Build a model alias sunset plan for AI API gateways

Model aliases are convenient until they become part of your production contract.

An alias such as latest, pro, fast, or default looks harmless in a demo. It lets the SDK call a route without forcing the application to know every provider model id. That is useful during early exploration. It becomes risky when a production workflow, an invoice review, or a support investigation has to answer one plain question: which model actually ran?

OpenAI-compatible gateways need a clean way to retire aliases. A good sunset plan keeps old integrations working for a short period, gives new requests an exact model id, records the pricing version that admitted the call, and leaves enough evidence for engineering, support, and procurement to review the change later.

AIWave is built for teams that want one OpenAI-compatible route to Chinese model families such as DeepSeek, GLM, Kimi, Qwen, ERNIE, MiniMAX, Doubao, StepFun, and MiMo. That routing surface is useful when the client should stay stable while the route policy changes. It also means alias changes need a written migration path.

This article gives one pattern for sunsetting model aliases without hiding behavior from the teams that depend on the gateway.

Start with the failure mode

The dangerous alias change is silent.

A request used deepseek-fast yesterday. Today the same alias resolves to another route, or to a new provider variant, or to a model with a different cache bucket. The application still returns text, so the incident does not look like an outage. The problem shows up later when cost, latency, answer shape, or tool behavior no longer matches the test evidence.

For Tier 1 and Tier 2 teams, that is a bad procurement story. A platform owner cannot ask finance to trust a gateway that changes effective routes without a dated record. A support engineer cannot debug a failed agent run if the logs only show the alias. A security reviewer cannot approve a migration if the provider boundary is described by a nickname.

The alias may stay in the request. The resolved model must never be vague.

Check the current pricing source

Before writing this article, I checked AIWave's public pricing endpoint on 2026-09-02 at 13:11 UTC. The endpoint returned success=true, pricing_version=a42d372ccf0b5dd13ecf71203521f9d2, 63 route records, and auto_groups=["default"]. The response also exposed group ratios of default=3 and vip=1.

The same live response included these route fields:

Route	model_ratio	completion_ratio	cache_ratio	Enabled groups
deepseek-v4-flash	0.319	3	0.0318	default, vip, svip
deepseek-v4-pro	0.957	3	0.0333	default, vip, svip
glm-5.1	1.05	3.142857	0.32381	default, vip, svip
kimi-k3	2.25	5	0.2	default, vip, svip

Those are gateway catalog fields, not a claim that every request will produce the same bill. Store the source URL, checked time, pricing version, effective group, requested alias, resolved route, and token buckets beside each migration test.

If an alias sunset plan cannot say which pricing version applied, the plan is not ready.

Define three names for every request

Alias migrations go wrong when one field does too much work.

Use three separate names:

The alias names in this section are design examples, not current public AIWave model ids. Use exact catalog ids such as deepseek-v4-flash, deepseek-v4-pro, glm-5.1, and kimi-k3 when you configure production clients.

Field	Example	Purpose
requested_model	deepseek-fast	What the client sent
resolved_model	deepseek-v4-flash	What the gateway executed
policy_version	alias-policy-2026-09-02	Which alias map made the decision

This separation protects old clients while giving reviewers a real route name. It also lets you phase out the alias without losing the historical request shape.

{
  "request_id": "req_01J_alias_example",
  "requested_model": "deepseek-fast",
  "resolved_model": "deepseek-v4-flash",
  "policy_version": "alias-policy-2026-09-02",
  "pricing_version": "a42d372ccf0b5dd13ecf71203521f9d2",
  "effective_group": "default",
  "status": "success"
}

Do not store raw prompts or secrets in this record. The alias evidence needs route, policy, pricing, token, and status fields. It does not need user content.

Inventory aliases before you change them

The first step is a read-only inventory. Count aliases by customer segment, SDK version, endpoint, and job type. A web chat request and a nightly agent run should not share the same migration risk score.

Use a query like this against your request ledger:

select
  requested_model,
  resolved_model,
  count(*) as calls,
  count(distinct account_id_hash) as accounts,
  min(created_at) as first_seen,
  max(created_at) as last_seen
from gateway_request_log
where created_at >= datetime('now', '-30 days')
group by requested_model, resolved_model
order by calls desc;

The result tells you which aliases are still live and which exact routes they produce. If one alias already maps to multiple resolved models, stop and document why. The answer may be A/B testing, fallback policy, account groups, or a bug. Do not announce the sunset until you can explain that spread.

Put aliases into states

A sunset plan needs a state machine. Dates alone are not enough because some teams will miss a date and some clients will lag.

Use states that the gateway can enforce:

State	Gateway behavior	User-facing behavior
active	Alias resolves normally	No warning
deprecated	Alias resolves, warning attached	Response header or dashboard warning
pinned	Alias resolves only to its old route	No silent upgrade
blocked_for_new_keys	Existing keys work, new keys must use exact ids	Console rejects new alias use
removed	Alias returns a clear error	Error includes replacement ids

The pinned state matters. It gives existing production traffic stability while new integrations move to exact ids. Without that state, teams often choose between a risky silent change and a hard break.

Make warnings machine-readable

A warning in a blog post or changelog is not enough. Put the warning where SDKs, dashboards, and CI checks can read it.

For OpenAI-compatible responses, the body shape may be constrained by the client library. Headers are a practical place for migration hints:

X-Gateway-Requested-Model: deepseek-fast
X-Gateway-Resolved-Model: deepseek-v4-flash
X-Gateway-Alias-State: deprecated
X-Gateway-Alias-Replacement: deepseek-v4-flash
X-Gateway-Policy-Version: alias-policy-2026-09-02
X-Gateway-Pricing-Version: a42d372ccf0b5dd13ecf71203521f9d2

If your gateway does not expose custom headers, write the same fields into an account-visible usage ledger. The important part is that the migration evidence is attached to real requests, not only to release notes.

Add a client-side guard

Platform teams can catch alias use before requests reach production. Keep the check boring and explicit.

from dataclasses import dataclass


@dataclass(frozen=True)
class ModelPolicy:
    allowed_exact_models: set[str]
    deprecated_aliases: dict[str, str]
    allow_aliases_in_dev: bool = True


def validate_model_for_environment(
    *,
    requested_model: str,
    environment: str,
    policy: ModelPolicy,
) -> str:
    if requested_model in policy.allowed_exact_models:
        return requested_model

    replacement = policy.deprecated_aliases.get(requested_model)
    if replacement and environment in {"local", "staging"} and policy.allow_aliases_in_dev:
        return replacement

    if replacement:
        raise ValueError(
            f"model alias {requested_model!r} is deprecated; "
            f"use exact model id {replacement!r}"
        )

    raise ValueError(f"model {requested_model!r} is not allowed by policy")


policy = ModelPolicy(
    allowed_exact_models={"deepseek-v4-flash", "deepseek-v4-pro", "glm-5.1", "kimi-k3"},
    deprecated_aliases={"deepseek-fast": "deepseek-v4-flash"},
)

model = validate_model_for_environment(
    requested_model="deepseek-fast",
    environment="production",
    policy=policy,
)

This guard does not need to know the provider's full catalog. It only needs to protect the application's supported set.

Tie the migration to pricing evidence

Aliases are not only a routing problem. They are also a cost explanation problem.

When the alias policy changes, capture a small evidence packet:

Evidence	Why it belongs
Alias policy version	Explains the resolution rule
Pricing source URL	Lets reviewers recheck the catalog
Pricing checked time	Prevents stale screenshots from becoming facts
Pricing version	Links the request to the gateway snapshot
Effective account group	Explains group-specific calculation behavior
Token buckets	Separates input, cached input, and output
Replacement model ids	Gives developers exact strings to use

A request may still be billed by units, credits, quota, or invoice rows, depending on the gateway. The public article should not invent a blended public price from internal ratios. Keep the evidence in the same unit the gateway reports.

Test old and new clients together

Run the alias migration as a compatibility test, not as a copy edit.

Build a fixture that sends the same redacted prompt through both the old alias and the replacement id in a staging gateway that still accepts the alias. Record resolved model, pricing version, usage fields, response status, and stop reason.

from openai import OpenAI

client = OpenAI(
    base_url="https://gateway.example/v1",
    api_key="YOUR_API_KEY_HERE",
)


def probe(model: str) -> dict:
    response = client.chat.completions.create(
        model=model,
        messages=[
            {
                "role": "user",
                "content": "Return a JSON checklist for a redacted API migration test.",
            }
        ],
        temperature=0,
        max_tokens=500,
    )

    return {
        "requested_model": model,
        "response_model": response.model,
        "usage": response.usage.model_dump() if response.usage else None,
    }


for model in ["deepseek-fast", "deepseek-v4-flash"]:
    print(probe(model))

Use synthetic or redacted prompts for this test. Do not use customer transcripts to prove that an alias resolves.

Publish a migration window

Give developers a narrow, dated path:

Date	State	Action
Day 0	deprecated	Warnings begin in ledger and response metadata
Day 14	blocked_for_new_keys	New keys must use exact model ids
Day 30	pinned	Existing alias stays on its old resolved route
Day 60	removed	Alias returns a clear replacement error

The exact dates should match your support load and customer contracts. The structure matters more than the length. New traffic moves first. Existing traffic gets a stable route while owners update code.

Write the removal error for developers

A removal error should tell the developer what to do next. It should not force them to open a ticket just to find the replacement id.

{
  "error": {
    "type": "model_alias_removed",
    "message": "The model alias 'deepseek-fast' has been removed. Use 'deepseek-v4-flash' or another exact model id from the catalog.",
    "requested_model": "deepseek-fast",
    "replacement_models": ["deepseek-v4-flash"],
    "policy_version": "alias-policy-2026-09-02",
    "docs_url": "https://aiwave.live/docs/models"
  }
}

This is more useful than a generic unknown-model error. It tells the developer the alias used to exist and names the supported path forward.

What procurement should see

Procurement does not need every request body. It needs proof that the route did not change behind the team's back.

Give them a short migration report:

Field	Example
Alias retired	deepseek-fast
Replacement	deepseek-v4-flash
First warning date	2026-09-02
New-key block date	2026-09-16
Removal target	2026-11-01
Pricing source	https://aiwave.live/api/pricing
Pricing checked at	2026-09-02T13:11:09Z
Pricing version	a42d372ccf0b5dd13ecf71203521f9d2

That report turns the migration from a vague platform change into an auditable event.

Operational checks

Run these checks daily during the migration window:

Check	Failure signal
Alias used by new keys	The console or API allowed new deprecated usage
Missing resolved model	The ledger cannot prove what ran
Missing policy version	Support cannot reproduce the alias map
Missing pricing version	Finance cannot tie usage to a dated catalog
Multiple replacements without policy	The alias is doing hidden routing work
Production alias count not falling	Owners may not have seen the warning
Secret pattern in migration notes	A draft or log contains key-like material

The last row belongs in every content and support workflow. Migration examples can show placeholders, but they should never publish real keys, customer ids, private prompts, or internal payment details.

Source links to keep close

Keep these sources beside the migration ticket:

Source	Use
AIWave pricing	Public gateway pricing context
https://aiwave.live/api/pricing	Machine-readable pricing snapshot
AIWave models docs	Exact model ids and catalog context
AIWave trust page	Public trust and operational context
DeepSeek pricing	Provider bucket context for DeepSeek routes
QwenCloud pricing	Context, cache, and tool billing behavior

Recheck these sources before changing a rollout date. Model ids, cache fields, provider capabilities, and account groups can change after a successful test.

Final checklist

Before retiring a model alias, make sure the gateway can answer these questions:

1. Which clients still send the alias?
2. Which exact model does the alias resolve to?
3. Which policy version made that decision?
4. Which pricing version admitted the request?
5. Which account group applied?
6. Which replacement id should new integrations use?
7. When do warnings, new-key blocks, pinned routing, and removal begin?
8. What evidence can support and procurement inspect without seeing secrets?

Aliases make exploration easier. Exact resolved routes make production explainable. A sunset plan lets you keep both for long enough to migrate without turning yesterday's shortcut into tomorrow's mystery bill.