Jarvislabs vs Vast.ai
Compare Vast.ai and Jarvislabs for self-service GPU instances, committed capacity, and training and inference workloads.
The Verdict: Jarvislabs vs Vast.ai
Vast.ai lets you select GPU offers from a marketplace. Jarvislabs provides root-access VMs, Templates, persistent filesystems, and inference products, with committed capacity and H200 SXM InfiniBand clusters available through a capacity discussion. Compare the complete environment and operational work alongside the live rental price. Marketplace on-demand rentals should not be confused with interruptible bids.
Choose Jarvislabs if:
- +You want VMs, Templates, storage, and inference within one platform
- +You want published GPU rates and a direct capacity discussion for larger workloads
- +You want managed serving configurations for supported models
Choose Vast.ai if:
- +Marketplace offers across different GPU configurations
- +On-demand, reserved, and interruptible rental options
- +Choice of hosts and locations
What you can build on Jarvislabs
VMs and Templates
Use a VM with full root access for your own kernel and Docker stack, or start with a preconfigured Template. GPU quantities depend on the model and region, with up to 8 GPUs per instance.
Explore VMsServerless inference
Deploy an OpenAI-compatible API with vLLM, SGLang, or Ollama. Workers autoscale and can scale to zero. GPU runtime is billed per worker-minute; retained storage continues billing. Currently in beta.
Explore ServerlessManaged Endpoints
Deploy a supported model with the GPU, serving image, precision, and parallelism selected and maintained by the Jarvislabs team.
How Managed Endpoints workPersistent filesystems
Keep datasets, checkpoints, and weights outside an instance’s lifecycle. A filesystem can attach to multiple instances in your account within its region. Storage is billed separately.
Explore filesystemsVM networking
Connect VMs privately with a VPC, control public ingress with Security Groups, and retain a public address with a Reserved IP. Reserved IPs are billed separately; cross-cloud private connectivity is not currently offered.
Explore networking capabilitiesCLI and Python SDK
Automate availability checks, launches, file transfers, training scripts, logs, and pause/resume workflows through the jl CLI and Python SDK.
Explore developer toolsGPU instances are available in Europe and India, with GPU types and quantities varying by region. Serverless, network filesystems, and VPC, Security Group, and Reserved IP features currently run in India regions. Choose deployment location by latency, data residency, and available features, wherever your team is based.
From self-service instances to committed capacity
Launch self-service instances with up to 8 GPUs per instance, or talk to Jarvislabs about committed capacity and H200 SXM InfiniBand clusters with shared storage for multi-node training. Share your GPU count, workload, preferred region, start date, and duration so sales can confirm a supported configuration, availability, and terms.
Compare a live quote
Vast.ai prices depend on live marketplace offers. No fixed median is shown because a current comparable sample has not been verified.
View Vast.ai pricing · View Jarvislabs pricingFeature Comparison
| Feature | Jarvislabs | Vast.ai |
|---|---|---|
| Instance billing | Per-minute | per second |
| Persistent Storage | Available (billed separately) | Yes |
| Inference options | Serverless (beta), Managed Endpoints, or your own VM stack | Serverless; compare the selected offer and runtime |
| GPUs per instance | Up to 8; varies by GPU and region | Varies by instance configuration |
| GPU instance locations | Europe, India | Global (wherever hosts are) |
| Multi-node capacity | H200 SXM InfiniBand clusters; contact sales | Confirm topology and capacity with the provider |
| Community Cloud | No (dedicated only) | Yes |
Vast.ai: Strengths and Considerations
Strengths
- +Marketplace offers across different GPU configurations
- +On-demand, reserved, and interruptible rental options
- +Choice of hosts and locations
Considerations
- -Evaluate each host and offer individually
- -Interruptible rentals need checkpoint and restart handling
- -Check storage persistence, transfer costs, and rental duration
Frequently Asked Questions
Is Vast.ai cheaper than Jarvislabs?
A live marketplace offer may cost less than a Jarvislabs instance. Check the GPU variant, CPU and RAM, storage and transfer charges, rental duration, and host conditions. An old marketplace median cannot establish the cost of a comparable deployment today.
How should I evaluate sensitive workloads?
Review isolation, data location, access controls, and contractual requirements for the exact service. Jarvislabs VMs support VPCs and Security Groups in supported regions, but these features alone do not establish compliance for a workload. Evaluate both providers against your requirements.
Which platform has better availability?
Availability changes by GPU type, quantity, and region on both platforms. Check live inventory for an immediate launch. For a planned run, discuss the required start date and committed capacity rather than assuming on-demand inventory will remain available.
Can I run inference on either platform?
Both have inference options. Jarvislabs offers Serverless with autoscaling and an OpenAI-compatible API, plus Managed Endpoints for supported models. Compare deployment control, model support, regional latency, and recovery behaviour for your traffic.
How should I plan for interruptions?
Vast.ai distinguishes on-demand, reserved, and interruptible instances. Jarvislabs also offers spot pricing for selected GPUs. Checkpoint interruptible jobs and keep important outputs on storage with the required lifecycle. On-demand compute still needs a recovery plan.
Plan your workload
Start with self-service GPU instances, or discuss committed capacity and H200 SXM InfiniBand clusters with our team.
Get startedProduct comparison reviewed: September 5, 2026 · View all comparisons