01Start with a narrow common interface
A gateway should begin with the smallest interface shared by the providers it supports. In practice, that often means a request containing messages, a model identifier, generation parameters, and a streaming preference.
The gateway can normalize the basic request shape, but it should not pretend that every provider accepts the same parameters. A parameter that exists for one model may be ignored, rejected, or interpreted differently by another.
A practical design is to separate three layers:
- A common request and response format for ordinary application code.
- Capability metadata describing what a model actually supports.
- An escape hatch for provider-specific options when the common format is not enough.
Without the capability layer, developers discover incompatibilities at runtime. Without the escape hatch, the gateway eventually becomes the limiting interface.
02Model names are part of the contract
Provider model names change. Models are renamed, deprecated, or exposed through different endpoint names in different regions and products.
A gateway therefore needs a stable mapping between the name used by an application and the provider model that handles the request. That mapping should be inspectable. Silent changes make debugging difficult, especially when output quality or latency changes after a routing update.
It is also useful to distinguish between a logical model choice and a concrete provider deployment. An application may ask for a fast coding model, while the gateway resolves that request to a specific provider model according to the current configuration.
That separation makes routing possible, but it also means the resolved model should be available in logs and usage records.
03Streaming is not just a transport detail
Streaming responses look similar from the application’s point of view, but providers differ in event formats, metadata, termination signals, and error behavior.
A gateway needs to decide what it guarantees. For example:
- Does it emit only text deltas, or tool-call and reasoning events as well?
- How does it represent a provider error after partial output has already been sent?
- Can a request be retried after the first token has reached the client?
- How are usage totals reported when the provider sends them only at the end?
Retries are particularly delicate. Retrying a non-streaming request may be safe for some workloads. Retrying after a partial streamed response can produce duplicated or confusing output. The gateway should make this distinction explicit rather than applying one retry policy to every request.
04Errors should retain useful provider context
Normalizing every failure into 500 Internal Server Error is convenient but not helpful.
Applications need to distinguish authentication failures, invalid parameters, rate limits, unavailable providers, timeouts, and upstream server errors. A common error schema can expose a stable category while retaining the provider name, provider status, request identifier, and whether any output was delivered.
That information helps both automated fallback and human debugging.
Fallback also needs limits. If a request fails because the input is invalid, sending the same request to three other providers will not solve the problem. If a provider times out before producing output, a fallback may be reasonable. The decision should depend on the failure category and the request state.
05Capability differences cannot be routed away
A routing layer can choose another model, but it cannot manufacture a capability that the replacement model does not have.
Tool calling, structured output, image input, long context, system instructions, and token accounting all vary across providers. A gateway should expose these differences in its model metadata and documentation.
This matters for application design. A team may decide that a feature requires structured output and tool calling, while another workflow can use a cheaper text-only model. Treating both workflows as identical makes routing less predictable.
06Cost tracking needs request-level data
“Which model is cheapest?” is usually the wrong first question. The answer depends on input size, output size, caching, provider pricing, retries, and the work performed by the application around the model call.
A useful usage record should include at least:
- logical model requested;
- concrete provider model used;
- provider;
- input and output usage when available;
- request duration;
- retry count;
- final status;
- estimated cost and the pricing version used for that estimate.
Cost estimates should be labeled as estimates. Provider billing can include details that are not visible at request time.
07Observability should explain routing decisions
A gateway is another service in the request path, so it needs enough telemetry to answer basic questions:
- Why was this model selected?
- Which fallback, if any, was attempted?
- How long did routing and provider response each take?
- Was the request streamed?
- Did the provider return complete usage information?
Logs should avoid storing sensitive prompts and responses by default. Request identifiers, model metadata, timing, status categories, and usage summaries are often enough to debug routing behavior without copying application data into another system.
08Vendor portability has a boundary
A unified API can reduce integration work and make provider changes easier. It does not make providers interchangeable.
Prompt behavior, tool schemas, refusal behavior, tokenization, latency, output style, and quality can all change when a request moves between models. Any serious migration still needs application-level tests.
The realistic goal is to reduce the mechanical cost of trying or replacing a provider. The goal is not to promise identical output from every model.
09Where AGIRouter fits
AGIRouter is exploring this model-aggregation approach: access supported models from multiple providers through one platform and a unified API, while keeping model choice available to the developer.
The useful test is whether the platform makes comparison and switching easier without hiding the trade-offs described above. Model access, capability information, usage visibility, and honest documentation matter more than a claim that one model is best for every task.
For teams building with multiple models, which part becomes painful first: request normalization, streaming, error handling, cost tracking, or model evaluation?
AGIRouter: https://agirouter.org
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