Token Inflation: How Dishonest Providers Can Overcharge for Large Language Model Usage
Per-token billing is now the standard pricing model for commercial large language models (LLMs), so the honesty of reported token counts directly affects what users pay. We show that this kind of billing is hard to audit by design: providers hide the model, the tokenizer, and the execution to protect their IP, mitigate jailbreaks, and preserve user privacy, which means an auditor can only inspect proofs the provider supplies. The audit therefore reduces to a consistency check on the provider's own reports. We call this a trust paradox: every audit must trust some artifact, but current frameworks trust exactly the ones a provider has the strongest reason to manipulate. We study three recen...
| Authors | Shahinul Hoque, Jinghuai Zhang, Jinyuan Sun et al. |
|---|---|
| Primary category | cs.CR |
| Published | 28 May 2026 |
| Last updated at source | 28 May 2026 |
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