LLM Self-Hosted vs API Calculator
Calculate when self-hosting an LLM pays off vs using cloud APIs. Compare costs for GPT-4o, Claude, Llama, and more.
LLM Cost Configuration
Workload
Your estimated monthly token usage (1M = 1,000,000)
API Model
Selecting a model fills in its blended $/MT
Self-Hosted Configuration
Heavier models need more VRAM and lower throughput
Affects host idle power draw
Affects host idle power draw
Adds ~$25/TB-month for fast NVMe
Cost Configuration
% of hardware + power + storage
Advanced Options
API batch processing discount
% of tokens saved via caching
GPU utilization → effective self-host $/token
Estimates only — GPU rental, power, and API pricing are approximate as of 2026. Effective self-hosted throughput is a rough heuristic. Verify with your provider and benchmark your own workload before committing.
Recommendation
Use Cloud API
Self-hosting won't pay off for the foreseeable future. Stick with APIs.
Cloud API Cost
Self-Hosted Cost
Break-Even
Never
1-Year (self-host)
$33,267.91
3-Year (self-host)
$92,410.85
1-Year Savings
+$33,229.66
API Effective $/M tokens
$3.19
After caching + batch discount
Self-Host Effective $/M tokens
$410.71
At your model throughput + utilization
GPU
NVIDIA A100 80GB
VRAM
80 GB
Power
400 W
GPU Count
1
Methodology
Break-even (months) = Setup cost ÷ (API monthly − Self-hosted monthly), where setup = 1.5× the first month.
Thresholds: break-even < 12 months → self-host; > 36 months → API; in between → hybrid.
API monthly = (tokens × (1 − caching%)) ÷ 1M × $/MT × (1 − batch%). Self-host monthly = hardware + power + storage + network + maintenance. Hardware scales up if the model's VRAM exceeds your provisioned GPU memory.
Frequently Asked Questions
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