Self-Hosting vs API: Break-Even Calculator for Open-Weight LLMs
Compare monthly API costs against self-hosting costs — GPU rental or owned hardware, amortized with electricity and overhead. Pick a model, a config, your volume, and see the exact break-even point.
| Volume | API /mo | Self-host /mo | Winner |
|---|---|---|---|
| 1M/day | $69 | $18,221 | API |
| 10M/day | $690 | $18,221 | API |
| 50M/day | $3,450 | $18,221 | API |
| 100M/day | $6,900 | $18,221 | API |
| 500M/day | $34,500 | $18,221 | Self-host |
When does self-hosting an LLM make sense?
Self-hosting an open-weight LLM trades the per-token pricing of a managed API for a roughly fixed monthly GPU cost. That trade makes sense once your sustained volume is high enough that the fixed cost beats the per-token bill. The exact crossover depends on three things: the API price per million tokens, the GPU config you need to run the model, and your utilization of that hardware.
For modern frontier open-weight models (GLM-5.1, DeepSeek V3, Llama 4 Maverick), you typically need 4–8 datacenter-class GPUs. That puts the monthly floor in the $2,000–$20,000 range depending on GPU class and rental vs own. API pricing for the same models is cheap enough that break-even often lands at tens to hundreds of millions of tokens per day. For smaller models (Gemma 4, Phi-4) that fit on a single consumer GPU, the floor is much lower and break-even arrives sooner.
What drives the break-even point?
Three levers: (1) the API's blended price per million tokens (70% input, 30% output is a reasonable default); (2) your self-host monthly cost, which is mostly GPU rental or amortized hardware plus electricity; and (3) overhead — engineer time, monitoring, egress. The tool exposes all three as inputs so you can test your real numbers.
Frequently asked questions
When does self-hosting an LLM actually save money?
Self-hosting starts beating API pricing once you have sustained high volume — roughly tens of millions of tokens per day for frontier open-weight models. Below that, API costs remain lower than renting dedicated GPUs. This calculator shows the exact break-even for your model and volume.
How much does it cost to self-host an LLM?
Monthly cost ranges from about $300 for a small model on consumer GPU rental to $20,000+ for a frontier model on an 8×H100 node. Cost depends on the GPU class, GPU count, mode (rent or own), and your overhead assumptions.
What GPU do I need to run Llama 4 Maverick?
Llama 4 Maverick has ~400B total parameters with 17B active. At FP8 quantization you need roughly 2×A100 80GB or better; at FP8 with full throughput, 8×H100 is the recommended config. The calculator auto-selects a sensible default per model.
Is renting GPUs or buying hardware cheaper?
For sustained 24/7 use over multiple years, buying hardware can be cheaper than renting — the calculator amortizes hardware over 4 years and includes electricity, PUE, and overhead. For burst or short-lived workloads, rental wins.
Can I self-host GPT-5 or Claude?
No. Proprietary models from OpenAI, Anthropic, Google, and xAI have no open weights. You can only use them via their APIs. Self-hosting applies to open-weight models like Llama, DeepSeek, Qwen, GLM, Kimi, Mistral, and Gemma.
Related tools
Know when it’s worth switching models
The model to choose, the cheaper alternative, and the release we would wait on.
Read a sample issueJoin 2,000+ readers.
One email each week. Unsubscribe anytime.