Should a customer call the model provider's API directly, or use the model through their cloud platform such as Amazon Bedrock or Google Vertex AI?

It depends mostly on the customer's cloud, procurement, security and data-residency rules, and on which features they need. A cloud platform keeps data, billing, identity and networking inside an account the customer already governs, which often makes security approval and purchasing much faster. The provider's own API usually gets new models and features first. Compare the two on the customer's actual requirements, and keep the code able to switch.

Why a cloud platform often wins in enterprises

• Procurement: spending goes through an existing cloud contract and commitments, no new vendor to approve.
• Data and security: the cloud provider is the data processor under terms the customer has already reviewed. AWS says Bedrock's model providers have no access to customer prompts and completions, and offers encryption, private networking (VPC, PrivateLink) and activity logging in CloudTrail.
• Identity and access: the customer's existing IAM roles, policies and audit.
• Region choice: models served from regions the customer already uses for data residency.

Why the provider's API can win

• Newest models and features often arrive there first; some features (particular tools, betas) may be missing or later on cloud platforms. Check the specific features you need on each platform.
• One integration across clouds for a multi-cloud customer.
• Simpler setup for smaller teams without a cloud governance process.

What to compare, concretely

1. The models and versions available on each platform, in the customer's regions.
2. The features the solution needs: tool use, structured outputs, caching, batch, citations, file handling.
3. Data terms: retention, training use, zero-retention options, who processes the data. Anthropic's data retention documentation, for example, notes that on Bedrock and Google Cloud the cloud provider is the data processor.
4. Quotas and rate limits, and how fast they can be raised.
5. Price, including discounts from existing commitments.
6. Support and incident processes.

Keep it portable

Put model calls behind one small interface, keep prompts and evaluations independent of the platform, and test on both if a switch is likely. Platform choices change with contracts.

A sample recommendation

"You're on AWS with a strict data-residency requirement and an existing commitment, so Bedrock in eu-central-1. We'll confirm the features we need are available there, and design so we can use the direct API for development or switch if a feature we need lags."

What interviewers look for: knowing that the decision is driven by the customer's governance and feature needs, and checking specifics rather than assuming.