LLM API versus GPU rental cost
Compare your API token bill with a rental budget. A lower compute bill does not prove the selected GPU can serve the model or meet your latency target.
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 lowest listed single-GPU firm offer meeting that capacity is Tesla V100 (unspecified) at DataCrunch, $0.194/hour.
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. 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. A 720-hour month is a comparison convention, not a calendar forecast.
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.
Updated rental rates 2026-10-02; API rates 2026-09-27. Use the model memory pages to shortlist hardware; configurations without a supported cache estimate cannot be labelled as fitting automatically.