AI API Throughput Planner & Cost Estimator
Estimate sustainable RPM, concurrency, and monthly cost before your AI API traffic hits provider limits.
Rate limit inputs
Inputs stay editable even when a published tier is available. Override them if your account or region differs from the public docs.
Uses RPM plus total TPM (input + output).
Workload shape
No published preset mapped for this model yet. Enter your account limits manually.
Sustainable RPM
—
RPM
Limiting factor
Custom / manual
—
Safe concurrency
—
In-flight requests at the current average latency
Monthly cost at steady load
$2376.00
GPT-5 Mini
- Requests / day
- 57,600
- Requests / month
- 1,728,000
- Approx batchable requests
- —
- Daily quota status
- —
Constraint breakdown
Each published limit is converted into a max sustainable RPM for the request shape above. The smallest value is the real ceiling.
| Constraint | Max steady RPM | Why |
|---|---|---|
| No published preset mapped for this model yet. Enter your account limits manually. | ||
Recommendations
- Verify your live limits in the provider dashboard before using this plan in production.
Source
How to Use This Tool
- Choose a model with a published preset, or switch to any tracked model and enter your own limits manually.
- Set your average input tokens, output tokens, latency, and target steady/peak RPM to match your production traffic.
- Review the sustainable RPM calculation to see whether request count, input tokens, output tokens, or daily quota becomes the bottleneck first.
- Adjust tiers or override the limit fields with your real account quotas if the provider dashboard differs from the public docs.
- Use the monthly cost estimate and recommendations to decide whether to queue, split traffic, shorten prompts, or move up a tier.
Why throughput planning matters before launch
Pricing calculators tell you what a workload costs. They do not tell you whether the workload will survive real traffic. The first production failure is often not cost, but a hard RPM or TPM ceiling that turns into 429s during a launch spike.
That is why this planner translates published provider limits into a request-shape-aware ceiling. A model might look cheap on a per-token basis while still being unusable for your prompt size, output length, or burst profile.
The right production plan usually combines three decisions: which model tier you can afford, how much prompt or output length you can trim, and what overflow strategy you need when traffic exceeds the primary model ceiling.
Last updated: April 2026
FAQ
What does this planner calculate?
It translates published or manually entered rate limits into a sustainable requests-per-minute ceiling for your specific request shape. It also estimates safe concurrency, daily/monthly volume, and model cost at the steady load you enter.
Why can the limiting factor be TPM instead of RPM?
Because long prompts or large outputs consume token budgets much faster than request budgets. A model can allow hundreds of requests per minute on paper, but still fail far earlier if each request is large.
Should I trust the published presets blindly?
No. Provider dashboards, enterprise contracts, preview access, and regional quotas can differ from public docs. Use the published tier as a baseline, then override the fields with your real account limits before launch.
Why are the limit inputs still editable when a published tier exists?
Because public docs are not the whole truth. Enterprise contracts, region-specific quotas, preview models, and billing tier changes can all change what your account actually gets. The preset is a baseline, not a lock.
Does this planner replace provider dashboards?
No. It is a decision tool. Use it to pressure-test a launch plan, compare models, and estimate cost at your target RPM. Before production, verify the live limits in OpenAI, Anthropic, or Google dashboards.