All LLM Models

Browse 880 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.

MIST Mini 8B Thinking

olaverse · 8.0B · runs from 4.0 GB

MIST Mini 8B Thinking 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.

SmolLM2 70M

codelion · 69M · runs from 0.4 GB

SmolLM2 70M is a 69M-parameter open language model from codelion in the SmolLM 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.

StorySupra 10M

SupraLabs · 13M · runs from 0.3 GB

StorySupra 10M is a 13M-parameter open language model from SupraLabs. It supports a context window of up to 256 tokens. See its VRAM requirements by quantization and which GPUs and Macs can run it locally below.

CAT Thinking 8B

cyberagent · 8.2B · runs from 4.1 GB

CAT Thinking 8B is a 8.2B-parameter open language model from cyberagent. 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.

Gemma 2 Mitra E

buddhist-nlp · 9.2B · runs from 4.8 GB

Gemma 2 Mitra E is a 9.2B-parameter open language model from buddhist-nlp 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.

Instella 3B

amd · 3.1B · runs from 7.3 GB

Instella 3B is a 3.1B-parameter open language model from amd. 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.

XiaoHong V1

CongJ-Pan · 8.2B · runs from 4.1 GB

XiaoHong V1 is a 8.2B-parameter open language model from CongJ-Pan. 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.

Distil Qwen3 0.6B Text2sql

distil-labs · 596M · runs from 0.7 GB

Distil Qwen3 0.6B Text2sql is a 596M-parameter open language model from distil-labs 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.

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.

Huihui LFM2.5 8B A1B Abliterated

huihui-ai · 8.5B · runs from 4 GB

Huihui LFM2.5 8B A1B Abliterated is a 8.5B-parameter open language model from huihui-ai in the LFM2.5 family. 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.

Granite Guardian 3.2 8B Factuality Detection

IBM · 8.2B · runs from 4.1 GB

Granite Guardian 3.2 8B Factuality Detection is a 8.2B-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.

Llamatron 8B V1

Naphula · 8.0B · runs from 4.0 GB

Llamatron 8B V1 is a 8.0B-parameter open language model from Naphula 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.

Protgpt2 Distilled Tiny

littleworth · 39M · runs from 0.0 GB

Protgpt2 Distilled Tiny is a 39M-parameter open language model from littleworth. It supports a context window of up to 1,024 tokens. See its VRAM requirements by quantization and which GPUs and Macs can run it locally below.

Nafie 473M

nafie-ai · 473M · runs from 1.0 GB

Nafie 473M is a 473M-parameter open language model from nafie-ai. It supports a context window of up to 1,024 tokens. See its VRAM requirements by quantization and which GPUs and Macs can run it locally below.

Qehwa Pashto Llm

junaid008 · 7.6B · runs from 3.6 GB

Qehwa Pashto Llm is a 7.6B-parameter open language model from junaid008. 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.

Nemotron Flash 3B

NVIDIA · 2.7B · runs from 6.0 GB

Nemotron Flash 3B is a 2.7B-parameter open language model from NVIDIA in the Nemotron family. It supports a context window of up to 29,000 tokens. See its VRAM requirements by quantization and which GPUs and Macs can run it locally below.

Apex 1 Instruct 350M

LH-Tech-AI · 350M · runs from 0.8 GB

Apex 1 Instruct 350M is a 350M-parameter open language model from LH-Tech-AI. See its VRAM requirements by quantization and which GPUs and Macs can run it locally below.

Qliphoth 12B V1.2

OccultAI · 12.2B · runs from 5.9 GB

Qliphoth 12B V1.2 is a 12.2B-parameter open language model from OccultAI. It supports a context window of up to 1,024,000 tokens. See its VRAM requirements by quantization and which GPUs and Macs can run it locally below.

Ouro Hybrid 1.4B

chili-lab · 1.5B · runs from 3.7 GB

Ouro Hybrid 1.4B is a 1.5B-parameter open language model from chili-lab. 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.

KernelLLM

Meta · 8.0B · runs from 4.0 GB

KernelLLM is a 8.0B-parameter open language model from Meta. 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.

NextCoder 7B

Microsoft · 7.6B · runs from 3.6 GB

NextCoder 7B is a 7.6B-parameter open language model from Microsoft. 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.

Riva Translate 4B Instruct

NVIDIA · 4.2B · runs from 2.3 GB

Riva Translate 4B Instruct is a 4.2B-parameter open language model from NVIDIA. 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.

Meme Trix MoE 14B A8B V1

Naphula · 13.7B · runs from 6.4 GB

Meme Trix MoE 14B A8B V1 is a 13.7B-parameter open language model from Naphula. It supports a context window of up to 1,073,152 tokens. See its VRAM requirements by quantization and which GPUs and Macs can run it locally below.

Supra Mini V6 1M

SupraLabs · 1M · runs from 0.3 GB

Supra Mini V6 1M is a 1M-parameter open language model from SupraLabs. It supports a context window of up to 1,024 tokens. See its VRAM requirements by quantization and which GPUs and Macs can run it locally below.

ERNIE 4.5 0.3B Paddle

Baidu · 361M · runs from 1.0 GB

ERNIE 4.5 0.3B Paddle is a 361M-parameter open language model from Baidu in the ERNIE 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.

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.

Valuoty Industry Plc 4B

ICSFR-HF-ORG-01 · 4.4B · runs from 2.4 GB

Valuoty Industry Plc 4B is a 4.4B-parameter open language model from ICSFR-HF-ORG-01. 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.

Styx 12B

DarkArtsForge · 12.2B · runs from 5.9 GB

Styx 12B is a 12.2B-parameter open language model from DarkArtsForge. 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 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.

MedScholar 1.5B

yasserrmd · 1.5B · runs from 1.0 GB

MedScholar 1.5B is a 1.5B-parameter open language model from yasserrmd. 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.