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
Gemma 3 270M IT Heretic
p-e-w · 268M · runs from 0.4 GB
266
11Gemma 3 270M IT Heretic is a 268M-parameter open language model from p-e-w in the Gemma 3 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.
Scout 4B
vanta-research · 4.3B · runs from 2.5 GB
Scout 4B is a 4.3B-parameter open language model from vanta-research. 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.
Protocol Phantom 12B
DarkArtsForge · 12.2B · runs from 5.9 GB
Protocol Phantom 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.
Nandi Mini V1.1 600M Intermediate Checkpoint 400GT
FrontiersMind · 649M · runs from 1.8 GB
Nandi Mini V1.1 600M Intermediate Checkpoint 400GT is a 649M-parameter open language model from FrontiersMind. 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.
Turkish Gemma 4B T1 Scout
ytu-ce-cosmos · 4.3B · runs from 2.5 GB
Turkish Gemma 4B T1 Scout is a 4.3B-parameter open language model from ytu-ce-cosmos 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.
BharatGPT 3B Indic
CoRover · 3.2B · runs from 7.1 GB
BharatGPT 3B Indic is a 3.2B-parameter open language model from CoRover. See its VRAM requirements by quantization and which GPUs and Macs can run it locally below.
LFM2.5 8B A1B Opus Distil
reaperdoesntknow · 8.5B · runs from 4 GB
LFM2.5 8B A1B Opus Distil is a 8.5B-parameter open language model from reaperdoesntknow. 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.
GigaChat3 10B A1.8B Base
ai-sage · 11.5B · runs from 5.5 GB
GigaChat3 10B A1.8B Base is a 11.5B-parameter open language model from ai-sage. 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.
YanoljaNEXT EEVE Instruct 2.8B
yanolja · 2.8B · runs from 2.2 GB
YanoljaNEXT EEVE Instruct 2.8B is a 2.8B-parameter open language model from yanolja. 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.
Mellum2 12B A2.5B Instruct SFT
JetBrains · 12.1B · runs from 5.5 GB
Mellum2 12B A2.5B Instruct 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.
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.
Functiongemma 270M Ft Mobile Actions
litert-community · 270M · runs from 0.6 GB
Functiongemma 270M Ft Mobile Actions is a 270M-parameter open language model from litert-community in the Gemma family. 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.
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. 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.
NousCoder 14B
Nous Research · 14.8B · runs from 6.9 GB
NousCoder 14B is a 14.8B-parameter open language model from Nous Research. It supports a context window of up to 81,920 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.