AIWave API / Aug 28, 2026

Default vs VIP Billing Groups for AIWave API Requests

Verify AIWave API request cost by recording effective group, live pricing rows, token usage, cache fields, and route owner before procurement review.

Keyword report: 2026-08-26Tier 1/2 developer focusSources checked Aug 28, 2026

This guide uses source checks from Aug 28, 2026. Provider and gateway prices can change; preserve the checked date with every forecast.

Why This Topic Matters Now

The Aug 27 topic queue calls out a practical buyer problem: Default x3 vs VIP x1, how to verify the group that billed your request. That topic is valuable because a developer can integrate an OpenAI-compatible endpoint successfully and still be confused by the final charge if the account's effective group is not visible in the estimate. Pricing pages show token rows. Billing groups explain how an account can experience those rows.

This article is for engineering and finance teams evaluating AIWave in Tier 1 and Tier 2 markets. It avoids any promise that an account action automatically changes billing group. Instead, it gives a verification pattern: read the live pricing feed, capture the group metadata available to the account, send a small placeholder-key request, store usage fields, and attach the route owner. That is the right level of evidence before a larger workload is approved.

Source Facts Checked Today

AIWave /api/pricing checked on Aug 28, 2026 returned 63 model records and group_ratio values of default 3 and vip 1. The feed also returned auto_groups with default and a pricing_version hash. Treat those values as publication-day evidence, not a permanent contract. If a finance worksheet uses a multiplier, store the checked timestamp and the account group used for the request sample.

The same live feed listed multiple enabled groups per model. For example, deepseek-v4-pro, deepseek-v4-flash, glm-5.1, kimi-k3, qwen3.6-flash, and step-3.5-flash-2603 were all enabled for default, vip, and svip in the data returned during this run. Enabled group and effective billing group are related fields, but they are not the same evidence. One says a group may access a route; the other says which multiplier applied.

DeepSeek rows checked through AIWave on Aug 28, 2026 provide a useful worked example. The live row translated deepseek-v4-pro to $1.914 input, $5.742 output, and $0.063736 cache-hit input per 1M tokens before applying any visible group multiplier. A billing review should preserve base row, token usage, cache usage, group multiplier, and final charge as separate columns so the team can reconcile the number later.

Planning Matrix

A source-dated planning matrix keeps the page useful for engineers and procurement reviewers. It turns a search query into an auditable route decision instead of a loose model preference.

EvidenceWhere it comes fromDecision it supports
pricing_versionAIWave /api/pricingWhich rate set was reviewed
base model rowAIWave pricing feedToken cost before group math
effective groupAccount or request evidenceMultiplier selection
enabled groupsModel metadataRoute availability
usage objectAPI response or logsActual token count
cache-hit fieldUsage and route ledgerInput split
route ownerInternal configWho approves changes

Implementation Pattern

The implementation pattern keeps credentials as placeholders, pins the AIWave base URL, records the model, and leaves room for route-specific controls. Production applications should move credentials into environment or secret storage.

from decimal import Decimal

AIWAVE_API_KEY = "YOUR_API_KEY_HERE"

def reconcile_request(row, usage, group_multiplier):
    input_cost = Decimal(usage["input_tokens"]) / Decimal(1_000_000) * Decimal(str(row["input_per_1m"]))
    output_cost = Decimal(usage["output_tokens"]) / Decimal(1_000_000) * Decimal(str(row["output_per_1m"]))
    cache_cost = Decimal(usage.get("cache_hit_tokens", 0)) / Decimal(1_000_000) * Decimal(str(row["cache_hit_per_1m"]))
    return round((input_cost + output_cost + cache_cost) * Decimal(str(group_multiplier)), 6)

deepseek_pro = {"input_per_1m": 1.914, "output_per_1m": 5.742, "cache_hit_per_1m": 0.063736}
sample_usage = {"input_tokens": 250_000, "output_tokens": 40_000, "cache_hit_tokens": 100_000}
print(reconcile_request(deepseek_pro, sample_usage, group_multiplier=1))

Separate Access From Billing

A model row can list several enabled groups. That tells a developer which account groups can call the route, but it does not prove which group priced one request. Put enabled groups and effective group in different columns. During a trial, ask the operator or account UI to confirm the effective group for the test identity. If the team cannot confirm it, mark the forecast as provisional and do not use it for procurement approval.

Store the Pricing Version

The live feed exposes pricing_version, which is a useful audit handle. Put that value into the worksheet beside the checked date. A future rate-card update can then be compared against the exact set used in the original decision. This is especially useful for teams that run a one-week proof of concept and then approve production traffic two weeks later. Without the version, a rate change can look like a math error.

Use a Redacted Probe Request

The first probe should use a small redacted prompt, placeholder credential handling, and a route that is already visible to the account. Record status, model, input tokens, output tokens, cache-hit tokens when available, latency, request timestamp, pricing_version, and effective group. Do not send customer content to prove a billing calculation. A small probe is enough to verify compatibility and reconcile the first line item.

Reconcile Before Forecasting

A cost forecast should be built only after at least one request has been reconciled. Start with the base model row, multiply by input and output tokens, apply cache-hit pricing separately, then apply the group multiplier that actually belongs to the account. This process may feel slower than copying a headline number, but it creates a worksheet that engineering, finance, and support can read together.

Group Changes Need Owners

If an account moves from one group to another, record the date, reason, owner, and expected effect on forecasts. Do not bury the change inside a pricing cell. A group move affects every model route used by that account, so it should be treated like a billing configuration event. Route owners should review output caps, retry ceilings, and monthly limits after the group changes because higher traffic may follow approval.

Procurement Review

Procurement should not approve a large AIWave workload from a screenshot alone. Ask for the live pricing row, pricing_version, checked date, effective group, route name, usage fields, and a reconciliation formula. Engineering should provide the exact test prompt category without exposing sensitive content. Support should be able to explain which row and group were used if the invoice differs from the forecast.

Final Checklist

Before using AIWave group math in a budget, verify access, verify effective group, store pricing_version, capture one redacted request, reconcile tokens, and assign a route owner. Do not promise that account funding or account age changes the group unless that specific account evidence exists. With those controls in place, default and vip group differences become auditable instead of surprising.

Source Links

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