RFdiffusion3 remote tool#
TOU validation and deployment status (2026-08-16)#
RFdiffusion3 under the optimization kit’s
fastmode, with the kit’s file overlay applied, ran on the NVIDIA GB10 (aarch64, cc 12.1). Three unconditional 60-mers in one held worker took 19.4 s, 1.6 s and 1.6 s – the largest residency gain of the six providers, because the compile trace and the CUDA-graph capture are paid once per process. A live call through this entry point returned two designs with no chain breaks and no clashes. Peak reserved is 12.49 GiB at 400 residues and 4 designs, measured, and peak is driven by length rather than by count. Public publication, cross-user isolation, concurrency, recovery and design quality are unvalidated; keep this deployment private.
Operation:
rfdiffusion3_designStart:
python -m tooluniverse.remote.rfdiffusion3.rfdiffusion3_toolEndpoint:
http://127.0.0.1:8040/mcpProvider configuration: this provider is on the remote-tool standard, so the model runs in its own environment built from a pinned lock, and the weights are declared with a size and a sha256 and verified before the worker starts. Keep provider data, weights, caches and credentials outside Git. Use one worker: the resident worker serves one request at a time by design, and a second in-flight request queues on its lock rather than doubling peak VRAM. The measured VRAM budget is 12.49 GiB; read the envelope it was measured at in the manifest before co-tenanting anything else on the card, because a larger request exceeds it.
TOU check:
tu doctor --forward http://127.0.0.1:8040/mcp --jsonPrivate relay:
tu serve --share --forward http://127.0.0.1:8040/mcp --name validation-rfdiffusion3 --workers 1
Non-loopback binding requires TOOLUNIVERSE_API_TOKEN; otherwise keep the
server on loopback. The relay requires TOOLUNIVERSE_SERVICE_KEY. Public
publication and independent-caller testing were not run.
New-user check: python scripts/remote_validation/setup_skill_preflight.py --implementation rfdiffusion3. Add --check-provider-env before launch, --live
after launch, and --check-connect-prereqs before sharing. Live preflight
checks exact MCP discovery only; it does not run or validate a model.
The authenticated 2026-08-16 Platform matrix found all 30 private owner relays
online and all 41 operations discoverable. It imported each implementation as
unpublished owner draft(s), configured a 120-second timeout, and invoked it
through /expert-sessions/{id}/test. This implementation was added after
that matrix and was not part of it, so none of that evidence covers it: it has
not been exercised through the Platform at all, and everything above was
measured locally, on one card, through the loopback endpoint. Public
publication, independent-caller authorization/isolation, broad saturation and
persistent supervision are unvalidated here.
Overview#
RFdiffusion3 protein backbone design from a design specification
Weights and kit are pinned: src/tooluniverse/remote/rfdiffusion3/provider.toml
declares the upstream kit by commit, the environment by lock file, and every
weight file with its byte count and digest. Nothing is fetched at request time.
The measured peak VRAM for this host is written to
~/.cache/tooluniverse/measured/rfdiffusion3.json, and that per-host file – not the
number in the manifest – is what a scheduler should read.