All LLM Models
Browse 1138 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
Lynx Instruct 30B
bineric · 30.5B · runs from 13.4 GB
36.8K
4Lynx Instruct 30B is a 30.5B-parameter open language model from bineric. 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.
Llama3.1 Typhoon2 8B Instruct
typhoon-ai · 8.0B · runs from 4.0 GB
Llama3.1 Typhoon2 8B Instruct is a 8.0B-parameter open language model from typhoon-ai 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.
Ruadapt Qwen2.5 7B Ext U48 Instruct
RefalMachine · 7.6B · runs from 3.6 GB
Ruadapt Qwen2.5 7B Ext U48 Instruct is a 7.6B-parameter open language model from RefalMachine 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.
Qwen1.5 MoE A2.7B Chat
Alibaba · 14.3B · runs from 6.8 GB
Qwen1.5 MoE A2.7B Chat is a 14.3B-parameter open language model from Alibaba 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.
EXAONE 3.5 32B Instruct
LGAI-EXAONE · 32.0B · runs from 15.0 GB
EXAONE 3.5 32B Instruct is a 32.0B-parameter open language model from LGAI-EXAONE in the EXAONE 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.
Deepseek Moe 16B Base
DeepSeek · 16.4B · runs from 7.7 GB
Deepseek Moe 16B Base is a 16.4B-parameter open language model from DeepSeek in the DeepSeek 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.
Gemma 4 E4B IT OBLITERATED
OBLITERATUS · 8.0B · runs from 3.9 GB
Gemma 4 E4B IT OBLITERATED is a 8.0B-parameter open language model from OBLITERATUS 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.
TIPO 500M
KBlueLeaf · 508M · runs from 0.7 GB
TIPO 500M is a 508M-parameter open language model from KBlueLeaf. 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.
Mythos Nano
squ11z1 · 3.1B · runs from 1.7 GB
Mythos Nano is a 3.1B-parameter open language model from squ11z1. 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.
Deepseek Coder 1.3B Base
DeepSeek · 1.3B · runs from 1.3 GB
Deepseek Coder 1.3B Base is a 1.3B-parameter open language model from DeepSeek in the DeepSeek Coder 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.
OneReason 0.8B Pretrain Competition
OpenOneRec · 801M · runs from 0.8 GB
OneReason 0.8B Pretrain Competition is a 801M-parameter open language model from OpenOneRec. 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.
Qwen3.6 27B MTPLX Optimized Speed
Youssofal · 4.7B · runs from 2.7 GB
Qwen3.6 27B MTPLX Optimized Speed is a 4.7B-parameter open language model from Youssofal 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.
Nemotron Cascade 8B
NVIDIA · 8B · runs from 4 GB
Nemotron Cascade 8B is a 8B-parameter open language model from NVIDIA in the Nemotron 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.
MiniCPM 2B Sft BF16
OpenBMB · 2B · runs from 1.9 GB
MiniCPM 2B Sft BF16 is a 2B-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.
Falcon 7B Instruct
TII UAE · 7.2B · runs from 3.4 GB
Falcon 7B Instruct is the instruction-tuned version of TII's Falcon 7B, fine-tuned on a mix of chat and instruction datasets to follow user prompts more reliably. It was among the early open models to show that a well-tuned 7B model could handle conversational tasks, summarization, and basic reasoning without requiring massive hardware. While newer models have since raised the bar, Falcon 7B Instruct remains a lightweight option for users who want a responsive local assistant with modest resource requirements.
Codegemma 2B
Google · 2.5B · runs from 1.2 GB
Codegemma 2B is a 2.5B-parameter open language model from Google in the Gemma 2 family. See its VRAM requirements by quantization and which GPUs and Macs can run it locally below.
Llm Jp 3.1 13B Instruct4
llm-jp · 13.7B · runs from 7.8 GB
Llm Jp 3.1 13B Instruct4 is a 13.7B-parameter open language model from llm-jp. 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.
ERNIE 4.5 0.3B PT
Baidu · 361M · runs from 0.5 GB
ERNIE 4.5 0.3B PT is a 361M-parameter open language model from Baidu in the ERNIE 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.
Qwen3.6 35B A3B Claude 4.7 Opus Reasoning Distilled
lordx64 · 36.0B · runs from 15.7 GB
Qwen3.6 35B A3B Claude 4.7 Opus Reasoning Distilled is a 36.0B-parameter open language model from lordx64 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.
Llama 2 13B HF
Meta · 13.0B · runs from 6.1 GB
Llama-2-13b-hf is Meta's 13-billion-parameter base (pretrained, not instruction-tuned) language model from the original Llama 2 family, intended as a general-purpose foundation for natural-language generation and further fine-tuning rather than direct assistant-style chat, for which Meta released separate Llama-2-Chat checkpoints. It is an auto-regressive transformer trained on 2 trillion tokens of publicly available data with a September 2022 knowledge cutoff, using a global batch size of 4 million tokens; unlike the 70B model, the 13B size does not use grouped-query attention. It is a historically significant open-weight release rather than a current state-of-the-art model by 2026 standards. At 13 billion parameters, it fits on a single consumer GPU once quantized. Context length is 4,096 tokens. It is released under the Llama 2 Community License, a custom license that is free for most commercial and research use but requires organizations with more than 700 million monthly active users to request separate permission from Meta. It was published in July 2023.
OCC RAG 1.7B
occ-ai · 1.7B · runs from 1.3 GB
OCC RAG 1.7B is a 1.7B-parameter open language model from occ-ai. 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.
Gemma 4 12B OBLITERATED
OBLITERATUS · 12.0B · runs from 6.1 GB
Gemma 4 12B OBLITERATED is a 12.0B-parameter open language model from OBLITERATUS 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.
CodeLlama 34B HF
Meta · 33.7B · runs from 15.0 GB
CodeLlama 34B HF is a 33.7B-parameter open language model from Meta in the Code Llama 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.
Gemma 2B IT
Google · 2.5B · runs from 1.2 GB
Gemma 2B IT is a 2.5B-parameter open language model from Google in the Gemma 2 family. See its VRAM requirements by quantization and which GPUs and Macs can run it locally below.
Baichuan 7B
baichuan-inc · 7B · runs from 15.4 GB
Baichuan-7B is Baichuan Intelligent Technology's open-source base pretrained language model, not instruction-tuned, with 7 billion parameters trained on around 1.2 trillion bilingual Chinese-English tokens. It follows a LLaMA-like Transformer design with rotary position embeddings, SwiGLU feedforward layers, and RMSNorm pre-normalization, and was positioned at release as state of the art among models of its size on the Chinese C-Eval and English MMLU benchmarks. Its 7B size makes it easy to run on a single consumer GPU. Context length is 4,096 tokens. It is released under the custom Baichuan-7B license, which is more permissive than LLaMA's original license and explicitly allows commercial use. It was published in June 2023, as one of the earliest fully open Chinese-English base models; Baichuan later released larger and instruction-tuned successors.
Ouro 1.4B
ByteDance · 1.4B · runs from 3.6 GB
Ouro 1.4B is a 1.4B-parameter open language model from ByteDance. 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.
Huginn 0125
tomg-group-umd · 3.9B · runs from 8.6 GB
Huginn 0125 is a 3.9B-parameter open language model from tomg-group-umd. See its VRAM requirements by quantization and which GPUs and Macs can run it locally below.
Granite 4.2 30B
IBM · 29.3B · runs from 13.3 GB
Granite 4.2 30B is a 29.3B-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.
Deepseek Moe 16B Chat
DeepSeek · 16.4B · runs from 7.7 GB
Deepseek Moe 16B Chat is a 16.4B-parameter open language model from DeepSeek in the DeepSeek 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.
Olmo Hybrid 7B
Allen AI · 7B · runs from 15.3 GB
Olmo Hybrid 7B is a 7B-parameter open language model from Allen AI in the OLMo family. 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.