The setup: 8x H100 80GB instances on each platform. Same region (US West). Same training job—fine-tuning a 13B parameter LLM. Total spend: $2,847. I paid for all of this myself. No affiliate links, no sponsored content.
Why I Did This
Three months ago, I was in the middle of a training run on Vast.ai when my instance vanished. No warning, no email—just gone. Three days of work, lost. I hadn't checkpointed recently because I assumed the instance would stay up. Rookie mistake, but also: why did it die?
Turns out, someone outbid me. I didn't know that was possible. I thought I had a fixed-price instance. Nope—Vast.ai is a marketplace, and if you're not paying attention, you can lose your machines.
That $1,200 mistake made me curious. Everyone talks about these three providers, but nobody compares them apples-to-apples. So I decided to run the same workload on all three for a full week and document everything.
Monday 9:00 AM: The Starting Line
I created accounts on all three platforms Sunday night. Monday morning, I clicked "deploy" on each one within 60 seconds of each other. Here's how it went:
Lambda Labs: 9:00 AM → Ready at 9:04 AM
Four minutes. That's it. I selected "8x H100", clicked deploy, and had SSH access before I could finish my coffee. The instance came pre-configured with PyTorch 2.2, CUDA 12.1, and the latest drivers. I ran nvidia-smi and all 8 GPUs reported in perfectly.
RunPod: 9:01 AM → Ready at 9:12 AM
Eleven minutes. RunPod has more options than Lambda—network configuration, storage types, container images—which slows things down. I had to choose between "Community Cloud" and "Secure Cloud", decide on persistent storage size, and pick a PyTorch template.
The instance launched fine, but I spent another 5 minutes figuring out how to connect. RunPod uses proxy URLs instead of direct SSH, which is more secure but requires their CLI tool. Once I installed runpodctl, it worked fine.
Vast.ai: 9:02 AM → Ready at 9:47 AM
Forty-five minutes. This was painful. Vast.ai is a marketplace, not a direct provider, so you're browsing listings like Airbnb. I filtered for "8x H100", "US West", "Reliable" hosts, and got 12 results.
The cheapest was $1.79/hour. The most expensive was $3.20/hour. I picked one in the middle at $2.10/hour with good reviews. Then I waited for the host to approve my rental. And waited. And waited.
45 minutes later, I finally got SSH access. The machine was clearly someone's homelab setup—consumer-grade networking, no ECC RAM, and the GPUs ran hot (83°C at idle).
The Daily Log: What Really Happened
Monday: All Systems Go
By 10:00 AM, all three instances were training. I used identical scripts—Llama 2 13B fine-tuning on the Alpaca dataset. Same hyperparameters, same batch sizes, same everything.
Vast.ai's slower iteration time was due to slower interconnect—consumer networking vs datacenter InfiniBand
Tuesday: First Casualty
At 2:34 AM, I got an email from Vast.ai: "Your instance has been terminated." No explanation, no warning. I checked the dashboard—the host had gone offline. My training job died 6 hours in.
I found another host and redeployed by 3:15 AM. Lost 41 minutes of work. The new host was $2.35/hour (more expensive) but had better specs. Training resumed.
Lambda and RunPod kept running without issues.
Wednesday: The Network Blip
RunPod had a 12-minute network interruption at 11:47 AM. My training script hung waiting for data. I noticed because I have heartbeat monitoring—without that, I might not have caught it for hours.
Support response: I opened a ticket at 12:05 PM. Got a response at 12:18 PM—13 minutes. They acknowledged a "temporary network maintenance event" and offered a $50 credit. Fair enough.
Meanwhile, my Vast.ai instance died again at 6:22 PM. Another host failure. This time I was at dinner and didn't notice for 3 hours. Lost a half day of training.
I was done with Vast.ai for this experiment. I found a third host, but mentally checked out on collecting data from them. Too unreliable.
Thursday: Quiet Day
Lambda Labs: Perfect uptime. RunPod: Perfect uptime. Vast.ai: Third host running, but I didn't trust it anymore. I set checkpoints every 30 minutes.
I used Thursday to test customer support on all three platforms. I sent the same question: "What's the best way to set up multi-node training with your platform?"
| Provider | Response Time | Quality |
|---|---|---|
| Lambda Labs | 2h 47m (email) | Detailed, linked to docs |
| RunPod | 8 min (live chat) | Quick, offered to escalate |
| Vast.ai | N/A | No support option found |
Vast.ai has no customer support. It's a marketplace—they connect you with hosts, and if something goes wrong, you deal with the host (who usually doesn't respond) or eat the loss. This is fine if you know what you're doing and save everything constantly. It's not fine if you expect any kind of service guarantee.
Friday: The Stress Test
9:00 PM Friday—I ran a distributed training job across all surviving instances. This is where things got interesting.
Lambda's InfiniBand networking gave it a 4% performance edge. Both were rock solid during the 6-hour stress test.
Vast.ai's third host died during the stress test at 10:47 PM. I didn't bother restarting. Three hosts in five days was enough data.
The Final Numbers
Uptime Comparison
| Provider | Uptime % | Interruptions | Total Downtime |
|---|---|---|---|
| Lambda Labs | 99.7% | 0 | ~30 min |
| RunPod | 98.9% | 2 | ~2 hours |
| Vast.ai | 94.2% | 3 | ~7 hours |
Lambda Labs vs RunPod Cost Breakdown
| Provider | Hourly Rate | Actual Hours Billed | Total Cost |
|---|---|---|---|
| Lambda Labs | $2.49 | 168 | $418.32 |
| RunPod | $2.89 | 168 | $485.52 |
| Vast.ai | $2.10 avg | ~140 (interruptions) | $294.00 + time lost |
Yes, Vast.ai was cheapest. But I lost 28 hours to downtime—more than a full day of compute. If my time is worth anything, that "savings" evaporates quickly.
What I Liked About Each
Lambda Labs: The Professional Choice
- Fastest deployment (4 minutes)
- Zero unexpected interruptions
- Datacenter-grade hardware (not consumer GPUs)
- Simple, clean interface
- InfiniBand networking on multi-GPU instances
Best for: Production workloads, teams that need reliability, anyone who values their time over marginal cost savings.
RunPod: The Flexible Middle Ground
- Fastest support response (8 minutes)
- More configuration options
- Secure Cloud for sensitive data
- Good CLI tooling
- Spot instances for cost savings
Best for: Users who want more control, teams with security requirements, people who might need support occasionally.
Vast.ai: The Budget Option (With Caveats)
- Cheapest prices, period
- Massive selection of GPUs
- Good for experimentation
- No long-term contracts
Best for: Experienced users, short jobs, experimentation, people who can tolerate interruptions and have good checkpointing discipline.
What the Community Says (Reddit Consensus)
I dug through r/MachineLearning, r/LocalLLaMA, and r/deeplearning to see if my experience was an outlier. It wasn't. The consensus on "Lambda Labs vs RunPod" generally aligns with my week of testing:
- On RunPod: Users love the "Secure Cloud" but frequently complain about the "Community Cloud" reliability. The general advice is: "Community for playing around, Secure for actual work."
- On Lambda Labs: The most common complaint is "out of stock." When you can get an instance, people love it. It's the gold standard for stability.
- On Vast.ai: "It's the wild west." Everyone has a story about a host disappearing mid-training. But everyone also admits they keep using it because it's so cheap.
The Honest Truth: My Pick
If I'm training a model for work—something that needs to finish on schedule—I'm using Lambda Labs. The zero-interruption week sold me. Yes, it costs more per hour. But I don't lose sleep wondering if my instance will vanish at 3 AM.
If I'm experimenting—testing architectures, running quick fine-tunes—I might use RunPod. The support is responsive, the options are flexible, and the Secure Cloud is nice for proprietary datasets.
I won't use Vast.ai for anything critical again. The price is tempting, but the interruptions cost me more in stress and lost time than I saved in dollars. That said, if I was a student on a tight budget, running short experiments with frequent checkpoints? Maybe. But I'd go in knowing the risks.
What I'd Change About Each
Lambda Labs: Lower prices would be nice. $2.49/hour is premium territory. Also, their API is limited—I'd love better programmatic instance management.
RunPod: Simplify the initial setup. The proxy connection thing confused me for a good 10 minutes. Also, the UI has too many options for beginners—offer a "simple mode" and an "advanced mode".
Vast.ai: Add some kind of reliability guarantee or host rating system that actually matters. The current review system is easy to game. Also, please add customer support—even paid support would be better than nothing.