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
Helium 1 2B
kyutai · 2.0B · runs from 1.4 GB
16.2K
52Helium 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.
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.
GLM 5.2 Speculator.dspark
RedHatAI · 3.8B · runs from 1.8 GB
GLM 5.2 Speculator.dspark is a 3.8B-parameter open language model from RedHatAI in the GLM 5 family. See its VRAM requirements by quantization and which GPUs and Macs can run it locally below.
Qwen3.8 4B
empero-ai · 4.7B · runs from 2.5 GB
Qwen3.8 4B is a 4.7B-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.
Mistral Small 24B Instruct 2501 Quantized.w8a8
RedHatAI · 23.6B · runs from 10.7 GB
Mistral Small 24B Instruct 2501 Quantized.w8a8 is a 23.6B-parameter open language model from RedHatAI in the Mistral 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.
Hermes 2 Pro Llama 3 8B
Nous Research · 8.0B · runs from 4.0 GB
Hermes 2 Pro Llama 3 8B is a 8.0B-parameter open language model from Nous Research 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.
Moondream1
vikhyatk · 1.9B · runs from 4.1 GB
Moondream1 is a 1.9B-parameter open language model from vikhyatk. See its VRAM requirements by quantization and which GPUs and Macs can run it locally below.
AFM 4.5B
Arcee AI · 4.6B · runs from 2.4 GB
AFM 4.5B is a 4.6B-parameter open language model from Arcee AI. 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.
Llama 3.1 8B Lexi Uncensored v2
Orenguteng · 8.0B · runs from 4.0 GB
Llama 3.1 8B Lexi Uncensored v2 is a 8.0B-parameter open language model from Orenguteng 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 3.2 Korean Bllossom 3B
Bllossom · 3.2B · runs from 1.9 GB
Llama 3.2 Korean Bllossom 3B is a 3.2B-parameter open language model from Bllossom 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.
GLM 4 9B 0414
Z.ai · 9.4B · runs from 4.4 GB
GLM 4 9B 0414 is a 9.4B-parameter open language model from Z.ai in the GLM 4 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.
Ouro 2.6B Thinking
ByteDance · 2.7B · runs from 6.4 GB
Ouro 2.6B Thinking is a 2.7B-parameter open language model from ByteDance. 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.
Qwen3.8 4B Distill
empero-ai · 4.7B · runs from 2.5 GB
Qwen3.8 4B Distill is a 4.7B-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.
Yi 1.5 9B
01.AI · 8.8B · runs from 4.3 GB
Yi 1.5 9B is a 8.8B-parameter open language model from 01.AI in the Yi 1.5 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.
Mathstral 7B v0.1
Mistral AI · 7.2B · runs from 3.6 GB
Mathstral 7B v0.1 is a 7.2B-parameter open language model from Mistral 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.
Qwen3.6 27B Uncensored HauhauCS Aggressive MTP
AIOpsInSpace · 27B · runs from 10.0 GB
Qwen3.6 27B Uncensored HauhauCS Aggressive MTP is a 27B-parameter open language model from AIOpsInSpace in the Qwen 3.6 family. See its VRAM requirements by quantization and which GPUs and Macs can run it locally below.
K2 Horizon 3.7B
IFM · 5.1B · runs from 10.6 GB
K2 Horizon 3.7B is a 5.1B-parameter open language model from IFM. It supports a context window of up to 524,288 tokens. See its VRAM requirements by quantization and which GPUs and Macs can run it locally below.
Lfm2.5 2.6B Fable5 Coding Agent Heretic
saidutta69 · 2.7B · runs from 1.6 GB
Lfm2.5 2.6B Fable5 Coding Agent Heretic is a 2.7B-parameter open language model from saidutta69 in the LFM2.5 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.
TinyStories 33M
roneneldan · 33M · runs from 0.1 GB
TinyStories 33M is a 33M-parameter open language model from roneneldan. 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.
Gemma 3n E4B IT Litert Lm
Google · 4B · runs from 1.9 GB
Gemma 3n E4B IT Litert Lm is a 4B-parameter open language model from Google in the Gemma 3 family. See its VRAM requirements by quantization and which GPUs and Macs can run it locally below.
SOLAR 10.7B v1.0
Upstage · 10.7B · runs from 5.3 GB
SOLAR 10.7B v1.0 is a 10.7B-parameter open language model from Upstage in the Solar 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.
Qwen3.8 2B
empero-ai · 2.3B · runs from 1.4 GB
Qwen3.8 2B is a 2.3B-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.
NuExtract 1.5 Tiny
numind · 494M · runs from 0.5 GB
NuExtract 1.5 Tiny is a 494M-parameter open language model from numind. 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.
Phi 3 Medium 4k Instruct
Microsoft · 14.0B · runs from 6.7 GB
Phi 3 Medium 4k Instruct is a 14.0B-parameter open language model from Microsoft in the Phi 3 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.
Internlm2 5 20B Chat
InternLM · 19.9B · runs from 9.1 GB
Internlm2 5 20B Chat is a 19.9B-parameter open language model from InternLM in the InternLM 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.
Rwkv 4 169M Pile
RWKV · 169M · runs from 0.1 GB
Rwkv 4 169M Pile is a 169M-parameter open language model from RWKV. See its VRAM requirements by quantization and which GPUs and Macs can run it locally below.
Phi 1
Microsoft · 1.4B · runs from 0.7 GB
Phi 1 is a 1.4B-parameter open language model from Microsoft in the Phi 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.
Llama 3 ELYZA JP 8B
elyza · 8.0B · runs from 4.0 GB
Llama 3 ELYZA JP 8B is a 8.0B-parameter open language model from elyza 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.
PapersRAG 1.5B
metaresearch · 1.5B · runs from 1.0 GB
PapersRAG 1.5B is a 1.5B-parameter open language model from metaresearch. 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.