.wave

Founded by Thomas Minassian in 2025

Run continuous inference for real-time voice and streaming speech models

Pricing model

Demo

Rating

★ Mixed Reviews

Time to value

Requires Expertise

You can use .wave to run stateful real-time artificial intelligence models that process live inputs throughout continuous sessions. It provides infrastructure for low-latency streaming speech recognition and full-duplex conversational voice interactions. The system maintains GPU state across recurring session steps rather than treating each input as an isolated request. You can access pre-hosted models through the live API or run custom continuous models on managed GPU deployments, achieving significantly higher concurrent session capacity without dropping audio frames or missing strict timing deadlines.

What .wave does

Deploy live audio streaming models to productionConnect client voice streams to full-duplex AI modelsTranscribe real-time incoming audio streams without latencyScale concurrent speech sessions per GPUMonitor session timing contracts to prevent audio frame dropsRun managed inference infrastructure for custom stateful modelsContinuous GPU kernel keeping model state active between framesFull-duplex conversational voice inference APIReal-time streaming speech-to-text processingGuaranteed timing contracts for recurring audio sessionsHigher concurrent session density per graphics processing unitManaged private deployments for custom continuous models

Pricing breakdown

Pricing model: Book a demo

Tutorials & Demos

Frequently asked

Hugging Face

Want a tailored answer?

See whether .wave fits your stack.

Techbible weighs .wave against what you already pay for, your team shape, and the work that's actually happening. Free to start.

Side by side

Compare .wave

Search the catalog or pick a similar tool to compare pricing, features, and fit.

Or pick from similar tools

More in AI Hosting & Inference

All tools →

Groq

Run open-source language models and machine learning inference at high speeds

Modal

Run serverless AI model training, inference, and batch jobs on cloud GPUs

Ollama

Run open large language models locally on your machine or in the cloud

AI Infrastructure For Developers • Beam

Run sandboxes, inference, and training with ultrafast boot times, instant autoscaling, and a developer experience that just works.

Cerebras

Run high-speed artificial intelligence model inference and training on wafer-scale chips

Cerebrium

Deploy and scale machine learning models on serverless GPUs with pay-per-second pricing

Clockwork Systems, Inc.

Keep distributed machine learning workloads running through GPU and network hardware failures

CloudRift

Manage and virtualize private GPU clusters for enterprise model training and inference