All LLM Models
Browse 50 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
Qwen1.5 14B Chat
Alibaba · 14.2B · runs from 8 GB
10.9K
112Qwen1.5 14B Chat is a 14.2B-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.
Qwen1.5 7B Chat
Alibaba · 7.7B · runs from 4.7 GB
Qwen1.5 7B Chat is a 7.7B-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.
Qwen 14B Chat
Alibaba · 14.2B · runs from 6.6 GB
Qwen 14B Chat is a 14.2B-parameter open language model from Alibaba in the Qwen 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.
Qwen1.5 7B
Alibaba · 7.7B · runs from 4.7 GB
Qwen1.5 7B is a 7.7B-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.
Qwen 7B
Alibaba · 7.7B · runs from 3.6 GB
Qwen 7B is a 7.7B-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.
CodeQwen1.5 7B
Alibaba · 7.3B · runs from 3.5 GB
CodeQwen1.5 7B is a 7.3B-parameter open language model from Alibaba in the Qwen 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.
Qwen1.5 14B
Alibaba · 14.2B · runs from 8 GB
Qwen1.5 14B is a 14.2B-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.
Qwen 14B
Alibaba · 14.2B · runs from 6.6 GB
Qwen 14B is a 14.2B-parameter open language model from Alibaba in the Qwen 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.
Qwen 1 8B
Alibaba · 1.8B · runs from 0.9 GB
Qwen 1 8B is a 1.8B-parameter open language model from Alibaba in the Qwen 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.
Qwen3.5 4B
Alibaba · 4.7B · runs from 2.5 GB
Qwen3.5 4B is a 4.7B-parameter open language model from Alibaba 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.
Qwen3.5 9B
Alibaba · 9.7B · runs from 4.7 GB
Qwen3.5 9B is a 9.7B-parameter open language model from Alibaba 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.
Qwen3.5 0.8B
Alibaba · 873M · runs from 0.7 GB
Qwen3.5 0.8B is a 873M-parameter open language model from Alibaba 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.
Qwen1.5 MoE A2.7B
Alibaba · 14.3B · runs from 6.8 GB
Qwen1.5 MoE A2.7B is a Mixture of Experts (MoE) model from Alibaba Cloud's Qwen 1.5 generation, with 14.3 billion total parameters but only 2.7 billion active parameters per forward pass. The MoE architecture allows it to deliver performance closer to dense 7B models while requiring less compute during inference, as only a subset of expert layers are activated for each token. The model supports a 32K token context window and requires VRAM proportional to its total parameter count for loading, despite lower compute cost per token. It is an interesting architectural variant for users exploring efficient inference and MoE models locally. Released under a custom Qwen license.
Qwen2 1.5B
Alibaba · 1.5B · runs from 1.0 GB
Qwen2 1.5B is a 1.5-billion parameter base (pretrained) model from Alibaba Cloud's older Qwen 2 generation. It was trained on a multilingual corpus and supports a context window of up to 32K tokens. As a base model, it is designed for fine-tuning and research rather than direct conversational use. While superseded by the Qwen 2.5 series in terms of training data quality and benchmark performance, Qwen2 1.5B remains a lightweight option for experimentation and as a baseline for comparison. Released under the Apache 2.0 license.
Qwen3 14B Base
Alibaba · 14.8B · runs from 6.9 GB
Qwen3 14B Base is a 14.8B-parameter open language model from Alibaba in the Qwen 3 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 · 2.7B · runs from 1.9 GB
Qwen1.5 MoE A2.7B Chat is a 2.7B-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.
Qwen2.5 Coder 0.5B
Alibaba · 494M · runs from 0.5 GB
Qwen2.5 Coder 0.5B is a 494-million parameter code-specialized model from Alibaba Cloud, the smallest in the Qwen 2.5 Coder series. It is designed for ultra-lightweight deployment where code-aware text generation is needed with minimal hardware resources. The model runs on virtually any GPU and even on CPU-only setups. While limited in capability compared to larger coding models, it is useful for basic code completion, prototyping, and experimentation. It supports a 128K token context window. Released under the Apache 2.0 license.
Qwen1.5 1.8B
Alibaba · 1.8B · runs from 1.5 GB
Qwen1.5 1.8B is a 1.8B-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.
Qwen2.5 Coder 14B
Alibaba · 14.8B · runs from 7.0 GB
Qwen2.5 Coder 14B is a 14.8B-parameter open language model from Alibaba 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.
WebWorld 8B
Alibaba · 8.2B · runs from 4.1 GB
WebWorld 8B is a 8.2B-parameter open language model from Alibaba. 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.