H100 80 GB · A100 80 GB · A100 40 GB

The accelerators — and what they will not do

Three cards built for one job: holding a model and doing arithmetic on it, faster than anything else here. They have stacked memory, error correction and the ability to pool with each other. They have no display output and no video encoder — not a slow one, none — and knowing that before you order is worth more than any benchmark on this page.

40 and 80 GB Stacked memory, ECC No video encoder

Two things people are surprised by

They cannot encode video. At all.

NVIDIA’s own encode and decode support matrix records zero NVENC engines on the A100 and zero on the H100. They decode — five engines on the A100, seven on the H100 — but there is no encoder on the board, so every frame these cards produce has to be encoded by the processor instead. If your pipeline has video coming out of it, this is the wrong shelf, and the L40S with its three AV1 encoders is the right one. That is one page across at /l40s.

These cards also have no display outputs. They are headless compute parts. Nothing that expects a framebuffer — a virtual desktop, a remote workstation, a game server — belongs on them.

The A100 is not obsolete, and the 40 GB card is not a mistake

The A100 is the previous generation, and it reads its weights at 1,555 GB/s with 40 GB and 1,935 GB/s with 80 GB. For a model that fits, that read rate is what decides how many tokens a second you get, and it remains far ahead of every non-stacked card in the catalogue. The 40 GB card holds a thirty-billion-parameter model at eight-bit precision comfortably, which is most of what people actually serve, at a fraction of what the H100 costs each month.

Buy the H100 when the model genuinely needs Hopper — the transformer engine, FP8, the newer tensor units — or when the run has to finish sooner rather than merely finish. Buy an A100 when the question is whether it fits and how fast it reads, which is the more common question.

The specifications, as published

Figures from NVIDIA’s own datasheets and the Tesla specification tables, cited in the source of this page. Where a figure could not be sourced against the exact part we fit, this page prints nothing rather than a guess.

H100 80GB

Architecture

Hopper

Card memory

80 GB HBM2e

Board power

350 W

Card interface

PCIe Gen 5 x16

Hardware video encoders

None. Decode only (7 engines)

Error-correcting memory

Yes

A100 80GB

Architecture

Ampere

Card memory

80 GB HBM2e

CUDA cores

6,912

Memory bandwidth

1,935 GB/s

Board power

300 W

Card interface

PCIe Gen 4 x16

Hardware video encoders

None. Decode only (5 engines)

Error-correcting memory

Yes

A100 40GB

Architecture

Ampere

Card memory

40 GB HBM2

CUDA cores

6,912

Memory bandwidth

1,555 GB/s

Board power

250 W

Card interface

PCIe Gen 4 x16

Hardware video encoders

None. Decode only (5 engines)

Error-correcting memory

Yes

The H100 shows no core count and no bandwidth above, and that is deliberate. Our part is recorded in the store under a core count belonging to the SXM module, which is a card that bolts to a baseboard rather than into a slot; the 80 GB HBM2e memory it also records belongs to the PCIe card, which is what actually goes into these machines. Rather than pick one and print it confidently, the page prints the memory both sources agree on and omits the rest. Ask us and we will tell you exactly which board is going in yours.

What they are good at

One job, done better than anything else on this site.

Reading weights quickly

Stacked memory is the difference between this shelf and every other. Once a model is resident, generation speed is governed by how fast the card can read its own weights, and these read one and a half to two times faster than the quickest non-stacked card we fit.

Pooling into one address space

These parts carry NVLink, so two of them in one machine can be made to behave as one larger pool rather than two separate ones. The workstation and consumer cards in the catalogue cannot do this at all. It is a build we quote rather than a checkout option.

Running for weeks unattended

Error correction throughout, and hardware built for continuous load rather than for bursts. For a training run measured in weeks with real money behind it, that is not a luxury feature.

Being yours alone

One tenant per physical machine and the card passed straight through — no MIG partition, no vGPU profile, no time-slicing scheduler and nobody else’s job on it. Elsewhere an “A100 instance” is frequently a slice of one.

The three of them side by side, and what sits above

From our own shelves. All of these are orderable today, in the same chassis, so the question is which is worth the difference.

Cheapest complete machine first. Every figure read from the order catalogue when this page was served.
CardCard memoryThe cardCheapest complete machine
A100 40GB40 GB HBM2$699$772.47
A100 80GB80 GB HBM2e$899$972.47
RTX PRO 6000 Blackwell 96GB96 GB GDDR7 ECC$1,299$1,382.67
H100 80GB80 GB HBM2e$1,599$1,682.67

The last row is there because it is the honest comparison and most listings hide it: the RTX PRO 6000 Blackwell holds 96 GB, more than any accelerator on this page. Read its memory and its money against the H100’s in the table above rather than taking our word for either. What it gives up is read rate and NVLink; what it gains is four video encoders and ray tracing. If your question is will it fit, read /rtx60 before you commit to this shelf.

Which machine they go in, and what link they get there

The A100 is a PCIe Gen 4 card and the H100 is Gen 5, while our platforms are Gen 3 and Gen 4. The H100 therefore never gets the full bus it was designed for on any machine we run, and this page says so rather than leaving you to find out.

Intel Xeon Silver / Gold

H100 80GB

Slot: PCIe 3.0, 48 lanes per socket. Card: PCIe Gen 5.

A quarter or less of the bus the card was designed for. Worth avoiding when the work crosses the slot every step, and irrelevant once the weights are resident.

AMD EPYC

H100 80GB

Slot: PCIe 4.0, 128 lanes per socket. Card: PCIe Gen 5.

About half the bus the card was designed for. That costs a training loop streaming batches off the host; it costs an inference server or a transcoder nothing, because the weights are already on the card.

Intel Xeon E5-2600 v3/v4

A100 80GB, A100 40GB

Slot: PCIe 3.0, 40 lanes per socket. Card: PCIe Gen 4.

About half the bus the card was designed for. That costs a training loop streaming batches off the host; it costs an inference server or a transcoder nothing, because the weights are already on the card.

Intel Xeon Silver / Gold

A100 80GB, A100 40GB

Slot: PCIe 3.0, 48 lanes per socket. Card: PCIe Gen 4.

About half the bus the card was designed for. That costs a training loop streaming batches off the host; it costs an inference server or a transcoder nothing, because the weights are already on the card.

AMD EPYC

A100 80GB, A100 40GB

Slot: PCIe 4.0, 128 lanes per socket. Card: PCIe Gen 4.

Full width. The slot is at least the generation the card was designed for, so nothing is left on the table.

Whether that costs you anything depends entirely on the shape of the work. An inference endpoint whose weights are resident barely touches the slot and will not notice. A training loop streaming a fresh batch from host memory on every step will notice on every step. If you are not sure which you are, tell us what the job is before you order — it decides the machine, not the card.

What actually fits in 80 GB

Weights only, rounded up. A row counts as fitting when it leaves a fifth of the card’s 80 GB free for the KV cache, the activations and the runtime — which is head-room, not luxury.
Model16-bit8-bit4-bit
7-8 billion parameters16 GB — fits8 GB — fits5 GB — fits
13-14 billion parameters28 GB — fits14 GB — fits8 GB — fits
30-34 billion parameters68 GB — does not fit34 GB — fits19 GB — fits
70 billion parameters140 GB — does not fit70 GB — does not fit38 GB — fits

The 40 GB A100 holds the same table one rung down: a thirty-to-thirty-four-billion-parameter model at eight-bit precision fits, the same model at sixteen-bit does not. A seventy-billion model at sixteen-bit does not fit any single card we sell — that is a two-card build, and the reason the NVLink line above matters.

What they cost, with the machines they go in

The card is one line on the invoice and the machine is another. Both halves below come from one reading of the order catalogue, so the price and the specification beside it always belong to each other.

Read from the order catalogue when this page was served. The card is a separate line; the machine does not get dearer because of what is plugged into it.
CardThe machine it goes inThe cardComplete, per month
A100 40GBIntel Xeon E5-2600 v3/v4
Intel Xeon E5-2620 v4 Octo Core 2.10 GHz · 32 GB DDR4 · 2 × SATA 500 GB (RAID 1) · 1 Gbps · PCIe 3.0
$699$772.47
Configure this build →
A100 40GBIntel Xeon Silver / Gold
Intel Xeon Silver 4110 8 Core 2.10 GHz · 16 GB DDR4 · 2 × SATA-SSD 240 GB (RAID 1) · 1 Gbps · PCIe 3.0
$699$782.67
Configure this build →
A100 40GBAMD EPYC
AMD EPYC 7413 24 CORE 2.65 GHz 128MB L3 CACHE · 32 GB DDR4 · 1 × SATA-SSD 240 GB · 1 Gbps · PCIe 4.0
$699$916.59
Configure this build →
A100 80GBIntel Xeon E5-2600 v3/v4
Intel Xeon E5-2620 v4 Octo Core 2.10 GHz · 32 GB DDR4 · 2 × SATA 500 GB (RAID 1) · 1 Gbps · PCIe 3.0
$899$972.47
Configure this build →
A100 80GBIntel Xeon Silver / Gold
Intel Xeon Silver 4110 8 Core 2.10 GHz · 16 GB DDR4 · 2 × SATA-SSD 240 GB (RAID 1) · 1 Gbps · PCIe 3.0
$899$982.67
Configure this build →
A100 80GBAMD EPYC
AMD EPYC 7413 24 CORE 2.65 GHz 128MB L3 CACHE · 32 GB DDR4 · 1 × SATA-SSD 240 GB · 1 Gbps · PCIe 4.0
$899$1,116.59
Configure this build →
H100 80GBIntel Xeon Silver / Gold
Intel Xeon Silver 4110 8 Core 2.10 GHz · 16 GB DDR4 · 2 × SATA-SSD 240 GB (RAID 1) · 1 Gbps · PCIe 3.0
$1,599$1,682.67
Configure this build →
H100 80GBAMD EPYC
AMD EPYC 7413 24 CORE 2.65 GHz 128MB L3 CACHE · 32 GB DDR4 · 1 × SATA-SSD 240 GB · 1 Gbps · PCIe 4.0
$1,599$1,816.59
Configure this build →

Bandwidth is unmetered in both directions with no egress charge, which on this shelf is usually the largest hidden cost elsewhere — a training run pulling a dataset in and pushing checkpoints out moves a great many bytes, and per-gigabyte egress is charged on every one of them. One IPv4 address is included, there is no contract and one month is the default term. For every other card we fit, priced the same way, read the whole catalogue, priced. For machines racked and ready today, /instant.

Questions people actually ask about these cards

Can I transcode video on an A100 or an H100?

Not in hardware. Neither card has an encoder — NVIDIA’s support matrix records zero NVENC engines on both — so encoding falls to the processor and runs at processor speed. They do decode, so a pipeline that reads video and produces something other than video is fine. If you need frames out, the L40S has three AV1 encoders and is a great deal cheaper: /l40s.

Is the card sliced into MIG instances?

Not by us. You get the whole physical card passed through to your own operating system, on a machine with nobody else on it. These parts support MIG, so you may partition your own card if you want to; that is your decision on your own machine, not something done to it before it reaches you. This is worth checking wherever else you shop — a great many “A100” offerings are one slice of one.

A100 40 GB or 80 GB?

Capacity first, then read rate. If the model and its context fit in forty gigabytes with a fifth left over, the smaller card is the better purchase and the ladder above shows the gap. The 80 GB card also reads faster — 1,935 GB/s against 1,555 — so if you are near the ceiling on either capacity or throughput, take the larger one.

Which driver and CUDA version do I get?

Whichever you install. The machine arrives with a clean operating system and root, and you pin the driver, the CUDA release and the framework build to whatever your code was tested against. Nothing upgrades underneath you. If you would rather the driver were installed before handover, say so on the order and name the version.

How soon can I have one?

These are the parts most likely to be bought in rather than fitted from stock, and you are told which before you pay rather than after. A current-generation accelerator on allocation is the longest lead time we quote. /instant lists machines racked and ready right now.