LLM Hangar / Alternatives / Baseten
A Baseten alternative that runs in your own AWS account
What Baseten is good at
Baseten is an inference platform for teams that deploy models as a product. It bills GPU time by the minute, autoscales dedicated deployments, packages custom serving code, and puts real engineering effort into per-model performance. If you ship several models, need autoscaling that follows traffic, or want custom pre- and post-processing around a model, Baseten is the better choice, and nothing below argues otherwise.
Why teams look for an alternative
The reasons below are the ones Baseten's own pages document, as published on 22 August 2026.
- Your own VPC is an Enterprise feature. Baseten's pages describe self-hosted and VPC deployment as Enterprise options. On the self-serve plans, inference runs on Baseten's infrastructure.
- Regions are a sales conversation. Its pricing page points customers who need compute in other regions to sales. A team that needs EU residency cannot simply select it.
- The GPU minutes are Baseten's, not your provider's. Credits, reserved capacity and negotiated rates with AWS, Nebius or RunPod do not apply to minutes bought from a third party.
Side by side
| Baseten | LLM Hangar | |
|---|---|---|
| Runs in your own cloud account | Self-hosted and VPC on Enterprise | Yes: AWS, Nebius or RunPod, self-serve |
| EU pinning surcharge | Not stated; other regions via sales | None: one checkbox pins every resource to EU member-state regions |
| Self-serve BYOC | No | Yes, 24-hour trial |
| Audit log tier | Not stated | Every plan, including the trial |
| Who sees the prompt | Baseten's infrastructure handles the request on hosted plans | Only the endpoint on your instance; nothing passes through LLM Hangar |
| Pricing model | Per GPU minute (H100 listed at $0.10833 per minute) | $39 per month for the platform; GPU hours billed by your provider |
| Certifications | See Baseten's trust pages | None claimed yet; controls are described on the security page |
What LLM Hangar is not
It is not an autoscaling inference platform or a serverless per-token API. Each deployment is one model on one GPU shape that fits it, served by a standard inference server, running in your account until you stop or delete it. That suits steady private workloads and teams that want their own endpoint without DevOps; it does not suit bursty low-volume traffic or custom serving pipelines. The Lab plan runs one GPU shape per deployment, and the catalog is curated (with the option to deploy a Hugging Face repository of your choosing).
Questions people ask
Does Baseten run in my own cloud account?
Baseten's published pages describe self-hosted and VPC deployment as Enterprise options, and compute in other regions as something to arrange with sales. Its self-serve plans run inference on Baseten's infrastructure. LLM Hangar provisions into your own AWS, Nebius or RunPod account on every plan, including the trial.
How does per-minute GPU billing compare with an instance in my account?
Baseten bills GPU time by the minute (an H100 is listed at $0.10833 per minute on its pricing page). With LLM Hangar the GPU is an instance in your own account at your provider's hourly rate, plus a flat $39 per month for the platform. Which is cheaper depends on your provider, region and utilisation; the live price matrix shows current hourly rates per model and provider.
Can I move a model from Baseten to LLM Hangar?
For open-weight models, yes: pick the model from the catalog or paste its Hugging Face repository id, choose a GPU shape that fits, and point your OpenAI-compatible client at the new endpoint. Custom serving code written for Baseten's Truss framework would need to be replaced by the standard inference server LLM Hangar runs (vLLM or SGLang). See deploy a model.