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SageMaker Alternatives: Cheaper Cloud GPUs for Data Science (May 2025)
Eight services that undercut SageMaker on price while matching its ease of use
Published:
May 19, 2025
Last updated:
May 19, 2025

Why look beyond SageMaker?
SageMaker is a managed ML platform, but you pay for that convenience in three ways:
Higher base instance rates. An A10G (ml.g5.xlarge) is $1.21/hr and an A100 (ml.p4d.24xlarge) costs $37.68/hr for the whole 8-GPU node — you cannot rent a single A100. (SageMaker pricing)
Always-on meters. Notebooks, endpoints and EBS storage keep billing until you shut them down.
Regional GPU scarcity. Popular U.S. regions often have long wait times.
If your goal is fast, low-cost prototyping, the five alternatives below beat SageMaker on per-GPU price and let you start with a single GPU.
Quick cost comparison
Provider | GPU model | On-demand price per GPU hour* | Notes / source |
---|---|---|---|
Thunder Compute | A100 80 GB | $0.78 | |
RunPod | A100 80 GB | $1.19 | |
Lambda Cloud | A100 40 GB | $1.29 | |
Paperspace | A100 40 GB | $1.15 | |
AWS SageMaker | A10G 24 GB | $1.21 | SageMaker pricing |
AWS SageMaker | A100 40 GB** | $4.71 (must rent 8×) | SageMaker ml.p4d.24xlarge |
*U.S. East on-demand rates, May 2025.
**Effective per-GPU cost when you divide $37.68 by eight.
Five practical SageMaker alternatives
1. Thunder Compute
GPU focus: A100 40 GB and 80 GB nodes.
Pay-as-you-go: $0.57–$0.78 per GPU hour.
Developer workflow: Spin up EC2-style SSH instances or use the free VS Code extension to run notebooks against remote GPUs from your laptop. Starter templates (Llama 4 fine-tune, Stable Diffusion XL, LoRA, etc.) replace SageMaker JumpStart.
2. Plain EC2 + open-source tooling
EC2 g5.xlarge (A10G) costs $1.01/hr and p4d.24xlarge $32.77/hr, but you avoid the SageMaker surcharge and can script everything with Terraform or Ansible.
3. Paperspace Gradient
Notebook-centric workflow with one-click A100 jobs. A100 40 GB is $1.15/hr and storage is bundled, so it is simpler than SageMaker endpoints.
4. Lambda GPU Cloud
Targets multi-GPU jobs but also rents single A100s at $1.29/hr. Their CLI feels similar to AWS CLI and supports spot pools.
5. RunPod
Community pool offers A100 80 GB from $1.19/hr with per-second billing and automatic Jupyter images. Useful for bursty weekend experiments.
Thunder Compute vs SageMaker: apples-to-apples A100 math
Scenario | SageMaker | Thunder Compute |
---|---|---|
Fine-tune Llama 3 8B for 45 min | Needs ml.p4d (8 × A100) → $28.26 | Single A100 40 GB → $0.57 |
Two hours of SDXL image tests | ml.g5.xlarge → $2.42 | A100 40 GB → $1.14 |
Result: Thunder Compute is 95%+ cheaper for short, single-GPU jobs.
Developer experience considerations
Feature | SageMaker | Thunder Compute |
---|---|---|
IDE in browser | SageMaker Studio | VS Code remote extension |
Bring your own Docker | Limited, needs ECR | Any public/private image |
Templates / JumpStart | Built-in | Notebook templates in console |
Stop-billing toggle | Manual shutdown of Studio, endpoints, EBS |
|
Try Thunder Compute free
Ready to prototype? Create an account and claim $20 in monthly credits. Fire up an A100, open VS Code and start coding within minutes.
Looking for raw prices first? See the full Thunder Compute A100 pricing.

Carl Peterson
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