Argus · Nebius execution record and cloud asset gate

Status on 2026-10-22: Token Factory model inference completed; an AI Cloud H100 job processed all twelve fox source-bound photo/render pairs and produced verified diagnostic outputs. The fox mesh, textures, and fixed-camera renders shown in the demo were computed locally. The cloud stage audited those saved assets; it did not reconstruct or promote a new model. See the twelve-view diagnostic and cost report.

Verified execution

The B300 smoke log showed NVIDIA B300 SXM6, driver 580.173.02, CUDA 13.0, and 275040 MiB device memory. Nebius reported container execution from 2026-10-22T04:53:37.930440300Z to 04:53:38.510811462Z for that job. Container time does not establish total billable time or cost.

The H100 job used gpu-h100-sxm, preset 1gpu-16vcpu-200gb, and reported COMPLETED. Its container executed from 2026-10-22T06:29:32.920721850Z to 06:29:35.243632245Z; the log showed NVIDIA H100 80GB HBM3 and PyTorch 2.9.0+cu130. The CUDA arithmetic took about 0.223 seconds. It averaged twelve scores that were already computed locally: control RGB MAE 15.548863728841145, candidate 15.553794066111246, candidate better in six views. The candidate remained not_promoted. The job did not load the original photos or masks, reconstruct geometry, generate a material, render a camera view, or produce a new asset. The label ARGUS_GPU_PROOF in its historical log is overbroad; it identifies this receipt, not proof of a cloud product stage.

The replay input SHA-256 is f743ce1b0833c60aa1e38d67b76995cf4484d1d7062977a7e817a9c5e9cebf5e; the local source report SHA-256 is 538724b63ea6e47de53ce27da432d91bac4a31d69920a5d8c70d133302dd0e59. The uploaded entrypoint SHA-256 was d18f9be69ea5562004ce5579fd7fe71ba07b6d42b64017434bc614aed5968c53. Provider exports on Robin's Windows machine are local review bundle/argus-nebius-h100-job.json (SHA-256 58c072e5ba3a61d13c793054c9a426a9b6fb99b49202d3d2aa5e2ae73838ba30) and adjacent argus-nebius-h100-logs.txt (SHA-256 e616b48aa504d8104a47c2d373c5a036295b95bdd51fb564046ca9873f62140a). Preserve these records; do not repeat this billable scalar test. ship_argus_nebius_gpu_job.py is retained only to reproduce its historical entrypoint and now requires --historical-replay.

First meaningful cloud asset job: completed diagnostic

The H100 audit accepted 12 source-bound bundles via a private Nebius Object Storage mount. Its manifest SHA-256 was ff39dedacb5cd9f1dd606d7f9723fabc8c56f46bbb16d91cc535b30f9c8bb5df. Nebius reported COMPLETED, with execution from 2026-10-22T19:09:44.149409247Z to 19:09:49.994890703Z. The output report SHA-256 was db2521329dee3223394275c2eb4f641b9cb9aa1856135b521dfe9318947c18f5; 24 PNG heatmaps and the JSON report were downloaded and hash verified. Its mean neutral and candidate RGB MAE values were 15.41145 and 15.40383 respectively at 360 × 542, with eight of twelve views lower-error for the candidate. The change is very small and the sampling contract differs from the full-resolution local gate, so the material remains diagnostic. The cost method and caveats are in the linked report.

Next cloud asset stage

The next Nebius AI Cloud stage can move asset generation or full-resolution camera parity to the cloud. ship_gof_backend.py is an actual CUDA surface-evaluation path, but its pinned extension and scene dependencies must be packaged and qualified on the selected cloud GPU before it is a runnable job. The fox material and original-camera comparison in ship_fox_material_model.py and ship_fox_material_camera_compare.py is the output-parity target: it loads the GLB, texture atlases, original photographs and masks, twelve camera transforms, and light receipt, then writes images and a per-view report. Those two scripts use NumPy/SciPy and trimesh, with no demonstrated CUDA path; merely moving them into a GPU container would not prove GPU processing. Their current runner uses a pinned local Docker image and Ahab-mounted working tree. Neither runtime and source package is ready for Nebius yet.

For a future paid asset-generation job, package one immutable input manifest covering its exact scene data, photos, masks, cameras, script revision, pinned extension, and container image. Preserve source ownership and camera bindings. Write a retrievable mesh, field, or rendered images plus a report; logs alone are insufficient. Compare that artifact against a frozen local result using the same cameras and record metrics and differences. Include the fox fixed-camera material comparison if the cloud stage produces a compatible surface or asset; do not substitute its CPU execution for CUDA evidence.

Do not promote geometry or materials merely because the cloud job succeeds. Preserve the local report's diagnostic status and the existing failed or conditional qualification gates. The cloud acceptance gate is reproducible execution and artifact parity, not a claim that the fox is already game ready. The exact AI Cloud billable cost remains unknown until a billing record is captured. Token Factory balance and access do not establish AI Cloud credits. Published-rate arithmetic and measured usage are in the linked report.

Official setup: Nebius Serverless AI Jobs quick start and CLI setup.