All LLM Models

Browse 1214 LLM models with VRAM requirements, quantization options, and hardware compatibility.

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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.

MoziAI 27B MTP

chenyumo · 27B · runs from 12.2 GB

MoziAI 27B MTP is a 27B-parameter open language model from chenyumo. 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.

Qwen3.8 27B Cold Fusion GAIN V1.1

DavidAU · 27.8B · runs from 12.6 GB

Qwen3.8 27B Cold Fusion GAIN V1.1 is a 27.8B-parameter open language model from DavidAU 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.

Qwen3.5 4B PTBR

lucasmg09 · 4B · runs from 1.5 GB

Qwen3.5 4B PTBR is a 4B-parameter open language model from lucasmg09 in the Qwen 3.5 family. See its VRAM requirements by quantization and which GPUs and Macs can run it locally below.

Txgemma 2B Predict

Google · 2.6B · runs from 1.2 GB

Txgemma 2B Predict 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.

LFM2 2.6B Longevity

Liquid AI · 2.6B · runs from 1.5 GB

LFM2 2.6B Longevity is a 2.6B-parameter open language model from Liquid AI in the LFM2 family. 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.

Qwen3 8B Heretic

DreamFast · 8.2B · runs from 4.1 GB

Qwen3 8B Heretic is a 8.2B-parameter open language model from DreamFast 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.

Aya Expanse 32B

Cohere · 32.3B · runs from 15.1 GB

Aya Expanse 32B is Cohere Labs' 32.3-billion-parameter multilingual chat model, built on the Command-R model family and refined through data arbitrage, multilingual preference training, safety tuning, and model merging aimed at closing the performance gap between English and lower-resource languages. It is optimized to perform well across 23 languages including Arabic, Chinese, French, Hindi, Japanese, and Russian, and Cohere reported it outperforming much larger models such as Llama 3.1 405B and Mistral Large 2 on multilingual evaluation. At 32.3 billion parameters, it needs a high-end consumer GPU or multi-GPU setup once quantized. It is released under the CC BY-NC 4.0 license, restricting use to non-commercial purposes only, and was published in October 2024, as the 32B counterpart to the smaller Aya Expanse 8B model.

SIQ 1 35B

AlexWortega · 34.7B · runs from 15.1 GB

SIQ 1 35B is a 34.7B-parameter open language model from AlexWortega. 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.

SILMA 9B Instruct v1.0

silma-ai · 9.2B · runs from 4.8 GB

SILMA 9B Instruct v1.0 is a 9.2B-parameter open language model from silma-ai. 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.

Baichuan2 7B Base

baichuan-inc · 7B · runs from 3.3 GB

Baichuan2-7B-Base is Baichuan Intelligence's second-generation 7-billion-parameter pretrained base model, a bilingual English/Chinese language model, not instruction-tuned, trained on 2.6 trillion tokens of high-quality data, up from 1.2 trillion for the original Baichuan-7B. It reports the best results among same-size open models on Chinese and English benchmarks including C-Eval, MMLU, CMMLU, and BBH. A separately released Baichuan2-7B-Chat provides the aligned, conversational counterpart to this base checkpoint, along with a 4-bit quantized chat variant. At 7 billion parameters it runs easily on a single consumer GPU. Context length is 4,096 tokens. It is released under a custom Baichuan2 Community License plus Apache 2.0 for the code: free for research, and free for commercial use only for organizations with under 1 million daily active users that are not themselves software or cloud service providers, subject to a written authorization request. It was published in August 2023.

Qwen3.6 27B MTPLX Optimized

Youssofal · 26.9B · runs from 12.2 GB

Qwen3.6 27B MTPLX Optimized is a 26.9B-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.

Fable Traces

AliesTaha · 4.0B · runs from 2.2 GB

Fable Traces is a 4.0B-parameter open language model from AliesTaha. 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.

OFFELLIA Gemma 4 E4B 8B Claude 4.6 Opus Reasoning MTP

Brunobkr · 4B · runs from 1.9 GB

OFFELLIA Gemma 4 E4B 8B Claude 4.6 Opus Reasoning MTP is a 4B-parameter open language model from Brunobkr in the Gemma 4 family. See its VRAM requirements by quantization and which GPUs and Macs can run it locally below.

Edge0 8B A1B Preview

Edge0 · 7.9B · runs from 16.4 GB

Edge0 8B A1B Preview is a 7.9B-parameter open language model from Edge0. 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.

Sarashina2.2 3B Instruct v0.1

sbintuitions · 3.4B · runs from 2.1 GB

Sarashina2.2 3B Instruct v0.1 is a 3.4B-parameter open language model from sbintuitions. 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.

Muse Glimmer 30B Heretic

darkc0de · 29.8B · runs from 13.1 GB

Muse Glimmer 30B Heretic is a 29.8B-parameter open language model from darkc0de in the Muse Glimmer 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.

TinyLlama 1.1B Chat V0.6

TinyLlama · 1.1B · runs from 0.8 GB

TinyLlama 1.1B Chat V0.6 is a 1.1B-parameter open language model from TinyLlama in the TinyLlama 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.

Gollem V4 250M Pl

SlayerLab · 250M · runs from 0.6 GB

Gollem V4 250M Pl is a 250M-parameter open language model from SlayerLab. See its VRAM requirements by quantization and which GPUs and Macs can run it locally below.

Neural Chat 7B v3 3

Intel · 7.2B · runs from 3.6 GB

Neural Chat 7B v3 3 is a 7.2B-parameter open language model from Intel. 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.

Baguettotron

PleIAs · 321M · runs from 0.6 GB

Baguettotron is a 321M-parameter open language model from PleIAs. 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.

DeepSeek Coder v2 Lite Base

DeepSeek · 15.7B · runs from 7.4 GB

DeepSeek Coder v2 Lite Base is a 15.7B-parameter open language model from DeepSeek in the DeepSeek Coder family. It supports a context window of up to 163,840 tokens. See its VRAM requirements by quantization and which GPUs and Macs can run it locally below.

Pollux 4B Judge

ai-forever · 4.0B · runs from 2.2 GB

Pollux 4B Judge is a 4.0B-parameter open language model from ai-forever. 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.

Gemma 3n E2B IT Litert Lm

Google · 2B · runs from 0.9 GB

Gemma 3n E2B IT Litert Lm is a 2B-parameter open language model from Google in the Gemma 3 family. See its VRAM requirements by quantization and which GPUs and Macs can run it locally below.

Shieldgemma 2B

Google · 2.6B · runs from 1.2 GB

Shieldgemma 2B 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.

Tiny Aya Global

Cohere · 3.3B · runs from 7.4 GB

Tiny Aya Global 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.

MiniCPM5 2B SFT

OpenBMB · 2.5B · runs from 1.5 GB

MiniCPM5 2B SFT is a 2.5B-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.

GigaChat 20B A3B Base

ai-sage · 20B · runs from 9.0 GB

GigaChat 20B A3B Base is a 20B-parameter open language model from ai-sage. 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.

Llama Krikri 8B Instruct

ilsp · 8.2B · runs from 4.0 GB

Llama Krikri 8B Instruct is a 8.2B-parameter open language model from ilsp in the Llama 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.

Deeplm 108M

samcheng0 · 108M · runs from 0.2 GB

Deeplm 108M is a 108M-parameter open language model from samcheng0. See its VRAM requirements by quantization and which GPUs and Macs can run it locally below.

GLM 5.3 DFlash2

incoai · 2.5B · runs from 1.4 GB

GLM 5.3 DFlash2 is a 2.5B-parameter open language model from incoai in the GLM 5 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.