GPU Rent Hub3D rendering

GPU rendering server rental, by the week or the month.

GPU Rent Hub rents dedicated GPU rendering servers for Blender Cycles, Octane, Redshift and V-Ray at $390 a month for an RTX 4090 and $240 a month for a 48 GB A40, paid in Bitcoin, Ethereum, USDT, USDC, Monero, Solana or Litecoin with no identity verification.

Updated 2026-09-01
265RTX 4090 free across three sites
$0.49Per GPU-hour on an 8-way 4090 node
48 GBLargest scene a card with RT cores holds
20 TBOutbound included, per instance
01 Definition

What is a GPU rendering server?

The workload closest to a classic render farm, and the buying logic is not the AI buying logic.

A GPU rendering server is a dedicated machine whose graphics cards run the renderer, rented for a fixed term instead of billed per frame. The renderer holds the whole scene in the card's VRAM: geometry, the acceleration structure over it, every texture at the resolution it is sampled at, and the frame buffer. A scene cannot be split across two cards the way a language model is. Extra cards add frames per hour, not memory.

Why this differs from buying for AI

An inference stack shards a 70B model across four cards, so people shop for total VRAM across a node. A renderer has no equivalent: it either fits on the card or falls back to host memory across PCIe, and every renderer is slower on that path.

Scaling differs too. Training cards spend their time talking to each other, which is why interconnect dominates the price of a multi-GPU cluster rental. Render cards never talk, so a plain PCIe chassis is enough.

The three numbers that decide it

VRAM
Must hold the heaviest frame. Not negotiable.
RT cores
Used by OptiX in Cycles, and by Redshift and Octane. Generation matters more than count.
Card count
Frames per hour. Buy it against the deadline, not the scene.
Memory bandwidth matters less here than for inference. Texture fetch and BVH traversal are latency-bound more than bandwidth-bound, which is why a 696 GB/s A40 is a serviceable render card and a poor inference card.
02 The table

Which GPU should you rent for 3D rendering?

Nine cards in the fleet carry RT cores. Eight are worth a render queue, in the order we recommend them; the ninth is the L4, whose 58 RT cores sit behind 300 GB/s at 72 W.

GPUVRAMRT coresMonthlyPer GPU-hourWeeklyIn stock
RTX 4090Ada · 1.01 TB/s · start here24 GB128$390/mo$0.54$110265
RTX 5090Blackwell · 1.79 TB/s32 GB170$540/mo$0.75$155100
RTX A6000Ampere · ECC · workstation driver48 GB84$290/mo$0.40$8265
A40Ampere · ECC · passive48 GB84$240/mo$0.33$6837
RTX 6000 AdaAda · ECC · workstation driver48 GB142$460/mo$0.64$13026
L40SAda · ECC · datacenter driver48 GB142$520/mo$0.72$14874
RTX 3090Ampere · 936 GB/s24 GB82$230/mo$0.32$65186
RTX A5000Ampere · ECC · 230 W24 GB64$190/mo$0.26$5551
Per GPU-hour is the monthly price divided by the 720 hours in a term. RT core counts come from the card specification, not a benchmark: they tell you the width and generation of the ray tracing hardware, not how fast your scene resolves. Live stock across DFW-1, IAD-1 and PDX-1 is on the GPU catalogue.

Start with the RTX 4090. 24 GB, 128 third-generation RT cores, $390 a month or $110 a week, 265 free. Most product, motion graphics, character and arch-viz work fits inside 24 GB.

Move to the RTX 5090 when frames stop fitting. $540 buys 32 GB of GDDR7 at 1.79 TB/s and 170 fourth-generation RT cores, at 575 W that costs you nothing because power is in the price.

Go to 48 GB when 32 will not hold the scene. The A40 at $240 is the cheapest 48 GB we rent, $5 per gigabyte. The RTX A6000 at $290 is the same Ampere silicon with a workstation driver. Both have 84 RT cores: memory picks, not speed picks.

Pay $460 for the RTX 6000 Ada to get Ada ray tracing and 48 GB together: 142 RT cores, 960 GB/s, ECC, 300 W. The L40S is the same silicon at $520, worth it if the box also runs AI video generation.

03 Sizing

How much VRAM does a render node need?

The scene sets the floor. Everything else on the invoice is a choice; this is not.

Sizing a render card by scene weight. Under 12 GB: product shots, motion graphics, interiors with 2K textures. 12 to 24 GB: arch-viz exteriors with vegetation, character work with 4K texture sets, most freelance and small studio shots, so an RTX 4090. 24 to 32 GB: dense foliage, several 8K texture sets, moderate volumetrics, so an RTX 5090. 32 to 48 GB: VFX with render-time displacement, large volume caches, city-scale environments, so an A40, RTX A6000 or RTX 6000 Ada. Over 48 GB: cut the texture budget, or accept the renderer's out-of-core path and the speed it costs.

Measure rather than guess. Cycles prints peak memory at the end of a render, and Redshift and Octane report VRAM in use. Take the heaviest frame in the sequence, not the first, and add roughly 2 GB for driver, framebuffer and denoiser. Between two cards, take the larger. Memory and bandwidth for all fifteen models are in the GPU VRAM guide.

04 Scaling

Do more GPUs make rendering faster?

Nearly linearly, which is unusual. Each card renders its own tiles or frames and none of them wait.

RTX 4090 instanceMonthlyGPU-hours in termPer GPU-hour
1 card$390720$0.54
2 cards−5% multi-GPU$7411,440$0.51
4 cards−8% multi-GPU$1,4352,880$0.50
8× RTX 4090 nodesingle chassis$2,8105,760$0.49
8× RTX 4090 node, one week$7901,344$0.59
The 8-way node is one machine: 64 vCPU, 376 GB of RAM, 2 TB of local NVMe, a 100G port and a private VLAN included, in all three regions. Two and four card instances apply the multi-GPU discount schedule to the single-card price.

Near-linear is not linear. Every card loads the scene and builds its own acceleration structure, so a 90 second load is paid eight times, and denoising and file writing do not scale. For an animation, give each card whole frames rather than tiles of one frame.

Eight 24 GB cards are eight 24 GB cards. They are not one 192 GB card. If the scene does not fit on one, it does not fit on eight.
The A40, RTX A6000, RTX A5000 and RTX 3090 take an NVLink bridge in pairs at 112 GB/s. A few renderers pool memory across that bridge, most do not, and nothing pools across PCIe. Confirm it before planning a 96 GB scene on two 48 GB cards.
05 Worked example

Is renting a render node cheaper than a per-frame render farm?

An 8× RTX 4090 node is $2,810 a month: 5,760 GPU-hours, or $0.49 per GPU-hour. The rest is arithmetic.

Frame time on one RTX 4090Frames per node-hourFrames per monthCost per frame
4 minutesmotion graphics, product12086,400$0.03
8 minutes6043,200$0.07
12 minutestypical arch-viz animation4028,800$0.10
20 minutes2417,280$0.16
30 minutesheavy VFX shot1611,520$0.24
Assumes the queue is never empty and the frame time is measured on your own scene on one RTX 4090. This is division, not a benchmark: substitute your own frame time and the table rewrites itself.

Now the other side. Farms bill per frame, per node-minute or in their own points. Convert the quote into dollars per GPU-hour, then divide $2,810 by it.

Farm rate, per GPU-hour equivalentBreakeven GPU-hoursof the node's 5,760Cards busy, on average
$0.604,68381%6.5 of 8
$0.903,12254%4.3 of 8
$1.202,34241%3.3 of 8
$1.501,87333%2.6 of 8
Farm rates here are illustrative of the range once a per-frame or per-point price is converted to GPU-hours. They are not quotes from a named vendor, and a farm's upload, storage and priority tiers are not in them.

When you should use a render farm instead

For one short project a farm is probably cheaper, and you should hear that here rather than on an invoice. A 250 frame shot at 12 minutes a frame is 50 GPU-hours: about $45 on a farm at $0.90, against $2,810 here, because you rented the month.

The month wins when the queue is never empty: a studio rendering continuously, an animation in production for a quarter, a batch that runs every night. The same crossover for single cards is on monthly versus hourly GPU rental.

If your renderer is CPU-side, Corona, Arnold CPU or V-Ray CPU, we are the wrong shop. An RTX 4090 instance ships 8 vCPU and the 8-way node has 64, sized to feed graphics cards rather than to render on their own.
Do not rent an H100, H200 or B200 to render. They carry no RT cores, so OptiX has nothing to accelerate against, and the MI300X is not an OptiX device at all. They cost three to ten times the RTX 4090 and would be slower at this.
Two cases the arithmetic misses: assets you would rather not upload to a farm's storage, and a custom pipeline no farm submitter supports.
06 Hardware detail

Do you need ECC memory and workstation drivers to render?

For some pipelines yes, for most no. Which of our cards have what.

01

ECC memory

The A40, RTX A6000, RTX A5000, L40S and RTX 6000 Ada carry ECC GDDR6. Worth having for a 20 hour volume bake. In a six minute frame you just render again.

GeForce cards: 4090, 5090, 3090. No ECC.
02

Workstation drivers

The RTX A6000, RTX 6000 Ada and RTX A5000 run the professional driver branch, on a more conservative cadence. Take them if your pipeline is certified against it.

For Cycles, Redshift and Octane the branch does not change the image.
03

Renderer licences

Bring your own Octane, Redshift or V-Ray licence. They count per machine or per GPU, and a rented node counts like one you own.

No licence server sits in the image.
04

Power is included

A 575 W RTX 5090 and a 300 W A40 cost the same to run here, which is nothing. Pick on VRAM and RT cores, not wattage.

19 MW across the fleet, 99.97% uptime.
05

Stock and where it sits

RTX 4090: 120 in DFW-1, 84 in IAD-1, 61 in PDX-1. RTX A6000: 34, 20 and 11. A40: 22, 15 and none.

06

Cards you already own

Render cards age slowly and hold value, so colocating often beats renting over three years. Up to 350 W is $95 per GPU a month, 600 W is $135.

07 Working on it

How do you run Blender or Redshift on a rented render node?

Root over SSH, and a browser console for when SSH is the thing that broke.

1

Deploy the node

Ubuntu 24.04 with driver 570 and CUDA 12.8, or Debian 12 with the driver alone. Root in ninety seconds.

2

Push the project

rsync over unmetered inbound. 250 GB of NVMe on a 4090, 500 GB on the 48 GB cards, 2 TB on the node.

3

Render headless

blender -b with the OptiX device selected, or the Redshift and Octane command-line renderers.

4

Pull the frames back

20 TB of outbound included, about 166,000 multi-layer 4K EXRs at 120 MB. Beyond that, $4 per TB.

Several nodes, one project drive

A network volume at $14 per TB a month is NVMe-backed, triple-replicated in the region, attaches to several instances at once and survives the instance that made it. Mount it on every render node and keep it when the term ends. A private VLAN at $25 a month removes the public hop between nodes.

Weekly terms for a project burst

A week is the shortest term we sell: $110 for an RTX 4090, $130 for an RTX 6000 Ada, $790 for the 8-way node. About 20% more per GPU-hour than a month, and it converts to a monthly term without reprovisioning.

Payment is a balance funded in BTC, ETH, USDT, USDC, XMR, SOL or LTC, $20 minimum. An account is a username and a password: no KYC GPU hosting, crypto payment.

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08 Questions

GPU rendering server rental, asked plainly.

Which GPU is best for Blender rendering?
The RTX 4090 for most work: 24 GB, 128 RT cores for OptiX, $390 a month or $110 a week, 265 free across our three sites. Take the RTX 5090 at $540 when a frame needs 32 GB, or a 48 GB A40 at $240 when it needs more.
How much does a GPU render node cost per month?
One RTX 4090 is $390 a month, $0.54 per GPU-hour across a 720 hour term. An 8× RTX 4090 node is $2,810, or $0.49 per GPU-hour for 5,760 GPU-hours. Power, a 100G uplink, 20 TB of outbound and the local NVMe are inside that price.
Is renting a render server cheaper than a render farm?
Only above roughly half utilisation. Against a farm working out at $0.90 per GPU-hour, our $2,810 node breaks even at 3,122 GPU-hours a month, about 4.3 of its 8 cards busy. For a single 250 frame shot, 50 GPU-hours of work, the farm wins outright at around $45.
How much VRAM do I need for 3D rendering?
Enough for the heaviest frame, since a scene cannot be split across cards. Under 12 GB covers product and motion graphics work, 12 to 24 GB most arch-viz and character shots, 24 to 32 GB dense foliage and 8K textures, and 32 to 48 GB VFX with render-time displacement.
Do more GPUs make rendering faster?
Close to linearly, because each card renders its own tiles or frames and none of them wait on the others. The scene load and structure build are paid once per card, so short frames scale worse than long ones. Extra cards never add memory: eight 24 GB cards are not one 192 GB card.
Can I rent a GPU render node for one week?
Yes. Seven days is our shortest term: $110 for an RTX 4090, $68 for a 48 GB A40, $790 for an 8× RTX 4090 node. That is about 20% more per GPU-hour than a month, and it converts to a monthly term without reprovisioning.
Do I need ECC memory or workstation drivers to render?
Usually not. The A40, RTX A6000, RTX A5000, L40S and RTX 6000 Ada have ECC memory, and the A6000, A5000 and 6000 Ada run the workstation driver branch. Take those when a studio pipeline is certified against it. Otherwise a GeForce RTX 4090 renders the same image for less.
Can I rent a render server with Bitcoin and no ID?
Yes. An account is a username and a password, with no email, no phone number and no identity document. Fund a balance in BTC, ETH, USDT, USDC, XMR, SOL or LTC from $20 and deploy in DFW-1 Dallas, IAD-1 Ashburn or PDX-1 Hillsboro. Operating since 15 March 2021.

Deployment detail is in the documentation, terms and renewals in the general FAQ, and every card, price and stock number on the GPU catalogue.

Put the queue on hardware you keep for the month.

An RTX 4090 render node in about ninety seconds, from $390 a month or $110 a week. Deposit $20 in any of seven coins, no email, no ID.

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