All LLM Models
Browse 719 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
OCC RAG 1.7B
occ-ai · 1.7B · runs from 1.3 GB
613
4OCC RAG 1.7B is a 1.7B-parameter open language model from occ-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.
Mellum2 12B A2.5B Thinking SFT
JetBrains · 12.1B · runs from 5.5 GB
Mellum2 12B A2.5B Thinking SFT 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.
PrunedHub Qwen3.5 35B A3B 80pct
GOBA-AI-Labs · 35B · runs from 16.4 GB
PrunedHub Qwen3.5 35B A3B 80pct is a 35B-parameter open language model from GOBA-AI-Labs in the Qwen 3.5 family. See its VRAM requirements by quantization and which GPUs and Macs can run it locally below.
Lucie 7B
OpenLLM-France · 6.7B · runs from 3.4 GB
Lucie 7B is a 6.7B-parameter open language model from OpenLLM-France. It supports a context window of up to 32,000 tokens. See its VRAM requirements by quantization and which GPUs and Macs can run it locally below.
Veritas 8B Fact Checker Non Thinking 1.0
resect-ai · 8.2B · runs from 4.1 GB
Veritas 8B Fact Checker Non Thinking 1.0 is a 8.2B-parameter open language model from resect-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.
Qwen3 4B Abliterated
huihui-ai · 4.0B · runs from 1.9 GB
Qwen3 4B Abliterated is a 4.0B-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.
Qwopus3.5 9B V3.5
Jackrong · 9.7B · runs from 19.9 GB
Qwopus3.5 9B V3.5 is a 9.7B-parameter open language model from Jackrong. 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.
Steelman 14B Ada
the-clanker-lover · 14B · runs from 6.5 GB
Steelman 14B Ada is a 14B-parameter open language model from the-clanker-lover. See its VRAM requirements by quantization and which GPUs and Macs can run it locally below.
Luciole 8B Base
OpenLLM-France · 8.1B · runs from 4.2 GB
Luciole 8B Base is a 8.1B-parameter open language model from OpenLLM-France. 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.
Granite Switch 4.1 8B Preview
IBM · 9.6B · runs from 19.8 GB
Granite Switch 4.1 8B Preview is a 9.6B-parameter open language model from IBM in the Granite 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.
Qwen3.5 9B Gemini 3.1 Pro Reasoning Distill
Jackrong · 9.7B · runs from 4.7 GB
Qwen3.5 9B Gemini 3.1 Pro Reasoning Distill is a 9.7B-parameter open language model from Jackrong in the Qwen 3.5 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.
MIST Mini 8B
olaverse · 8.0B · runs from 4.0 GB
MIST Mini 8B is a 8.0B-parameter open language model from olaverse. 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.
Kai 30B Instruct
NoesisLab · 32.8B · runs from 14.8 GB
Kai 30B Instruct is a 32.8B-parameter open language model from NoesisLab. 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.
GPT X2 125M CIx Long Context
reaperdoesntknow · 126M · runs from 0.6 GB
GPT X2 125M CIx Long Context is a 126M-parameter open language model from reaperdoesntknow. 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.
GrepSeek Qwen3.5 9B GRPO
alireza7 · 9.4B · runs from 19.4 GB
GrepSeek Qwen3.5 9B GRPO is a 9.4B-parameter open language model from alireza7 in the Qwen 3.5 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.
Hunyuan 0.5B Instruct
tencent · 539M · runs from 0.6 GB
Hunyuan 0.5B Instruct is a 539M-parameter open language model from tencent in the Hunyuan 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 8B
litert-community · 8B · runs from 3.7 GB
Qwen3 8B is a 8B-parameter open language model from litert-community in the Qwen 3 family. See its VRAM requirements by quantization and which GPUs and Macs can run it locally below.
Kappa 20B 131k Mxfp4
eousphoros · 20.9B · runs from 9.3 GB
Kappa 20B 131k Mxfp4 is a 20.9B-parameter open language model from eousphoros. 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.
Darwin 4B Genesis
FINAL-Bench · 7.5B · runs from 15.6 GB
Darwin 4B Genesis is a 7.5B-parameter open language model from FINAL-Bench. 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.
Phi 4 Quantized.w8a8
RedHatAI · 14.7B · runs from 7.0 GB
Phi 4 Quantized.w8a8 is a 14.7B-parameter open language model from RedHatAI in the Phi 4 family. It supports a context window of up to 16,384 tokens. See its VRAM requirements by quantization and which GPUs and Macs can run it locally below.
UniScientist 30B A3B
UnipatAI · 30.5B · runs from 13.4 GB
UniScientist 30B A3B is a 30.5B-parameter open language model from UnipatAI. 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 350M Extract
LiquidAI · 354M · runs from 0.5 GB
LFM2 350M Extract is a 354M-parameter open language model from LiquidAI. 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.
Falcon3 Mamba 7B Base
TII UAE · 7.3B · runs from 16 GB
Falcon3 Mamba 7B Base is a 7.3B-parameter open language model from TII UAE in the Falcon family. See its VRAM requirements by quantization and which GPUs and Macs can run it locally below.
Dolphin X1 Trinity Nano
dphn · 6.1B · runs from 3.0 GB
Dolphin X1 Trinity Nano is a 6.1B-parameter open language model from dphn in the Phi 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.
Apertus 8B MeditronFO
EPFLiGHT · 8.1B · runs from 4.0 GB
Apertus 8B MeditronFO is a 8.1B-parameter open language model from EPFLiGHT in the Apertus 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.
CyberPal2.0 20B
cyber-pal-security · 20.9B · runs from 9.3 GB
CyberPal2.0 20B is a 20.9B-parameter open language model from cyber-pal-security. 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.
Hebatron
HebArabNlpProject · 31.6B · runs from 13.8 GB
Hebatron is a 31.6B-parameter open language model from HebArabNlpProject. 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.
Jan V3.5 4B
janhq · 4.4B · runs from 2.4 GB
Jan V3.5 4B is a 4.4B-parameter open language model from janhq. 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.
Kimi K2.6 Eagle3
NVIDIA · 1.8B · runs from 1.1 GB
Kimi K2.6 Eagle3 is a 1.8B-parameter open language model from NVIDIA in the Kimi K2 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.
II Medical 8B 1706
Intelligent-Internet · 8.2B · runs from 4.1 GB
II Medical 8B 1706 is a 8.2B-parameter open language model from Intelligent-Internet. 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.