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
Rwkv 4 169M Pile
RWKV · 169M · runs from 0.1 GB
10.6K
9Rwkv 4 169M Pile is a 169M-parameter open language model from RWKV. See its VRAM requirements by quantization and which GPUs and Macs can run it locally below.
Phi 1
Microsoft · 1.4B · runs from 0.7 GB
Phi 1 is a 1.4B-parameter open language model from Microsoft in the Phi 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 3 ELYZA JP 8B
elyza · 8.0B · runs from 4.0 GB
Llama 3 ELYZA JP 8B is a 8.0B-parameter open language model from elyza 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.
PapersRAG 1.5B
metaresearch · 1.5B · runs from 1.0 GB
PapersRAG 1.5B is a 1.5B-parameter open language model from metaresearch. 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.
T5gemma 2B 2B Ul2
Google · 5.6B · runs from 2.6 GB
T5gemma 2B 2B Ul2 is a 5.6B-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.
Ouro 1.4B Thinking
ByteDance · 1.4B · runs from 3.6 GB
Ouro 1.4B Thinking 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.
Qwen3.8 2B Distill
empero-ai · 2.3B · runs from 1.4 GB
Qwen3.8 2B Distill is a 2.3B-parameter open language model from empero-ai 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.
Sarvam 1
sarvamai · 2.5B · runs from 1.6 GB
Sarvam 1 is a 2.5B-parameter open language model from sarvamai. 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.
Granite 3.1 2B Instruct
IBM · 2.5B · runs from 1.5 GB
Granite 3.1 2B Instruct is IBM's 2.5-billion-parameter dense instruction-tuned model, fine-tuned from Granite-3.1-2B-Base on permissively licensed open instruction datasets plus internally generated synthetic data aimed at long-context problems. It targets business-assistant work such as summarization, classification, extraction, question answering, retrieval-augmented generation, code tasks and function calling, and supports twelve languages including English, German, Spanish, French, Japanese, Arabic and Chinese. At this size it runs on almost any consumer GPU, and on a laptop CPU once quantized. Context length is 131,072 tokens. It is released under the Apache 2.0 license, permitting unrestricted commercial and research use, and was published in December 2024. IBM has since superseded it with Granite 3.3 2B Instruct, which keeps the same size class.
Supra 50M Instruct
SupraLabs · 52M · runs from 0.3 GB
Supra 50M Instruct is a 52M-parameter open language model from SupraLabs. 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.
Meta Llama 3 8B Instruct Abliterated v3
failspy · 8.0B · runs from 4.0 GB
Meta Llama 3 8B Instruct Abliterated v3 is a 8.0B-parameter open language model from failspy 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.
Dolphin 2.9.1 Llama 3 70B
dphn · 70.6B · runs from 31.0 GB
Dolphin 2.9.1 Llama 3 70B is a 70.6B-parameter open language model from dphn 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.
VibeThinker 3B
WeiboAI · 3.1B · runs from 1.7 GB
VibeThinker 3B is a 3.1B-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.
Ouro 2.6B
ByteDance · 2.7B · runs from 6.4 GB
Ouro 2.6B is a 2.7B-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.
Title
desert-ant-labs · 352M · runs from 0.5 GB
Title is a 352M-parameter open language model from desert-ant-labs. 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.
ALLaM 7B Instruct Preview
humain-ai · 7.0B · runs from 4.3 GB
ALLaM 7B Instruct Preview is a 7.0B-parameter open language model from humain-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.
Huihui Qwen3 8B Abliterated v2
huihui-ai · 8.2B · runs from 4.1 GB
Huihui Qwen3 8B Abliterated v2 is a 8.2B-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.
Qwen Marketing
marketeam · 8.2B · runs from 18.0 GB
Qwen Marketing is a 8.2B-parameter open language model from marketeam in the Qwen family. See its VRAM requirements by quantization and which GPUs and Macs can run it locally below.
Midnight Miqu 70B V1.5
sophosympatheia · 69.0B · runs from 30.3 GB
Midnight Miqu 70B V1.5 is a 69.0B-parameter open language model from sophosympatheia. It supports a context window of up to 32,764 tokens. See its VRAM requirements by quantization and which GPUs and Macs can run it locally below.
Ternary Bonsai 2 27B MTP
ProCreations · 27B · runs from 12.6 GB
Ternary Bonsai 2 27B MTP is a 27B-parameter open language model from ProCreations. See its VRAM requirements by quantization and which GPUs and Macs can run it locally below.
Granite Switch 4.1 3B Preview
IBM · 4.1B · runs from 8.8 GB
Granite Switch 4.1 3B Preview is a 4.1B-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.
Goedel Prover v2 8B
Goedel-LM · 8.2B · runs from 4.1 GB
Goedel Prover v2 8B is a 8.2B-parameter open language model from Goedel-LM. 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.
Meta Llama Guard 2 8B
Meta · 8.0B · runs from 17.7 GB
Meta Llama Guard 2 8B is a 8.0B-parameter open language model from Meta in the Llama family. See its VRAM requirements by quantization and which GPUs and Macs can run it locally below.
Mamba 1.4B HF
State Spaces · 1.4B · runs from 0.6 GB
Mamba 1.4B HF is a 1.4B-parameter open language model from State Spaces. See its VRAM requirements by quantization and which GPUs and Macs can run it locally below.
Llama3 8B Chinese Chat
shenzhi-wang · 8.0B · runs from 4.0 GB
Llama3 8B Chinese Chat is a 8.0B-parameter open language model from shenzhi-wang 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.
MiniCPM5 1B Base
OpenBMB · 1.1B · runs from 0.8 GB
MiniCPM5 1B Base is a 1.1B-parameter open language model from OpenBMB in the MiniCPM 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.
Mamba 2.8B HF
State Spaces · 2.8B · runs from 1.3 GB
Mamba 2.8B HF is a 2.8B-parameter open language model from State Spaces. See its VRAM requirements by quantization and which GPUs and Macs can run it locally below.
Mixtral 34Bx2 MoE 60B
cloudyu · 60.8B · runs from 26.6 GB
Mixtral 34Bx2 MoE 60B is a 60.8B-parameter open language model from cloudyu in the Mixtral family. It supports a context window of up to 200,000 tokens. See its VRAM requirements by quantization and which GPUs and Macs can run it locally below.
MiniCPM5 2B Base
OpenBMB · 2.5B · runs from 1.5 GB
MiniCPM5 2B Base is a 2.5B-parameter open language model from OpenBMB in the MiniCPM family. It supports a context window of up to 524,288 tokens. See its VRAM requirements by quantization and which GPUs and Macs can run it locally below.
Gemma 2 2B Jpn IT
Google · 2.6B · runs from 5.8 GB
Gemma 2 2B Jpn IT is a 2.6B-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.