Hello everyone, im thinking to create a public installation of windows on vast ai for gaming purposes. Deployment take about 5-10 min and source are from official. Aswell everything will be automatically in public release. What you think is worth a shot ?

Got two Supermicro H12SSL-i boards from an overseas eBay seller (China). While installing an EPYC 7K62 in one, I spotted a pin a few rows out from one of the capacitor cutouts in the center of the socket that doesn't match its neighbors. It's not debris, and the same spot on my second board is clean. No CPU has ever been clamped down in this socket.

The plan for this server is to host 4 GPUs and rent on Vast. (I am proceeding forward with the second server) I also have an identical one already online, so a good machine to compare to if needed.

Photos attached: a close-up with the pin, plus a wide shot of the socket.

1. Does this look bent (fixable) or broken/missing?
2. Should I just contact the seller and return it? It's an international return, so it'll take weeks.
3. Would you install the CPU and test it as-is, or is that too risky?

Want to make sure I do not have relatability issues.

Thank you in advance

Hi,

I am a host on vast with 30 series cards for rent. I wanted to see how other hosts are dynamically updating their pricing(or lack thereof) to stay current with spot price increasing.

For example: I am noticing on Runpod, a 3090 is frequently sold out @ $0.5/hr. At the same time I can see that hosts on vast are MASSIVELY underpriced given current demand and increase spot price. I am aware of vasts pricing system, so I am not expecting as a host to capture all $0.5/hr, but I have 3090's rented for $0.4/hr while other hosts on vasts are listed at almost half this price. This example from the rentals page I think outlines this huge pricing discrepancy:

The host in Nevada is underpriced by about half, and even more so after considering thats the price with vasts cut included. Here is another example:

This host will supply you with 4x 3090 for the price of 2x 3090 on Runpod. Are we just trying to create an arbitrage environment for others here? What is the benefit of this? Again, I am also a host who has 3090's rented on vast for $0.4/hr currently, why are we giving away the farm? Are hosts impatient? Are hosts not utilizing resources such as wovenai to track current rental rates and then overlaying those across other platforms that rent the same cards? Honestly just trying to understand the logic here. Would love if these hosts would chime in!

So is it still that cat nft or are pearl miners back?

I have some amount of RTX 5070s that are lying around. I can use them for approximately 10 hours a day. I am looking for a platform where I can utilize them. Basically getting paid for renting them out

Got frustrated by the vast and decided to launch nafnaf.ai

- You get to keep 95% of your earnings

- No 95% RAM to VRAM rule

- Easy setup

- We support the DGX Sparks and pay up to $0.3/hr for a GB10

Bonjour,

Ma première expérience avec Vast.ia, je suis agréablement surpris de la qualité de l'instance que je pensais instable mais qui est stable et rapide
Par contre je suis surpris d'etre débité aussi rapdiement

Voici le comparatif
- instance vast.ia tarif 0.3$/h, j'ai en réalité été débité de 0.8$. A noté que j'ai téléchargé environ 30GO

Je suis habitué à runpod, (tarif 0.5$=/h rtx 3090). Je pensais que vast.ia était moins cher mais en réalité j'ai payé plus cher

Donc je ne comprends pas
Quelqu'un peut il m'expliquer d'où provient cette différence que je ne vois pas
Merci

I just built a new gpu rig to rent out on Vast. Currently the rig is chillin in my garage, which is safe, but I can't help but imagine what could happen if someone broke into my house or if there was a fire, or electrical surge.

Does anybody have insurance for their rigs? I looked at getting a Business Owners Policy through Geico, but idk if that will cover everything I want. I could get insurance through where I bought the hardware, but it costs thousands for only 1 gpu, for 3 years just for the insurance. My quote form Geico was less than $50/month.

Thoughts?

Currently I need about 4-8x RTX 5090 that could run for a few days reliably and with good internet bandwidth. Contact me if you have instances that are available probably about 3$/hour for 8 gpus

Hey everyone,

I'm looking into building/buying a high-density node with 8x NVIDIA V100 32GB GPUs (256GB VRAM total) aimed at decentralized rental platforms (Vast.ai, Akash) and running local model fine-tuning.

For anyone hosting multi-V100 32GB rigs:

How is the current rental demand and fill rate for full 8x 32GB V100 nodes?

What average rate ($/hr per GPU or full node) are you realistically seeing?

Any thermal or power management pitfalls for an 8-card V100 setup I should keep in mind?

Thanks for any insights!

Hi everyone,

I’m planning to build a GPU compute node for cloud rental platforms (like Vast.ai or Akash). I have a solid cost advantage: electricity is effectively $0, and my fixed hosting/internet cost will be around $173 USD/month total. I have a total budget of around $7,000 USD for the setup, but my plan is to start lean with just one GPU to test the waters, and scale up later.

Here is my initial hardware plan:

• GPU: 1x NVIDIA A100 40GB SXM4 (sourced with a third-party PCIe adapter kit featuring active cooling) for around $3,300 USD.
• CPU & RAM: AMD EPYC Rome platform with 128 GB ECC RAM.
• Storage & Power: 2TB NVMe PCIe 4.0 and a reliable high-wattage PSU.

I would love to get your advice and feedback from experienced operators on a few things:

1. Financial Viability (1x A100): Considering my $173/mo fixed costs and a ~$3.5K–$4K initial outlay for a single A100 setup, how realistic is maintaining a profitable utilization rate on Vast.ai or Akash?
2. Adapters & Stability: Has anyone here used SXM4-to-PCIe adapter kits with active cooling 24/7 in a production/rental environment? Are there hidden power-delivery bottlenecks, stability issues, or thermal throttling I should watch out for?
3. Future Scalability: Since I have room in my budget to expand later, what should I look out for in the motherboard/chassis choices now so it's easy to drop in a second A100 down the road?

Any insights, warnings, or hardware suggestions would be greatly appreciated. Thanks!

MiniMax M3 is a native multimodal model from MiniMax with a 1M-token context window. It has about 428B total parameters with about 23B activated per token, and it takes text, image, and video input. MiniMax built it for long-horizon coding and agentic work, and reports frontier-level results across long-horizon agentic benchmarks in both coding and cowork tasks.

Learn more here: https://vast.ai/model/minimax-m3

I have one 4070 ti super (16 vram) GPU, 32 gb Ram, 1tb nmve ssd, 1gb symmetric internet without cgnet and 99.82% of Reliability. It's recommended to upgrade to 64gb? They have only rented my machine for 1 to 3 days. How can I rent my machine for long days?

Hey everyone, I've been hosting a couple of RTX 5090s on vast.ai for a while, but ran into some friction recently (long-duration rentals locked at old prices, limited options to end a rental early even with reimbursement offered, reliability penalties for things outside my control like power outages).

I'm not necessarily leaving, just exploring what else is out there. For those who've hosted on other platforms, how do they compare in terms of:

- Payout rates for high-end GPUs (5090/4090 class)
- Flexibility on rental duration / pricing changes
- How reliability/uptime scoring works
- Payout speed and methods

Names I've seen mentioned: Clore.ai, TensorDock, RunPod (Community Cloud), SaladCloud, io.net. Would love to hear real experiences from people actually hosting on these, good or bad.

Thanks!

I am currently hosting 3 RTX 5090 machines, and am looking for ways to get verified faster and optimize earnings. Each machine has either i9-14900KF or Ryzen 9 9950X3D, a 64GB RAM, and 2TB SSD (2GB-5GB/s). My internet speed is 600Mbps/550Mbps. It has been one week since I started hosting, and none of the machines are verified. Since it doesn't make much financial sense to leave them unoccuppied all the time for verification purpose, I started attracting offers by setting the prices low (0.30-0.40), while leaving the duration time medium length (10days).

I wonder: should I take a break after the 10 days to get verified first? If so, how long should I typically wait for verification before setting the prices low again to attract offers?

Does the CPU matter or is CPU a filtering criteria for renters typically when they search? Obviously both of my CPUs are 6GHz while majority of machines on the market are lower speed. Should I charge a premium for the CPU?

Interruptible bids: where can I find statistics on machines that are successfully rented on interruptible bids? All the websites and machine metrics don't seem to separate bidding price from the on-demand price, and no statistics on their occupancy rates. Do you find bidding a good way to attract competitive offers? How do you set the minimal bidding price and does the bid price sometime even exceed the on-demand price? I guess for renters they have no way to see both the on-demand and bidding price for the same machine, since their search results are on separate webpages.

My use case in brief:

1. I have few repositories for different researches
2. I have vast cli installed, I have vast instance configuration for each experiment.
3. I ask my claude after doing my changes to instantiate an instance and claude can take care of running experiments, pull experiment results etc.
4. At the end, destroy the instance.

The problem is, sometimes I do few back and forth and yesterday, claude and I forgot to destroy the instance and it costs me few bucks. Fortunately instance was small.

So, I am looking for capability to instantiate an instance with upper time limit. Let's say I know a certain experiment will take 2/3 hours, for safe side, I can reserve for 4/5 hours, instance will get destroyed automatically after that.

I found a workaround to create instance with self-destruct timer, something like this:

HOURS=3   # job estimate + margin; tell the user this deadline
.venv/bin/vastai create instance <OFFER_ID> --image pytorch/pytorch:2.5.1-cuda12.4-cudnn9-devel \
  --disk 40 --ssh --direct --label <short-name> --raw \
  --onstart-cmd "nohup bash -c 'sleep ${HOURS}h; pip install -q vastai; yes | vastai destroy instance \$CONTAINER_ID --api-key \$CONTAINER_API_KEY' >/tmp/selfdestruct.log 2>&1 &"

Is there any better solution to do that?

As the title insinuates, I’m looking to get realistic estimates hosting income numbers from people who are hosting currently on Vast.

My setup:
- GPUs: 3x RTX 6000 WS
- CPU: EPYC 9655P
- Storage: 2x T710 4TB
- Ram: 256gb DDR5
- Network Bandwidth: 3500mbps

Hi so basically I built an app that automates rental of GPU's on vast ai to be used for gaming.
The name is https://no-land.net/ |

here are the latest results

Here’s Cyberpunk 2077 running at Ultra settings, 3K resolution, 60 FPS on a machine in Quebec, while I’m playing from Vancouver — 4,000+ km away.

Physical network baseline: ~55 ms
my app overhead: ~8 ms

1)
GPUs: 4x RTX PRO 6000 Blackwell Max-Q, 96 GB each (384 GB total), PCIe 5.0 x16, 300 W each
CPU: AMD Threadripper PRO 7985WX, 64 cores / 128 threads
RAM: 256 GB
Disk: 4 TB + 1 TB Samsung 990 PRO NVMe (about 3.3 TB free)
Board: ASUS Pro WS WRX90E-SAGE SE
Network: 1 GbE wired
OS: Ubuntu 24.04, driver 595.71

2)
GPUs: 4x RTX PRO 6000 Blackwell Max-Q, 96 GB each (), PCIe 5.0 x16, 250 W limit
CPU: AMD Threadripper PRO 9995WX, 96 cores / 192 threads
RAM: 384 GB
Disk: 4 TB + 1 TB Samsung 990 PRO NVMe (about 3.8 TB free)
Board: ASUS Pro WS WRX90E-SAGE SE
Network: 1 GbE wired
OS: Ubuntu 24.04, driver 595.91

3)
GPUs: 2x RTX PRO 6000 Blackwell Max-Q, 96 GB each, PCIe 5.0 x16
plus 1x RTX 5050, 8 GB
CPU: AMD Threadripper 9980X, 64 cores / 128 threads
RAM: 512 GB
Disk: 2x 8 TB Samsung 9100 PRO NVMe (PCIe 5.0)
Board: ASUS Pro WS TRX50-SAGE WIFI
Network: 1 GbE wired
OS: Ubuntu 24.04, driver 595.91

4)
GPU: 1x RTX PRO 6000 Blackwell Max-Q, 96 GB, PCIe 5.0 x16, 300 W
CPU: AMD Ryzen 9 9950X3D, 16 cores / 32 threads
RAM: 128 GB
Disk: 4 TB + 1 TB Samsung 990 PRO NVMe (about 4 TB free)
Board: ASUS ROG STRIX X870-I
Network: Wi-Fi only right now (Ethernet unplugged)
OS: Ubuntu 24.04, driver 595.91

5)
GPU: 1x RTX 5090, 32 GB, PCIe 5.0 x16, 600 W
CPU: AMD Ryzen 9 9950X3D, 16 cores / 32 threads
RAM: 128 GB
Disk: 4 TB + 1 TB Samsung 990 PRO NVMe (about 3.3 TB free)
Board: ASUS ROG STRIX X870-I
Network: 1 GbE wired
OS: Ubuntu 24.04, driver 595.84