Cosmos
SkillCloud & infraUse when working on Cosmos world model serving, inference, serverless training smoke validation, backend selection, or rendering limitations.
Available today. Use it from your connected AI after setup.
No other account needed.
Connect ahel once, and every AI you use reads what you have installed.
Then ask your AI: use the Cosmos skill
What this skill tells your AI
The instructions your AI receives, as published by nebius/nebius-physical-ai in skills/tools/cosmos/SKILL.md and read by ahel’s review.
Cosmos is the world model tool for synthetic data generation and video generation.
It requires a GPU. RT cores are not required for standard serving, inference, or the serverless training smoke path, unlike Isaac Lab. Cosmos visual-generation/rendering paths have the same container EGL/DRI gap as Genesis.
Interfaces
Cosmos3-specific guidance lives as agent skills, not CLI commands:
skills/atomic/cosmos3-setup/SKILL.mdskills/atomic/cosmos3-codebase-nav/SKILL.mdskills/atomic/cosmos3-env-troubleshoot/SKILL.mdskills/workflows/cosmos3-inference/SKILL.mdskills/workflows/cosmos3-post-training/SKILL.md
API:
POST /servePOST /inferPOST /trainfor serverless Jobs smoke validationGET /statusGET /system-infoGET /list
CLI:
npa workbench cosmos deploy
npa workbench cosmos serve
npa workbench cosmos infer
npa workbench cosmos train --runtime serverless --smoke
npa workbench cosmos finetune
npa workbench cosmos optimize
npa workbench cosmos status
npa workbench cosmos system-info
npa workbench cosmos list
Backend Selection
Use --backend to select one of:
basicnimtriton
Only basic is implemented today. nim and triton are exposed as enum
choices but intentionally exit as not implemented. For multiple models, use
named workbenches or the deploy/serve model swap pattern.
E2E Status
Cosmos is validated end-to-end on Nebius through the public CLI serverless training smoke path:
npa workbench cosmos train --runtime serverless --smoke
W13 run w13-cosmos-e2e-20260521T233523Z completed on gpu-h100-sxm and
uploaded checkpoint.json to S3. This closes the named Workbench tool matrix
gap for an artifact-bearing Cosmos workflow.
Known constraints:
finetuneandoptimizeare placeholders.- Basic serverless endpoint inference validates endpoint/job completion, but generated endpoint outputs do not yet have a public CLI serverless-side S3 export contract.
- EGL/DRI-dependent visual-generation/rendering paths remain deferred.
Predict2 CUDA Wheel Contract
The npa-cosmos Predict2 1.0.9 image uses NVIDIA's complete v1.2.0
cu128_torch27 wheel set: torch 2.7.0, torchvision 0.22.0, flash-attn 2.7.3,
NATTEN 0.21.0, and Transformer Engine 1.13.0. Keep these as one ABI-locked
unit. Do not bump torch alone, and do not replace either custom-kernel wheel
with a source build during an image refresh.
Predict2 1.0.9's package metadata still pins triton 3.2.0 for its former torch
2.6 stack, while torch 2.7 requires triton 3.3.0. Install Predict2 itself with
--no-deps, exclude torch/torchvision/triton and the three NVIDIA kernel
packages from its derived dependency closure, and constrain every subsequent
resolver pass to torch 2.7.0, torchvision 0.22.0, and triton 3.3.0. Otherwise a
later broad dependency can silently replace the selected cu128 stack.
An architecture import check is insufficient. A release validation must read
torch._C._cuda_getArchFlags() and find sm_100, then execute both custom
kernels on B200: a real flash-attn forward and the exact pinned
Predict2 NeighborhoodAttention module with one of the model's shipped NATTEN
configurations. Run checkpoint-backed Video2World with --natten whenever the
operator has access to NVIDIA's gated checkpoint. If access is denied, record
that generation as unverified with the HTTP evidence; the model-module kernel
smoke is valid kernel-compatibility evidence, but it is not a generated-video
result.
Predict2 1.0.9 rejects B300 capability 10.3 in its own [90, 100] allowlist;
forward-compatible sm_100 wheel SASS does not bypass that check. Route this
pin to B200 or H100 and require a real-forward negative test when rechecking
B300.
Cosmos Transfer B300 Contract
The published Cosmos Transfer 2.5 cu128 image is validated for B200, not B300.
On physical B300 it reaches real Control2WorldInference model construction,
then torch.nn.init.trunc_normal_ JIT-compiles an erfinv kernel and CUDA 12.8
NVRTC rejects capability 10.3 with invalid value for --gpu-architecture.
This demonstrates that wheel SASS coverage alone cannot establish compatibility
for workloads that generate kernels at runtime. A B300 port must move the whole
locked environment to CUDA 13/cu130 and pass the full depth-conditioned
Video2Video smoke; a CUDA probe or import is not sufficient.
Sim2Real VLM (hosted evaluator)
Sim2Real stage 8 evaluates every exact Stage 7 rollout with one CPU-only leaf:
MiniMaxAI/MiniMax-M3, hosted by Nebius Token Factory. The former public
Cosmos3 model was retired; explicit serving Cosmos3 overrides remain supported.
Implementation lives in npa.workbench.cosmos.reason. The hosted evaluator leaf uses the
CPU controller image, bounded deterministic event-frame selection, and the
existing OpenAI-compatible Token Factory client. Stage 9 consumes its event-local
structured judgments directly after exact coverage and provenance checks. It
must never request a GPU or require the general-purpose Reason image.
Access setup: configure NEBIUS_TOKEN_FACTORY_KEY privately, run npa workbench token-factory models, and confirm the exact selected model plus a minimal
inference before submitting. Model availability is key/project-specific.
The canonical workflow model knob is config.cosmos3_model; the legacy
VLM_COSMOS3_MODEL override remains. MiniMax-M3 has its own Community License
(see docs/workbench/token-factory-deprecation-verification.md); it is not a
Cosmos model. The stable Cosmos3 lane/schema names are compatibility names.
For explicit legacy Cosmos3 selections, model materials are
OpenMDW-1.1; retain
skills/LICENSE-NVIDIA-COSMOS3-OPENMDW-1.1 and
skills/NOTICE-NVIDIA-COSMOS3. Hosted weights never enter NPA image layers.
Operational Safety
Managed VM deploy defaults to in-place updates for existing aliases. Terraform
plans that would destroy or replace critical infrastructure are blocked unless
the operator passes --replace and confirms with --yes for automation.
BYOVM deploys record endpoint_strategy: public or endpoint_strategy: ssh_fallback in ~/.npa/config.yaml. Live status, serve, and infer
commands honor that strategy and self-heal blocked public endpoints through a
transient SSH-local route.
Signals
- GitHub stars
- 28
- Forks
- 15
- Last commit
- Sep 2026
Advanced
- Catalog kind
- skill
- Gateway key
cosmos- Source
- github.com/nebius/nebius-physical-ai