Cloud GPU Providers with Zero Egress Fees

What “zero egress fees” actually means when you rent cloud GPUs

Egress is the data that leaves a provider’s network — the bytes you download out of the cloud to your laptop, to another cloud, or to end users. Many infrastructure platforms meter this traffic and bill per gigabyte, while charging little or nothing for ingress (data flowing in). A “zero egress” or “$0 egress” GPU host promises that pulling your data back out costs nothing beyond the compute you already rented. On a GPU platform this is a meaningful distinction, because AI and rendering workloads are unusually data-heavy on the way out: model checkpoints, exported weights, rendered frames, batch inference results, and synthetic datasets all have to travel somewhere once the GPU finishes.

The reason egress is priced separately at all is that bandwidth to the public internet is a real upstream cost for providers. Platforms that advertise no egress fees are either absorbing that cost into the hourly GPU rate, operating in a network where transit is cheap, or restricting the included free transfer to traffic that stays within their own backbone. Reading which of those applies to each entry in the comparison above is the whole game.

Why egress matters for real GPU workflows

The hourly price of a GPU is only one line on the invoice. For data-intensive jobs, transfer can quietly become a second bill — and unlike compute, it is hard to predict in advance. Egress pricing bites hardest in these patterns:

• Training that exports large checkpoints — multi-billion-parameter models produce checkpoints measured in tens or hundreds of gigabytes. If you snapshot frequently and copy each one off-platform, metered egress can rival the GPU spend.
• High-throughput batch inference — generating embeddings, captions, or transformed media for millions of items means the output volume can dwarf the input. That output is egress the moment it leaves the provider.
• Rendering and video — finished frames and encoded video are large and almost always pulled back out to storage or delivery, making rendering one of the most egress-sensitive GPU workloads.
• Multi-cloud and hybrid pipelines — moving a dataset or model between a GPU host and a separate object store, vector database, or serving tier crosses a network boundary every time, and each crossing can be metered.
• Serving models to real users — if the GPU box itself answers API requests, every response token or image streamed to a client is egress.

Zero egress removes the part of the bill that scales with how much you actually use the results of your compute. For experimentation it barely registers; for production pipelines that ship gigabytes per hour, it can be the difference between two providers whose hourly GPU rates looked identical.

The fine print behind “no egress”

Not every “free egress” claim covers the same thing, and the asterisks are where buyers get surprised. When comparing the entries above, check exactly which of these a provider means:

• Truly unmetered public egress — any download to the open internet is free, with no per-GB charge at all. This is the strongest form and the one most useful for production serving.
• Free internal egress only — transfer is free as long as it stays inside the provider’s own region or backbone, but leaving to the public internet or another cloud is still billed. Useful only if your storage and compute live with the same vendor.
• A generous free tier, then metered — a fixed number of free gigabytes or terabytes per month, after which normal egress rates apply. Fine for small jobs, a trap for high-volume ones.
• Bandwidth-capped “free” — no per-GB charge, but the port speed is throttled, so large transfers are slow rather than expensive. You pay in wall-clock time instead of dollars.
• Egress free but storage egress separate — pulling from attached block storage may be free while pulling from a separate object store is not. The boundary is what gets billed.

There is a genuine trade-off to weigh. A provider that bundles free egress may carry a slightly higher hourly GPU rate, because that bandwidth cost has to live somewhere. For an egress-light workload — long training runs that keep checkpoints in place, or interactive notebook work — paying a lower hourly rate with metered egress you never trigger can be cheaper overall. The right choice depends entirely on your output-to-compute ratio.

What to check before you commit

• Whether free egress applies to public internet traffic or only intra-provider transfer.
• Any monthly cap on the free allowance and the per-GB rate once you exceed it.
• The port/bandwidth limit, since “free but slow” still costs you GPU-hours while data drains.
• Whether storage retrieval (object store reads, snapshot exports) is counted as egress separately from network egress.
• How the policy interacts with spot or interruptible instances — you may need to evacuate data quickly when a node is reclaimed, and metered egress on a deadline is painful.

Reading the comparison above for egress

Estimate your egress before you read the table: roughly how many gigabytes leave the platform per run, multiplied by how many runs per month. Pair that with the hourly GPU rate shown above. A host with zero egress and a marginally higher hourly price often wins for production serving, batch inference, and rendering, where output volume is high and predictable. For training-heavy, output-light work, weigh the lower hourly rate first and treat egress as a secondary factor. Because both bandwidth policies and prices change, use the live comparison above for the current per-hour rates and confirm each provider’s egress terms against the points listed here.

Frequently asked questions

Does “zero egress” mean all my data transfer is free?

Not always. It reliably means outbound traffic carries no per-gigabyte charge, but some providers limit that to traffic staying inside their own network, or include only a fixed monthly allowance before metering begins. Inbound transfer (ingress) is almost universally free everywhere, so the egress claim is the part worth verifying.

How much can egress fees realistically add to a GPU bill?

It depends entirely on output volume. A few experimental notebooks generate negligible egress, so the fee is a rounding error. A production pipeline that exports large checkpoints, renders video, or serves model responses to users can move terabytes a month, at which point metered egress can become a sizable fraction of the total — sometimes approaching the compute cost itself.

Should I always pick a zero-egress provider?

No. Free egress sometimes comes with a slightly higher hourly GPU rate. If your workload keeps data in place — long training runs, interactive development — you may pay less overall with a cheaper hourly rate and metered egress you rarely trigger. Match the policy to your output-to-compute ratio rather than treating zero egress as automatically better.

Is free egress ever throttled?

Yes. Some providers offer no per-gigabyte charge but cap port speed, so a large export is slow rather than costly. Since the GPU clock may keep running while data drains, “free but slow” still has a real cost in GPU-hours. Always check the bandwidth limit alongside the pricing.