After 6 months with CoreWeave: it’s not the worst, but there are better options out there.
Context
I started using CoreWeave about six months ago for a machine learning project involving image processing. The scale was moderate, with around 5000 images to preprocess and train a model. We were a small team of three developers, juggling this project alongside our regular duties. I thought CoreWeave would make our lives easier, given its focus on GPU cloud computing, but I quickly realized it wasn’t as smooth as I’d hoped.
What Works
There are a few things that CoreWeave does right. First off, the pricing structure is somewhat appealing. If you’re just getting started or working on smaller tasks, you can find some decent rates. For example, their GPU instances start at $0.40 per hour, which is competitive for entry-level models. Moreover, they offer a variety of GPU types, from RTX 3060s to A6000s, allowing for flexibility based on your workload.
Another feature that I found useful was their API. It’s pretty straightforward to set up and start a new instance. Here’s a quick example for spinning up an instance:
curl -X POST https://api.coreweave.com/v1/instances \
-H "Authorization: Bearer YOUR_API_KEY" \
-H "Content-Type: application/json" \
-d '{
"instanceType": "A6000",
"region": "us-east-1",
"image": "ubuntu:latest"
}'It’s quick and gets the job done. You can also manage your instances through a web dashboard, which is fairly user-friendly.
What Doesn’t
Now let’s get to the crux of the issue: CoreWeave has some serious shortcomings. For starters, their customer support is lacking. I’ve spent hours trying to get clarity on billing issues and never received a satisfactory response. Imagine being stuck on a deadline with an error that says:
Error: Instance not running. Please contact support.
Well, contacting support is easier said than done. You may have to wait days for a reply, which can stall your project. And let me tell you, deadlines don’t wait for anyone—I’ve learned that the hard way.
Additionally, the performance of certain GPU instances can be inconsistent. My training times varied, and I would sometimes see my model training take twice as long for no apparent reason. For instance, when I used an A6000, I expected it to complete a training cycle in around 4 hours, but it sometimes stretched to 8 hours. That’s a killer when you’re racing against deadlines.
Comparison Table
| Provider | Starting Price per Hour | GPU Types | Customer Support Rating | Instance Startup Time |
|---|---|---|---|---|
| CoreWeave | $0.40 | RTX 3060, A6000 | 2/5 | 5 minutes |
| AWS EC2 | $0.70 | V100, A10g | 4/5 | 3 minutes |
| Google Cloud | $0.60 | V100, A100 | 4.5/5 | 4 minutes |
The Numbers
Let’s talk numbers. Based on my six months of usage, I’ve gathered the following performance and cost data:
- Total instances spun up: 50
- Average training time for a single model: 6 hours
- Total cost incurred: $800
- Instances with performance drops: 30% of the time
In comparison, using AWS for a similar workload would have cost about $1,200, but the performance consistency was a lot better. Google Cloud could’ve been around $1,000, but again, with the added benefit of reliable support and faster instance startups.
Who Should Use This
If you’re a solo dev building a quick prototype or testing something out, CoreWeave can be a decent choice. The lower cost can make it appealing for experimentation. However, if you’re just dipping your toes into GPU computing, be prepared for some bumps along the way. You may end up spending more time troubleshooting than coding. Honestly, I wish I had taken a more cautious route myself—my naive enthusiasm led to a lot of late nights.
Who Should Not
If you’re part of a larger team aiming to deploy production-level applications, CoreWeave probably isn’t the right fit. The lack of reliable support and inconsistent performance can create headaches that you just don’t need. If you need something dependable, you might want to skip CoreWeave entirely. Please don’t repeat my mistakes; go with a provider that delivers on both service and reliability.
FAQ
Q1: Can I scale my resources easily with CoreWeave?
A1: Yes, you can scale resources, but be prepared for some delays. The API might respond quickly, but the actual provisioning can take longer than advertised, which is frustrating.
Q2: What types of workloads are best suited for CoreWeave?
A2: It’s best for smaller-scale workloads or proof-of-concept projects. For anything mission-critical, you should consider alternatives.
Q3: Is there any free tier available?
A3: No, CoreWeave doesn’t offer a free tier. You’ll have to pay from the get-go, so plan your budget accordingly.
Q4: How does CoreWeave compare to other cloud options?
A4: It’s cheaper, but the trade-off is reliability and customer service. If you’re looking for top-notch service, look elsewhere.
Q5: Can I get my money back if I’m unhappy?
A5: CoreWeave does not provide refunds, so make sure to do your research before committing your budget.
Data Sources
Data sourced from official documentation and community benchmarks from platforms like Guru99 and Cloud Cost Calculation.
Last updated May 20, 2026. Data sourced from official docs and community benchmarks.
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