All LLM Models
Browse 593 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
Qwen3.5 9B Abliterated
lukey03 · 9.0B · runs from 4.4 GB
2.5K
53Qwen3.5 9B Abliterated is a 9.0B-parameter open language model from lukey03 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.
Qwen2.5 7B Instruct Uncensored
Orion-zhen · 7.6B · runs from 3.6 GB
Qwen2.5 7B Instruct Uncensored is a 7.6B-parameter open language model from Orion-zhen in the Qwen 2.5 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.
OpenGuardrails Text 2510
openguardrails · 14.8B · runs from 6.9 GB
OpenGuardrails Text 2510 is a 14.8B-parameter open language model from openguardrails. 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.
Baichuan2 7B Base
baichuan-inc · 7B · runs from 3.3 GB
Baichuan2 7B Base is a 7B-parameter open language model from baichuan-inc in the Baichuan family. 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.
Nemotron Terminal 8B
NVIDIA · 8.2B · runs from 4.1 GB
Nemotron Terminal 8B is a 8.2B-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.
Nemotron Content Safety Reasoning 4B
NVIDIA · 4.3B · runs from 2.5 GB
Nemotron Content Safety Reasoning 4B is a 4.3B-parameter open language model from NVIDIA in the Nemotron 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.
Emo 1b14b 1T
Allen AI · 13.6B · runs from 6.3 GB
Emo 1b14b 1T is a 13.6B-parameter open language model from Allen AI. 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.
Veyra 30M Base
veyra-ai · 35M · runs from 0.3 GB
Veyra 30M Base is a 35M-parameter open language model from veyra-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.
Finance Llama3 8B
instruction-pretrain · 8.0B · runs from 4.0 GB
Finance Llama3 8B is a 8.0B-parameter open language model from instruction-pretrain in the Llama 3 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.
Huihui Qwen3 4B Abliterated v2
huihui-ai · 4.0B · runs from 2.2 GB
Huihui Qwen3 4B Abliterated v2 is a 4.0B-parameter open language model from huihui-ai 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.
MediPhi Instruct
Microsoft · 3.8B · runs from 2.7 GB
MediPhi Instruct is a 3.8B-parameter open language model from Microsoft in the Phi 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.
Carbon 8B
HuggingFaceBio · 8.3B · runs from 4.1 GB
Carbon 8B is a 8.3B-parameter open language model from HuggingFaceBio. 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.
Smol Llama 101M GQA
BEE-spoke-data · 101M · runs from 0.4 GB
Smol Llama 101M GQA is a 101M-parameter open language model from BEE-spoke-data in the Llama family. 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.
Domyn Small v1.0
domyn · 9.8B · runs from 4.7 GB
Domyn Small v1.0 is a 9.8B-parameter open language model from domyn. 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.
Qwen3.5 9B Uncensored
LEONW24 · 9B · runs from 4.2 GB
Qwen3.5 9B Uncensored is a 9B-parameter open language model from LEONW24 in the Qwen 3.5 family. See its VRAM requirements by quantization and which GPUs and Macs can run it locally below.
Nanowhale 100M
Hugging Face · 110M · runs from 0.5 GB
Nanowhale 100M is a 110M-parameter open language model from Hugging Face. 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.
Qwen3 1.7B Abliterated
huihui-ai · 1.7B · runs from 0.8 GB
Qwen3 1.7B Abliterated is a 1.7B-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 0.6B Heretic Abliterated Uncensored
DavidAU · 596M · runs from 0.7 GB
Qwen3 0.6B Heretic Abliterated Uncensored is a 596M-parameter open language model from DavidAU 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.
Llama 3.1 Nemotron Safety Guard 8B v3
NVIDIA · 8.0B · runs from 4.0 GB
Llama 3.1 Nemotron Safety Guard 8B v3 is a 8.0B-parameter open language model from NVIDIA in the Llama 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.
Context 1
chromadb · 20.9B · runs from 9.3 GB
Context 1 is a 20.9B-parameter open language model from chromadb. 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.
Arch Router 1.5B
katanemo · 1.5B · runs from 1.0 GB
Arch Router 1.5B is a 1.5B-parameter open language model from katanemo. 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.
Qwen3 0.6B
litert-community · 0.6B · runs from 0.3 GB
Qwen3 0.6B is a 0.6B-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.
Vicuna 13B V1.3
LMSYS · 13B · runs from 6.1 GB
Vicuna 13B V1.3 is a 13B-parameter open language model from LMSYS in the Vicuna 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.
Llama Poro 2 8B Instruct
LumiOpen · 8.0B · runs from 4.0 GB
Llama Poro 2 8B Instruct is a 8.0B-parameter open language model from LumiOpen in the Llama 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.
AFM 4.5B
Arcee AI · 4.6B · runs from 2.4 GB
AFM 4.5B is a 4.6B-parameter open language model from Arcee AI. 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.
EuroMoE 2.6B A0.6B 2512
utter-project · 2.6B · runs from 1.5 GB
EuroMoE 2.6B A0.6B 2512 is a 2.6B-parameter open language model from utter-project. 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.
MiniCPM MoE 8x2B
openbmb · 8x2B · runs from 7.8 GB
MiniCPM MoE 8x2B is a 8x2B-parameter open language model from openbmb in the MiniCPM family. 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.
MedPsy 4B
qvac · 4.4B · runs from 2.4 GB
MedPsy 4B is a 4.4B-parameter open language model from qvac. 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.
Turkish Gemma 9B T1
ytu-ce-cosmos · 9.2B · runs from 4.8 GB
Turkish Gemma 9B T1 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.
Claim Extractor 4B Q 2605
principled-intelligence · 4.7B · runs from 9.8 GB
Claim Extractor 4B Q 2605 is a 4.7B-parameter open language model from principled-intelligence. 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.