Match the output
Use the same model version, quality target, precision, video resolution and duration. A base model and an enhanced hosted pipeline are different products.
+ 03 / THE ECONOMICS
More intelligence.
Less overhead.↗
Your infrastructure should open possibilities, not consume your entire budget. Understand when dedicated capacity can change the economics of your workload.
THE 1/30 SCENARIO
$30,000 in monthly API spend. $1,000 in total monthly deployment costs. That is 1/30 of the spend—and an illustration of what to investigate, not a promised result.
MAKE THE NUMBERS YOURSYour workload.
Your workload.
A different equation.
Compare your API budget with the full monthly cost of an equivalent dedicated deployment.
$
$
$
YOUR COST SCENARIOUSD / MONTH
1/30*
of your current API spend
Potential annual savings$348,000
↘ 96.7%* Illustrative scenario, not a quote or measured benchmark. Adjust all inputs to your workload. No savings or equivalent performance are guaranteed.
Get a workload-specific assessmentMINIMAX H3 / FROM MEASUREMENT TO A MODEL
What would 1/30 require?
A measured 5.17-second video took 93.19 seconds of generation. At the provider’s reference output-only rate of $0.08/second for 768p, the output would cost about $0.4133.
Reaching 1/30 of that requires an effective generation-compute cost of about $0.532 per GPU-hour or less. Explore the assumptions below.
Provider pricing referenceModelled compute cost / clip$0.0129API / compute ratio31.9×
Assumption only: the hourly rate is not a verified Eigenvector price. Excludes operations, idle/cold-start overhead beyond the selected utilisation, storage, transfer, licences, failed jobs and margin. Local INT8 + Turbo8 quality is not assumed equivalent to the full hosted pipeline.
THE MATH, IN PLAIN SIGHT
Monthly deployment cost = compute + operations and licences. Annual difference = (API spend − deployment cost) × 12. The ratio is rounded for display. All amounts are in USD, exclude taxes and are user-controlled estimates.
COMPARE LIKE WITH LIKEThe details
The details
make the difference.
A useful cost comparison accounts for the entire workload—not just a GPU-hour.
Count the full cost
Include compute, idle capacity, orchestration, storage, transfer, licences, operations, support and any external model components.
Measure actual demand
Utilisation matters. Batch throughput and interactive latency describe different workloads; neither should be substituted for the other.
A note on MiniMax H3.
Private H3-Base inference and the official hosted 2K pipeline have different component boundaries. A fair comparison must specify which generation, preprocessing, reference-input and regeneration costs are included. No measured 1/30 H3 saving is asserted on this website.
See the model provider’s current pricing ↗One conversation.
A whole new trajectory.