| name | cosmos |
| description | Use when working on Cosmos world model serving, inference, serverless training smoke validation, backend selection, or rendering limitations. |
Cosmos
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.md
skills/atomic/cosmos3-codebase-nav/SKILL.md
skills/atomic/cosmos3-env-troubleshoot/SKILL.md
skills/workflows/cosmos3-inference/SKILL.md
skills/workflows/cosmos3-post-training/SKILL.md
API:
POST /serve
POST /infer
POST /train for serverless Jobs smoke validation
GET /status
GET /system-info
GET /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:
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:
finetune and optimize are 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.
Sim2Real VLM (self-hosted Reason2 + Reason3)
Sim2Real stage 8 evaluates rollouts with two workbench-hosted Cosmos Reason
models in parallel sibling GPU jobs — not Token Factory:
nvidia/Cosmos-Reason2-8B (vlm_eval_reason2)
nvidia/Cosmos-Reason2-2B (vlm_eval_reason3, self-hosted default second checkpoint)
nvidia/Cosmos3-Super-Reasoner is a Token Factory hosted model id only
(no Hugging Face repo). Use npa workbench token-factory reason for that path;
do not set it as VLM_REASON3_MODEL on self-hosted sim2real runs.
Implementation lives in npa.workbench.cosmos.reason. The npa-cosmos3-reason
image runs component-vlm-eval; dual eval merges judgments via
merge_dual_reason_evaluations. Pool sizing divides k8s_max_parallel_gpus by
two jobs per rollout (NPA_SIM2REAL_VLM_DUAL_REASON=1, default). With
k8s_max_parallel_gpus=16 and ROLLOUT_COUNT=8, all 16 GPUs can run VLM eval.
Hugging Face setup (required once per account): accept each gated repo at
https://huggingface.co while signed in, then put HF_TOKEN in
~/.npa/credentials.yaml and mirror it into the cluster hf-ngc-tokens secret.
See sim2real-workflow.md.
Env knobs: VLM_REASON2_MODEL, VLM_REASON3_MODEL, VLM_REASON2_IMAGE,
VLM_REASON3_IMAGE, NPA_COSMOS_REASON2_CACHE, NPA_COSMOS_REASON3_CACHE.
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.