BitFan
Public Service Atlas for Bittensor
BitFan
TEUTONIC lets ordinary users try a public chat version of its large language model, while technical users can join competitions for making large-scale AI training more efficient across many internet-connected machines.
TEUTONIC began as a system for training large language models across many internet-connected machines. Current public surfaces show a public chat page for Covenant-72B, public research artifacts, dashboards, and an active Crusades competition. The original training protocol appears dormant according to the newer repo, so the current live product is better understood as model artifact plus training-efficiency competition. The real target user is a machine-learning researcher, infrastructure engineer, GPU operator, or technically strong participant. Ordinary users can try the chat page, but the deeper project is technical. Verified user count, customer count, revenue, and profit: No reliable public source found. Public signals include dashboard activity, repo activity, model downloads, and project-reported participant counts. These are weak proxies, not proof of market adoption.
The real target user is a machine-learning researcher, infrastructure engineer, GPU operator, or technically strong participant. Ordinary users can try the chat page, but the deeper project is technical.
Verified user count, customer count, revenue, and profit: No reliable public source found. Public signals include dashboard activity, repo activity, model downloads, and project-reported participant counts. These are weak proxies, not proof of market adoption.
Closest alternatives: Prime Intellect, Gensyn, Nous Research/Psyche, and Together AI.
Templar is a real technical project with public outputs, public code, research, dashboards, a model, and live developer participation. It is not a polished mainstream AI app. Its strength is transparency and research depth; its weakness is product clarity and commercial proof.
