All LLM Models
Browse 529 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
SILMA 9B Instruct v1.0
silma-ai · 9.2B · runs from 4.8 GB
5.5K
83SILMA 9B Instruct v1.0 is a 9.2B-parameter open language model from silma-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.
Sarvam 1
sarvamai · 2.5B · runs from 1.6 GB
Sarvam 1 is a 2.5B-parameter open language model from sarvamai. 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.
Sarashina2.2 3B Instruct v0.1
sbintuitions · 3.4B · runs from 2.1 GB
Sarashina2.2 3B Instruct v0.1 is a 3.4B-parameter open language model from sbintuitions. 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.
TinyLlama 1.1B Chat V0.6
TinyLlama · 1.1B · runs from 0.8 GB
TinyLlama 1.1B Chat V0.6 is a 1.1B-parameter open language model from TinyLlama in the TinyLlama 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.
Neural Chat 7B v3 3
Intel · 7.2B · runs from 3.6 GB
Neural Chat 7B v3 3 is a 7.2B-parameter open language model from Intel. 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.
Baguettotron
PleIAs · 321M · runs from 0.6 GB
Baguettotron is a 321M-parameter open language model from PleIAs. 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.
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.
DeepSeek Coder v2 Lite Base
DeepSeek · 15.7B · runs from 7.4 GB
DeepSeek Coder v2 Lite Base is a 15.7B-parameter open language model from DeepSeek in the DeepSeek Coder family. It supports a context window of up to 163,840 tokens. See its VRAM requirements by quantization and which GPUs and Macs can run it locally below.
Pollux 4B Judge
ai-forever · 4.0B · runs from 2.2 GB
Pollux 4B Judge is a 4.0B-parameter open language model from ai-forever. 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.
Shieldgemma 2B
Google · 2.6B · runs from 1.2 GB
Shieldgemma 2B is a 2.6B-parameter open language model from Google in the Gemma 2 family. See its VRAM requirements by quantization and which GPUs and Macs can run it locally below.
Llama Krikri 8B Instruct
ilsp · 8.2B · runs from 4.0 GB
Llama Krikri 8B Instruct is a 8.2B-parameter open language model from ilsp in the Llama 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.
Deeplm 108M
samcheng0 · 108M · runs from 0.2 GB
Deeplm 108M is a 108M-parameter open language model from samcheng0. See its VRAM requirements by quantization and which GPUs and Macs can run it locally below.
Vaultgemma 1B
Google · 1.0B · runs from 2.3 GB
Vaultgemma 1B is a 1.0B-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.
Gemma 4 12B IT Abliterated Uncensored
OpenYourMind · 12.0B · runs from 6.1 GB
Gemma 4 12B IT Abliterated Uncensored is a 12.0B-parameter open language model from OpenYourMind 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.
Mistral 7B v0.2
mistral-community · 7.2B · runs from 3.6 GB
Mistral 7B v0.2 is a 7.2B-parameter open language model from mistral-community 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.
Josiefied Qwen3 8B Abliterated V1
Goekdeniz-Guelmez · 8.2B · runs from 4.1 GB
Josiefied Qwen3 8B Abliterated V1 is a 8.2B-parameter open language model from Goekdeniz-Guelmez in the Qwen 3 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.
PLLuM 12B Chat
CYFRAGOVPL · 12.2B · runs from 5.9 GB
PLLuM 12B Chat is a 12.2B-parameter open language model from CYFRAGOVPL. 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.
II Medical 8B
Intelligent-Internet · 8.2B · runs from 4.1 GB
II Medical 8B 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.
Polyglot Ko 1.3B
EleutherAI · 1.4B · runs from 0.7 GB
Polyglot Ko 1.3B is a 1.4B-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.
Schematron 3B
inference-net · 3B · runs from 1.8 GB
Schematron 3B is a 3B-parameter open language model from inference-net. 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.
MythoMax L2 13B
Gryphe · 13B · runs from 7.5 GB
MythoMax L2 13B is a 13B-parameter open language model from Gryphe. 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.
Fanar 1 9B Instruct
QCRI · 8.8B · runs from 4.7 GB
Fanar 1 9B Instruct is a 8.8B-parameter open language model from QCRI. 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 3n E2B IT Litert Lm
Google · 2B · runs from 0.9 GB
Gemma 3n E2B IT Litert Lm is a 2B-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.
Nemotron Orchestrator 8B
NVIDIA · 8.2B · runs from 4.1 GB
Nemotron Orchestrator 8B is a 8.2B-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.
Bella Bartender 8B Llama3.1
juiceb0xc0de · 8.0B · runs from 3.0 GB
Bella Bartender 8B Llama3.1 is a 8.0B-parameter open language model from juiceb0xc0de 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.
KONI Llama3.1 8B Instruct 20241024
KISTI-KONI · 8.0B · runs from 4.0 GB
KONI Llama3.1 8B Instruct 20241024 is a 8.0B-parameter open language model from KISTI-KONI 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.
Saul 7B Instruct V1
Equall · 7.2B · runs from 3.6 GB
Saul 7B Instruct V1 is a 7.2B-parameter open language model from Equall. 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.
Cali 0.1B
Sandroeth · 124M · runs from 0.3 GB
Cali 0.1B is a 124M-parameter open language model from Sandroeth. See its VRAM requirements by quantization and which GPUs and Macs can run it locally below.
Qwen3 4B Gemini 3.1 Pro Reasoning Distilled
khazarai · 4B · runs from 2.2 GB
Qwen3 4B Gemini 3.1 Pro Reasoning Distilled is a 4B-parameter open language model from khazarai 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.
OpenMath Nemotron 1.5B
NVIDIA · 1.5B · runs from 1.0 GB
OpenMath Nemotron 1.5B is a 1.5B-parameter open language model from NVIDIA in the Nemotron 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.