DataCrunch rebranded to Verda in 2026, and datacrunch.io now redirects to verda.com. Same company, same European AI cloud, new name. If you are comparing it to Runpod, the two are closer than most matchups in this category: both are self-serve, both publish every rate, both offer serverless and self-service clusters, and neither makes you talk to sales before you can deploy.
The differences that decide it are not mostly in the rate card, so start with what each one is built around.
What each one is built around
Verda is a European full-stack AI cloud with an in-house research lab. Its lineup starts at the data center tier and goes up to rack-scale GB300, its compliance story is unusually complete for a company this size, and it sells hardware-attested confidential computing as a product rather than a feature. It is built for teams whose workload already justifies a data center GPU.
Runpod is an AI developer cloud. It covers the same data center tier and then keeps going downward, into the cards that most AI work actually runs on. A pod is running in under 30 seconds, and teams move from Pods to Serverless to Clusters without changing vendors. It is built for the stretch between the first experiment and production, which is where most teams spend most of their time.
Both are self-serve. Both publish every rate. Neither makes you sign a contract to start. That makes this a closer comparison than most in this category, and it means the price table below is worth reading carefully rather than skimming for a winner. Neither one wins it outright.
Published on-demand rates
Runpod prices are Secure Cloud and pull live from our pricing data, so they are current as you read this. Verda prices are single-GPU on-demand, verified 13 August 2026 against verda.com/pricing. SXM against SXM throughout. Bundled vCPU and system RAM are shown because the hourly rate alone hides a real difference between the two.
Verda undercuts on current-generation data center cards from RTX PRO 6000 upward. Runpod undercuts from the A100 down.
Two of those margins are thinner than they look. The H100 SXM gap is four cents an hour. And the B300 row is not quite like-for-like: Runpod’s card carries 288GB of VRAM against Verda’s 268GB, so per gigabyte of memory Runpod is fractionally the cheaper of the two despite the higher hourly rate.
The bundled resources cut the other way
Runpod ships materially more system RAM on most shared cards: 283GB against 170GB on B200, 276GB against 182GB on H200, 188GB against 90GB on RTX PRO 6000, 167GB against 60GB on RTX 6000 Ada. Verda ships more vCPU on most of them, 44 against 24 on H200 and 30 against 20 on H100.
Which one you want depends on the job. Data loading, preprocessing and multi-stream video work are CPU-bound often enough that Verda’s core count is the better deal. Anything that stages large datasets in host memory, or runs CPU offload during training, gets more out of Runpod’s RAM. This is why comparing bare hourly rates misleads in both directions.
Where the lineups genuinely differ
Runpod goes much further down the stack. Ten Runpod cards are priced at or under the L40S at {{gpu:l40s}}/hr: RTX 5090 at {{gpu:rtx-5090}}, RTX 6000 Ada at {{gpu:rtx-6000-ada}}, L40 at {{gpu:l40}}, RTX 4090 at {{gpu:rtx-4090}}, RTX A6000 at {{gpu:rtx-a6000}}, RTX 3090 at {{gpu:rtx-3090}}, L4 at {{gpu:l4}}, A40 at {{gpu:a40}} and the RTX A5000 at {{gpu:rtx-a5000}}. Verda has two under a dollar: the RTX A6000 at $0.61 and a Tesla V100 at $0.17. The V100 is genuinely cheap and it is also a 2017 card with 16GB, which rules out most current work.
If your job fits on a 24GB card, Runpod has four to pick from and none costs more than the RTX 4090 at {{gpu:rtx-4090}}/hr: the 4090 itself, the 3090 at {{gpu:rtx-3090}}, the L4 at {{gpu:l4}} and the RTX A5000 at {{gpu:rtx-a5000}}. Verda has effectively none.
Verda is NVIDIA only. Runpod lists AMD MI300X with 192GB at $2.39/hr. If your stack is ROCm, that settles it.
Verda goes higher at the top. GB300 NVL72 at $8.62/hr per GPU, and rack-scale NVLink v5 from a single tray up to two or more racks. Runpod does not offer GB300.
Verda’s compliance posture is more built out. SOC 2 Type II, GDPR, EU data residency, and hardware-attested confidential computing on B200, B300 and RTX PRO 6000. The confidential variants carry roughly a 2% premium: B200 CC is $6.23 against $6.11, B300 CC $7.65 against $7.50, RTX PRO 6000 CC $1.93 against $1.89. That is a small price for attestation if a security review is what stands between you and a deployment.
Clusters
Both companies sell a product called Instant Clusters, which makes this section easy to misread. They are different products with the same name.
Verda’s version runs 16 to 64 GPUs with InfiniBand, self-service through the console, API, Terraform or SkyPilot, priced per GPU: GB300 $8.62, B300 $7.50, B200 $6.11, H200 $4.00.
Runpod Instant Clusters publish H200 SXM at $4.31/hr and A100 SXM at $1.79/hr per GPU. L40S, H100 SXM and B200 cluster capacity is contact-sales.
On the one card both publish at cluster scale, Verda is cheaper: $4.00 against $4.31 on H200. Verda also publishes more of its cluster lineup self-serve. If multi-node is your starting point rather than your eventual destination, price it on both.
Spot and interruptible capacity
Verda publishes a spot rate at exactly 50% of on-demand across every card, which is the most aggressive published discount in this comparison and the single strongest reason to look at them. H200 spot is $2.00/hr. B200 spot is $3.06.
That number does not belong in the table above, because spot capacity is interruptible and on-demand capacity is not. Comparing the two directly would flatter whichever side you put in the spot column. Runpod’s equivalent is Community Cloud, which is also lower-priced and lower-guarantee. Check Community rates directly on the pricing page before you compare, and price the interruption risk into both.
If your training job checkpoints cleanly and can survive being preempted, half price is half price and you should run the numbers properly.
Serverless
Both companies sell scale-to-zero GPU containers, so this is not a differentiator in either direction.
Verda publishes serverless rates above its on-demand ones: B300 $8.25/hr, B200 $6.72, H200 $4.40, H100 SXM $3.58, RTX PRO 6000 $2.08, L40S $1.51. Runpod Serverless is billed per second of active worker time. Pull the current Runpod Serverless rates alongside these before deciding, because the comparison turns on billing granularity and idle behavior rather than the headline number.
Storage
Verda charges $0.20 per GiB per month across NVMe, shared filesystem and container registry alike. Runpod charges $0.10 per GB per month for container disk, and network storage runs $0.07 per GB under 1TB and $0.05 above it.
The units differ, so convert before comparing. A GiB is 1.074 GB, which makes Verda’s rate about $0.186 per GB. Against Runpod’s network storage at $0.07 that is roughly 2.7 times more, and against container disk at $0.10 it is close to double. On a storage-heavy workload that gap compounds faster than any per-hour GPU difference in the table above.
Reserved pricing
Verda publishes its commitment ladder, which is unusual and useful: 2% off at one month, 3% at three, 4% at six, 8% at a year, 25% at two years.
Read it before committing. The first six months of commitment buy almost nothing, and the meaningful discount only arrives at two years. That is a long time to fix a GPU choice in a market where the hardware turns over annually and published rates move month to month on every provider in it.
How to choose
Three questions settle most of it.
Does your work need a data center GPU at all? If no, Runpod’s sub-$1 tier has no real equivalent on the other side, and that gap is far larger than any per-hour difference on an H100.
Are you living on H200 or Blackwell? If yes, Verda is cheaper on-demand on every one of those cards, and the H200 margin in particular is worth acting on.
Can your workload tolerate interruption? If yes, price Verda’s spot against Runpod’s Community Cloud rather than against either on-demand column, and let that comparison decide.
Below the A100 line, Runpod is the straightforward answer. Above it, Verda is cheaper per hour and Runpod bundles more RAM, so check which of those your job actually cares about.
FAQ
Is DataCrunch the same as Verda?
Yes. DataCrunch rebranded to Verda in 2026 and datacrunch.io redirects to verda.com. Same company, same infrastructure, same European AI cloud. Older comparisons and reviews using the DataCrunch name still describe the same service.
Is Verda cheaper than Runpod?
It depends on the card. Of the nine GPUs both companies publish, Verda is cheaper on five and Runpod on four. Verda is cheaper on B300, B200, H200, H100 SXM and RTX PRO 6000. Runpod is cheaper on A100 SXM, L40S, RTX 6000 Ada and RTX A6000, and has ten cards priced at or under {{gpu:l40s}}/hr against Verda’s two. The largest single gap is H200, where Verda is $4.00 against Runpod’s {{gpu:h200}}.
What does Verda cost?
On-demand as of 13 August 2026: GB300 $8.62/hr, B300 $7.50/hr, B200 $6.11/hr, H200 $4.00/hr, H100 SXM $3.25/hr, RTX PRO 6000 $1.89/hr, A100 SXM 80GB $1.79/hr, A100 SXM 40GB $1.29/hr, L40S $1.37/hr, RTX 6000 Ada $1.04/hr, RTX A6000 $0.61/hr, Tesla V100 $0.17/hr. Spot is 50% of on-demand on every card. Storage is $0.20 per GiB per month. Reserved discounts run from 2% at one month to 25% at two years.
Does Verda offer AMD GPUs?
No. Verda’s lineup is NVIDIA only. Runpod lists AMD MI300X with 192GB at $2.39/hr on Secure Cloud.
Which is better for a small fine-tune or a hobby project?
Runpod, by a wide margin. A 7B fine-tune or a Stable Diffusion workload runs on a 24GB card. Runpod has the RTX A5000 at {{gpu:rtx-a5000}}/hr, the 3090 at {{gpu:rtx-3090}} and the 4090 at {{gpu:rtx-4090}}. Verda’s only comparable option is a 2017-era V100 with 16GB.
Which is better for a large training run?
Verda is cheaper per hour on H200, B200 and B300, and cheaper again on spot if your job checkpoints cleanly. Runpod bundles more system RAM on those same cards, 276GB against 182GB on H200, which matters if you stage data in host memory or run CPU offload. Price both against your actual configuration rather than the headline rate.
Does Verda have serverless GPUs?
Yes. Verda sells auto-scaling containers with scale-to-zero, priced above its on-demand instances: H200 $4.40/hr, H100 SXM $3.58/hr, L40S $1.51/hr. Runpod Serverless bills per second of active worker time. Both scale to zero, so compare on billing granularity and idle behavior rather than on whether the feature exists.
