JarvisLabs
JarvisLabs provides on-demand cloud GPUs and notebooks for AI/ML developers who need flexible GPU compute.
Pros
- On-demand cloud GPU access for ML/AI workloads
- Jupyter notebook environments for research
- flexible pay-as-you-go model without long-term contracts
Cons
- GPU compute can be expensive for sustained workloads
- limited to technical users comfortable with Jupyter
- no built-in collaboration tools mentioned
Cost
GPU instances are billed on demand by the hour: the NVIDIA H200 SXM is $3.99/hr, the H100 SXM $2.69/hr, the RTX Pro 6000 Blackwell $1.89/hr, the A100 80GB $1.49/hr, the A100 40GB $0.89/hr, the L4 $0.44/hr and the A30 $0.41/hr; CPU-only virtual machines run from $0.05/hr for 2 vCPU and 8 GB, through $0.10/hr for 4 vCPU and 16 GB, $0.20/hr for 8 vCPU and 32 GB and $0.40/hr for 16 vCPU and 64 GB, to $0.79/hr for 32 vCPU and 128 GB; storage is $0.10 per GB per month, in-region egress is free, and billing is per minute with the ability to pause at any time; no free credits or reserved plans are listed.
Verdict
Best for AI/ML researchers and developers who need temporary GPU access without infrastructure commitment.
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