All LLM Models
Browse 856 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
DeepSeek V4 Flash JANG CRACK
dealignai · 33.5B · runs from 14.6 GB
DeepSeek V4 Flash JANG CRACK is a 33.5B-parameter open language model from dealignai in the DeepSeek V4 family. 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.
Qwen3 4B Gemini 3.1 Pro Reasoning Distilled
khazarai · 4B · runs from 2.2 GB
Qwen3 4B Gemini 3.1 Pro Reasoning Distilled is a 4B-parameter open language model from khazarai in the Qwen 3 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.
OpenMath Nemotron 1.5B
NVIDIA · 1.5B · runs from 1.0 GB
OpenMath Nemotron 1.5B is a 1.5B-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.
Qwen3 4B Instruct 2507 Heretic
p-e-w · 4.0B · runs from 2.2 GB
Qwen3 4B Instruct 2507 Heretic is a 4.0B-parameter open language model from p-e-w in the Qwen 3 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.
Llama3 OpenBioLLM 70B
aaditya · 70B · runs from 30.7 GB
Llama3 OpenBioLLM 70B is a 70B-parameter open language model from aaditya 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.
Bielik 4.5B V3.0 Instruct
speakleash · 4.8B · runs from 10.5 GB
Bielik 4.5B V3.0 Instruct is a 4.8B-parameter open language model from speakleash. See its VRAM requirements by quantization and which GPUs and Macs can run it locally below.
TildeOpen 30B
TildeAI · 30.7B · runs from 13.8 GB
TildeOpen 30B is a 30.7B-parameter open language model from TildeAI. 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.
Penguin VL 8B
tencent · 8.7B · runs from 17.9 GB
Penguin VL 8B is a 8.7B-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.
MiroThinker 1.7 Mini
miromind-ai · 30.5B · runs from 13.4 GB
MiroThinker 1.7 Mini is a 30.5B-parameter open language model from miromind-ai. 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.
Gemma 3n E4B IT Litert Lm
Google · 4B · runs from 1.9 GB
Gemma 3n E4B IT Litert Lm is a 4B-parameter open language model from Google in the Gemma 3 family. See its VRAM requirements by quantization and which GPUs and Macs can run it locally below.
AI21 Jamba Reasoning 3B
AI21 Labs · 3.2B · runs from 1.7 GB
AI21 Jamba Reasoning 3B is a 3.2B-parameter open language model from AI21 Labs in the Jamba 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.
Mellum2 12B A2.5B Base
JetBrains · 12.1B · runs from 24.7 GB
Mellum2 12B A2.5B Base 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.
LFM2.5 8B A1B Base
LiquidAI · 8.5B · runs from 4 GB
LFM2.5 8B A1B Base is a 8.5B-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.
OpenThinker3 1.5B
open-thoughts · 1.5B · runs from 1.0 GB
OpenThinker3 1.5B is a 1.5B-parameter open language model from open-thoughts. 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.
SpatialLM1.1 Qwen 0.5B
manycore-research · 604M · runs from 1.5 GB
SpatialLM1.1 Qwen 0.5B is a 604M-parameter open language model from manycore-research in the Qwen 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.
Qwen3.5 2B Claude 4.6 Opus Reasoning Distilled
Jackrong · 2.3B · runs from 1.4 GB
Qwen3.5 2B Claude 4.6 Opus Reasoning Distilled is a 2.3B-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.
Thinkless 1.5B RL DeepScaleR
Vinnnf · 1.8B · runs from 1.1 GB
Thinkless 1.5B RL DeepScaleR is a 1.8B-parameter open language model from Vinnnf. 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.
Zeta 2.1
zed-industries · 8.3B · runs from 4.1 GB
Zeta 2.1 is a 8.3B-parameter open language model from zed-industries. 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 4B Safety Thinking
MerlinSafety · 4.2B · runs from 2.3 GB
Qwen3.5 4B Safety Thinking is a 4.2B-parameter open language model from MerlinSafety 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.
Qwen3.5 4B Claude 4.6 Opus Reasoning Distilled
Jackrong · 4.7B · runs from 2.5 GB
Qwen3.5 4B Claude 4.6 Opus Reasoning Distilled is a 4.7B-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.
OmniSVG1.1 8B
OmniSVG · 8B · runs from 16.4 GB
OmniSVG1.1 8B is a 8B-parameter open language model from OmniSVG. 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.
MiniMax Text 01
MiniMaxAI · 456.1B · runs from 913.0 GB
MiniMax Text 01 is a 456.1B-parameter open language model from MiniMaxAI in the MiniMax family. It supports a context window of up to 10,240,000 tokens. See its VRAM requirements by quantization and which GPUs and Macs can run it locally below.
Codegemma 7B IT
Google · 8.5B · runs from 4.0 GB
Codegemma 7B IT is a 8.5B-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.
Gemma4 12B Mtp Assistant
sjakek · 12B · runs from 5.6 GB
Gemma4 12B Mtp Assistant is a 12B-parameter open language model from sjakek in the Gemma 4 family. See its VRAM requirements by quantization and which GPUs and Macs can run it locally below.
Claude OSS
squ11z1 · 9.0B · runs from 4.4 GB
Claude OSS is a 9.0B-parameter open language model from squ11z1. 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.
Nemotron Research Reasoning Qwen 1.5B
NVIDIA · 1.8B · runs from 1.1 GB
Nemotron Research Reasoning Qwen 1.5B is a 1.8B-parameter open language model from NVIDIA in the Qwen 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.
WebWorld 8B
Alibaba · 8.2B · runs from 4.1 GB
WebWorld 8B is a 8.2B-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.
Qwen3.5 9B Abliterated
lukey03 · 9.0B · runs from 4.4 GB
Qwen3.5 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.