CrowdTensor is an Apache-2.0 open-source protocol for checkpointed volunteer model-training Campaigns. A Campaign pins immutable model/data revisions and gives admitted CPU/GPU/TPU Cells bounded work. Accepted LoRA deltas advance one auditable checkpoint; contributor disappearance s or reassigns work instead of discarding committed progress.
The completed feasibility run used:
Qwen/Qwen2.5-7B-Instruct@a09a35458c702b33eeacc393d103063234e8bc28
openai/gsm8k@740312add88f781978c0658806c59bc2815b9866
71.875% -> 74.219%
The practical preregistered threshold passed; the paired bootstrap interval included zero, so no statistical-significance or broad-capability claim is made.
A smaller Founding SmolLM2/WikiText-2 Campaign now serves live aggregate status. Two maintainer-operated private Kaggle GPU Cells seeded its first round through the public HTTPS contribution path. Enrollment remains controlled, and the project still lacks independent physical multi-host evidence and permissionless adversarial safety.
I would value review of the Draft 7B RFC, especially the fresh-holdout design, the 256-to-1,024-step extension rule, quantized 16 GB GPU work units, delta validation, and maintainer/rollback policy.