CoreWeave just launched their own AI Object Storage. Our take? We love to see it.
At first glance, it might look like a competitive offering, but as far as we’re concerned, the more storage options out there, the better for builders. It’s another sign that object storage has officially arrived as a key ingredient in the AI stack.
Now, your AI stack can look like this: Fast, flexible storage close to your GPUs from CoreWeave (essential for training and inference). And when the run’s over? Move it to Backblaze B2 Overdrive to keep it ready for your next run at the right temperature and price-to-performance ratio.
More options mean more ways to build smart, cost-efficient pipelines that let teams train faster and iterate more without getting locked in. We’ll always cheer for that.
Why object storage is essential for AI workloads
How do you balance scalability with performance while staying on budget? This ebook explores how object storage enhances every stage of the pipeline from collection to training to deployment, and provides real-world use cases.
Why object storage matters in the AI stack
Every AI model depends on moving massive datasets through training, inference, and retraining cycles. Each stage requires fast, reliable access to data. That’s where object storage comes in.
Object storage enables this by offering:
- Elastic scalability for petabyte-scale data.
- Reliability and durability across long model lifecycles.
- Lifecycle management features to balance cost, performance, and accessibility.
As AI projects scale, smart data management becomes just as important as GPU performance. High-end GPUs can only deliver full value when they’re continuously fed the right data at the right time. When data sits in the wrong tier or takes too long to retrieve, compute resources go underused. And that means wasted time and money.
Balancing performance and cost in AI workloads
CoreWeave’s Local Object Transport Accelerator (LOTA) delivers up to 7GB/s throughput per GPU, helping data move quickly between storage and compute. With pricing around $110 per terabyte (about $60 with discounts) and regional capacity up to 10TiB, it’s built for performance-critical workloads where proximity to GPUs makes a measurable difference.
Its launch adds more choice to the ecosystem and highlights the growing demand for storage built specifically for AI. As more specialized options emerge, organizations are thinking carefully about how to right-size their infrastructure for each stage of the AI lifecycle.
When maximum performance is the goal, GPU-adjacent storage like CoreWeave’s can help teams squeeze out every last bit of speed during intensive training cycles. But for most AI workloads, B2 Overdrive provides the right balance of cost and performance. It offers the throughput and durability needed to support active training while keeping pricing predictable and scalable.
Many AI builders combine these strengths through a multi-cloud setup. Teams might use CoreWeave Object Storage when latency and proximity to GPUs deliver measurable gains, and then keep the rest of their AI pipeline on B2 Overdrive so datasets remain readily available for retraining, testing, or deployment.
Example configuration:
- CoreWeave Object Storage for specialized, compute-intensive training where every millisecond counts. It’s ideal for short bursts of high-throughput processing, such as large-scale model fine-tuning or time-sensitive inferencing.
- B2 Overdrive for the broader AI workflow, including day-to-day training, staging, versioning, and long-term dataset management. It provides the performance needed for ongoing model development while keeping data costs predictable and accessible across teams and environments.
B2 Overdrive offers:
- Storage at roughly $15 per terabyte
- High throughput and rapid access for post-training workflows
- Simple APIs and event notifications to automate data movement across environments
This kind of architecture gives teams the freedom to use each platform where it shines. Backblaze handles the heavy lifting for most workloads, while CoreWeave adds targeted acceleration when raw GPU performance is the top priority. The result is a flexible, cost-aware workflow that supports both innovation and scale.
AI infrastructure that plays to every strength
The most effective AI setups use the right cloud for the right job. They run training where GPUs can perform at their peak, and store data where it stays organized and ready to move when needed.
B2 Overdrive provides a foundation for this strategy, offering a layer of object storage that keeps data secure, accessible, and easy to integrate across environments. Teams can combine each platform’s strengths to achieve speed when it’s needed, scalability that endures, and freedom from lock-in and runaway costs.
The AI ecosystem is expanding, and with the right partners, so are the possibilities.
See how Backblaze B2 Overdrive keeps AI data fast, flexible, and affordable.
