--- title: "AuK and AuK-Flash | Micdrop" description: "AuK and AuK-Flash tested as the voice of a local call, and why they run seven times slower than they should on a 24 GB machine." url: "https://micdrop.dev/docs/ai-integration/local-models/explorations/auk" --- * [Getting Started](/docs/getting-started) * [Client (Browser)](/docs/client) * [Installation](/docs/client/installation) * [React Hooks](/docs/client/react-hooks) * [Start/Stop Call](/docs/client/start-stop-call) * [Pause/Resume Call](/docs/client/pause-resume-call) * [Mute/Unmute Call](/docs/client/mute-unmute-call) * [Call State](/docs/client/call-state) * [Display Conversation Messages](/docs/client/display-conversation-messages) * [Handling Tool Calls](/docs/client/handling-tool-calls) * [Device Management](/docs/client/devices-management) * [Voice Activity Detection (VAD)](/docs/client/vad) * [Turn Detection](/docs/client/turn-detection) * [Reducing Latency](/docs/client/latency) * [Error Handling](/docs/client/error-handling) * Utility Classes * [Mic](/docs/client/utility-classes/mic) * [MicdropClient](/docs/client/utility-classes/micdrop-client) * [MicRecorder](/docs/client/utility-classes/mic-recorder) * [Speaker](/docs/client/utility-classes/speaker) * [Client (React Native)](/docs/react-native) * [Installation](/docs/react-native/installation) * [Hooks and Call State](/docs/react-native/hooks) * [Audio Output and Devices](/docs/react-native/audio-output) * [Voice Activity Detection (VAD)](/docs/react-native/vad) * [Turn Detection](/docs/react-native/turn-detection) * [Using Another Audio Library](/docs/react-native/custom-audio) * [Server (Node.js)](/docs/server) * [Installation](/docs/server/installation) * [With Fastify](/docs/server/with-fastify) * [With NestJS](/docs/server/with-nestjs) * [Auth and Parameters](/docs/server/auth-and-parameters) * [First Message](/docs/server/first-message) * [Dictation and Text-Only Calls](/docs/server/dictation) * [Partial Messages](/docs/server/partial-messages) * [Save Messages](/docs/server/save-messages) * [Resume a Conversation](/docs/server/resume-conversation) * [Recording Audio](/docs/server/recording-audio) * [Error Handling](/docs/server/error-handling) * [Tools](/docs/server/tools) * [Extract Value from Answer](/docs/server/extract) * [Auto End Call](/docs/server/auto-end-call) * [Semantic Turn Detection](/docs/server/semantic-turn-detection) * [Noise Filtering](/docs/server/noise-filtering) * [Micdrop Protocol](/docs/server/protocol) * [AI Integrations](/docs/ai-integration) * Provided Integrations * [AI SDK](/docs/ai-integration/provided-integrations/ai-sdk) * [Cartesia](/docs/ai-integration/provided-integrations/cartesia) * [ElevenLabs](/docs/ai-integration/provided-integrations/elevenlabs) * [Gladia](/docs/ai-integration/provided-integrations/gladia) * [Gradium](/docs/ai-integration/provided-integrations/gradium) * [Kokoro](/docs/ai-integration/provided-integrations/kokoro) * [Mistral](/docs/ai-integration/provided-integrations/mistral) * [OpenAI](/docs/ai-integration/provided-integrations/openai) * [Piper](/docs/ai-integration/provided-integrations/piper) * [Pocket TTS](/docs/ai-integration/provided-integrations/pocket-tts) * [Qwen3-TTS](/docs/ai-integration/provided-integrations/qwen-tts) * [Whisper](/docs/ai-integration/provided-integrations/whisper) * Custom Integrations * [Agent (LLM)](/docs/ai-integration/custom-integrations/custom-agent) * [Speech-to-Text (STT)](/docs/ai-integration/custom-integrations/custom-stt) * [Text-to-Speech (TTS)](/docs/ai-integration/custom-integrations/custom-tts) * Fallback Strategies * [FallbackAgent](/docs/ai-integration/fallback-strategies/agent-fallback) * [FallbackSTT](/docs/ai-integration/fallback-strategies/stt-fallback) * [FallbackTTS](/docs/ai-integration/fallback-strategies/tts-fallback) * [Local Models](/docs/ai-integration/local-models) * [Local LLM](/docs/ai-integration/local-models/agent) * [Local STT](/docs/ai-integration/local-models/speech-to-text) * [Local TTS](/docs/ai-integration/local-models/text-to-speech) * [Latency and Memory](/docs/ai-integration/local-models/performance) * [Explorations](/docs/ai-integration/local-models/explorations) * [MiniCPM5-2B](/docs/ai-integration/local-models/explorations/minicpm) * [Mistral 7B](/docs/ai-integration/local-models/explorations/mistral-7b) * [Voxtral Mini 3B](/docs/ai-integration/local-models/explorations/voxtral-stt) * [Voxtral TTS 4B](/docs/ai-integration/local-models/explorations/voxtral-tts) * [AuK and AuK-Flash](/docs/ai-integration/local-models/explorations/auk) * [IA Vocale Souveraine 🇫🇷🇪🇺](/docs/ai-integration/sovereign-voice-ai) * [Migration](/docs/migration) * [Upgrade to v3](/docs/migration/v3) [Micdrop](/) › [Documentation](/docs/getting-started) › [AI Integrations](/docs/ai-integration) › [Local Models](/docs/ai-integration/local-models) › [Explorations](/docs/ai-integration/local-models/explorations) # AuK and AuK-Flash Tested as the voice. AuK first looked very slow, but most of that came from its inference script using too much memory. Once that is fixed, the same weights run seven times faster. AuK is a speech model released by Tencent in September 2026, with 1.5 billion parameters, under an MIT license that covers the weights. Besides text to speech, it edits recordings (emotion, accent, spoken words), separates music from voice, and generates a voice from an instruction. AuK-Flash is the distilled version. Tencent says it is 4.5 times faster, with four sampling steps instead of thirty-two and no classifier-free guidance. It needs Python, PyTorch and three checkpoints, because it reads its instruction through a multimodal encoder that it does not ship: Checkpoint On disk AuK 6.3 GB AuK-Flash 6.3 GB Qwen2.5-Omni-3B 11 GB A Mac has no CUDA, so both models ran with `--device mps` on a MacBook Pro M2, on the same three second sentence. With the code as published, AuK-Flash took 3 minutes 27 and AuK took 3 minutes 11. The distilled model was slower although it does a quarter of the sampling work. The expected cost is much lower: the sampling network has 1.1 billion parameters and runs over 190 tokens for four steps, about 3.4 TFLOP, which a GPU rated at 3.6 TFLOPS in `fp32` should process in about one second. Profiling showed the time moving between phases from one run to the next: 110 seconds in the text encoder in one run, 86 seconds in the VAE decoder in another, for the same total. This points to memory pressure rather than to one slow operation. The pipeline used **21.3 GB** of memory on a 24 GB laptop. The cause is one line in `AukInfer`. The Qwen encoder is loaded in `bf16`, then the constructor converts the whole model, encoder included, to `fp32`: ``` thinker = Qwen2_5OmniThinkerForConditionalGeneration.from_pretrained( text_encoder_config.text_encoder_path, torch_dtype=torch.bfloat16,)# ... later, over the whole CFMEdit, encoder includedmodel = model.to(torch.float32) ``` Keeping the 3 billion parameter encoder in `bf16` brings memory down to 13.8 GB and makes generation 7 times faster. Whisper still transcribes both outputs word for word: Model Sampling Held Generation, as shipped Generation, encoder in `bf16` AuK 32 steps, CFG 21.3 GB 3 min 11 54 s AuK-Flash 4 steps 21.3 GB 3 min 27 27 s With the memory fixed, AuK-Flash is twice as fast as AuK. One sampling step takes 1 to 1.5 seconds, and the first step also compiles the Metal kernels. Forcing the `bf16` autocast that the code reserves for CUDA made generation slower, 48 seconds instead of 27, and `fp16` produced NaN in the latent. On Metal, `fp32` is the fastest option. Three seconds of speech in 27 seconds is still 9 times slower than real time, so AuK is not usable for a call on this machine. The next test would be a GPU with enough memory to run the whole model in `fp32`, as the code expects. Two limits would remain on such a GPU. AuK needs the duration of the audio before generating it, through `gen_seconds` or an estimate from a reference text, while a call only knows the sentence. And it returns the whole utterance at once, without streaming, so the wait before the first word equals the time to generate the whole answer. [Previous← Voxtral TTS 4B](/docs/ai-integration/local-models/explorations/voxtral-tts)[NextIA Vocale Souveraine 🇫🇷🇪🇺 →](/docs/ai-integration/sovereign-voice-ai)