ESM C embedding remote tool#
TOU validation and deployment status (2026-08-16)#
ESM Cambrian 6B ran on the NVIDIA GB10 (aarch64, cc 12.1) with the optimization kit OFF – stock ESM C, a supported mode of the kit and not a workaround.
exactis not reachable on this card: itsfusedlever needs flash-attn, which publishes no aarch64 wheel, and this kit refuses to load at all rather than degrade (“a mode is all of its levers”). Verified on FOUR CONSECUTIVE IDENTICAL REQUESTS in one held worker: build 141.7 s, then forwards of 0.69 / 0.076 / 0.074 / 0.074 s at a flat 24.07 GiB peak reserved. That ratio is the point of this deployment – a per-request process spends 141.7 s reading 23.7 GiB of weights to do 0.076 s of work. Peak is nearly flat in length (28.75 GiB at 1600 residues, 1.19x the 100-residue figure), because the constant 6B parameter term dominates. Public publication, cross-user isolation, concurrency, recovery and embedding quality are untested; keep this deployment private.
Operation:
run_esmc_embedStart:
python -m tooluniverse.remote.esmc.esmc_toolEndpoint:
http://127.0.0.1:8037/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 28.75 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://127.0.0.1:8037/mcp --jsonPrivate relay:
tu serve --share --forward http://127.0.0.1:8037/mcp --name validation-esmc --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 esmc. 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#
ESM Cambrian protein language model: sequence embeddings and masked-LM logits
Weights and kit are pinned: src/tooluniverse/remote/esmc/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/esmc.json, and that per-host file – not the
number in the manifest – is what a scheduler should read.