Baseten alternative
Xinference vs Baseten:
sovereign inference for production
Both platforms give you managed serving, autoscaling and an OpenAI-compatible API. The difference is where your data lives, that our engineers take the workload from pilot to production with you, and what the invoice looks like.
Xinference runs on your infrastructure or ours, in Australia.
client = OpenAI(
- base_url=CURRENT_PLATFORM_ENDPOINT,
- api_key=CURRENT_PLATFORM_KEY,
base_url="https://api.xinference.co/v1",
api_key=XINFERENCE_API_KEY,
)
# prompts, tools and streaming stay exactly as they are.* Figures reported by Xinference and measured against closed-source API list prices, not against Baseten. Savings and speed-up both vary by workload, which is why we measure yours during the proof of concept.
Xinference vs Baseten: what each one solves
Both are managed inference platforms for open-weight and custom models. They were built for different teams.
For a team taking a proof of concept to production with constraints Baseten was not designed around: data that has to stay in Australia, a cost case that has to hold for an Australian budget, and infrastructure decisions that are yours to make. Our engineers run the pilot, the migration and the production rollout with you rather than handing you a checklist.
BasetenFor a product team whose product depends on AI and who wants the runtime engineering handled. It is a US-centric company and serving runs on capacity it arranges, on its managed runtime rather than in your environment.
The choice is rarely about features. It is about where your data is allowed to live, who is on the call when something breaks at 3pm Sydney time, and whether a US-dollar invoice works for your finance and compliance teams.
Where Xinference differs from Baseten
Four differences that decide the question for most Australian teams. None of them are about whether the platform can serve your model.
Australian data residency by default
Prompts, outputs, fine-tunes and the models themselves are served and stored on Australian infrastructure, in your environment or ours. Residency is the default setting rather than a region you have to ask for.
Your infrastructure, not ours
Run it on your own cloud account, on GPUs you already own, or on our Australian cloud. Baseten serving is tied to Baseten's managed runtime. Ours goes wherever your constraints are, and our engineers stand it up with you.
An invoice your finance team recognises
Per token, or per GPU-hour, invoiced by our Australian entity. No foreign exchange line and no offshore vendor to explain to procurement. Up to 70% lower cost than closed-source APIs.*
Nothing goes cold
Dedicated deployments hold their capacity instead of scaling to zero, so the first request after a quiet afternoon answers like every other one.
Xinference vs Baseten: feature comparison
Last verified 22 September 2026
| What matters | |
Baseten |
|---|---|---|
| Data residency | Australia, in your environment or oursPrompts, outputs, fine-tunes and models stay onshore. | US-centric, served on capacity Baseten arrangesNot an environment you control. |
| Model choice | 300+ open models, plus your own custom and fine-tunedOne API for all of them. | Open-weight and custom models |
| Managed serving | Deployment, autoscaling and monitoring included | Deployment, autoscaling and monitoring included |
| Where it runs | Your cloud, your own hardware, or our Australian cloud | Baseten-managed multi-cloud; self-host on enterprise plans |
| Lock-in | Model, infrastructure and hardware agnostic | Serving tied to Baseten's managed runtime |
| Pricing model | Per token, or per GPU/hourMetered both ways. Enterprise rates on request. | Per-minute GPUs, or per-token model APIs |
| Cost | Up to 70% lower than closed-source APIs*Invoiced by our Australian entity. | Billed in US dollars |
| Performance | 2-4x faster responses*No cold starts on dedicated deployments. | Optimised runtime; scale-to-zero deployments cold start |
| Support | The same engineers from pilot through to productionIncluded, not an enterprise tier. Australian hours. | Forward-deployed engineering on enterprise plans |
*Figures reported by Xinference against closed-source API list prices; savings and speed-up both vary by workload. Baseten details taken from its public pricing and documentation pages on the date above.
How a migration off Baseten runs
API workloads move by changing a base URL. Dedicated deployments take a little more, and our engineers do that work with you: the same team from the first pilot through to production, in your timezone.
Repackage
We repackage a Truss or a custom container for Xinference. Fine-tunes come across as they are.
Stand up
The same models go live on your infrastructure, or on our Australian cloud.
Run both
Your traffic hits both at once. Nothing gets switched off while we compare latency and cost on your own requests.
Cut over
When the numbers satisfy you. A base URL and a key is the whole application change.
All four steps happen inside the proof of concept, before you commit to anything, and the engineers who run them are the ones who support the workload afterwards.
Which is the better fit, Xinference or Baseten?
Choose Xinference when
- A regulator, a customer contract or your own policy says the data has to stay in Australia.
- The environment has to be yours: your cloud account, or hardware in your own racks.
- Procurement needs an Australian invoice and a cost case that holds against an Australian budget.
- You want a guided rollout: the same engineers through the pilot, the migration and production support, not a support tier you buy into.
Choose Baseten when
- You have no residency or sovereignty constraint and want serving fully managed on capacity the vendor arranges.
- You would rather hand the runtime engineering to the vendor than keep the infrastructure decisions in-house.
Not ready to think about infrastructure yet? Start on the hosted Model API and move to dedicated compute when the volume justifies it.
Xinference vs Baseten pricing
Baseten bills dedicated deployments per minute of GPU time and its model APIs per token, in US dollars. Xinference bills hosted model APIs per token and dedicated deployments per GPU-hour, invoiced by our Australian entity, and runs just as happily on GPUs you already own or rent.
We price your specific workload side by side as part of the proof of concept, so the cost case is built on your traffic rather than a benchmark.
Moving from Baseten: common questions
Is Xinference a Baseten alternative?
For Australian teams, yes. Both platforms serve open-weight and custom models with managed autoscaling behind an OpenAI-compatible API, so a workload that runs on Baseten runs on Xinference without an application rewrite. What changes is everything around the workload: the data stays in Australia, the deployment can sit in your own cloud account or on your own hardware, the invoice comes from an Australian entity, and the same engineers take you from pilot to production on Australian hours.
We package our models as a Truss. Does that come across?
Yes. Our engineers repackage a Truss or a custom container for Xinference as part of the proof of concept, so this is not work that lands on your team. Fine-tuned weights and adapters come across as they are and remain yours. Models you serve through Baseten's model APIs rather than your own packaging move by pointing the client at a different base URL.
Our Baseten deployments scale to zero. What happens to cold starts?
Dedicated deployments on Xinference hold their capacity rather than scaling to zero, so there is no cold start on the first request after a quiet period and no need to send synthetic traffic to keep a replica warm. That is a deliberate trade: you are paying for reserved capacity instead of paying nothing while idle, which is the right trade once a workload has steady production traffic and the wrong one for something used twice a week. We will tell you which one your traffic looks like during the proof of concept.
Baseten bills GPUs by the minute. How does per GPU-hour compare?
Finer billing granularity only saves money on workloads that are genuinely idle for long stretches, and it costs you the cold starts described above. For steady production traffic the granularity stops mattering and the rate does. Xinference bills hosted model APIs per token and dedicated deployments per GPU-hour, with custom enterprise rates for larger workloads, and you can run the platform on GPUs you already own or rent so your existing compute contracts stay in place. We build the side-by-side against your actual traffic rather than a list price.
Baseten puts forward-deployed engineers on enterprise accounts. What do we get?
The same thing, and not only on enterprise accounts. One team of our engineers carries the workload from the first pilot through the migration and into production support, working your hours rather than the edges of an offshore day. It is the reason the migration steps above are ours to run rather than a checklist we hand you, and it does not sit behind a pricing tier.
Can we keep running in our own cloud account?
Yes, and that is the structural difference between the two platforms. Baseten serving runs on Baseten's managed runtime, with self-hosting available on enterprise plans. Xinference deploys into your existing cloud account, onto GPU hardware you own in your own data centre, or onto our managed cloud in Australia. All three run the same platform and the same API, so you can start on ours for a proof of concept and move to your own for production, or the reverse, without rebuilding anything. Xinference is also available through AWS Marketplace if you would rather buy against an existing AWS commitment.
Bring your workload onshore.
Tell us which models you serve today and roughly what traffic they take. We will stand them up on Xinference, run them alongside what you have now, and show you the latency and the invoice before you decide anything.