--- title: "Local STT | Micdrop" description: "Which Whisper checkpoint to run locally, and why a checkpoint tied to one language beats a heavier generic one." url: "https://micdrop.dev/docs/ai-integration/local-models/speech-to-text" --- * [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) # Local STT Whisper is the local option, running inside the Node process through [@micdrop/whisper](/docs/ai-integration/provided-integrations/whisper). Choose the checkpoint mainly by the language of the call, not by its size. Checkpoint Languages Download On a 3 second sentence Word errors in French `tiny` Around a hundred ~45 MB ~320 ms Not measured `base` Around a hundred ~85 MB ~440 ms 25% `small` Around a hundred ~250 MB ~1000 ms 22% `turbo` Around a hundred ~850 MB ~3800 ms 17% `french` French ~390 MB ~1100 ms 2% Word errors were measured on five French sentences with proper nouns, numbers and homophones. Latencies were measured on a MacBook Pro M2, on CPU, with the model loaded. ## Choosing the checkpoint Whisper always processes a 30 second window, whatever the length of the sentence, so a larger checkpoint makes every sentence slower, short ones included. A larger checkpoint is more accurate in English. For other languages, a checkpoint fine-tuned on that language is both more accurate and faster than a larger generic one. The `french` checkpoint is as fast as `small`, and more accurate in French than `turbo`, which is twice as large and 3 times slower. It also writes numbers in words instead of digits, which the voice needs. The generic `base` checkpoint gets a quarter of the words of a French sentence wrong. The [Whisper page](/docs/ai-integration/provided-integrations/whisper) gives the repository behind each shorthand, and how to pick a checkpoint fine-tuned on another language. ## Naming the language Set `language` when you know the language of the call. It skips language detection and avoids a wrong guess on a short sentence. ``` new WhisperSTT({ model: 'french', language: 'fr',}) ``` ## Where it runs On a Mac, transcription runs on the CPU. Transformers.js has no GPU device there, and the CoreML provider was slower than the CPU on these models. The [latency and memory](/docs/ai-integration/local-models/performance) page has the measurements and the options for Windows and Linux. ## What was measured and set aside [Voxtral Mini 3B](/docs/ai-integration/local-models/explorations/voxtral-stt) transcribes more accurately than Whisper `base`, but is 35 times slower per utterance. [Previous← Local LLM](/docs/ai-integration/local-models/agent)[NextLocal TTS →](/docs/ai-integration/local-models/text-to-speech) On this page * [Choosing the checkpoint](#choosing-the-checkpoint) * [Naming the language](#naming-the-language) * [Where it runs](#where-it-runs) * [What was measured and set aside](#what-was-measured-and-set-aside)