My honest Sambanova Cloud review: Is it right for you?

Kenneth Pangan
Written by

Kenneth Pangan

Amogh Sarda
Reviewed by

Amogh Sarda

Last edited November 6, 2025

Expert Verified

In the middle of this AI gold rush, it seems like every company is desperate for more computing power. The whole conversation is about GPUs, but with constant shortages and crazy high costs, teams are starting to look for a better way. This is where SambaNova Systems comes in, a big player in the specialized AI hardware game, promising a faster, more efficient option.

Their platform, SambaNova Cloud, claims it can be up to 10x faster than traditional GPUs for certain AI jobs. But what does that actually mean for your business? This SambaNova Cloud review is a straightforward, no-fluff look at what the platform does, who it’s for, and whether it’s the right tool for you, or if a more direct, business-focused solution makes more sense.

What is SambaNova Cloud?

SambaNova Cloud is an AI platform built for one main thing: running huge AI tasks. Don't think of it like a general cloud provider like AWS or Google Cloud. It’s more like a specialized, high-performance engine. It runs on SambaNova's own custom hardware, the Reconfigurable Dataflow Unit (RDU), which was designed from the ground up for the unique way AI models work.

What they’re really offering is simple: faster and more efficient performance for popular open-source models like Llama 3 and DeepSeek compared to running them on standard GPUs. You can find it on the AWS Marketplace, which tells you it’s a tool for enterprise developers who are building custom AI applications on some serious infrastructure.

A deep dive into key features

Alright, let's get into the nuts and bolts of what makes SambaNova tick. The technology is impressive, but it also shines a light on who the platform is really for.

The secret sauce: Reconfigurable Dataflow Unit (RDU) architecture

SambaNova’s key innovation is its Reconfigurable Dataflow Unit, or RDU. Here's a simple way to think about it: while a GPU is a jack-of-all-trades that juggles lots of different tasks, an RDU creates a custom, super-optimized "assembly line" for a specific AI model. It maps out how data moves through the model and reconfigures the hardware to match that flow perfectly. This cuts down on the time wasted shuffling data between memory and processing cores, which is a massive bottleneck for GPUs.

This slick approach is how SambaNova can boast such big performance gains for AI inference. It’s a clever design, but it's also deeply technical and all about optimizing the very lowest level of the AI stack.

Support for top open-source models

A big plus for SambaNova Cloud is that it supports popular open-source Large Language Models (LLMs). The platform is fine-tuned to run models like Llama, DeepSeek, and Qwen. For any company trying to avoid getting locked into a proprietary ecosystem like OpenAI’s, this is a huge deal. It gives you the freedom to pick the best model for your specific job.

But let's be real, having access to powerful models is only half the story. You still need people in-house who know how to choose the right one, fine-tune it with your company’s data, and then build a usable application around it. The model is just the engine; you still have to build the rest of the car.

Built for enterprise developers

Everything about SambaNova’s product screams "for developers only." Features like "SambaManaged" (a ready-to-go solution for data centers) and secure AWS PrivateLink connections are designed for big companies with deep engineering benches. These are great tools for teams building custom AI apps from the ground up, who need a rock-solid foundation to build on.

This is where the difference between SambaNova and a platform like eesel AI becomes incredibly clear. While SambaNova gives you the raw engine, eesel AI gives you the entire car, ready to drive off the lot. Instead of messing with complex infrastructure, eesel AI has one-click integrations that connect right to the tools your team already lives in, like Zendesk, Slack, and Confluence. You can go from signing up to having a working AI agent in a few minutes, not a few months.

Performance and practical use cases

Speed is SambaNova’s main selling point, but how does that translate to actual value? And more importantly, who can really use it?

What about that 10x speed claim?

SambaNova says its RDU-powered platform can be "up to 10x faster than GPUs." Looking at customer reviews on the AWS marketplace, users are genuinely happy with the speeds. For its very specific job, running inference on massive, open-source models, the RDU architecture seems to deliver.

But you have to ask: what does that raw speed mean for an average business? For a customer support team, the processing speed of the LLM is just one small piece of the puzzle. An AI solution is only as good as its workflow automation, its integrations, its ability to pull context from different places, and its accuracy. After all, a fast wrong answer is still a wrong answer.

SambaNova's impressive AI inference speeds are explored in this video, offering a deeper look at the technology that challenges both Groq and Nvidia.

Who is SambaNova Cloud actually for?

The perfect SambaNova customer is a company with a dedicated team of AI and machine learning engineers. We're talking about AI-first companies, huge enterprises building their own AI tools, and research labs that are pushing the limits of what's possible.

Their own use cases tell the story. They work with financial firms building real-time trading tools and power "Deep Research" agents that have to chew through a ton of tokens to create detailed reports. These users are building highly customized apps from scratch and need the kind of foundational, high-performance horsepower that SambaNova provides.

The reality of building vs. buying

Using SambaNova Cloud is just the first step in what can be a long and expensive project. Once you have access to their fast hardware, your team still needs to:

  • Build the business logic for your application.

  • Develop and set up workflow automation.

  • Create a user interface for your employees or customers.

  • Figure out monitoring, reporting, and maintenance.

This is a multi-month project that requires a serious, ongoing investment in engineering talent.

This is where a "buy" solution like eesel AI just changes the entire equation. Instead of building from scratch, you get a complete, out-of-the-box AI Agent that plugs right into your help desk. It learns from your past tickets, knowledge bases, and other documents to give accurate, relevant answers. You can set it up and have it running in minutes, solving a real business problem on day one without writing a single line of code.

Pricing and user feedback

Cost and reputation matter. Let’s see how SambaNova holds up.

Pricing explained

According to their AWS Marketplace listing, SambaNova has a pay-as-you-go model based on how much you use it.

  • Model: Consumption-based

  • Usage Fee: $0.01 per "unit"

The first thing that probably jumps out at you is the vagueness of what a "unit" actually is. Is it a token? A query? An hour of processing time? This lack of clarity makes it almost impossible to predict costs. For any business running automated workflows or busy chatbots, this kind of consumption model can lead to bills that spiral out of control.

This is a world away from the clear and predictable pricing of eesel AI. Our plans are based on a fixed number of AI interactions per month, and we never charge you per resolution. This lets you set a budget and scale up your AI use without worrying about a nasty surprise at the end of the month.

FeatureSambaNova Cloudeesel AI
Pricing ModelConsumption-based (per "unit")Tiered subscription (fixed interactions/mo)
PredictabilityLow (costs can scale unpredictably)High (predictable monthly/annual cost)
Hidden FeesPotential for high costs with heavy useNone, no per-resolution fees
TrialDepends on AWS setup and commitmentFree trial with a self-serve setup

What employees and users are saying

Public reviews help paint a fuller picture.

On one hand, AWS users seem to love the platform. Reviews mention how "fast and effortless" it is to test models, and they're blown away by the speeds. This confirms that the tech itself is solid and lives up to its performance promises for its target audience of developers.

On the other hand, anonymous employee reviews on sites like Blind tell a different story. They bring up concerns about disorganized management, constant and chaotic strategy changes, and a struggle to actually bring their product to market effectively. While the engineers get high praise, the leadership and business strategy are questioned. For any company looking for a stable, long-term partner, that kind of internal instability can be a major red flag.

The verdict: Is SambaNova Cloud right for you?

So, what's the final call? The answer really depends on who you are and what you're trying to do.

SambaNova Cloud is a seriously powerful piece of tech for a very specific group: expert developers and ML engineers who need the absolute best performance to build custom AI applications from the ground up. If you have a team of engineers and a multi-month plan to build your own AI tool, it’s worth a look.

For most businesses, especially teams in support, IT, and operations, it's like buying a Formula 1 engine when what you really need is a car. The raw power is there, but you can't use it to get anywhere without building the entire vehicle around it.

A simpler, faster path to support automation with eesel AI

If you’re a Head of Support or an IT manager, you don't have the time or budget to kick off a massive infrastructure project. You need to solve today's problems, like cutting down ticket volume and making your agents more efficient, right now.

That’s where eesel AI comes in. We offer a platform built specifically for support automation that delivers real value in minutes, not months. Here’s how we're different:

  • Go live in minutes: Connect your help desk and knowledge sources with a few clicks and see results on the very first day.

  • Truly self-serve: You can set up, configure, and launch your AI agent all on your own. No mandatory sales calls or long demos needed.

  • Test with confidence: Our powerful simulation mode lets you test the AI on thousands of your past tickets, so you can see exactly how it will perform before it ever talks to a customer.

  • Unify all your knowledge: Train your AI on everything from past tickets and macros to articles in Confluence and Google Docs. This makes sure your AI has all the context it needs to give accurate, genuinely helpful answers.

A screenshot of the eesel AI simulation feature, which provides a safe testing environment and is a key part of this SambaNova Cloud review's comparison.
A screenshot of the eesel AI simulation feature, which provides a safe testing environment and is a key part of this SambaNova Cloud review's comparison.

Ready to see what an AI support platform built for teams like yours can actually do? Start your free eesel AI trial and automate your first tickets in minutes.

Frequently asked questions

SambaNova Cloud is an AI platform built on custom Reconfigurable Dataflow Unit (RDU) hardware specifically for running large AI tasks, particularly inference on popular open-source models. It acts as a specialized, high-performance engine for enterprise developers building custom AI applications.

The RDU is SambaNova’s custom hardware that creates highly optimized "assembly lines" for specific AI models by reconfiguring itself to match data flow. This design significantly reduces data shuffling bottlenecks common with GPUs, leading to substantial performance gains for AI inference.

The ideal customer for SambaNova Cloud is typically an AI-first company, a large enterprise with a dedicated team of AI and machine learning engineers, or a research lab. These organizations build highly customized AI applications from scratch and require foundational, high-performance computing.

The blog notes that SambaNova Cloud's pricing is consumption-based at $0.01 per "unit," but it highlights the vagueness of what a "unit" actually defines. This lack of clarity makes it challenging for businesses to accurately predict and budget for their AI operational costs.

While the raw speed is impressive for specific tasks like inference on massive models, for most businesses, raw processing speed is only one component of an effective AI solution. Overall business value also depends significantly on factors like workflow automation, integrations, context retrieval, and the accuracy of the AI's output.

Integrating SambaNova Cloud involves a multi-month engineering project that extends far beyond just accessing the fast hardware. Teams need to develop business logic, set up workflow automation, create user interfaces, and establish monitoring and maintenance protocols, requiring a significant ongoing investment in engineering talent.

Yes, while the technical performance receives high praise from AWS users, anonymous employee reviews on platforms like Blind raise concerns about disorganized management and chaotic strategy changes. This internal instability could be a significant consideration for companies seeking a stable, long-term technology partner.

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Kenneth Pangan

Writer and marketer for over ten years, Kenneth Pangan splits his time between history, politics, and art with plenty of interruptions from his dogs demanding attention.