Gradients

SN56 Gradients is a tailoring service for AI models: a customer drops off a model and a dataset, pays by the hour, and gets back a model fitted to their data, cut by whichever tailor won this week's contest.

The commodity, explained from zero

Fine-tuning is taking a model someone else trained and adjusting it on a company's own examples: support tickets, product photos, legal clauses. The result is a checkpoint, a saved model file, delivered to the customer's Hugging Face account. Gradients sells this by the hour. The rate card, read from a file in the repository because the pricing page loads only with JavaScript, runs from $10 an hour for the smallest text models to $50 for the largest, and $5 an hour for image models.

The customer is anyone: "0 AI training knowledge needed". A job starts from a web form or one API call to api.gradients.io/v1/tasks/create with a model, a dataset and hours to complete. The materials name no customers and give no usage figure. The news page's last post is from November 2025; the boldest claim, from February 2025, is that Gradients beat TogetherAI and Google as "the best 0-Click Training Platform in the World".

Why it is on Bittensor at all

The subnet's argument is that competition finds better training recipes than one company's engineers. Miners do not sell GPU time; they submit training code, and the code that wins is published at github.com/gradients-opensource for anyone to copy. The comparison breaks here: a tailor keeps the pattern, while a winning Gradients tailor must hand the pattern to the public, and the shop's own machines, not the tailor's, do the sewing.

How the work gets done

Miners (the tailors) run a small endpoint that tells validators which GitHub repository and commit to enter in each weekly tournament, and pay an entry fee in TAO. Validators (the judges) clone the code, build it in a locked-down container, run it on validator-owned GPUs, upload the model to Hugging Face and score it against the other entries, deciding knockout rounds "per held-out sample, not on mean loss". Within a tournament the top three ranks are paid roughly 76, 19 and 5 percent of that tournament's emission, the subnet's share of newly minted TAO, and a champion whose margin passes a 0.10 threshold has the excess multiplied by 2.0. Before a tournament closes, the team reads the winning code for exploits.

How you would know it works

The API reference at api.gradients.io/docs is live, and a public endpoint, GET /v1/network/status, reports completed jobs without a login. No benchmark table exists on the site; the research page needs an account.

What is missing

The entry fees disagree: the README quotes one set of TAO fees for the three tournament types, while the miner guide and the fees API quote double. The chain description is a slogan with a typo, "Best AutoML plaftorm in the world", and the discord and additional fields hold the literal word "None". The contact info@gradients.io matches the chain but appears only inside a news post. The only support path is Discord; there is no status page or SLA. The miner guide's clone URL still points at the old rayonlabs organisation.

Go deeper

• Front door with API example
• The miner guide, single source
• API reference for buyers

Metaphor: a tailoring service with a weekly cutting contest. Every claim is drawn from the evidence set or the subnet's own materials; "(inferred)" marks a conclusion rather than a quote. Corrections.