GeForce RTX 4090 D · 24 GB GDDR6X

RTX 4090D — and why it is not an RTX 4090

The card we fit is the 4090 D, the export-compliance edition NVIDIA built for the Chinese market. It is not a rebadge and it is not a fake: it is a genuine AD102 card with fewer shaders and the same 24 GB of memory. If you came here searching for a 4090 server, this page exists to tell you the difference before you pay for it.

24 GB GDDR6X Two encoders, AV1 No ECC

What the D means

In December 2023 the United States Department of Commerce set an export threshold that the RTX 4090 exceeded. NVIDIA cut a version down to clear it and sold that version in China: the RTX 4090 D. It launched on 28 December 2023 and it has 14,592 CUDA cores against the full card’s 16,384 — about eleven per cent fewer shaders.

Everything else is the same card. Twenty-four gigabytes of GDDR6X on a 384-bit bus, the same 1,008 GB/s of memory bandwidth, the same 2.52 GHz boost clock, the same third-generation ray-tracing cores and fourth-generation tensor cores, the same two AV1 encoders. Nothing that depends on memory capacity or memory speed changes at all, which covers most of what a rented card is asked to do: the models that fit in 24 GB still fit, and the frames that stream still stream.

Where it does cost you is raw arithmetic throughput on work that saturates the shaders — a long render, a batch training run. Budget roughly a tenth less than a full 4090 and you will not be surprised. We say so here rather than printing “RTX 4090” on the page and letting you find out, which is what most listings do.

Across the 56 cards in the catalogue: RTX 4090D holds 24 GB, 13 cards we fit hold more, and 11 cost more per month. Read the whole ladder on the whole catalogue, priced.

The specification, as published

Ada Lovelace. Figures from NVIDIA’s own RTX 40 series documentation, cited in the source of this page.

RTX 4090D

Architecture

Ada Lovelace

Card memory

24 GB GDDR6X

CUDA cores

14,592

Memory bandwidth

1,008 GB/s

Board power

425 W

Card interface

PCIe Gen 4 x16

Hardware video encoders

2 NVENC, 1 NVDEC, AV1

Error-correcting memory

No

What it is good at, and what it is not

This is a consumer card in a rack. That is its whole advantage and its whole limitation, and both are worth saying plainly.

Good at: arithmetic per pound

GeForce silicon is the cheapest way to buy this much compute. There is no professional driver licence in the price and no datacentre margin, so for work where a wrong bit means a retry rather than a disaster — batch rendering, game servers, hobby training, inference you can re-run — it is very hard to beat.

Good at: video, unlike the accelerators

Two hardware encoders with AV1 and a decoder. A 4090 D will transcode all day. The A100 and H100 further up the catalogue cannot encode a single frame in hardware — they have no encoder at all — so for anything with video in it this card is not the compromise, it is the correct answer.

Bad at: anything that needs more than 24 GB

Twenty-four gigabytes is the wall, and it arrives sooner than people expect: a thirteen-billion-parameter model at eight-bit precision fits, the same model at sixteen-bit does not, and a seventy-billion model does not fit at any precision. The table below is exact about it.

Bad at: work that cannot tolerate a flipped bit

No error-correcting memory, and no certified professional driver. For a multi-week run with no checkpointing, or for a workload under a licence that requires a professional card, the answer is a card from the workstation shelf instead. Those are on the whole catalogue, priced.

What it replaced, and what replaces it

From our own shelves rather than from a vendor roadmap. All three of these are orderable today, in the same chassis, so the question is not which is newest but 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
RTX 309024 GB GDDR6X$239$309.93
RTX 4090D24 GB GDDR6X$299$372.47
RTX 509032 GB GDDR7$399$472.47

The RTX 3090 has the same 24 GB and is the older, slower, cheaper way to get it — if capacity is what you are buying and speed is not, read the RTX 30 series page before you spend the difference. The RTX 5090 steps up to 32 GB, and is a PCIe Gen 5 card on platforms that are Gen 3 and Gen 4, so read the section below before assuming newer is faster here.

Which machine it goes in, and what link it gets there

The 4090 D is a PCIe Gen 4 card. Two of our three platforms that take it are Gen 3, and one is Gen 4.

Intel Xeon E5-2600 v3/v4

RTX 4090D

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

RTX 4090D

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

RTX 4090D

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.

This is the fact behind support ticket #3347, where a customer moved to a newer card on an older platform and rendered slower than before. Once the scene or the weights are resident on the card the slot is idle and its generation stops mattering. It matters when the work crosses the slot on every step.

What actually fits in 24 GB

Weights only, rounded up. A row counts as fitting when it leaves a fifth of the card’s 24 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 — does not fit14 GB — fits8 GB — fits
30-34 billion parameters68 GB — does not fit34 GB — does not fit19 GB — fits
70 billion parameters140 GB — does not fit70 GB — does not fit38 GB — does not fit

The other ceiling is power: this card draws up to 425 W on its own, which is what makes more than one of them in a chassis a build we quote rather than a box you tick.

What it costs, with the machine it goes 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
RTX 4090DIntel 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
$299$372.47
Configure this build →
RTX 4090DIntel 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
$299$382.67
Configure this build →
RTX 4090DAMD 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
$299$516.59
Configure this build →

Bandwidth is unmetered in both directions with no egress charge, 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 this card

Will I get a full RTX 4090 if I ask?

Not from this page. What we fit is the 4090 D, and the page says so rather than printing “RTX 4090” and hoping. If your work genuinely needs the extra eleven per cent of shaders, tell us what it is and we will say whether we can source the part and what the lead time would be, rather than shipping the D and calling it a 4090.

Does the D affect CUDA, drivers or software compatibility?

No. It reports as an Ada Lovelace GeForce card, takes the ordinary GeForce driver, and every CUDA release, framework build and renderer that runs on a 4090 runs on it. The difference is a shader count, not an architecture.

Is the card shared with anyone else?

No. One tenant per physical machine, and the card is passed straight through to your own operating system — no hypervisor, no partition, no time-slicing. You install and pin your own driver and CUDA release, and nothing upgrades underneath you.

4090 D or RTX 3090, if I only care about the 24 GB?

Then the 3090 is very likely the better buy, and the ladder above shows the gap. The 4090 D is meaningfully faster and has AV1 encoding the 3090 does not; the 3090 has the same capacity for less money every month. If the model fits either way and the runs are not back to back, the older card wins on arithmetic.

How soon can I have one?

It depends on whether the card is already fitted, already on our shelf, or has to be bought in — and you are told which before you pay. /instant lists machines racked and ready right now.