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

Elbaz NVIDIA Nemotron 3 Nano 30B A3B PRISM

Ex0bit · 30B · runs from 14.0 GB

2.5K 26

Elbaz NVIDIA Nemotron 3 Nano 30B A3B PRISM is a 30B-parameter open language model from Ex0bit in the Nemotron family. See its VRAM requirements by quantization and which GPUs and Macs can run it locally below.

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Baichuan2 7B Base

baichuan-inc · 7B · runs from 3.3 GB

2.4K 86

Baichuan2 7B Base is a 7B-parameter open language model from baichuan-inc in the Baichuan 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.

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Nemotron Terminal 8B

NVIDIA · 8.2B · runs from 4.1 GB

2.3K 26

Nemotron Terminal 8B is a 8.2B-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.

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Nemotron Content Safety Reasoning 4B

NVIDIA · 4.3B · runs from 2.5 GB

2.3K 19

Nemotron Content Safety Reasoning 4B is a 4.3B-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.

ChatReasoning

Param2 17B A2.4B Thinking

bharatgenai · 17.2B · runs from 34.7 GB

2.2K 53

Param2 17B A2.4B Thinking is a 17.2B-parameter open language model from bharatgenai. 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.

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Emo 1b14b 1T

Allen AI · 13.6B · runs from 6.3 GB

2.1K 25

Emo 1b14b 1T is a 13.6B-parameter open language model from Allen 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.

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Veyra 30M Base

veyra-ai · 35M · runs from 0.3 GB

2.1K 2

Veyra 30M Base is a 35M-parameter open language model from veyra-ai. 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.

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Finance Llama3 8B

instruction-pretrain · 8.0B · runs from 4.0 GB

2.0K 76

Finance Llama3 8B is a 8.0B-parameter open language model from instruction-pretrain 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.

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Huihui Qwen3 4B Abliterated v2

huihui-ai · 4.0B · runs from 2.2 GB

2.0K 30

Huihui Qwen3 4B Abliterated v2 is a 4.0B-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.

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MediPhi Instruct

Microsoft · 3.8B · runs from 2.7 GB

1.9K 69

MediPhi Instruct is a 3.8B-parameter open language model from Microsoft in the Phi 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.

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Carbon 8B

HuggingFaceBio · 8.3B · runs from 4.1 GB

1.9K 45

Carbon 8B is a 8.3B-parameter open language model from HuggingFaceBio. 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.

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Smol Llama 101M GQA

BEE-spoke-data · 101M · runs from 0.4 GB

1.9K 33

Smol Llama 101M GQA is a 101M-parameter open language model from BEE-spoke-data in the Llama family. 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.

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Qwen3 42B A3B 2507 Thinking Abliterated Uncensored TOTAL RECALL v2 Medium MASTER CODER

DavidAU · 42.4B · runs from 18.4 GB

1.9K 35

Qwen3 42B A3B 2507 Thinking Abliterated Uncensored TOTAL RECALL v2 Medium MASTER CODER is a 42.4B-parameter open language model from DavidAU 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.

ChatCodeReasoning

Domyn Small v1.0

domyn · 9.8B · runs from 4.7 GB

1.9K 15

Domyn Small v1.0 is a 9.8B-parameter open language model from domyn. 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.

ChatReasoning

Baichuan M3 235B

baichuan-inc · 235.1B · runs from 100.4 GB

1.9K 93

Baichuan M3 235B is a 235.1B-parameter open language model from baichuan-inc in the Baichuan 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.

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Qwen3.5 9B Uncensored

LEONW24 · 9B · runs from 4.2 GB

1.8K 8

Qwen3.5 9B Uncensored is a 9B-parameter open language model from LEONW24 in the Qwen 3.5 family. See its VRAM requirements by quantization and which GPUs and Macs can run it locally below.

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JoyAI LLM Flash

jdopensource · 49.3B · runs from 21.9 GB

1.8K 159

JoyAI LLM Flash is a 49.3B-parameter open language model from jdopensource. 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.

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Nanowhale 100M

Hugging Face · 110M · runs from 0.5 GB

1.8K 63

Nanowhale 100M is a 110M-parameter open language model from Hugging Face. 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.

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Qwen3 1.7B Abliterated

huihui-ai · 1.7B · runs from 0.8 GB

1.8K 14

Qwen3 1.7B Abliterated is a 1.7B-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.

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Qwen3 0.6B Heretic Abliterated Uncensored

DavidAU · 596M · runs from 0.7 GB

1.7K 28

Qwen3 0.6B Heretic Abliterated Uncensored is a 596M-parameter open language model from DavidAU 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.

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Internlm 7B

InternLM · 7B · runs from 15.4 GB

1.7K 96

Internlm 7B is a 7B-parameter open language model from InternLM in the InternLM 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.

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Seed OSS 36B Base

ByteDance-Seed · 36.2B · runs from 15.9 GB

1.7K 62

Seed OSS 36B Base is a 36.2B-parameter open language model from ByteDance-Seed in the Seed-OSS 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.

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Llama 3.1 Nemotron Safety Guard 8B v3

NVIDIA · 8.0B · runs from 4.0 GB

1.7K 13

Llama 3.1 Nemotron Safety Guard 8B v3 is a 8.0B-parameter open language model from NVIDIA 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.

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Context 1

chromadb · 20.9B · runs from 9.3 GB

1.7K 413

Context 1 is a 20.9B-parameter open language model from chromadb. 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.

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Arch Router 1.5B

katanemo · 1.5B · runs from 1.0 GB

1.6K 264

Arch Router 1.5B is a 1.5B-parameter open language model from katanemo. 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.

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FastVLM 7B

Apple · 7.8B · runs from 15.9 GB

1.6K 269

FastVLM 7B is a 7.8B-parameter open language model from Apple. 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.

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Steerling 8B

guidelabs · 8.4B · runs from 18.5 GB

1.6K 106

Steerling 8B is a 8.4B-parameter open language model from guidelabs. See its VRAM requirements by quantization and which GPUs and Macs can run it locally below.

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GLM 4.7 Flash Heretic

Olafangensan · 29.9B · runs from 13.8 GB

1.6K 17

GLM 4.7 Flash Heretic is a 29.9B-parameter open language model from Olafangensan in the GLM 4 family. It supports a context window of up to 202,752 tokens. See its VRAM requirements by quantization and which GPUs and Macs can run it locally below.

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Qwen3 0.6B

litert-community · 0.6B · runs from 0.3 GB

1.6K 11

Qwen3 0.6B is a 0.6B-parameter open language model from litert-community in the Qwen 3 family. See its VRAM requirements by quantization and which GPUs and Macs can run it locally below.

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Vicuna 13B V1.3

LMSYS · 13B · runs from 6.1 GB

1.6K 203

Vicuna 13B V1.3 is a 13B-parameter open language model from LMSYS in the Vicuna 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.

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