A complete overview of Baseten: Features, pricing, and alternatives

The AI space is buzzing. We all see the flashy models that can write, code, and create art out of thin air. But behind the scenes, there’s a whole world of infrastructure that actually makes these things work. These are the engines powering the AI revolution, and one name you’ll hear in that conversation is Baseten.

Baseten zeroes in on a super important, but often unglamorous, part of the AI process: inference. In simple terms, inference is what happens when you actually run a trained model to get an answer. For anyone trying to build a real AI strategy, getting a handle on platforms like Baseten is a must.

So in this article, we’re going to pull back the curtain on Baseten. We'll look at what it is, what it does, how the pricing works, and where it fits into the grand scheme of things. We’ll also get real about when a heavy-duty infrastructure tool like Baseten is the right call, and when you’d be better off with something more focused on your specific problem.

What is Baseten?

Baseten is an AI infrastructure platform that helps companies get their machine learning models up and running in a real-world, production setting. It’s less about being the AI itself and more like the high-performance plumbing that lets the AI do its job without falling over.

As Baseten's CEO put it in a Fortune article, they provide the "picks and shovels" or the "train tracks" for AI models. After a model has been trained, inference is the step where you put it to work making predictions. Baseten gives companies a place to run their custom models, or even popular open-source ones, without the massive headache of building and managing all the complex hardware themselves.

And they’re not just a small startup with a cool idea. With a fresh $150 million in funding and partnerships with cloud giants like Google Cloud and AWS, Baseten has proven it’s a serious player for technical teams building products with AI at their core.

Baseten's core products and features

Baseten’s toolkit is designed for a technical crowd, we're talking engineers who live and breathe this stuff. It’s important to be clear that this isn't a platform you can just switch on and hand over to your business teams. Using it well requires some real technical chops.

Baseten Model APIs for popular open-source models

A big part of what Baseten offers is a set of APIs that give you instant access to popular open-source models like DeepSeek and Llama. For developers, this is a huge time-saver. Instead of the pain of downloading, configuring, and tweaking these giant models on their own, they can just make an API call. It lets teams get prototypes and new features built way faster. Baseten says this approach also brings big performance wins, getting over 225% better cost-performance by using the latest NVIDIA hardware.

Dedicated Baseten deployments for custom AI models

If your company has already invested the time and money to build its own AI models, Baseten offers dedicated deployments. This is basically a private, scalable, and secure playground for your custom models to run. Your team gets total control over the hardware, letting them pick specific NVIDIA GPUs and tune everything just right for your performance needs.

That level of control is amazing for specialized use cases, but it’s really built for organizations that have their own Machine Learning Operations (MLOps) teams. It’s not a simple fix for a department like customer support that’s just trying to answer tickets faster.

The Baseten technology under the hood

Baseten gets its speed from a mix of top-tier hardware and finely tuned software. The platform gives users access to some seriously powerful GPUs, like the NVIDIA B200 and A100 series, which you need to run large models without a long wait.

On the software side, they use things like NVIDIA's TensorRT-LLM, an open-source library that optimizes how large language models run. By using this tech, Baseten has helped its customers see a 2x improvement in throughput and cut the time-to-first-token in half. These kinds of details show just how technical the platform is and the engineering skill needed to make it sing.

A detailed look at Baseten pricing

Baseten operates on a pay-as-you-go model, charging you for the computing resources you use. This is pretty standard for infrastructure platforms and works well for technical teams who can keep a close eye on their usage. For a business department, though, this model can create unpredictable costs that are a nightmare for budgeting.

Baseten Model APIs pricing

If you use Baseten's ready-to-go models, you're charged per million tokens processed (both for what you send in and what you get back).

Model	Input (per 1M tokens)	Output (per 1M tokens)
GLM 4.6	$0.60	$2.20
GPT OSS 120B	$0.10	$0.50
DeepSeek V3.1	$0.50	$1.50
Kimi K2 0905	$0.60	$2.50

Note: Prices are based on public information from September 2025 and are subject to change. For the latest numbers, you should always check the official Baseten pricing page.

Baseten dedicated deployments pricing

When you deploy your own models, the pricing switches to a per-minute bill based on the GPU or CPU instance you're running.

GPU Instance	Specs	Price (per minute)
T4	16 GiB VRAM, 4 vCPUs	$0.01052
A10G	24 GiB VRAM, 4 vCPUs	$0.02012
A100	80 GiB VRAM, 12 vCPUs	$0.06667
H100	80 GiB VRAM, 26 vCPUs	$0.10833
B200	180 GiB VRAM, 28 vCPUs	$0.16633

Note: Prices are based on public information from September 2025 and are subject to change. Again, head to the official Baseten pricing page for the most current rates.

For a business function like customer service, this per-minute GPU cost is a wild card. Imagine a sudden flood of support tickets, that would translate directly to a spike in your infrastructure bill. This is where you see a big difference with tools like eesel AI, which offers clear, fixed monthly pricing with no surprise fees per resolution. That predictability makes it much easier to budget for AI and grow your support team without worrying about costs spiraling out of control.

Who is Baseten for?

Figuring out who Baseten is actually for is the key to knowing if it's the right fit for you. For most business teams, there are far more practical options out there.

The ideal Baseten customer

Baseten is made for a technical audience: machine learning engineers, data scientists, and developers whose work revolves around AI. It's the right tool for companies that are all-in on building their own AI apps or need a powerful, scalable way to deploy open-source models.

You can see this in their customer list, which includes companies like Writer and Patreon. These are tech-savvy organizations with strong in-house engineering teams that need a robust backend for their AI products.

Why Baseten isn't for most business teams

The main catch with Baseten is that it’s infrastructure, not a finished product. A Head of Support can't just log into Baseten and start automating tickets. The road to get there would be long, complicated, and very expensive.

It would look something like this:

1. First, you'd need to hire a team of pricey machine learning engineers.

2. Then, they'd spend months building or fine-tuning an AI model just for your customer support needs.

3. Next, they would use a platform like Baseten to get that model running.

4. Finally, you’d need ongoing engineering resources to keep an eye on the model and the infrastructure.

That’s easily a 6 to 12-month project, which just isn't realistic for most business departments that need to solve a problem now.

The Baseten alternative: AI applications that work out of the box

For business leaders, the smarter move is an application-specific AI platform that deals with all that underlying complexity for you. These platforms are built to solve one particular problem, like customer support, and they’re ready to go from day one.

A perfect example for customer service and internal help desks is eesel AI. Instead of building from the ground up on infrastructure like Baseten, you get a tool that starts adding value immediately.

The difference in approach is pretty stark. With Baseten, you're signing up for a long, resource-heavy engineering project. With eesel AI, it's way simpler: connect your knowledge sources, set up how you want the AI to behave, and you're off to the races.

Here’s what that actually means with eesel AI:

• Go live in minutes: You can connect your Zendesk, Confluence, and other tools with one-click integrations. No MLOps team or custom code needed.

• Genuinely self-serve: No need to sit through mandatory demos or deal with long sales cycles. You can sign up, configure your AI, test it on past tickets, and launch it all by yourself.

• You're in control: You get to decide exactly which tickets get automated and what the AI is allowed to do, which lets you roll it out gradually and safely.

The bottom line on Baseten: Infrastructure vs. application

Baseten is a fantastic and necessary platform for the builders of the AI world, the technical teams creating the next wave of AI products. It gives them the raw power and control they need to run complex models at scale.

But it’s important to know the difference: Baseten gives you the engine, but most businesses just need the car. For a specific job like automating customer support, an application-focused solution is faster, cheaper, and a whole lot more practical. The right tool really just depends on your goal: are you building a new AI product from scratch, or are you trying to solve a business problem today?

This video explains how Baseten helps companies deploy and scale their AI models more efficiently.

Ready to automate support without the engineering headache?

If you want to deploy an AI agent that learns from your existing knowledge and plugs right into your helpdesk in minutes, check out eesel AI. It delivers powerful support automation without the MLOps complexity. You can start a free trial and see for yourself.