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Job configuration reference

Fields you set when you create a GPU Container Job or a Managed Inference Job.

You set these fields when you create a job, either in the web interface or with cosmicac jobs create. The job type determines which fields apply. In non-interactive mode, set each field with the flag in the CLI flag column. For the create flow, see Create a GPU Container Job and Create a Managed Inference Job.

Common fields

These fields apply to every job type.

FieldRequiredCLI flagDescription
Job typeYes--typeThe kind of job to create, either GPU Container or Managed Inference.
Job nameYes--nameA name to identify the job.
TagsYes--tagsOne or more labels for the job. The CLI accepts a comma-separated list.
LocationYes--locationWhere the job runs, for example IN. The CLI lists the locations your racks report.
NotificationsNo--notifyThe job lifecycle events this job reports. Takes a comma-separated list of job_failed, job_degraded, job_recovered, and job_restart_storm, or all, or none. Defaults to all four. An event also needs the matching switch on in SettingsNotifications before it reaches your webhook. See What controls delivery.

GPU configuration

These fields select the job's hardware.

FieldRequiredCLI flagDescription
GPUYes--gpu-typeThe GPU to use, for example GH100_H100_SXM5_80GB. The CLI lists the GPU types your racks report.
GPU countYes--gpu-countNumber of GPUs.
CUDA / driverYes--driverGPU driver version. CosmicAC supports only CUDA 12.9.

Set the GPU type and count in one flag with --gpu TYPE=COUNT, for example --gpu H100=2. This replaces --gpu-type and --gpu-count.

GPU Container parameters

These fields apply to a GPU Container Job.

FieldRequiredCLI flagDescription
Base OS imageYes--base-imageBase OS image for the container. CosmicAC supports only Ubuntu22.04/CUDA12.9.
DiskYes--root-disk-size-gbRoot disk size in GB. One of 250, 500, or 1000.

vLLM Managed Inference parameters

These fields apply to a vLLM Managed Inference Job.

FieldRequiredCLI flagDescription
ModelYes--modelHugging Face model ID to serve, for example MiniMaxAI/MiniMax-M2.5.
Runtime image (CUDA)Yes--runtime-imageServing runtime image as a Docker image reference. One of vllm/vllm-openai:v0.15.1 or vllm/vllm-openai:v0.17.1.
Data typeYes--data-typeNumeric precision the model runs at, for example BF16 or Auto.
QuantisationYes--quantisationQuantisation scheme, for example fp8 or awq.
Tensor parallelYes--tensor-parallelNumber of GPUs to split the model across.
GPU memory utilizationYes--gpu-memory-utilizationFraction of GPU memory to use, between 0 and 1.
Max concurrent sequencesYes--max-concurrent-sequencesMaximum requests handled at once.
Max model lengthYes--max-model-lengthMaximum model context length.
Reasoning parserYes--reasoning-parserParser for the model's reasoning output.
Video & image inputYes--multimodalWhether the model accepts multimodal input. true or false.
Root disk sizeYes--root-disk-size-gbVM root disk size in GB. One of 250, 500, or 1000.
Environment variablesNo--envEnvironment variables passed to the inference service.
Endpoint nameYes--endpoint-nameName of the inference endpoint. Must be unique across active inference jobs.
ReplicasYes--replicaNumber of endpoint replicas.
Require Authorization headerYes--require-auth-header / --no-auth-headerWhether callers must send an authorization header. true or false.

Parakeet Managed Inference parameters

These fields apply to a Parakeet Managed Inference Job.

FieldRequiredCLI flagDescription
ModelYes--modelParakeet model to serve, nvidia/parakeet-tdt-0.6b-v3.
Endpoint nameYes--endpoint-nameName of the transcription endpoint.
Chunk durationYes--chunk-durationAudio chunk length in seconds, for example 600. Minimum 10.
Chunk overlapYes--chunk-overlapOverlap between chunks in seconds, for example 5. Must be less than the chunk duration. Minimum 5.
Max file sizeYes--max-file-size-mbMaximum upload size in MB, for example 1024. Minimum 1024.
Require Authorization headerYes--require-auth-header / --no-auth-headerWhether callers must send an authorization header. true or false.

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