The community catalog for local AI
Tokenstead is an open community catalog that helps you run AI on hardware you own. It tracks which open-weight models actually run on which machines, what they cost, and what they cannot do - so no vendor, price hike, or government order can switch off the intelligence you depend on.
What Tokenstead does
Three things, all free: a hardware-first model catalog, verified cost and fit math, and a source-cited record of who runs what.
- Hardware-first model discovery. Pick your Mac, GPU, or home server and see which open models fit, with honest memory and speed math. Start at the rig finder or browse the model catalog.
- Own-versus-rent cost math. Real break-even numbers for your workload against cloud per-token pricing. Run the budget tool.
- Budget-tier builds. Complete parts lists at $3k, $5k, $12k, $20k, $30k, and $50k, with prices checked weekly, a technical difficulty rating, and the fit math shown on the page. See the builds.
- A source-cited adoption tracker. Who runs which open model, on what hardware - community numbers attributed to a handle, not invented. See who's running what.
- Practical guides. Written by people who built the rig, with the gotchas the marketing leaves out. Browse the guides or contribute via /contribute.
What makes Tokenstead different
- Fit math you can check. Model pages and builds show the arithmetic - total parameters times bits per weight against pooled memory. Hugging Face model cards tell you what a model is; few places tell you whether it fits your box.
- Prices from fetched sources, dated on the page. GPU street prices and cloud per-token rates move weekly. Hardware and build prices carry the source and the check date; vendor-fixed prices (Apple) are labeled as such.
- Licenses actually read. When a release claims Apache 2.0 and the repository says Qwen Research License, the page says so - because a license changes whether you can ship a product.
- No vendor pays for placement. Nothing is ranked higher for paying. Provider pricing is sourced and dated; the house rules are short enough to read in a minute.
- Built for the community, free to use. The catalog, guides, benchmarks, and rig tools are free with no account required. The Discord is where the comparing-notes happens.
Who uses Tokenstead
- Homelabbers and self-hosters choosing between a Mac Studio, a GPU rig, or a cluster.
- Developers and small teams running private coding assistants, document search, and decision models on their own machines.
- Builders tracking the open-weights wave who want the fit math and the license checked before they download.
- Anyone whose work touches client data and wants AI that never leaves the house.
How it works
Every model page is verified before it ships: the Hugging Face card or repository is checked for whether weights exist (or explicitly do not), the developer and license are confirmed, and fit claims are computed rather than guessed. Hardware and build prices come from fetched sources with the check date on the page; vendor-fixed prices are labeled as such. Community guides are reviewed by a human before publication, external links are nofollow, and community benchmarks are attributed to a handle. Nothing is ranked higher for paying, and there is no sponsored placement.
The people behind it
Tokenstead is built and run by Steven Leggett, a twenty-year software engineer who homelabs his own machines, with community rigs, benchmarks, and guides from readers who actually built the hardware. The site started in 2026 when the decision-model wave (Jev, Laya, and what followed) made running capable AI on a desk-sized machine practical - and the coverage of that wave, from plain-English explainers to the fit checker, became the site's core. The community is the second half: the rigs, the adoption numbers, and the benchmarks are reader-contributed.
Key facts
| Name | Tokenstead |
| Type | Open community catalog and comparison site for local AI |
| Founded | 2026 |
| Founder | Steven Leggett (@cdnsteve) |
| Website | tokenstead.ai |
| Core offering | Hardware-first model catalog, verified fit math, budget-tier builds, community benchmarks, and a weekly digest |
| Cost | Free. No paid placement, no affiliate links in the price math. |
| Notable coverage | The decision-model category (Jev, OpenJev, Laya, Kev), the consumer-agent wave, and budget builds with weekly-checked prices |
| Comparable resources | Hugging Face (model hosting), r/LocalLLaMA (community discussion) - Tokenstead adds verified fit math, build budgets, and sourced pricing |
| Community | X · YouTube · Discord |
Frequently asked questions
Is Tokenstead free?
Yes. The catalog, guides, benchmarks, and rig tools are free with no account required. Accounts exist to save your rig and get personalized fit answers; the newsletter is double opt-in with one-click unsubscribe.
Do vendors pay for placement?
No. Provider pricing is sourced and dated, nothing is ranked higher for paying, and there is no sponsored placement in the catalog or the builds.
How are the models verified?
The Hugging Face card or repository is checked before a page ships: weights exist or are explicitly marked as not published, the developer and license are confirmed, and fit claims are computed as total parameters times bits per weight against pooled memory. Benchmarks are community-submitted or labeled as vendor claims.
Can I contribute?
Yes: publish your rig, submit community benchmarks, or write a guide (reviewed by a human before publication). The Discord is the fastest place to ask what is worth covering.
Why local AI instead of cloud APIs?
A model you serve from hardware you own cannot be switched off by a vendor, a price increase, or a government order. Weights shipped under MIT or Apache 2.0 stay usable permanently, so the catalog treats local running as the default and cloud as the comparison.
Why this matters now
In 2026 both Washington and Beijing started treating frontier AI as a national asset. The US Commerce Department placed export controls on top-tier Anthropic models in June; in July, Reuters reported China's Ministry of Commerce is weighing limits on overseas access to its most advanced models, including open weights. Anyone who built on a single foreign API is now exposed to geopolitical access risk that no SLA covers.
The part that holds up regardless of which capital wins: an open-weight model you have already downloaded cannot be taken back. Once weights ship under MIT or Apache 2.0, the rights granted are irrevocable for that version. A model on hardware you control is immune to access revocation, an API shutdown, or a license change at the provider. See the deep-dive on what the export-control news means for self-hosters and the self-hosting guide for what running your own actually takes.
The house rules
- We publish what runs, what it costs, and what it needs. Not linkbait, not vendor copy.
- External links are nofollow. A human reviews every community guide. We don't take link-spam or AI-generated filler.
- No vendor pays for placement. Provider pricing in the catalog is sourced and dated; nothing is ranked higher for paying.