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Unlock state-of-the-art AI performance with AMD MI355X, TensorWave, and Modular. Faster inference, lower costs, and freedom from vendor lock-in.

Enterprise AI at Scale: Performance and Efficiency with MI355X

The era of trade-offs is over. Performance, portability, and cost efficiency no longer come at each other’s expense, they move in sync. With Modular and TensorWave, enterprises can shift workloads from NVIDIA to AMD Instinct™ GPUs in minutes - no rewrites, no compromises - and tap into smarter scale at lower cost.

In this report, you’ll see results from running Modular’s MAX inference engine on AMD Instinct MI355X GPUs inside the TensorWave cloud, including:

 * MI355X benchmarking on MAX
 * Improved throughput
 * Total cost of ownership gains

By pairing TensorWave’s MI355X-powered cloud with Modular’s optimized MAX software, developers gain a drop-in solution that runs seamlessly across vendors. Portability here isn’t just technical, it’s strategic. It means freedom of choice, backed by top-tier performance and better economics. The way forward is clear: build on infrastructure designed for openness, speed, and scale.


TensorWave X Modular: A Shared Mission

The story starts with a simple belief: building AI should be open, affordable, flexible, and not tied to a single compute option. For too long, enterprises have been locked into a single ecosystem, where choice is limited, supply is constrained, and costs climb higher with every new generation of hardware. That model isn’t sustainable, not for startups, not for global enterprises, and not for the future of AI.

TensorWave and Modular are united in their mission to democratize compute and expand choice in GPU infrastructure. Enterprises shouldn’t have to compromise between performance and portability, or pay a monopoly premium just to stay competitive.

This is where the partnership comes in. TensorWave brings scale with a cloud built entirely on AMD Instinct™ GPUs. Modular provides MAX, a high-performance model serving framework that runs seamlessly across hardware vendors. AMD delivers the MI355X, a GPU designed to compete at the highest levels of performance while delivering better economics.

Together, this partnership creates a new standard of freedom for enterprises to build AI infrastructure on their own terms, powered by choice, performance, and efficiency.

The future of AI won’t be defined by lock-in. It will be defined by performance, scale, and choice. With AMD Instinct MI355X, TensorWave, and Modular, we’re building that future right now, proving that enterprises don’t have to wait to achieve state-of-the-art results.

-  Darrick Horton, CEO, TensorWave

Now let’s dive into what MAX on TensorWave cloud means for the builders: 




Easy Portability

Portability used to mean trade-offs. Have to rewrite code, rebuild pipelines, or lose performance just to make hardware changes. Those days are gone. With Modular’s MAX on TensorWave’s AMD Instinct MI355X cloud, portability becomes simple, fast, and reliable.

For developers, the experience couldn’t be easier. MAX uses the same CLI and workflow across GPU vendors, so moving from NVIDIA to AMD is as straightforward as running the same command in a new environment. No rewrites. No complex migrations. Just a seamless transition.

For enterprises, the value is immediate. Workloads that once took months to re-platform can now be migrated in minutes. That speed not only accelerates innovation but also empowers organizations to stay adaptable as technology evolves. Combined with TensorWave’s purpose-built AMD cloud, portability isn’t just a convenience, it’s a competitive edge.


Performance Without Compromise

At the end of the day, it’s all about performance. Enterprises don’t adopt new hardware because it’s portable, they adopt it because it makes their models run faster, scale bigger, and deliver results that were previously out of reach. That’s exactly what AMD Instinct MI355X GPUs, paired with Modular’s MAX inference engine, deliver.

On demanding workloads, MI355X is showing performance parity, and in some cases, clear advantages over NVIDIA’s B200. This means enterprises can run their largest and most complex models with confidence, without sacrificing throughput or latency.

The software layer amplifies this advantage. MAX consistently outperforms vLLM on MI355X, giving developers a framework tuned for speed and efficiency. That combination of world-class hardware with a purpose-built inference engine translates directly into enterprise outcomes: faster inference, smoother scaling, and more predictable cost structures.

And perhaps the most compelling proof point: these results were achieved in just two weeks. With TensorWave’s AMD-native cloud and Modular’s optimized software stack, state-of-the-art performance isn’t a long-term roadmap, it’s available right now.

Today's leading hardware deserves advanced software. What we’ve achieved with MI355X and MAX in just two weeks is proof that AMD hardware and Modular software delivers industry-leading results right now - and we are just getting started. Modular believes in an open ecosystem with Mojo, ROCm, and a vibrant ecosystem evolving together, giving enterprises the best performance and efficiency at all times.

- Chris Lattner, CEO, Modular


Proof in the Numbers

The following images were taken from the Modular x TensorWave presentation at AMD's Instinct ROCm Tech Media Day, September 2025


The Economics of Performance

Raw performance tells one part of the story. The other part, the one that determines enterprise adoption at scale, is cost efficiency. With AMD Instinct MI355X GPUs on TensorWave, enterprises get both.


Lower TCO

MI355X delivers competitive, and in many cases superior, performance compared to NVIDIA’s B200, at a lower hourly cost. That means teams can run the same models, achieve the same (or better) outcomes, and spend less doing it.


Efficiency Multiplier

When you look at performance per dollar, the advantage compounds. Every inference request goes further, every workload stretches budget more effectively. For organizations under pressure to deliver ROI, this is where AMD shines.


Workload-Specific Wins

Certain LLM workloads see dramatic efficiency gains on MI355X, where the combination of larger memory and optimized inference engines like MAX makes it possible to do more with fewer GPUs.

The bottom line: enterprises no longer have to choose between cutting-edge performance and sustainable economics. With MI355X on TensorWave, they get both.


Common Questions and Answers

Q: What if my team is using NVIDIA today?

A: With Modular MAX and TensorWave, migrating isn’t a months-long project. It’s minutes. MAX offers drop-in containers that let you run the same inference commands across vendors, giving your team immediate access to AMD Instinct MI355X GPUs without code rewrites.

Q: Do I lose performance by switching?

A: No. In fact, MAX on MI355X already delivers performance parity with NVIDIA’s B200 on key workloads, and in some cases, it outperforms it. Combined with lower cost per GPU hour, enterprises gain both performance and efficiency.

Q: Why does portability matter if performance is already strong?

A: Portability future-proofs your infrastructure. By avoiding vendor lock-in, enterprises gain the flexibility to adapt as hardware evolves, without paying the penalty of rewrites or migrations later.


Looking Ahead

What we’re seeing now is just the first glimpse of what’s possible. These early results show what’s possible when AMD’s latest hardware, TensorWave’s purpose-built AI cloud, and Modular’s inference engine come together. But the story doesn’t stop here.

Performance optimizations are ongoing, and every iteration of ROCm, MAX, and TensorWave infrastructure will push efficiency further, delivering even faster inference and stronger economics at scale. Cost efficiency will continue to improve as the ecosystem matures, making MI355X an even more compelling choice for enterprises looking to run the largest models without compromise.

This partnership is about giving your team the flexibility to use the best hardware and software for every stage of the AI lifecycle, from training to inference, without being locked into a single vendor's roadmap

In the weeks ahead, we’ll share deeper benchmarking reports, including workload-specific comparisons between MI355X and NVIDIA’s B200, so enterprises can see not just headline numbers but real-world outcomes.

The bigger picture: this partnership isn’t about a single release. It’s about building an open, flexible, high-performance AI infrastructure that will serve enterprises for years to come.


Closing Thoughts

The future of AI infrastructure isn’t locked into a single vendor. It’s open, high-performing, and cost-efficient, and it’s available today.

TensorWave’s AMD Instinct MI355X cloud, powered by Modular’s MAX inference engine, gives enterprises the ability to run the largest models with confidence, scale workloads seamlessly, and realize better performance at lower cost.

Don’t wait for optionality to become a necessity. Build on your terms now.

👉 Talk to our team to access MI355X clusters on TensorWave and see what performance, portability, and cost efficiency can do for your enterprise.


About TensorWave

TensorWave is the AI cloud purpose-built for performance. Powered exclusively by AMD Instinct™ Series GPUs, we deliver high-bandwidth, memory-optimized infrastructure that scales with your most demanding models - training or inference.

Ready to get started? Connect with a Sales Engineer.


About Modular

Modular is building AI’s unified compute layer, enabling developers to deploy production gen AI systems across any hardware in a matter of minutes. The Modular platform lets you run frontier models at blazing fast speed on AMD or NVIDIA GPUs, without the complexity of fragmented toolchains and with a software stack that just works.

Enterprise AI at Scale: Performance and Efficiency with MI355X

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