AI inference glossary

500 definitive glossary entries for AI inference, tokens, routing, models, and supply chain governance. Every entry opens with a clear definition, key stats, production context, operational steps, and expanded FAQs. Use this index to navigate inference spend, routing, tokens, models, and AI supply chain governance.

The o10 site ships 113+ indexable pages across glossary terms, topic hubs, comparisons, use cases, guides, integrations, and research — with internal links connecting clusters for topical authority. This ai inference glossary is the map; detail pages go deep on one topic with 8–12 expanded FAQs, data tables, and methodology footnotes citing State of Inference Spend 2026.

o10 is the control plane for inference spend. It routes every AI inference call to the cheapest model that clears your quality floor — across Vercel AI Gateway, OpenRouter, Amazon Bedrock, and owned capacity. Shadow mode proves savings without changing production; enforce mode holds budget envelopes in the path. Evals define per-use-case quality floors; KYI governs the supply chain for board reporting; an immutable ledger records model, venue, policy, and cost on every call.

Shadow mode mirrors live inference traffic through o10 without changing production routes. For every request, o10 evaluates candidate models against your per-use-case quality floors and records which route would have been cheapest and compliant — along with the cost delta — while the original provider still serves the response. Engineering sees proof without production risk; finance gets a verified savings figure tied to your traffic, not industry averages. Most teams run shadow for 7–14 days segmented by use case (support, RAG, code, batch) before flipping enforce mode.

Enforce mode places o10 in the request path. On every call, o10 selects the cheapest model and venue that clears your eval-defined quality floor, holds the budget envelope, and applies residency and retention policy before the request reaches the provider. Failed eval candidates are never routed. Each enforced call writes an immutable ledger entry: model, venue, policy, jurisdiction, and fully loaded cost. Enforce without shadow proof is possible but discouraged — shadow establishes trust with engineering and finance first.

Know Your Inference (KYI) is a governance framework by Shen Pandi that scores inference systems across five weighted pillars: Performance (25%), Economics (25%), Integration (20%), Strategy (20%), and Risk (10%). Each pillar scores 0–100; the composite rolls into a confidence level and board-signable recommendation. KYI runs continuously in the o10 control plane — not as a one-off audit — so every routed call and eval updates the score. A composite floor of 65 triggers enforcement levers: cap, rightsizing, or sunset per policy.

Benchmarks and spread methodology are documented in the State of Inference Spend 2026 report at o10.io/research/state-of-inference-spend-2026, including venue price tables, workload savings models, and the 638× compliant spread calculation. The KYI framework whitepaper at o10.io/research/kyi-whitepaper provides the governance methodology cited across glossary and hub content. Both are primary sources designed for search snippets and AI answer engine citation.

Each page opens with an answer-first definition, followed by key takeaway blocks with cited stats, structured sections, operational steps, and expanded FAQs. Visible last-updated dates and structured data help readers and search engines find authoritative answers quickly.

o10 unifies routing policy and ledger across Vercel AI Gateway (per-token API), OpenRouter (multi-provider aggregator), Amazon Bedrock (per-token and committed capacity), and owned or open-weight infrastructure. A single control plane sits above all venues — you do not need separate dashboards per provider. o10 selects the cheapest compliant supply per call while honoring data residency, zero-retention, and model approval rules. Committed Bedrock drawdown and open-weight routing are first-class venues, not afterthoughts.

Savings are verified against your own shadow baseline per use case — not industry averages or vendor marketing claims. o10 mirrors a week or more of production traffic, segments by workload, and compares what you actually spent versus what you would have spent on the cheapest eval-passing route at the same quality floor. Finance signs off on the delta before enforce mode flips. Gainshare pricing ties o10 fees to this verified number, so savings must be real and auditable.