Dedicated model · Available as managed deployment

Kokoro text-to-speech in Europe: managed deployment

Kokoro is an 82-million-parameter open-weight text-to-speech model with natural voices, fast enough for real-time use, under Apache-2.0. Available as a managed deployment: validated on AxForge hardware and deployed on a DGX Spark for your traffic only, as an OpenAI-compatible endpoint on hardware only you use, hosted in the EU.

Available as managed deployment eu-es-1 · Málaga Text → speech kokoro.axforge.ai
Request deployment Qwen3.8 27B, on the API now Hour, week, month or year. Hardware from €0.85/hour; managed service quoted per deployment.

Why Kokoro

What you get

Real-time on one machine82M parameters: a dedicated DGX Spark synthesises speech many times faster than real time, for many concurrent streams.
Natural voices, several languagesMultiple voices and languages in one small model, with quality close to models many times its size.
Apache-2.0Permissive weights: commercial use, no licence conversation, no per-character vendor pricing.

Specifications

The model

ModelKokoro by hexgrad
ModalitiesText → speech
Released2024-12
Popularity11.8M downloads / month on HuggingFace
LicenceOpen weights (Apache 2.0); commercial use permitted
AvailabilityAvailable as managed deployment, operated by AxForge on hardware reserved for you
HardwareNVIDIA DGX Spark (GB10, 128 GB unified memory), owned and operated by AxForge
RegionMálaga, Spain (eu-es-1)
PricingHardware from €0.85/hour, rental term: Hour, week, month or year. Managed service quoted per deployment. Request deployment and we confirm both in writing.

We publish only numbers we measure ourselves, and we haven't benchmarked this model on our nodes yet. For quality benchmarks, see the model card in the catalogue and the official card on HuggingFace.

Deployment

What "managed deployment" means

SystemA dedicated NVIDIA DGX Spark (GB10, 128 GB unified memory), reserved for you
Commercial modelHour, week, month or year. Hardware from €0.85/hour, managed service quoted per deployment
EndpointOpenAI-compatible /v1 on your own machine, only your traffic
LocationHosted in the EU: Málaga, Spain (eu-es-1)
Data handlingZero prompt retention, same policy as the serverless API

The model is validated on AxForge hardware and deployed on your system. After deployment, your endpoint speaks the OpenAI API with the model name you receive with the deployment.

Data & privacy

Zero prompt retention

Prompts and completions are processed in memory in the EU, not written to disk, not logged, not retained, and never used to train anything. We keep only request metadata (token counts, timestamps, status) for billing and operations. The full policy is at axforge.ai/privacy.

FAQ

Kokoro hosting: common questions

Is Kokoro on the AxForge serverless API?

Not on the serverless API. It is available as a managed deployment: validated on AxForge hardware and deployed on a DGX Spark for your traffic only. The serverless API serves Qwen3.8 27B.

How does Kokoro compare to Piper on the serverless API?

Piper is the lightweight TTS AxForge serves per character; Kokoro is the higher-quality option for a dedicated deployment where voice quality matters.

Which languages and voices does Kokoro support?

Several English voices plus other languages; AxForge lists the voices available in your build with the deployment.

How fast is Kokoro on your hardware?

We publish only numbers we measure ourselves, and we haven't benchmarked this model on our nodes yet. For quality benchmarks, see the official model card.

What does a dedicated Kokoro deployment look like?

A dedicated NVIDIA DGX Spark (GB10, 128 GB unified memory) rented by the hour, week, month or year, running Kokoro behind an OpenAI-compatible endpoint on your own machine, hosted in the EU with zero prompt retention.

What does EU Kokoro hosting cost?

Hardware from €0.85/hour, by the hour, week, month or year; the managed service is quoted per deployment. Request deployment and we confirm both in writing.

Ready to build on EU inference?

Request deployment Talk to an engineer

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