Download adoption Most Downloaded LLMs on Hugging Face
Download counts are useful adoption signals for open-weight and local models, but they are not the same as active users,
benchmark quality, or production API traffic. This page uses qualitative signals until precise download data is wired into the site.
Quick Answer
Models with strong open-weight ecosystems, many fine-tunes, and local deployment tutorials tend to dominate download attention.
Qwen, DeepSeek, Llama, Gemma, Mistral, and smaller specialist models often matter here because developers can inspect, fine-tune,
and run them outside a closed API.
Most Downloaded Chat LLMs
| Rank | Model | Provider | Model Type | Open Weights | Download Signal | Best For |
| #1 | Qwen | Alibaba | Chat / reasoning | Many open-weight releases | High | Open-weight chat and coding experiments |
| #2 | DeepSeek | DeepSeek | Reasoning / chat | Many open-weight releases | High | Reasoning, code, local deployment research |
| #3 | Llama | Meta | Chat / local | Open-weight family | High | Local deployment and broad ecosystem support |
| #4 | Mistral | Mistral AI | Chat / coding | Mixed open and closed releases | Medium | European model stack and developer APIs |
Most Downloaded Open-Weight Models
| Rank | Model | Provider | Model Type | Open Weights | Download Signal | Best For |
| #1 | Qwen3 family | Alibaba | Open-weight LLM | Yes / varies by release | High | Coding, reasoning, multilingual use |
| #2 | DeepSeek R1 distills | DeepSeek | Reasoning distills | Yes / varies by release | High | Reasoning experiments on smaller hardware |
| #3 | Llama 3.x / 4 family | Meta | Open-weight LLM | Yes / varies by release | High | General local model ecosystem |
| #4 | Gemma family | Google | Open-weight LLM | Yes / varies by release | Medium | Small local models and research |
Most Downloaded Small / Local Models
| Rank | Model | Provider | Model Type | Open Weights | Download Signal | Best For |
| #1 | Small Qwen variants | Alibaba | Small / local | Yes / varies by release | High | Local assistants and edge experiments |
| #2 | DeepSeek distill variants | DeepSeek | Small reasoning | Yes / varies by release | High | Reasoning behavior in smaller models |
| #3 | Phi family | Microsoft | Small / local | Yes / varies by release | Medium | Lightweight experimentation |
| #4 | Gemma small variants | Google | Small / local | Yes / varies by release | Medium | On-device and compact inference |
What Download Counts Can and Cannot Tell You
- Downloads can indicate ecosystem interest, local deployment demand, and downstream fine-tuning activity.
- They can be inflated by automated downloads, dependency installs, repeated downloads, and CI pipelines.
- They do not equal active users, API traffic, benchmark quality, or model safety.