Pricing
- Single Sign-On
- Regions
- Priority Support
- Audit Logs
- Resource Groups
- Deploy on optimized Inference Endpoints
- Update Spaces applications to a GPU
Pricing from the official site, verified Jun 2026. Always confirm current prices on the vendor site.
Pros & cons
Our analysisPros
- Over 500,000 models across all modalities
- Standard Python interface via Transformers library
- Hosted inference and Spaces for quick demos
- Supports text, image, audio, and multimodal tasks
- Enterprise private hosting available
Cons
- No free tier on paid/enterprise plans
- Paid plans start at $0.60
- Navigating 500k+ models requires expertise
What users say
Hugging Face is commonly used as both a model discovery platform and a deployment layer for researchers and engineers working across the ML ecosystem. A frequently noted strength is the Transformers library, which serves as the de facto standard Python interface for loading and running most open models locally. A common consideration is that the sheer volume of over 500,000 models makes curation and quality assessment a skill in itself.
Editorial summary based on public information.
Best for
ML researchers and developers discovering, hosting, or fine-tuning open models
Manually choose competitor
Hugging Face
| Feature | ||
|---|---|---|
| Pricing | Paid | — |
| Price from | $0.6/mo | — |
| Free tier | No | No |
| API | Yes | No |
| Open source | No | Yes |
| Platforms | Mobile App | Web |
| Models | Huggingface | — |
| Context window | 1M | — |
| Launched | 2024 | 2008 |
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Verified Jun 2026
Specs
| Pricing | Paid |
|---|---|
| Price from | $0.6/mo |
| Free tier | No |
| API | Yes |
| Open source | No |
| Platforms | Mobile App |
| Models | Huggingface |
| Context window | 1M |
| Launched | 2024 |
News
Hy4 makes the open-model choice a serving decision
August 30, 2026
Tencent’s Hy4 preview combines 770B total parameters, 49B activated per token, a 1M context, and documented vLLM and SGLang serving paths. Its internal evaluation is promising but not independent proof of general superiority.
Liquid AI Releases DSpark Checkpoints to Speed Up LFM2.5 Models on GPUs and Laptops
August 21, 2026
Liquid AI has released DSpark checkpoints that speed up its LFM2.5 models using speculative decoding. The new files work right away in llama.cpp and SGLang, but your actual speed gains depend on your hardware and tasks.
Liquid AI Releases Fast 3.1B Vision Model for Local Devices and Private Workloads
August 13, 2026
Liquid AI released LFM2.5-VL-3B, a 3.1-billion-parameter open-weight vision-language model built for on-device use. It brings quick visual processing to laptops and phones without sending private data to the cloud.

