization and which GPUs and Macs can run it locally below.