LLM API versus GPU rental cost
At 1 million input and 100,000 output tokens a month, Qwen2.5 7B Instruct Turbo through Together AI costs $0.33; the cheapest single GPU launched in 2022 or later with 24 GB or more that holds it, the 48 GB RTX 6000 Ada at Massed Compute ($0.79 an hour), costs $569 for a 720-hour month, so renting it pays only above about 1.9 billion tokens a month, if the card can serve that many. An older card that also holds the model, the 16 GB Tesla V100 at DataCrunch ($0.22 an hour), costs $158 and pays above about 528 million tokens.
Self-hosting the Qwen2.5 7B counterpart
The Qwen2.5 7B Instruct memory estimate is 4.9 GB at 4-bit weights, 4,096 context tokens, batch one and 20% headroom. The calculator opens on the cheapest single GPU launched in 2022 or later with 24 GB or more, the 48 GB RTX 6000 Ada at Massed Compute, $0.79 an hour. An older card holds it for less: the 16 GB Tesla V100 at DataCrunch, $0.22 an hour, also in the list.
This is a memory shortlist for the base model. Quantization and the API’s serving implementation may differ; output quality, speed and software compatibility are not assumed equal. Whether one card can serve your monthly volume depends on its tokens per second, which this calculator does not estimate. Other API models have no verified counterpart mapping in this calculator.
How the cost is calculated
API cost = (input tokens × input rate + output tokens × output rate) ÷ 1,000,000. Rental cost = per-GPU hourly rate × GPU count × rented hours. Break-even volume = rental cost ÷ the API's blended price per token at your input-to-output mix. A month is 720 hours, the convention used across the site, not a calendar forecast.
What it leaves out
The API estimate does not model cached input, batch discounts, long-context pricing separately billed reasoning tokens, or image/audio billing. The rental estimate excludes storage, egress, idle autoscaling, setup and operating time. It does not estimate tokens per second.
Rental rates checked 16 October 2026; API rates checked 16 October 2026. Use the model memory pages to shortlist hardware; configurations without a supported cache estimate cannot be labelled as fitting automatically.