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How we rank & score

Layer 2.5 · head to head

Replicate vs Modal

Ship a feature in an afternoon, or own the deployment model.

ReplicateModal
Can you leaveSticky. Leaving means rewriting against a different interface, not changing a hostname.Sticky. Leaving means rewriting against a different interface, not changing a hostname.
CounterpartyLow. Models are containerised with an open packaging format, so the exit is unusually clean for this layer.Low financially; high in code. Modal's programming model is genuinely delightful and genuinely non-portable — that is the trade.
What it isYou never see a GPU. You send a request and pay per token or per second of execution.You never see a GPU. You send a request and pay per token or per second of execution.
How you reach itYou call an endpoint. There is no infrastructure to see, and no infrastructure to move.You supply code; scaling and idle time are the provider's problem.
AcceleratorsA100, H100, L40S, T4 behind hosted modelsH100, A100, L40S, T4, and others
RegionsUSUS, EU
Pricing modelPer second of prediction time, per hardware class.Per second of GPU time, scale to zero, no idle charge.
Getting startedAPI key.Self-serve, generous free tier historically.
CapacityManaged.Managed pool.
OwnershipPrivate.Private.

Replicate

For: Product teams shipping a model-backed feature who do not want to think about GPUs at all.

The catch: Cold starts on unpopular models are long. The convenience premium over renting the same GPU directly is large and worth calculating once.

Economics: The most expensive way to buy a GPU-second and often the cheapest way to ship a feature. Both are true; which one matters depends on your volume.

Modal

For: Python teams who want infrastructure to disappear and are happy writing to a framework to get it.

The catch: Your deployment becomes Modal-shaped. Migrating off is a rewrite, not a redeploy. Price that in on day one, not year two.

Economics: Per-second billing with no idle cost is the cheapest possible shape for bursty inference. It is the wrong shape for a job that runs continuously.

Neither table row is a price

Deliberately. Published on-demand rates at this layer move weekly, and essentially nobody signing a real contract pays them — every serious buyer pays less than every list figure either of these companies publishes. Quoting one here would date this page within a month.

The GPU rental price index carries dated, sourced figures instead, and the durable finding there is the spread: the identical H100 rents from roughly $1.38 to $12.29 an hour depending only on who you rent it from.

The layers underneath both

Whichever you pick is renting you chips in a building that needs power. In 2026 that is the constraint that binds: Microsoft has disclosed an Azure backlog it cannot fill for want of megawatts rather than accelerators, and the US interconnection queue exceeds 2,600 GW with roughly 80% of projects withdrawing before they energise.

Layer 2 — Silicon · Layer 1 — Energy · The interconnection queue

Verified 2026-09-09. We do not benchmark clusters and take no position paid for by either company. Where a provider here runs a referral programme it has not moved its placement — the comparison was written before any link was attached.

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