More throughput per |

Your AI Stack, Fully Optimized

The best GPU for your next project is the one you already have.
Zymtrace squeezes more FLOPs from your infrastructure.
Profile-guided, agentic optimization for AI workloads.

Zero Friction Deploy
Cluster-Wide
Self-Hosted

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Maximize Tokens Per Dollar

Faster Inference.
Lower Cost.

Improve throughput, reduce latency, and lower cost-per-token across your inference fleet. Correlate token-level performance metrics with CPU and GPU profiles to pinpoint exactly what's stalling your inference engines.

vLLM

SGLang

Dynamo-triton

Powering Efficient AI

Find What's Stalling Your Training Runs

Distributed training bottlenecks compound fast. Identify performance bottlenecks across GPUs and AI accelerators by correlating hardware profiles with the CPU dispatch paths driving them, surfacing AllReduce stalls, memory transfer saturation, and batching inefficiencies. Works with NVIDIA CUDA, AWS Inferentia, PyTorch, JAX & Rust.

One zymtrace agent to zym them all!

Frictionless whole-system visibility across all major languages

Drop in zymtrace agent and identify the most expensive lines of code across your entire fleet —your code, third-party libs, interpreted or native, running on CPU or GPU. If it's using cycles, we help you improve its efficiency.

Reduce mean-time-to dopamine

Curated Insights

Most profilers throw flamegraphs at you and expect you to decode them. zymtrace's "Efficiency IQ" tells you exactly what's happening and shows you precisely what to do about it.

How it works

Zero instrumentation. Super low overhead continuous profiler

Step 1: Easy Installation

Deploy zymtrace in minutes with zero code changes. Available for Docker, Kubernetes, and as a binary.

Step 2: Intelligent Analysis

Our advanced analytics engine processes data to provide actionable insights, recommendations, and potential fixes.

Step 3: Optimize and Save

Implement our suggestions to optimize your system, reduce operational costs, and lower your carbon footprint.

OpenTelemetry Compliant

zymtrace is OpenTelemetry compliant, including support for OTEL resource attributes.

Fun Fact

The zymtrace team were part of the team that pioneered, open-sourced, and donated the eBPF profiler to OpenTelemetry. With zymtrace, we’re extending that same low-level engineering excellence to GPU-bound workloads and building a highly scalable profiling platform purpose-built for today’s distributed, heterogeneous environments — spanning both general-purpose and AI-accelerated workloads.

View OpenTelemetry eBPF Profiler

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Frequently asked questions

Is there a SaaS version of zymtrace?

Currently, only on-premises version is supported. If you're interested in a SaaS version, please contact us at support@zymtrace.com

Does zymtrace support only GPUs?

zymtrace is a whole-system profiler for any application, not just GPU code. While profiling, it automatically checks if the machine has an NVIDIA GPU. If one is present, it also detects CPU operations that launch GPU work and provides performance visibility into their interactions.

Is there support for TensorFlow?

Our current focus is on NVIDIA CUDA and PyTorch frameworks. If you have a specific use case for TensorFlow, we'd be happy to discuss it with you. support@zymtrace.com

Is Windows OS supported?

zymtrace is currently limited to Linux machines. We heavily utilize eBPF, which is not yet well-supported on Windows.

What is the performance overhead of the agent?

zymtrace is designed to operate within a minimal resource footprint, targeting just 1% CPU usage and less than 250MB of RAM. This efficiency allows for 24/7 operation on most workloads without noticeably impacting the profiled systems. For particularly resource-sensitive environments, zymtrace can be configured with lower sampling rates, providing valuable insights while further reducing its performance impact. The agent profiles itself so you can clearly see the overhead.

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