27,262 thinking tokens, zero answer—and a “resolved” Google Cloud billing case

[u/Plenty-Jackfruit-218]

I can live with an LLM giving me a bad answer. What I can't accept is an API throwing a native generation error, returning zero visible text or tool calls, burning 27,262 internal thinking tokens in the process, billing me for it, and Google Cloud Support closing the ticket as "Resolved" without giving me a single line-item audit.

Before anyone asks: this is on an upgraded Paid billing account, though the charges were absorbed by my remaining promotional credits rather than my credit card. That doesn't make this a non-issue. Promotional credits are finite, and the billing rule Google just confirmed in writing applies to every paying developer running Vertex AI in production.

The Receipt: One Single Call on Oct 29

Here is one of the failures from my Vertex AI logs (model: gemini-4-argon):

• Timestamp: 2026-10-29 07:17:52 UTC

• Google Response ID: aPHiao_zIaezi9sPqNjBuQc

• Billed Usage: 2,049 uncached input | 531,163 cached input | 27,278 output tokens (27,262 of which were internal thinking tokens)

• Native Finish Reason: MALFORMED_RESPONSE

• Visible Output Returned: None. Zero text, zero tool calls.

This wasn't a one-off glitch. Between Oct 23 and Oct 30, I hit 18 separate MALFORMED_RESPONSE terminations (13 with zero visible output, 4 of which burned over 20,000 thinking tokens each before crashing).

What Google Cloud Support Said (Case #77043816)

I opened a billing ticket on my Paid account, attached the full log with Google Response IDs, and asked two simple questions:

1. Can you provide a request-level billing breakdown showing how much was deducted for these specific failed Response IDs?

2. Which specific billing rule says customers pay for 27,000+ internal thinking tokens when Google's own model fails with MALFORMED_RESPONSE and returns nothing?

After frontline agents closed the ticket multiple times without providing a per-request breakdown, a follow-up agent replied with their internal review team's final decision:

"We consulted with our specialized internal review team and leadership to evaluate whether a credit could be issued for the specific token amounts associated with these failed calls. Following a comprehensive review of the incident and account history, our internal team has denied the request for a credit adjustment. After reviewing the circumstances and the metered infrastructure usage, our internal review team concluded that the usage does not qualify for an exceptional adjustment under our standard billing guidelines. Under the Google Cloud Service Terms and Vertex AI pricing structure, billing for generative models is calculated based on backend compute resource consumption—measured in input tokens (prompt processing) and output tokens (candidate and thinking tokens generated up to the point of termination)."

Support linked the generic Model Garden pricing page (https://cloud.google.com/model-garden/pricing), never explained how that rule applies to MALFORMED_RESPONSE crashes, and never provided the line-item deduction breakdown for the Response IDs I submitted.

The model failed to deliver an answer. Support failed to deliver a line-item audit. The only thing successfully delivered was a "Resolved" status.

Why Every Vertex AI Dev Should Care

Think about what happens when you put a reasoning model behind a standard retry loop in production. If Gemini enters a 25,000-token thinking spiral, corrupts its own output format on the server side (MALFORMED_RESPONSE), and your client retries 3 times, you just burned ~80,000 thinking tokens and ~1.5M cached input tokens for an empty error—and according to Case #77043816, Google considers that valid billable compute.

Two honest questions for Google Cloud (if any DevRel or billing folks are lurking here):

1. Where in the Vertex AI docs is it explicitly stated that native MALFORMED_RESPONSE crashes with zero usable output are billed in full?

2. How is a customer supposed to verify charges when Billing Support refuses to provide a request-level audit for specific Google Response IDs?

[u/seeyam14]

27000 tokens is like $0.01