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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 โ†’ effective self-host $/token

Estimates only โ€” 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

$3.19/mo
$38.25 / year

Self-Hosted Cost

$2,464.29/mo
$3,696.43 setup ยท $33,267.91 / yr
Hardware$2,100.00
Power$90.26
Network + Storage$50.00
Maintenance$224.03

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 รท (API monthly โˆ’ Self-hosted monthly), where setup = 1.5ร— the first month.

Thresholds: break-even < 12 months โ†’ self-host; > 36 months โ†’ API; in between โ†’ hybrid.

API monthly = (tokens ร— (1 โˆ’ caching%)) รท 1M ร— $/MT ร— (1 โˆ’ 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