Get Batch Inference Job
Authorizations
Bearer authentication using your Fireworks API key. Format: Bearer <API_KEY>
Path Parameters
The Account Id
The Batch Inference Job Id
Query Parameters
The fields to be returned in the response. If empty or "*", all fields will be returned.
Response
A successful response.
The creation time of the batch inference job.
The time when the batch inference job will expire (stop running); any completed requests will have been written to the output dataset by then.
This is the job's effective execution deadline, derived by the server as create_time + the bounded run window (see max_job_duration). It is exposed so customers can read back the concrete deadline without recomputing it client-side. OUTPUT_ONLY: it is always computed server-side and any client-supplied value is ignored (previously this was a SUPERUSER_ONLY input that overlapped with max_job_duration; the two are now unified as one public input (duration) + one public derived deadline (this timestamp)).
The email address of the user who initiated this batch inference job.
JobState represents the state an asynchronous job can be in.
JOB_STATE_UNSPECIFIED, JOB_STATE_CREATING, JOB_STATE_RUNNING, JOB_STATE_COMPLETED, JOB_STATE_FAILED, JOB_STATE_CANCELLED, JOB_STATE_DELETING, JOB_STATE_WRITING_RESULTS, JOB_STATE_VALIDATING, JOB_STATE_DELETING_CLEANING_UP, JOB_STATE_PENDING, JOB_STATE_EXPIRED, JOB_STATE_RE_QUEUEING, JOB_STATE_CREATING_INPUT_DATASET, JOB_STATE_IDLE, JOB_STATE_CANCELLING, JOB_STATE_EARLY_STOPPED, JOB_STATE_PAUSED, JOB_STATE_DELETED, JOB_STATE_ARCHIVED The name of the model to use for inference. This is required, except when continued_from_job_name is specified.
The name of the dataset used for inference. This is required, except when continued_from_job_name is specified.
The name of the dataset used for storing the results. This will also contain the error file.
Optional job-level system prompt. When set, it is injected as a leading system message into every input row that does NOT already begin with a system message (a row's own leading system message takes precedence). This lets callers avoid repeating a large, static system prompt on every row of the input dataset, shrinking the upload. Because the injected prefix is byte-identical across rows, prompt caching still applies.
Parameters controlling the inference process.
The update time for the batch inference job.
The precision with which the model should be served. If PRECISION_UNSPECIFIED, a default will be chosen based on the model.
PRECISION_UNSPECIFIED, FP16, FP8, FP8_MM, FP8_AR, FP8_MM_KV_ATTN, FP8_KV, FP8_MM_V2, FP8_V2, FP8_MM_KV_ATTN_V2, NF4, FP4, BF16, FP4_BLOCKSCALED_MM, FP4_MX_MOE Job progress.
The resource name of the batch inference job that this job continues from. Used for lineage tracking to understand job continuation chains.
The desired geographic region where the batch inference job runs.
Set multi_region to limit the job to a region group (US, EUROPE,
APAC, or GLOBAL). If unspecified, the job runs in any supported region.
The customer-requested wall-clock run window for the job: how long it may run before it is expired. This is the single public input that controls the job's lifetime. The server bounds it to [12h, 72h]; if unset it defaults to 24h. The resulting concrete deadline is surfaced as expire_time (= create_time + the bounded window) and the job is expired once that deadline passes. A duration (relative) is used rather than an absolute timestamp because the client does not know create_time at submit time. Customer-visible input.
Lifecycle milestone timestamps (validated / run-start / end) for the job.
True only while a job that has ALREADY started running is briefly
re-acquiring capacity after a mid-run preemption/stockout (i.e. it
regressed from RUNNING back to an internal PENDING/CREATING phase and is
waiting to resume). This is intentionally a transient sub-status annotation
on a job whose customer-facing state stays RUNNING — NOT a distinct
state value: the job is still running (progress is saved, it auto-resumes)
so introducing a new terminal-or-not enum value would force every state
consumer (SDK/CLI/internal maps/billing) to special-case "still running."
It drives the customer-facing "Briefly paused — waiting on capacity" card.
It must NOT be set during first-time provisioning before the job has ever
run, and is cleared once the job returns to RUNNING or reaches a terminal
state. So "state=RUNNING, waiting_on_capacity=true" means: running, momentarily
paused while it re-acquires capacity.