AWS vs CoreWeave for training

If your main goal is training large models, the short version is:

• AWS = safer default, broader ecosystem, better enterprise maturity
• CoreWeave = often better price/performance and easier access to lots of GPUs for ML-heavy workloads

When AWS is better

Choose AWS if you care most about:

• Enterprise reliability and compliance
• Tight integration with storage, networking, IAM, monitoring, VPCs, etc.
• Other cloud services beyond training
• Global footprint and mature support
• Long-term procurement/legal simplicity

AWS is usually the better choice if you’re running a mixed platform, need strong governance, or your org already lives in AWS.

When CoreWeave is better

Choose CoreWeave if you care most about:

• Getting a lot of GPUs quickly
• Lower cost for pure training
• ML-focused infrastructure
• Better availability of NVIDIA GPUs
• Less friction for large-scale training jobs

CoreWeave is often attractive for startups and ML teams that mostly need GPU compute + storage + networking for training, and don’t need all the extra cloud services.

Practical comparison for training

1. Cost

• CoreWeave often wins on raw GPU economics.
• AWS can become expensive fast, especially with high-end GPUs and data movement.

2. Availability

• CoreWeave may have better access to scarce GPUs.
• AWS can have capacity constraints depending on region/instance type.

3. Platform maturity

• AWS is much more mature.
• CoreWeave is more specialized and may feel less complete outside ML use cases.

4. Networking/storage for distributed training

• Both can work well.
• AWS has more mature tooling overall.
• CoreWeave is optimized for GPU workloads and can be very effective if your training stack is straightforward.

5. Vendor lock-in

• AWS can create broader lock-in because teams often use many AWS-native services.
• CoreWeave is more focused, which can mean less accidental complexity, but still requires adaptation.

Rule of thumb

• If training is the core workload and cost matters most: CoreWeave
• If you need a full cloud platform with training as one part of a larger stack: AWS

My recommendation

If you're choosing for LLM training or large distributed GPU training, I’d usually suggest:

• Start with CoreWeave for the training cluster itself
• Keep AWS for surrounding infrastructure if you already use it

That said, if you tell me:

• model size
• GPU type you need
• training time horizon
• budget
• whether you need compliance or multi-cloud

…I can give you a much more specific recommendation.