Unlimited Bandwidth and Unlimited Tokens — They're the Same Lie

While researching ISP pricing and oversubscription, I noticed something familiar. The same math that makes “unlimited 10 Gbps” work for broadband also makes “unlimited tokens” work for LLM inference. Both are selling potential capacity they know you can’t fully consume.

The ISP Model

An ISP sells 100 households “unlimited 10 Gbps” on a shared 10 Gbps pipe. They bet that at any given moment, only a fraction of those households are actively using bandwidth. The math holds because: - Most browsing uses < 5 Mbps - Peak hour lasts 2-3 hours - Even “heavy” use is bursty

The LLM Model

Now look at a GPT-5.6 inference API. They provision GPUs that can handle X tokens per second. They sell “unlimited tokens” or generous rate limits to Y customers where Y × typical_usage ≫ X.

The bet: - Most users send short queries - Peak hours are predictable (work hours in their region) - Even “heavy” users average far below their peak burst - Real-time inference is bursty (you think for 10 seconds, then send a prompt in 2 seconds)

Key Parallel

Concept	ISP World	LLM World
The pipe	GPON port / submarine cable	GPU cluster / inference server
The product	Unlimited 10 Gbps	Unlimited tokens
The bet	Most users are idle	Most users are thinking
Peak time	8 PM weekdays	US/EU business hours
Contention	24:1 (Simba)	Unknown, but similar
Hardware cap	Wi-Fi / Ethernet	Token context window
What you actually get	10 Gbps / 24 = 400 Mbps	X tokens / Y users

The Hardware Cap — You Can’t Consume It

Just as Wi-Fi caps your real bandwidth at ~270 Mbps regardless of plan, your reading speed caps your token consumption. Even with the fastest LLM:

A human reads at ~200-300 words per minute
A good LLM generates ~50-100 tokens per second
A 1,000-token response takes 10-20 seconds to generate
You then spend 30-60 seconds reading it

Your consumption rate is far below what the API can deliver. The provider knows this.

The Economic Incentive Is the Same

ISP: - Sell big plans people don’t need - Profit from users who never saturate - Raise prices only when contention breaks

LLM Provider: - Sell “unlimited” API tiers - Profit from users who hit rate limits rarely - Introduce tiered pricing when usage spikes

Both are selling headroom based on the statistical reality that most customers don’t use what they pay for.

The Difference

There is one difference: LLM inference can’t be as aggressively oversubscribed as bandwidth because inference is compute-bound not pipe-bound.

A GPON port can handle 24 homes because idle customers use near-zero bandwidth. LLM inference GPUs idle at near-zero utilization too — but the burst when a customer sends a prompt is much more intense relative to capacity. A single ChatGPT query can use hundreds of GPU-seconds.

So LLM providers are more cautious with oversubscription. But the principle is identical: they’re selling you access to a shared pool, not dedicated capacity.

What This Means

When you see “unlimited tokens” or “unlimited broadband,” mentally translate it to: “as many as we can give you before you notice the contention.”

For broadband, you don’t notice because your Wi-Fi caps you before the contention does.

For LLMs, you don’t notice because you read slower than the model generates.

In both cases, the bottleneck is you — not the provider.