All LLM Models

Browse 593 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.

GPT OSS 20B Heretic

p-e-w · 20.9B · runs from 9.3 GB

GPT OSS 20B Heretic is a 20.9B-parameter open language model from p-e-w in the GPT-OSS 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.

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.

XortronCriminalComputingConfig

darkc0de · 23.6B · runs from 10.7 GB

XortronCriminalComputingConfig is a 23.6B-parameter open language model from darkc0de. 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.

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.

Harness 1

pat-jj · 20.9B · runs from 9.3 GB

Harness 1 is a 20.9B-parameter open language model from pat-jj. 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.

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.

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.

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.

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.