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Tensormux / Built around your SLA

Reliable inference.
Nothing hidden.

Your users depend on every response. We're building inference you can stake your product on, with your SLA at the center and every trade-off in the open.

Start buildingTalk about your SLA

We're burning our GPUs so you can build free.$250 in credits. No card.

Your users don't see your infrastructure.
They feel it.

In the answer that arrives on time. The conversation that flows without a pause. The agent that keeps going. The experience that earns their trust. That's what reliability means to us.

Building for the long run.
With people who believe in the mission.

Backed byEntrepreneurs FirstMember ofNVIDIA Inception Program
Reliability is the product

Your SLA.
Our responsibility.

We're building the most reliable, most transparent inference service in the market. Because the team behind your inference should care about your users as much as you do.

A slow response is a user kept waiting. A failed request is a broken experience. Your SLA represents a promise to real people. We build around that promise, from the first conversation to production.

Talk about your SLA
Built around your application
The principles we build by
Start withYour workload and latency budget
Plan forThe demand your users create
Pay attention toTail latency, not just averages
Stay accountable toThe SLA your product needs
Your requirements set the standard.
Trust, with the details attached

You deserve the
whole picture.

A fast number means little without knowing how it was measured. A short conversation, a long RAG context, and a burst of agent traffic ask different things of inference.

Our commitment is to make those differences visible: workload-specific benchmarks, disclosed quantization, and honest limits on what each result tells you.

An open record of our work

Reliability is earned over time.
We intend to show our work along the way.

Published engineering report

Zero failures. Half the latency budget. $0.32 a million tokens.

The setup, the measurements, and the limitations.

Read the full report
One published test. A starting point, not the whole story.
Run it your way

Reliable inference.
Your choice of home.

Start in the open. Grow into managed cloud.
Or bring everything to your own GPUs.

A fast path to your first token.

Build on a managed GPU pool. Start with an endpoint and scale usage as your application grows.

  • Managed GPU pool
  • Usage dashboard
  • Autoscaling included
  • Standard support
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Tensormux cloud
TensormuxInference
GPU 1
GPU 2
GPU 3
Shared GPU pool
Pay per tokenNo reserved capacity
Familiar by design

A new endpoint.
The same workflow.

Keep the SDK you already use. Connect your application to the gateway and build on a familiar, OpenAI-compatible API.

Follow the quickstart
import OpenAI from "openai"; const client = new OpenAI({  baseURL: "http://localhost:8080/v1",  apiKey: "not-used-for-oss-backends",}); const response = await client.chat.completions.create({  model: "llama-3.1-8b",  messages: [{ role: "user", content: "Hello, world." }],});
Built in the open

Good tools get better
when everyone can build.

Explore our open source

Tensormux Gateway

OpenAI-compatible routing, health-based failover, and observability you self-host.

Python

kernel-skills

A skill library that helps AI agents write, optimize, and debug CUDA and Triton kernels.

TypeScript

TensorPath

Inference-optimization control plane: pick the best GPU, backend, and quantization for a model.

Python
Built for the promise you make to your users.

Your workload.
Our commitment.

Start buildingTalk to the founders