All LLM Models
Browse 739 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
GPT S 5M
AxiomicLabs · 5M · runs from 0.3 GB
769
12GPT S 5M is a 5M-parameter open language model from AxiomicLabs. It supports a context window of up to 512 tokens. See its VRAM requirements by quantization and which GPUs and Macs can run it locally below.
Falcon H1 7B Base
TII UAE · 7.6B · runs from 3.7 GB
Falcon H1 7B Base is a 7.6B-parameter open language model from TII UAE in the Falcon 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.
XortronCriminalComputingConfig
darkc0de · 23.6B · runs from 10.7 GB
XortronCriminalComputingConfig is a 23.6B-parameter open language model from darkc0de. 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.
OpenReasoning Nemotron 32B
NVIDIA · 32.8B · runs from 14.8 GB
OpenReasoning Nemotron 32B is a 32.8B-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.
Qwen3.6 35B A3b Crown Halo Mtp Dynamic
jcbtc · 35B · runs from 16.4 GB
Qwen3.6 35B A3b Crown Halo Mtp Dynamic is a 35B-parameter open language model from jcbtc in the Qwen 3.6 family. See its VRAM requirements by quantization and which GPUs and Macs can run it locally below.
Moore Lm
ouilyh · 42M · runs from 0.1 GB
Moore Lm is a 42M-parameter open language model from ouilyh. See its VRAM requirements by quantization and which GPUs and Macs can run it locally below.
Stable DiffCoder 8B Instruct
ByteDance-Seed · 8.3B · runs from 17.1 GB
Stable DiffCoder 8B Instruct is a 8.3B-parameter open language model from ByteDance-Seed. 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.
UserLM 8B
Microsoft · 8.0B · runs from 4.0 GB
UserLM 8B is a 8.0B-parameter open language model from Microsoft. 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.
NuExtract
numind · 3.8B · runs from 2.7 GB
NuExtract is a 3.8B-parameter open language model from numind. 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.
LFM2 1.2B Extract
LiquidAI · 1.2B · runs from 0.9 GB
LFM2 1.2B Extract is a 1.2B-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.
Text2cypher Gemma 2 9B IT Finetuned 2024v1
neo4j · 9B · runs from 4.2 GB
Text2cypher Gemma 2 9B IT Finetuned 2024v1 is a 9B-parameter open language model from neo4j in the Gemma 2 family. See its VRAM requirements by quantization and which GPUs and Macs can run it locally below.
SKT ST X 0 3B
sKT-Ai-Labs · 3.4B · runs from 1.8 GB
SKT ST X 0 3B is a 3.4B-parameter open language model from sKT-Ai-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.
Harness 1
pat-jj · 20.9B · runs from 9.3 GB
Harness 1 is a 20.9B-parameter open language model from pat-jj. 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.
Nanowhale 100M
cmpatino · 110M · runs from 0.5 GB
Nanowhale 100M is a 110M-parameter open language model from cmpatino. 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.
Nemotron H 8B Reasoning 128K
NVIDIA · 8.1B · runs from 17.8 GB
Nemotron H 8B Reasoning 128K is a 8.1B-parameter open language model from NVIDIA in the Nemotron family. See its VRAM requirements by quantization and which GPUs and Macs can run it locally below.
Josiefied Qwen3.5 0.8B Gabliterated V1
Goekdeniz-Guelmez · 853M · runs from 2.1 GB
Josiefied Qwen3.5 0.8B Gabliterated V1 is a 853M-parameter open language model from Goekdeniz-Guelmez 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.
Covenant 72B Chat
1Covenant · 72.7B · runs from 31.9 GB
Covenant 72B Chat is a 72.7B-parameter open language model from 1Covenant. 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.
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.
Mellum2 12B A2.5B Thinking SFT
JetBrains · 12.1B · runs from 5.5 GB
Mellum2 12B A2.5B Thinking SFT 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.
PrunedHub Qwen3.5 35B A3B 80pct
GOBA-AI-Labs · 35B · runs from 16.4 GB
PrunedHub Qwen3.5 35B A3B 80pct is a 35B-parameter open language model from GOBA-AI-Labs in the Qwen 3.5 family. See its VRAM requirements by quantization and which GPUs and Macs can run it locally below.
Lucie 7B
OpenLLM-France · 6.7B · runs from 3.4 GB
Lucie 7B is a 6.7B-parameter open language model from OpenLLM-France. It supports a context window of up to 32,000 tokens. See its VRAM requirements by quantization and which GPUs and Macs can run it locally below.
Veritas 8B Fact Checker Non Thinking 1.0
resect-ai · 8.2B · runs from 4.1 GB
Veritas 8B Fact Checker Non Thinking 1.0 is a 8.2B-parameter open language model from resect-ai. 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 4B Abliterated
huihui-ai · 4.0B · runs from 1.9 GB
Qwen3 4B Abliterated is a 4.0B-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.
Qwopus3.5 9B V3.5
Jackrong · 9.7B · runs from 19.9 GB
Qwopus3.5 9B V3.5 is a 9.7B-parameter open language model from Jackrong. 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.
Steelman 14B Ada
the-clanker-lover · 14B · runs from 6.5 GB
Steelman 14B Ada is a 14B-parameter open language model from the-clanker-lover. See its VRAM requirements by quantization and which GPUs and Macs can run it locally below.
Luciole 8B Base
OpenLLM-France · 8.1B · runs from 4.2 GB
Luciole 8B Base is a 8.1B-parameter open language model from OpenLLM-France. 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.
Granite Switch 4.1 8B Preview
IBM · 9.6B · runs from 19.8 GB
Granite Switch 4.1 8B Preview is a 9.6B-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.
Qwen3.5 9B Gemini 3.1 Pro Reasoning Distill
Jackrong · 9.7B · runs from 4.7 GB
Qwen3.5 9B Gemini 3.1 Pro Reasoning Distill is a 9.7B-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.
MIST Mini 8B
olaverse · 8.0B · runs from 4.0 GB
MIST Mini 8B is a 8.0B-parameter open language model from olaverse. 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.
Kai 30B Instruct
NoesisLab · 32.8B · runs from 14.8 GB
Kai 30B Instruct is a 32.8B-parameter open language model from NoesisLab. 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.
