All LLM Models
Browse 671 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
Schematron 8B
inference-net · 8B · runs from 4.0 GB
1.4K
31Schematron 8B is a 8B-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.
GPT X2 125M
AxiomicLabs · 144M · runs from 0.6 GB
GPT X2 125M is a 144M-parameter open language model from AxiomicLabs. 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.
DeepSWE Preview
agentica-org · 32.8B · runs from 14.6 GB
DeepSWE Preview is a 32.8B-parameter open language model from agentica-org. 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.
Pollux Judge 32B
ai-forever · 32.8B · runs from 14.8 GB
Pollux Judge 32B is a 32.8B-parameter open language model from ai-forever. 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.
Tiny Aya Water
Cohere · 3.3B · runs from 7.4 GB
Tiny Aya Water is a 3.3B-parameter open language model from Cohere in the Aya family. See its VRAM requirements by quantization and which GPUs and Macs can run it locally below.
Nemotron Terminal 32B
NVIDIA · 32.8B · runs from 14.6 GB
Nemotron Terminal 32B is a 32.8B-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.
Falcon H1 0.5B Instruct
TII UAE · 521M · runs from 0.6 GB
Falcon H1 0.5B Instruct is a 521M-parameter open language model from TII UAE in the Falcon family. It supports a context window of up to 16,384 tokens. See its VRAM requirements by quantization and which GPUs and Macs can run it locally below.
Qwen35 4B Soyuz Merged
AlexWortega · 4B · runs from 8.5 GB
Qwen35 4B Soyuz Merged is a 4B-parameter open language model from AlexWortega 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.
Penguin VL 2B
tencent · 2.2B · runs from 4.9 GB
Penguin VL 2B is a 2.2B-parameter open language model from tencent. 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.
Soren 1 Small
syntropy-ai · 1.9B · runs from 4.2 GB
Soren 1 Small is a 1.9B-parameter open language model from syntropy-ai. It supports a context window of up to 1,048,576 tokens. See its VRAM requirements by quantization and which GPUs and Macs can run it locally below.
Gemma 3 270M IT
litert-community · 270M · runs from 0.1 GB
Gemma 3 270M IT is a 270M-parameter open language model from litert-community in the Gemma 3 family. See its VRAM requirements by quantization and which GPUs and Macs can run it locally below.
GPT OSS 20B Heretic Ara v3
p-e-w · 21.5B · runs from 9.5 GB
GPT OSS 20B Heretic Ara v3 is a 21.5B-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.
Hunyuan 0.5B Pretrain
tencent · 539M · runs from 0.6 GB
Hunyuan 0.5B Pretrain 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.
Orca Mini 3B
pankajmathur · 3.4B · runs from 1.6 GB
Orca Mini 3B is a 3.4B-parameter open language model from pankajmathur in the Orca 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.
WebWorld 32B
Alibaba · 32.8B · runs from 14.6 GB
WebWorld 32B is a 32.8B-parameter open language model from Alibaba. 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.
T Pro IT 2.1
t-tech · 32.8B · runs from 14.6 GB
T Pro IT 2.1 is a 32.8B-parameter open language model from t-tech. 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.
Phi 4 Mini Flash Reasoning
Microsoft · 3.9B · runs from 2.3 GB
Phi 4 Mini Flash Reasoning is a 3.9B-parameter open language model from Microsoft in the Phi 4 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.
PicoMistral 23M
PicoKittens · 24M · runs from 0.3 GB
PicoMistral 23M is a 24M-parameter open language model from PicoKittens in the Mistral family. 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.
Qwen3.6 28B
0xSero · 28.2B · runs from 12.4 GB
Qwen3.6 28B is a 28.2B-parameter open language model from 0xSero in the Qwen 3.6 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.
Kumru 2B
vngrs-ai · 2.4B · runs from 1.4 GB
Kumru 2B is a 2.4B-parameter open language model from vngrs-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.
Kumru 2B Base
vngrs-ai · 2.4B · runs from 1.4 GB
Kumru 2B Base is a 2.4B-parameter open language model from vngrs-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.
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.
Qwen3.6 27B Uncensored HauhauCS Aggressive Safetensor Benchmark
DreamFast · 27.8B · runs from 12.6 GB
Qwen3.6 27B Uncensored HauhauCS Aggressive Safetensor Benchmark is a 27.8B-parameter open language model from DreamFast in the Qwen 3.6 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.