No verified raw inference model selector. Product, experiment and SDK operation names are not interchangeable API IDs.
Access
Experimental SDK requiring Augment credentials; APIs may change. search returns retrieved code; searchAndAsk calls a configured LLM separately.
Regions
No complete model-specific region inventory established.
Endpoint pricing has not been collected. Check the provider for applicable rates.
Data & enterprise terms
Augment says it does not train on customers’ proprietary code. The RLDB report distinguishes internal data and opt-in, appropriately licensed contributions. Indexes and product/account data may persist; the general privacy policy does not establish a universal fixed retention period or zero-data-retention contract.
Caching can reuse earlier input processing. Availability, lifetime and billing depend on the endpoint. A cache hit still generates a new response.
01 / INITIAL INPUTProcess & retain
The system processes eligible input and retains reusable state.
02 / LATER REQUESTCheck available state
Reuse depends on matching input, session state and the cache policy.
03 / CACHE HITReuse & generate
Reusing state can reduce repeated work. Any charges follow the billing rules below.
Augment · Context Engine SDK
Not verified
No model-specific prompt-cache contract established.
How it works
Not collected
No model-specific prompt-cache contract established.
Minimum reusable input
Not collected
No model-specific prompt-cache contract established.
Lifetime & refresh
Not collected
No model-specific prompt-cache contract established.
How to enable it
Not collected
No model-specific prompt-cache contract established.
Usage fields
Not collected
No model-specific prompt-cache contract established.
Billing rules
Not collected
No model-specific prompt-cache contract established.
Limits & data boundaries
Not collected
No model-specific prompt-cache contract established.
No verified cache rate for this endpoint. An empty rate is not a zero charge.
Caching reviewed 15 Oct 2026
What the measurements say
No benchmark observations have been added for this model. We do not turn a vendor description into a performance score.
Latency and throughput depend on the host, request size, reasoning settings and load. There is no measured speed or global usage figure in this record.
The record behind the model
Why it is included
Composite managed retrieval system using internally trained context models. It is not a single embedding checkpoint and includes non-model indexing and retrieval operations.
