How to download AI models without Hugging Face

You are here because huggingface.co is not an option: it does not load, it is blocked where you are, or you want files from a source you can check. Most of what ranks for "Hugging Face alternative" will not help with that, because it is built for running models, not obtaining them: deployment platforms, local inference apps, serving stacks. The channels that actually hand you open-weight files are a second hub, a mirror of the Hub, a self-hosted mirror, a quantized-model registry, and torrents. They differ on two things that decide the pick: whether an interrupted transfer resumes, and whether you can check the bytes against the publisher's own digests.

This page compares all of them in one table, maps each onto the situation that calls for it, and shows the check that makes any of them safe to trust. If you already know you want verified upstream files, start at the catalog: every model there ships as a torrent, no account, no token.

Why the usual alternatives lists do not answer this

Open the articles that rank for the phrase and you find platforms for serving models: managed deployment hosts, local runners, inference stacks. Their comparison criteria are all on the running side. Weight files appear only as a thing the tools fetch for you, from somewhere, somehow.

Some of the local apps make the problem worse, not better, because they download their models from Hugging Face under the hood. One popular runner is advertised on its one-click model downloads from Hugging Face. When the Hub itself is the thing that does not load, a tool that reaches for the Hub is not an alternative to it. The listicle answer and the downloading answer are different answers; this page is the second one.

When huggingface.co is genuinely out of reach

Four documented reasons cover nearly every "the site does not load" report. They have different fixes, so it pays to know which one is yours before you pick a channel.

• The region you are in. huggingface.co has been unreachable at the network level from mainland China since 2023. Users there report connection failures to the host in issue threads on unrelated projects, for example a ControlNet issue from March 2024 that quotes the connection error.
• The model's publisher. The Hub lets publishers region-restrict gated models: a model can carry a flag that disallows the EU, the flag is active only when the model is gated, and, in Hugging Face's own words, "The system identifies a user's location based on its IP address." Gated models also require an account, agreement to terms, and sharing contact information with the authors, who can block any user's access at any time without notice.
• Your office network. Even where the main site loads, a download needs several separate storage and CDN hostnames to be reachable too. Hugging Face's download documentation states that "allowlisting huggingface.co alone is not sufficient" and publishes the full hostname list, including a machine-readable copy. Corporate networks do block the host: one organization documented that unblocking a URL took around 20 to 25 days per request, and their tool still tried to reach huggingface.co with the weights already sitting on local disk, in an issue that tracks the whole episode.
• Export and sanctions law. The terms of service say it directly: "you may only access and use the Service in compliance with U.S. and other applicable export control and sanctions laws and regulations," per the terms themselves.

Five channels that hand you the files

One line each. The comparison table carries the detail.

• A second hub. ModelScope, at modelscope.cn, is a separate hub maintained by the ModelScope team. Most models there are public and download directly, and it hosts many of the same open-weight families: Llama, Qwen, DeepSeek, Yi, and Phi-3 models are named in its README.
• A community mirror. hf-mirror.com serves the Hub's files through a different front door, aimed at users who cannot reach huggingface.co. It supports the standard command-line tools, does not support signing in, which it states for account safety, and sends gated-repository users to the official site for a token.
• A self-hosted mirror. Two open-source routes: olah, which caches Hub files at file-block level as people download them, and a Caddy configuration whose public instance is hf-mirror.com. You run either yourself, inside your own fence.
• A quantized-model registry. Ollama's library is browsable without an account, with per-model size variants. What it hands you is a ready-to-run quantized copy, not the upstream safetensors.
• Torrents. Established torrent libraries host model weights too: Academic Torrents carries a full DeepSeek-R1 copy, 163 safetensors files, 688.59 GB, MIT-licensed. A verified archive is the same idea with the trust problem handled: this site mirrors upstream safetensors, verified at fetch time, with the revision pinned in a signed manifest.

The format fork happens here. Hubs and archives carry the upstream files, safetensors and configs exactly as published. Registries carry quants, which are third-party repacks: unless a GGUF file is listed in this archive's signed manifest, it did not come from this archive. Which file your hardware actually needs is the help page's question, not this one's.

The plumbing detail that makes mirrors work: the standard Hugging Face libraries read an environment variable called HF_ENDPOINT and use it instead of the default https://huggingface.co endpoint. The line lives in the library's constants.py, and the official environment-variable reference page does not list it. Every mirror, public or self-run, is that one variable pointed somewhere else:

# point the standard tools at a mirror endpoint
export HF_ENDPOINT=https://hf-mirror.com
huggingface-cli download --resume-download Qwen/Qwen3-4B --local-dir Qwen3-4B

That is the command-line route the mirror documents, resume flag included; the mirror's own hfd.sh tool resumes differently, by re-running the same command after an interruption. On the second hub the route is its Python library, installed with pip install modelscope. On the registry side it is a single ollama pull.

The comparison: resumable, verifiable, available

Seven rows: the Hub itself as the baseline, five channels, and this archive last, so you can see exactly what it adds. Two columns do the deciding. Resumable is what happens when your link drops at 80 percent. Verifiable is what the channel itself proves about the bytes it served you.

Three things the table says once you look across it. Resumability is close to universal now, so it rarely decides anything on its own. The Verifiable column is where the channels genuinely differ: two rows verify by design, two publish nothing, and the rest verify the transfer but not the source. And Where it works is why a comparison beats a recommendation: the strongest channel on paper is useless behind a fence that blocks it.

The torrent rows raise two questions this page deliberately does not own. Whether model torrents are legal and safe, plus the client walkthrough and the seeding ask, is the AI model torrents guide. What the magnet link actually hands your client is the magnet links and infohashes guide.

Pick by your situation

• The Hub does not load where you are. Use a second hub or a torrent. Both hand you files with zero dependence on huggingface.co reachability, and the torrent route adds a verification step you can run entirely offline.
• An office network blocks it. Torrents work if BitTorrent traffic is allowed on your network. If it is not, a self-hosted mirror you run inside the fence is the remaining route, and you accept the work of operating it.
• The Hub works, but you want the files from somewhere else. Any channel, then verify the digests before you load the model. The channel answers a delivery question; the bytes answer a trust question.
• You just want to run a model tonight. Pull from a registry and accept the trade: you get a quant, not upstream bytes. The help page picks the size for your RAM.
• The Hub is merely slow, not unreachable. That is a different problem with its own guide: speed tuning while the Hub still works is the slow-download guide's lane. This page is for when you are not using the Hub at all.

Mirrors borrow trust: check what any channel served you

A mirror is a stranger's copy of a 30 GB file. The question is not whether the operators are well intentioned; it is what the channel can prove. Registries check every blob by digest and fail the pull on a mismatch. Torrent clients hash-check every piece against the hashes in the torrent file, so a finished torrent is byte-identical to what that torrent described. Hub mirrors publish no integrity story of their own: the self-host tools' READMEs are silent on verification, and that silence is the honest thing to report rather than paper over.

The move that works everywhere is the digest cross-check. The publisher's file pages and the repository tree API publish a digest for every file: a 64-hex value for LFS-stored files and a 40-hex git oid for the small ones, with the method stated, sha256 for LFS files, sha1+size for git blobs. Whatever channel served you the bytes, hash what landed on your disk and compare. The exact commands live in the verify guide; this archive's version of the same idea is a signed manifest, where one minisign check covers every per-file digest and the pinned upstream revision, on the verify page.

Community sentiment on the big public mirror tracks the same conclusion: users call hf-mirror usable and unofficial, and the standard advice is to verify checksums as a precaution. The request for an official mirror option in the Hub's own client library was closed without one, in the issue that asked for it, which is why third-party mirrors exist at all.

This archive is one row of that table, not its frame. It mirrors upstream safetensors payloads, verifies them against Hugging Face at fetch time, pins the revision, and distributes them as torrents with no account and no token: the Llama-licensed NousResearch_Hermes-3-Llama-3.1-8B and the apache-2.0 Qwen_Qwen2.5-7B-Instruct are both there as upstream-byte torrents. The catalog is the list, and a model you need that is missing from it belongs on the requests page. Pick the channel your network allows, then verify the bytes whichever one you chose.