The 2026 enterprise AI infrastructure vendor SLA conversation resolves on five dimensions (uptime commitment with the denominator named explicitly, latency commitment at P95 and P99 negotiated into the MSA addendum because public SLAs typically omit it, support response tier per severity level, credit calculation scope and cap, exclusions list scope including scheduled-maintenance window, content-policy actions, capacity constraints, partial-availability events, and third-party-source outages); the publicly disclosed headline numbers (AWS Bedrock 99.9% monthly with 10/25/100% credit tiers, Azure OpenAI Service inheriting Azure platform 99.9% with PTU separate availability, Google Vertex AI 99.5%-99.9% varying per-model and per-region, OpenAI Enterprise 99.9%-99.99% per-customer in MSA, Anthropic Enterprise commitments per-customer with no public uniform tier) understate the year-two operational reality because exclusions list scope and credit calculation scope vary materially across vendors; the buying-committee discipline is to populate the per-vendor matrix at short-list rather than discover the gaps at year-one operational experience or year-two renewal.

Anchored on (a) AWS Bedrock SLA at aws.amazon.com/bedrock/sla/ (99.9% monthly uptime, 10/25/100% credit tiers, regional scope); (b) Azure OpenAI Service SLA inherited from Azure platform at 99.9% with standard Azure credit tiers and PTU-specific commitments per learn.microsoft.com/en-us/azure/ai-services/openai/concepts/service-levels; (c) Google Vertex AI SLA at cloud.google.com/vertex-ai/sla with varying per-model per-region commitments; (d) OpenAI Status page at status.openai.com for historical record and OpenAI Enterprise documented MSA-addendum SLA targets (99.9%-99.99%); (e) Anthropic Status page at status.anthropic.com plus Enterprise-tier per-customer SLA observations from 2025-2026 procurement-team interactions. The exclusion-scope characterisation is from current public SLA documentation; specific exclusions (content-policy actions for Azure OpenAI, model-update windows for Vertex AI, scheduled-maintenance windows across the hyperscalers) are the rows most likely to surprise at renewal. 60-day review cadence (26 Jul 2026). Trigger conditions: (1) any major vendor publishing a new SLA tier or restructuring the credit mechanism materially shifts the matrix; (2) a published industry-wide outage event (2026 analog to Dec 2024 Bedrock content-filter outage or Jan 2025 Azure OpenAI degradation) provides precedent that changes exclusions-list framing; (3) NIST AI RMF or sector-specific cybersecurity rules requiring specific SLA commitments for regulated workloads warrants matrix update; (4) Anthropic and OpenAI Enterprise SLA documentation reaching same transparency level as hyperscaler tier changes the model-vendor comparison materially. Sibling AM-174 covers cost-side calculation; AM-167 covers contract-side instruments; /agentic-ai-sla-architecture/ covers the customer-side SLA architecture this piece is the supply-side companion to (the architecture piece has 48 Copilot citations and is the inbound referrer for this comparison).