Route Acceptance Tests for DeepSeek Pro and Flash Worker Splits (September 2026)

[chawkian]

When a team splits AI work between a fast route and a deeper reasoning route, the first failure mode is usually not the model call itself. The failure is that nobody can explain why a request landed on one worker instead of the other.

For an OpenAI-compatible SDK, I think a DeepSeek Pro / Flash split needs acceptance tests before it becomes production routing policy. The tests should not try to prove that one model is universally better. They should prove that the application can classify work, pin the route decision, preserve the pricing snapshot, and reject ambiguous jobs before they create confusing usage rows.

I checked AIWave's live pricing endpoint for this discussion on Sep 4, 2026. The /api/pricing response returned success=true, 63 route records, pricing version a42d372ccf0b5dd13ecf71203521f9d2, auto_groups=["default"], and group ratios of default=3 and vip=1. A few route fields from that same snapshot were:

Model	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	svip, default, vip
qwen3-max	0.7810988945590882	4	absent	vip, svip, default

Those are route catalog fields, not a complete invoice. The final debit still depends on account group, token buckets, cache treatment, output size, retries, and the pricing version accepted at request time. That is exactly why the worker split should have tests that produce evidence, not only configuration.

The acceptance suite I would want has five fixtures.

First, a "latency-sensitive summary" fixture should always resolve to Flash unless the caller explicitly asks for deeper reasoning. The test input can be small, deterministic, and low temperature. The expected evidence is not just served_model=deepseek-v4-flash; it should also include the route reason, pricing version, token ceiling, and account group used for estimation.

Second, a "multi-step planning" fixture should resolve to Pro when the job contract says the answer requires traceable decomposition. This is not about making the SDK judge semantic quality after the fact. It is about proving that the app's own workload label maps to the intended route before dispatch.

Third, a "large repeated prefix" fixture should verify cache assumptions. If the workload depends on stable system instructions and repeated context, the SDK should record whether the request was expected to benefit from cache accounting. A route split that ignores cache shape can look correct in unit tests and still mislead finance later.

Fourth, a "retry class" fixture should separate transport retries from model-executed retries. If the first attempt never reached the provider, the usage row should not be interpreted the same way as two executed attempts. The SDK can expose this without storing raw prompts or completions.

Fifth, an "ambiguous route" fixture should fail closed. If the caller sends a job without a workload class, output cap, or route policy, the SDK should return a typed preflight error instead of silently picking a worker.

One possible test record:

{
  "fixture": "latency_sensitive_summary",
  "requested_model": "deepseek-v4-flash",
  "served_model": "deepseek-v4-flash",
  "route_reason": "workload_class:short_summary",
  "pricing_version": "a42d372ccf0b5dd13ecf71203521f9d2",
  "effective_group": "vip",
  "max_output_tokens": 700,
  "retry_class": "not_retried"
}

For aiwave-sdk-python, I would keep this as an optional helper around the normal client:

probe = client.aiwave.routes.acceptance_probe(
    model="deepseek-v4-flash",
    workload_class="short_summary",
    max_output_tokens=700,
)

assert probe.ok
assert probe.served_model == "deepseek-v4-flash"

The boundary matters. The gateway owns live route identity, account group, pricing version, and final usage. The SDK owns the developer-facing contract: before a workload runs, can the application prove that its worker split will produce interpretable evidence?

Open question: should route acceptance probes be part of the SDK test helpers, or should they live as examples that teams copy into their own CI?