Fastest production refresh of a continually updated model (hours)
The shortest interval, among vendors describing it in production, between a model update learned from live use and that update serving traffic. Derived metric cl_refresh_cadence_hours from rows citing each vendor's own description.
Reason through thisThe reading
One vendor's pipeline sets the reading; the refresh is a retrained adapter, not learning inside the model between sessions.
1 reading drawn from the derived metric cl_refresh_cadence_hours; 1 observation in the evidence.
Derived (cl_refresh_cadence_hours) from: Baseten blog and research posts. Baseten.
The numbers
| as of | reading | value | record |
|---|---|---|---|
| 2026-05-27 | — | 1.00 hours | reported |
Why it matters
How quickly deployment feeds back into the model is the return arrow's speed; a refresh measured in minutes is continual learning in all but name.
What cuts against it
Vendors describe their fastest path, not their typical one; an hour-long pipeline can still ship rarely, and a fast one can ship small, low-value updates.
How it is measured
- derived metric
cl_refresh_cadence_hours(formula in the semantic layer) - source Baseten blog and research posts · default tier 7 · Baseten; short quotation
- proxy product, behaviour · cadence quarterly · valve return arrow
Normal = an hour or more between learning from use and serving the update, the pace of a retrain-and-redeploy pipeline; fast = a quarter of an hour or less, updates flowing near-continuously. Every row is a vendor describing itself (tier 7), so the status caps at emerging.
Applied to metric:cl_refresh_cadence_hours.
Derived rows (1)
| as of | dims | value | inputs |
|---|---|---|---|
| 2026-05-27 | 1.00 hours | source1 |
Latest readings
- 2026-05-27 · 1.00 hoursas of 2026-05-27
Why this status, and its history
First reading: Trajectory's pipeline, as Baseten describes it, puts a freshly trained adapter behind a live endpoint in roughly an hour, on the edge of the normal band. The only source is the vendor's own description (tier 7), so the status caps at emerging.
- 2026-09-11unmeasured to emergingconf — → 30 · Claude (model)
First reading: Trajectory's pipeline, as Baseten describes it, puts a freshly trained adapter behind a live endpoint in roughly an hour, on the edge of the normal band. The only source is the vendor's own description (tier 7), so the status caps at emerging.
source1
Why this confidence
Rests on 1 observation from Baseten blog and research posts; best evidence tier 7, grade D; current.
Confidence is independent of status: 90–95 multiple strong independent sources; 70–89 good evidence, some ambiguity; 50–69 mixed or hard to operationalise; 0–49 limited or vague evidence.