All LLM Models

Browse 529 LLM models with VRAM requirements, quantization options, and hardware compatibility.

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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.

Turkish Gemma 9B v0.1

ytu-ce-cosmos · 9.2B · runs from 4.8 GB

Turkish Gemma 9B v0.1 is a 9.2B-parameter open language model from ytu-ce-cosmos in the Gemma 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.

Gemma 3 12B IT Heretic v2

diffusionmodels1254ani · 12.2B · runs from 6.2 GB

Gemma 3 12B IT Heretic v2 is a 12.2B-parameter open language model from diffusionmodels1254ani 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.

T5gemma L L Ul2 IT

Google · 1.2B · runs from 2.7 GB

T5gemma L L Ul2 IT is a 1.2B-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.

Supergemma4 E4b Abliterated

Jiunsong · 7.5B · runs from 3.7 GB

Supergemma4 E4b Abliterated is a 7.5B-parameter open language model from Jiunsong 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.

Sweep Next Edit v2 7B

sweepai · 7.6B · runs from 3.6 GB

Sweep Next Edit v2 7B is a 7.6B-parameter open language model from sweepai. 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.

Nidum Gemma 2B Uncensored

VibeStudio · 2.5B · runs from 1.4 GB

Nidum Gemma 2B Uncensored is a 2.5B-parameter open language model from VibeStudio in the Gemma 2 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.

VibeThinker 1.5B

WeiboAI · 1.8B · runs from 1.1 GB

VibeThinker 1.5B is a 1.8B-parameter open language model from WeiboAI. 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 8B Abliterated

huihui-ai · 8.2B · runs from 3.8 GB

Qwen3 8B Abliterated is a 8.2B-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.

CyberSecQwen 4B

lablab-ai-amd-developer-hackathon · 4.0B · runs from 2.2 GB

CyberSecQwen 4B is a 4.0B-parameter open language model from lablab-ai-amd-developer-hackathon in the Qwen 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.

Recursive Language Model 198M

Girinath11 · 198M · runs from 0.4 GB

Recursive Language Model 198M is a 198M-parameter open language model from Girinath11. It supports a context window of up to 512 tokens. See its VRAM requirements by quantization and which GPUs and Macs can run it locally below.

ErniePEUnleashed

Kezmark · 3.4B · runs from 1.9 GB

ErniePEUnleashed is a 3.4B-parameter open language model from Kezmark in the ERNIE 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 Heretic

DreamFast · 4.0B · runs from 2.2 GB

Qwen3 4B Heretic is a 4.0B-parameter open language model from DreamFast 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.

Xgen 7B 8k Base

Salesforce · 7B · runs from 3.3 GB

Xgen 7B 8k Base is a 7B-parameter open language model from Salesforce. 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.

GPT S 5M

AxiomicLabs · 5M · runs from 0.3 GB

GPT S 5M is a 5M-parameter open language model from AxiomicLabs. It supports a context window of up to 512 tokens. See its VRAM requirements by quantization and which GPUs and Macs can run it locally below.

Falcon H1 7B Base

TII UAE · 7.6B · runs from 3.7 GB

Falcon H1 7B Base is a 7.6B-parameter open language model from TII UAE in the Falcon 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.

Moore Lm

ouilyh · 42M · runs from 0.1 GB

Moore Lm is a 42M-parameter open language model from ouilyh. See its VRAM requirements by quantization and which GPUs and Macs can run it locally below.

UserLM 8B

Microsoft · 8.0B · runs from 4.0 GB

UserLM 8B is a 8.0B-parameter open language model from Microsoft. 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.

NuExtract

numind · 3.8B · runs from 2.7 GB

NuExtract is a 3.8B-parameter open language model from numind. 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.

LFM2 1.2B Extract

LiquidAI · 1.2B · runs from 0.9 GB

LFM2 1.2B Extract is a 1.2B-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.

Text2cypher Gemma 2 9B IT Finetuned 2024v1

neo4j · 9B · runs from 4.2 GB

Text2cypher Gemma 2 9B IT Finetuned 2024v1 is a 9B-parameter open language model from neo4j in the Gemma 2 family. See its VRAM requirements by quantization and which GPUs and Macs can run it locally below.

SKT ST X 0 3B

sKT-Ai-Labs · 3.4B · runs from 1.8 GB

SKT ST X 0 3B is a 3.4B-parameter open language model from sKT-Ai-Labs. 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.

Nanowhale 100M

cmpatino · 110M · runs from 0.5 GB

Nanowhale 100M is a 110M-parameter open language model from cmpatino. 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.

Josiefied Qwen3.5 0.8B Gabliterated V1

Goekdeniz-Guelmez · 853M · runs from 2.1 GB

Josiefied Qwen3.5 0.8B Gabliterated V1 is a 853M-parameter open language model from Goekdeniz-Guelmez 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.

OCC RAG 1.7B

occ-ai · 1.7B · runs from 1.3 GB

OCC 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.

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.

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.