All LLM Models
Browse 1242 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
NuExtract 1.5
numind · 3.8B · runs from 2.7 GB
1.4K
246NuExtract 1.5 is a 3.8B-parameter open language model from numind. 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.
Vicuna 13B V1.3
LMSYS · 13B · runs from 6.1 GB
Vicuna-13B v1.3 is LMSYS's 13-billion-parameter chat assistant, fine-tuned from the original LLaMA base model on roughly 125,000 user-shared conversations collected from ShareGPT via supervised instruction fine-tuning. It was one of the earliest widely used open chat models and helped popularize LLM-as-a-judge and human-preference evaluation methodology, being assessed with standard benchmarks, human preference, and the Chatbot Arena leaderboard. LMSYS positions it as a research and hobbyist tool rather than a production assistant. At 13B parameters it needs a capable consumer GPU at full precision, considerably less once quantized. Context length is 2,048 tokens, inherited from the original LLaMA base model. It carries a non-commercial license, consistent with LLaMA's original research-only weights. It was published in June 2023.
CRia LM 75M Instruct
sz14 · 76M · runs from 0.5 GB
CRia LM 75M Instruct is a 76M-parameter open language model from sz14. 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.
Schematron 8B
inference-net · 8B · runs from 4.0 GB
Schematron 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.
Goetia 24B V1.4
Naphula · 23.6B · runs from 10.7 GB
Goetia 24B V1.4 is a 23.6B-parameter open language model from Naphula. 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.
Meditron 7B
epfl-llm · 6.7B · runs from 14.8 GB
Meditron 7B is a 6.7B-parameter open language model from epfl-llm. See its VRAM requirements by quantization and which GPUs and Macs can run it locally below.
Petitgpt
yqi0 · 125M · runs from 0.3 GB
Petitgpt is a 125M-parameter open language model from yqi0. 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.
Huihui Spark X2.5 4B Abliterated
huihui-ai · 4.1B · runs from 2.2 GB
Huihui Spark X2.5 4B Abliterated is a 4.1B-parameter open language model from huihui-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.
Kimi K2.7 Code DFlash
NVIDIA · 3.5B · runs from 1.8 GB
Kimi K2.7 Code DFlash is a 3.5B-parameter open language model from NVIDIA in the Kimi K2 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.
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.
Manaca 1B Instruct
menezesbruno · 1.7B · runs from 1.1 GB
Manaca 1B Instruct is a 1.7B-parameter open language model from menezesbruno. 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.
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.
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.
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.
Cagliostro v3
bench-labs · 146M · runs from 0.7 GB
Cagliostro v3 is a 146M-parameter open language model from bench-labs. 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.
BananaMind 2 Mini
BananaMind · 28M · runs from 0.4 GB
BananaMind 2 Mini is a 28M-parameter open language model from BananaMind. 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.
Overfitter 1.0
BananaMind · 50M · runs from 0.4 GB
Overfitter 1.0 is a 50M-parameter open language model from BananaMind. 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.
Blaze SFT
SurjoLabs · 48M · runs from 0.4 GB
Blaze SFT is a 48M-parameter open language model from SurjoLabs. 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.
Gemma 3 1B IT Heretic Extreme Uncensored Abliterated
DavidAU · 1000M · runs from 0.8 GB
Gemma 3 1B IT Heretic Extreme Uncensored Abliterated is a 1000M-parameter open language model from DavidAU 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.
Qwen3.8 Flash Next 40B Prune Research
Davd-b01 · 40.7B · runs from 17.7 GB
Qwen3.8 Flash Next 40B Prune Research is a 40.7B-parameter open language model from Davd-b01 in the Qwen 3.8 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.
MiniMax M3 EAGLE3 GQA
Inferact · 3.1B · runs from 1.6 GB
MiniMax M3 EAGLE3 GQA is a 3.1B-parameter open language model from Inferact in the MiniMax 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.
Grug 12B
kai-os · 12.0B · runs from 25.0 GB
Grug 12B is a 12.0B-parameter open language model from kai-os. 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.
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.
Puro 2B Base
thu-pacman · 2.0B · runs from 1.4 GB
Puro 2B Base is a 2.0B-parameter open language model from thu-pacman. 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.
Evo2 7B
Aquiles-ai · 6.6B · runs from 14.5 GB
Evo2 7B is a 6.6B-parameter open language model from Aquiles-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.
Raptor 0.6 4B JANG 6M
OsaurusAI · 4.1B · runs from 8.7 GB
Raptor 0.6 4B JANG 6M is a 4.1B-parameter open language model from OsaurusAI. 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.
NCP ArchPreview Dolma3 8.9B Stage1
ArchSpace-Collection · 8.9B · runs from 19.7 GB
NCP ArchPreview Dolma3 8.9B Stage1 is a 8.9B-parameter open language model from ArchSpace-Collection. 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.
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.
