# Hugging Face: what's new, verdict & setup Canonical: https://theagenticweekly.com/tools/hugging-face · First covered by us (no vendor release date published): 2026-10-25 · Last verified: 2026-10-26 · Evidence: Tested (smoke test, 2026-10-26, SmolLM2-135M from the Hub) · Vendor: Hugging Face · Official site: https://huggingface.co/ > The hub where the ML community shares models, datasets and apps, with PRO, Team and Enterprise tiers. ## Verdict **The hub where the ML community shares models, datasets and apps, with PRO, Team and Enterprise tiers.** Good for: - Anyone sourcing open models and datasets Skip if: - You want a single polished chat app Tested. Tested 2026-10-26 (America/Chicago). Hugging Face's Hub searched without a login in 0.1 s, a 272 MB model downloaded in 3.61 s, and transformers ran it on CPU. Test environment: Linux x86_64 virtual machine (Debian 13), 8 vCPU, 15 GiB RAM, no GPU; no vendor account, login or API key. The model was local (SmolLM2-135M-Instruct downloaded from the Hugging Face Hub and run with the transformers library on CPU (not the Qwen2.5-3B used in other tests)); we tested the tool, not any vendor's hosted models. Not tested: Gated models, private repositories, uploads, Spaces and Inference Providers: all need an account or token; Download speed for large (multi-GB) models; Any model beyond one 135M-parameter model; quality of its output was not assessed; Timing of generation: the machine was heavily shared. These are smoke tests, not a benchmark. Full log: /tests/hugging-face. Test scope: - Kind and date: smoke test, 2026-10-26 (America/Chicago). Not a benchmark. - What we ran: Hugging Face's Hub searched without a login in 0.1 s, a 272 MB model downloaded in 3.61 s, and transformers ran it on CPU. - Model used: SmolLM2-135M-Instruct downloaded from the Hugging Face Hub and run with the transformers library on CPU (not the Qwen2.5-3B used in other tests) - Environment: Linux x86_64 virtual machine (Debian 13), 8 vCPU, 15 GiB RAM, no GPU; no vendor account, login or API key - Not tested: Gated models, private repositories, uploads, Spaces and Inference Providers: all need an account or token; Download speed for large (multi-GB) models; Any model beyond one 135M-parameter model; quality of its output was not assessed; Timing of generation: the machine was heavily shared. Full test log (commands, versions, raw output): [Hugging Face huggingface_hub 2.3.0, transformers 5.20.2, torch 2.14.1 (CPU): our test log](https://theagenticweekly.com/tests/hugging-face) Pricing: Official page, dated. Read from huggingface.co/pricing on 2026-10-25. (checked 2026-10-25) ## Best for - [Best AI tool for local LLM tools and model platforms](https://theagenticweekly.com/best/llm-platforms) (#-): Hub for models, datasets and Spaces with paid compute. ## Key facts Hugging Face's pricing lists PRO at $9 a month, Team at $20 per user a month, a $50 per user a month tier beside Enterprise, storage rates per TB, on-demand GPU hardware starting at $0, and dedicated inference starting at $0.033 an hour. - License: Varies by repository - Platforms: Web, API and libraries - Pricing model: Freemium - Free tier: Free hub account - Paid plans: PRO $9/month; Team $20 per user per month; a $50 per user per month tier is listed beside Enterprise; paid compute and storage - How to start: Create a free account at huggingface.co. - Catalog entry: facts read from the vendor's pages on 2026-10-25. We do not track release notes for this entry. ## How to set it up: Get started with Hugging Face These steps come from the vendor's own pages as read on 2026-10-25. We have not run Hugging Face. 1. **Get access.** Create a free account at huggingface.co. 2. **Check the limits and costs first.** Free hub account. Paid: PRO $9/month; Team $20 per user per month; a $50 per user per month tier is listed beside Enterprise; paid compute and storage. Read from huggingface.co/pricing on 2026-10-25. ## Pros and cons Pros: - Largest open model hub - Spaces hosting Cons: - License varies per model ## Alternatives - [Ollama](https://theagenticweekly.com/tools/ollama): The common way to run open models locally on macOS, Windows and Linux, with a cloud option and an MIT-licensed open-source core. - [Replicate](https://theagenticweekly.com/tools/replicate): Cloud API for running and fine-tuning open models, with per-use pricing. - [Together AI](https://theagenticweekly.com/tools/together-ai): AI cloud for open models: serverless inference, fine-tuning and GPU clusters, priced per token. - [Cohere](https://theagenticweekly.com/tools/cohere): Enterprise AI company: Command models, Rerank and the North platform. - [DeepSeek](https://theagenticweekly.com/tools/deepseek): Model API that works with the OpenAI and Anthropic SDK formats and can back agent tools such as Claude Code, GitHub Copilot and OpenCode. - [LiteLLM](https://theagenticweekly.com/tools/litellm): Python SDK and proxy that gives one OpenAI-style interface to many model providers. - [llama.cpp](https://theagenticweekly.com/tools/llama-cpp): LLM inference in C/C++: the open-source engine many local-model tools build on; MIT-licensed with near-daily build tags. - [LM Studio](https://theagenticweekly.com/tools/lm-studio): Desktop app for running open models locally; the homepage now leads with Bionic, an agent for work and code. - [Open WebUI](https://theagenticweekly.com/tools/open-webui): Self-hosted AI platform: a web interface that connects to Ollama and OpenAI-compatible models, under its own Open WebUI License. - [OpenRouter](https://theagenticweekly.com/tools/openrouter): Unified API to many models with fallbacks; a Free tier with 25+ free models and 4 free providers. - [Jan](https://theagenticweekly.com/tools/jan): Open-source alternative to ChatGPT that runs open models locally or connects to cloud models like GPT and Claude. - [GPT4All](https://theagenticweekly.com/tools/gpt4all): Local chatbot from Nomic that runs open-source models on your device; the latest GitHub release we saw is v3.10.0 from Feb 2025. ## FAQ ### What is Hugging Face? Hugging Face's pricing lists PRO at $9 a month, Team at $20 per user a month, a $50 per user a month tier beside Enterprise, storage rates per TB, on-demand GPU hardware starting at $0, and dedicated inference starting at $0.033 an hour. ### Is Hugging Face free? Free hub account. Paid: PRO $9/month; Team $20 per user per month; a $50 per user per month tier is listed beside Enterprise; paid compute and storage. Read from huggingface.co/pricing on 2026-10-25. Checked 2026-10-25; prices change, so confirm on the vendor's page. ### What license is Hugging Face under? Its license: Varies by repository. Read from the project's own pages on 2026-10-25. ## What we have not verified - Release date (none published on the pages we read; the date shown is the day we first covered this entry) - Free-tier quotas ## Sources - [Hugging Face](https://huggingface.co/) (fetched 2026-10-25) - [Hugging Face pricing](https://huggingface.co/pricing) (fetched 2026-10-25) ## How to cite Agentic Weekly, "Hugging Face: what's new, verdict & setup", last updated 2026-10-26, https://theagenticweekly.com/tools/hugging-face Keep the Reported or Tested label when you quote the verdict.