Fixed-Price vs Pay-As-You-Go Inference: Breakeven Utilization

Last updated: November 2026

Key takeaways

• Breakeven utilization u = P / (A x r), where P is the fixed plan price, A the monthly counted-token allowance and r your blended pay-as-you-go price per counted token.
• Per Spheron's analysis, fixed plans win once traffic fills about 60 to 80% of the allowance. Below that, metering wins even at a higher per-token rate.
• Spheron weights counted tokens as output 4x, fresh input 1x and cached input at a discount, so your token mix changes r.
• Low, bursty or uncertain usage is better served by pay-as-you-go.
• Compute r from your own logs before committing to a term.

The framework below comes from Spheron's breakeven utilization article; the numeric examples marked illustrative are ours, because the source does not publish plan prices.

What is breakeven utilization?

It is the share of a fixed plan's allowance you must actually use before the plan costs less than paying per token. If a plan costs P per month and includes A counted tokens, and the same tokens metered would cost r each, then the plan equals pay-as-you-go when you use u = P / (A x r) of the allowance. At 100% utilization, reserved and metered cost roughly the same when u equals 1.0, as in the source's illustrative Azure rate of $260 per PTU per month.

How do you calculate breakeven utilization?

Say a Growth plan includes A = 20 billion counted tokens a month, and your blended metered price is r = $0.50 per 1M counted tokens. Metered, the full allowance would cost 20,000 x $0.50 = $10,000. All numbers here are illustrative.

| Fixed plan price P | Breakeven utilization u | Reading | |---|---|---| | $5,000 | 50% | Wins if you use over 10B tokens | | $6,000 | 60% | Wins if you use over 12B tokens | | $7,000 | 70% | Wins if you use over 14B tokens | | $8,000 | 80% | Wins if you use over 16B tokens | | $10,000 | 100% | Never cheaper than metered |

If your traffic is spiky and averages 40% of the allowance, even the $5,000 plan loses to metering.

How do counted tokens change the answer?

In the source's scheme, output counts 4x, fresh input 1x and cached input much less. A chat agent that resends 8,000 cached tokens plus 200 new input and 300 output tokens per call counts about 1,400 tokens before the cached share (200 + 300 x 4), far below its 8,500 raw tokens. Heavy caching therefore stretches the allowance, which pushes your utilization down relative to raw tokens and your breakeven further away. Count tokens the way the plan counts them, not the way your logs do.

How many tokens per month justify reserved capacity?

The source cites an independent estimate that reserved-capacity crossover sits near 150 to 200 million tokens a month at 60 to 80% utilization. Below that volume, metered billing is almost always simpler and cheaper. Related reading: self-hosting vs API breakeven applies the same logic to owning GPUs.

How should you choose between fixed and metered pricing?

1. 1Pull 90 days of token logs and compute r on the plan's counting rules.
2. 2Check whether your peak-to-average ratio is high. Spiky traffic wastes allowance.
3. 3Compare at least two providers on the LLM pricing hub before signing a term.
4. 4If you sell your own AI product, the same logic applies to your customers: our guide on flat vs usage-based AI pricing shows where flat plans break.