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
K2 Horizon 0.9B
IFM · 1.1B · runs from 2.5 GB
K2 Horizon 0.9B is a 1.1B-parameter open language model from IFM. 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.
LFM2.5 1.2B Base
Liquid AI · 1.2B · runs from 0.9 GB
LFM2.5 1.2B Base is a 1.2B-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.
MoziAI 35B A3B MOE MTP
chenyumo · 35B · runs from 15.3 GB
MoziAI 35B A3B MOE MTP is a 35B-parameter open language model from chenyumo. 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.
Qwen1.5 1.8B
Alibaba · 1.8B · runs from 1.5 GB
Qwen1.5 1.8B is a 1.8B-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.
Qwen3.8 9B
empero-ai · 9.7B · runs from 4.7 GB
Qwen3.8 9B is a 9.7B-parameter open language model from empero-ai 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.
TinyDolphin 2.8 1.1B
QuixiAI · 1.1B · runs from 0.8 GB
TinyDolphin 2.8 1.1B is a 1.1B-parameter open language model from QuixiAI in the Phi 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.
Bitnet B1.58 2B 4T
Microsoft · 850M · runs from 2.2 GB
Bitnet B1.58 2B 4T is a 850M-parameter open language model from Microsoft. 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.
Jais 13B Chat
inceptionai · 13B · runs from 28.6 GB
Jais 13B Chat is a 13B-parameter open language model from inceptionai. See its VRAM requirements by quantization and which GPUs and Macs can run it locally below.
Foundation Sec 8B Reasoning
fdtn-ai · 8.0B · runs from 4.0 GB
Foundation Sec 8B Reasoning is a 8.0B-parameter open language model from fdtn-ai. 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.
HRM Text 1B
sapientinc · 1.2B · runs from 2.9 GB
HRM Text 1B is a 1.2B-parameter open language model from sapientinc. 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 3 12B IT Heretic v2
DreamFast · 12.2B · runs from 6.2 GB
Gemma 3 12B IT Heretic v2 is a 12.2B-parameter open language model from DreamFast in the Gemma 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.
Qwythos 9B Claude Mythos 5 1M
empero-ai · 9.4B · runs from 4.6 GB
Qwythos 9B Claude Mythos 5 1M is a 9.4B-parameter open language model from empero-ai. 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 2.7B
EleutherAI · 2.7B · runs from 6.0 GB
GPT Neo 2.7B is a 2.7B-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.
KAT Coder V2.5 Dev 35B A3B ABLITERATED UNCENSORED PHILADELPHIA CLASS
KridgeDookie · 34.7B · runs from 15.1 GB
KAT Coder V2.5 Dev 35B A3B ABLITERATED UNCENSORED PHILADELPHIA CLASS is a 34.7B-parameter open language model from KridgeDookie in the Phi 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.
YanoljaNEXT EEVE Instruct 10.8B
yanolja · 10.8B · runs from 5.3 GB
YanoljaNEXT EEVE Instruct 10.8B is a 10.8B-parameter open language model from yanolja. 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.
MagicPrompt Stable Diffusion
Gustavosta · 137M · runs from 0.1 GB
MagicPrompt Stable Diffusion is a 137M-parameter open language model from Gustavosta. 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.
Qwen1.5 4B
Alibaba · 4.0B · runs from 2.8 GB
Qwen1.5 4B is a 4.0B-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.
Zeta 2.1
zed-industries · 8.3B · runs from 4.1 GB
Zeta 2.1 is a 8.3B-parameter open language model from zed-industries. 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.
Gemma 4 26B A4B IT DFlash
z-lab · 26B · runs from 11.4 GB
Gemma 4 26B A4B IT DFlash is a 26B-parameter open language model from z-lab in the Gemma 4 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.
Gemma 4 31B IT DFlash
z-lab · 31B · runs from 13.5 GB
Gemma 4 31B IT DFlash is a 31B-parameter open language model from z-lab in the Gemma 4 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 4B Z Image Engineer V4
BennyDaBall · 4B · runs from 1.9 GB
Qwen3 4B Z Image Engineer V4 is a 4B-parameter open language model from BennyDaBall in the Qwen 3 family. See its VRAM requirements by quantization and which GPUs and Macs can run it locally below.
Aya 23 8B
Cohere · 8.0B · runs from 17.7 GB
Aya 23 8B is a 8.0B-parameter open language model from Cohere in the Aya family. See its VRAM requirements by quantization and which GPUs and Macs can run it locally below.
Unsloth Ornith 1.5 35B A3B
peculiar-ragdoll · 35B · runs from 14.9 GB
Unsloth Ornith 1.5 35B A3B is a 35B-parameter open language model from peculiar-ragdoll in the Ornith family. See its VRAM requirements by quantization and which GPUs and Macs can run it locally below.
Qwen3.8 9B Distill
empero-ai · 9.7B · runs from 4.7 GB
Qwen3.8 9B Distill is a 9.7B-parameter open language model from empero-ai 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.
LocoOperator 4B
LocoreMind · 4.0B · runs from 2.2 GB
LocoOperator 4B is a 4.0B-parameter open language model from LocoreMind. 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.
Llm Jp 4 33B Thinking
llm-jp · 33.2B · runs from 15.0 GB
Llm Jp 4 33B Thinking is a 33.2B-parameter open language model from llm-jp. 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.
Helium 1 2B
kyutai · 2.0B · runs from 1.4 GB
Helium 1 2B is a 2.0B-parameter open language model from kyutai. 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 3 12B IT Heretic
DreamFast · 12.2B · runs from 6.2 GB
Gemma 3 12B IT Heretic is a 12.2B-parameter open language model from DreamFast in the Gemma 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.
Qwen2 57B A14B Instruct
Alibaba · 57.4B · runs from 24.8 GB
Qwen2 57B A14B Instruct is a 57.4B-parameter open language model from Alibaba 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.
DeepHat V1 7B
DeepHat · 7.6B · runs from 3.6 GB
DeepHat V1 7B is a 7.6B-parameter open language model from DeepHat. 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.