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LatestKRAFTONRaon-Speech-21B-A3B
KRAFTONAny-to-Any

KRAFTON releases A.X-K2 Raon speech MoE model

The game maker's new open model blends text-to-speech and speech recognition in a single 21B mixture-of-experts system with just 3B active parameters.

Jul 27, 2026
NotableOther
A.X-K2 Raon Speech 21B-A3B

KRAFTON, the South Korean company best known as the studio behind PUBG, has published A.X-K2 Raon Speech 21B-A3B, an open speech model that handles both synthesis and recognition. The release is available now on Hugging Face.

The model is built as a mixture-of-experts system with roughly 21 billion total parameters but only about 3 billion active per token. That design lets a large model stay comparatively cheap to run at inference time, since only a fraction of its weights fire on any given pass — an approach that has become common in recent large language and multimodal releases.

One model, two directions

Rather than shipping separate systems for each task, Raon Speech aims to cover both ends of the speech pipeline in a single any-to-any architecture:

  • Text-to-speech (TTS) audio generation
  • Automatic speech recognition (ASR), or speech-to-text

Combining these capabilities is notable because most open speech stacks still rely on distinct specialized models. A unified system can simplify deployment and, in principle, share learned representations between listening and speaking.

The repository lists an "other" custom license, so teams evaluating the model for production should read the terms closely before building on it. KRAFTON has not published detailed benchmark figures alongside the initial release, so real-world quality across languages and audio conditions remains to be tested by the community. Still, the entry of a major game company into open speech modeling is a sign of how broadly the field is expanding beyond the usual AI labs.

Sources

  • KRAFTON/A.X-K2-Raon-Speech-21B-A3B

    Hugging Face

    Visit
OlderMicrosoft's Mage-VL Streams Video NativelyMicrosoft · Vision-Language · 3 months agoNewerLiquid AI ships a 350M encoder built for CPUsLiquidAI · Embeddings · 3 months ago

Get the model

Hugging Face

Specs

Parameters21B · MoE
Size42.4 GB
PrecisionBF16
ArchitectureRaonModel
LicenseOTHER
Downloads2.6K
Likes113

Can you run it?

Runs on a laptop — about 14.4 GB at 4-bit.

  • BF16 (as published)

    48 GB GPU (RTX 6000) or 2×24 GB · 64 GB Mac

    44.1 GB
  • 8-bit

    32 GB GPU (RTX 5090) · 48 GB Mac

    24.2 GB
  • 4-bit

    16 GB GPU (RTX 4080 / 5070 Ti) · 24 GB Mac

    14.4 GB
Your machine
  • Mixture-of-experts: all 21.2B parameters must be resident even though only 3B are active per token — active count affects speed, not memory.
  • KV cache approximated from model size (no config metadata) at 8,192 tokens.

Based on Hugging Face weights metadata. Assumes an 8K context and ~1 GB runtime overhead; actual needs vary. How we estimate


Modalities

Any-to-AnyText → SpeechSpeech → Text

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