diff --git a/README.md b/README.md
index 637f129..61a25ee 100644
--- a/README.md
+++ b/README.md
@@ -12,6 +12,7 @@ Bild- und Sprachausgabe. **Hermes und die Fach-MCPs laufen auf Unraid.**
 - Profile Router auf Port 8081
 - FLUX.2-klein-4B für Textbilder und Referenzbild-Bearbeitung auf der RTX 5080
 - XTTS auf der RTX 3060 mit Piper als CPU-Fallback
+- Whisper.cpp `large-v3-turbo` auf der CPU für lokale deutsche Spracherkennung
 - Live-Dashboard mit 21 Tagen Detailhistorie auf Port 8099
 - Portainer CE als optionale Container-Ansicht auf Port 9443
 - WireGuard-Gateway, Datenbackup und Athena-Operator
@@ -98,6 +99,11 @@ Standard, bis Hermes' Sitzungsfehler behoben ist.
 
 - Router: `http://192.168.1.212:8081/v1`
 - Athena-Dashboard: `http://192.168.1.212:8099`
+
+Der Router stellt Sprache OpenAI-kompatibel bereit: Sprachausgabe über
+`/v1/audio/speech` und Spracherkennung über `/v1/audio/transcriptions`. Das
+Whisper-Modell liegt persistent im Docker-Volume `whisper-data`; Audiodaten
+werden lokal auf Athena verarbeitet.
 - Portainer: `https://192.168.1.212:9443`
 - Hermes-Dashboard auf Unraid: `http://192.168.1.2:9119`
 
diff --git a/compose.yaml b/compose.yaml
index 0bd9a0f..ebd1d00 100644
--- a/compose.yaml
+++ b/compose.yaml
@@ -545,7 +545,9 @@ services:
       TTS_MODEL: piper
       TTS_VOICES: alloy
       TTS_DEFAULT_VOICE: alloy
-      ENABLE_STT: "false"
+      ENABLE_STT: "true"
+      STT_WORKER_URL: http://whisper:8084
+      STT_TIMEOUT: "300"
     networks: [frontend, control, inference]
     security_opt: ["no-new-privileges:true"]
     cap_drop: [ALL]
@@ -569,6 +571,8 @@ services:
         condition: service_healthy
       tts-gateway:
         condition: service_healthy
+      whisper:
+        condition: service_healthy
 
   image-worker:
     build:
@@ -710,6 +714,39 @@ services:
       retries: 12
       start_period: 10s
 
+  whisper:
+    build:
+      context: .
+      dockerfile: platform/docker/whisper/Dockerfile
+      args:
+        WHISPER_CPP_VERSION: ${WHISPER_CPP_VERSION:-v1.9.1}
+    image: mike-ai/whisper:local
+    container_name: mike-ai-whisper
+    restart: unless-stopped
+    read_only: true
+    tmpfs:
+      - /tmp:size=2g,mode=1777
+    volumes:
+      - whisper-data:/models
+    environment:
+      WHISPER_HOST: 0.0.0.0
+      WHISPER_PORT: "8084"
+      WHISPER_CLI: /opt/whisper.cpp/build/bin/whisper-cli
+      WHISPER_MODEL: /models/ggml-large-v3-turbo.bin
+      WHISPER_MODEL_URL: ${WHISPER_MODEL_URL:-https://huggingface.co/ggerganov/whisper.cpp/resolve/main/ggml-large-v3-turbo.bin}
+      WHISPER_THREADS: ${WHISPER_THREADS:-8}
+      WHISPER_LANGUAGE: ${WHISPER_LANGUAGE:-de}
+    networks: [frontend, inference]
+    security_opt: ["no-new-privileges:true"]
+    cap_drop: [ALL]
+    cap_add: [CHOWN, SETUID, SETGID]
+    healthcheck:
+      test: [CMD, curl, -fsS, "http://127.0.0.1:8084/status"]
+      interval: 10s
+      timeout: 5s
+      retries: 90
+      start_period: 20m
+
   llama-dashboard:
     build: ./platform/llama-dashboard
     image: mike-ai/llama-dashboard:local
@@ -809,6 +846,7 @@ networks:
 
 volumes:
   piper-data:
+  whisper-data:
   router-state:
   router-images:
   portainer-data:
diff --git a/docs/ARCHITECTURE.md b/docs/ARCHITECTURE.md
index 77f5e22..6fdba27 100644
--- a/docs/ARCHITECTURE.md
+++ b/docs/ARCHITECTURE.md
@@ -8,6 +8,7 @@ flowchart LR
     P --> Q[genau ein llama.cpp-Profil<br/>Qwen Fast / Medium / Large / Ultra / Uncensored]
     R --> I[FLUX.2-klein-4B<br/>RTX 5080, Text + Editing]
     R --> T[XTTS RTX 3060<br/>Piper CPU-Fallback]
+    R --> STT[Whisper.cpp large-v3-turbo<br/>CPU, lokale Spracherkennung]
 
     H --> U[MUA / Unraid MCP]
     H --> A[ARR-MCP]
diff --git a/docs/CURRENT_RUNTIME_NOTES.md b/docs/CURRENT_RUNTIME_NOTES.md
index 62bbdbe..2bd1b2c 100644
--- a/docs/CURRENT_RUNTIME_NOTES.md
+++ b/docs/CURRENT_RUNTIME_NOTES.md
@@ -2,6 +2,19 @@
 
 Stand: 3. September 2026
 
+## Lokale Spracherkennung
+
+Athena betreibt Whisper.cpp v1.9.1 mit `large-v3-turbo` als CPU-Dienst. Der
+Profile Router veröffentlicht ihn als OpenAI-kompatiblen Endpunkt
+`/v1/audio/transcriptions`; Standardsprache ist Deutsch. Modell und Download
+bleiben im persistenten Docker-Volume `whisper-data` erhalten.
+
+Ein lokaler Rundlauftest (Athena-TTS → WAV → Athena-STT) wurde erfolgreich
+durchgeführt. OpenClaw ist ebenfalls auf diesen lokalen Endpunkt eingestellt
+und wurde mit `openclaw infer audio transcribe` erfolgreich geprüft. Für den
+lokalen Provider ist der Zugriff auf Athenas private IP ausdrücklich erlaubt;
+andere private Ziele werden dadurch nicht freigeschaltet.
+
 ## Produktive llama.cpp-Runtime
 
 Alle Textprofile verwenden llama.cpp Build 10781,
diff --git a/platform/docker/whisper/Dockerfile b/platform/docker/whisper/Dockerfile
new file mode 100644
index 0000000..8c2925f
--- /dev/null
+++ b/platform/docker/whisper/Dockerfile
@@ -0,0 +1,35 @@
+FROM python:3.13.7-slim-bookworm
+
+ARG WHISPER_CPP_VERSION=v1.9.1
+
+RUN apt-get update \
+    && apt-get install -y --no-install-recommends \
+       build-essential ca-certificates cmake curl ffmpeg git gosu \
+    && git clone --branch "${WHISPER_CPP_VERSION}" --depth 1 \
+       https://github.com/ggml-org/whisper.cpp.git /opt/whisper.cpp \
+    && cmake -S /opt/whisper.cpp -B /opt/whisper.cpp/build \
+       -DCMAKE_BUILD_TYPE=Release \
+       -DGGML_NATIVE=ON \
+       -DWHISPER_BUILD_TESTS=OFF \
+       -DWHISPER_BUILD_SERVER=OFF \
+    && cmake --build /opt/whisper.cpp/build --config Release -j"$(nproc)" \
+    && apt-get purge -y --auto-remove build-essential cmake git \
+    && rm -rf /var/lib/apt/lists/* /root/.cache \
+    && useradd --system --uid 10004 --home-dir /nonexistent --shell /usr/sbin/nologin whisper
+
+WORKDIR /app
+COPY router/stt_worker.py /app/stt_worker.py
+COPY platform/docker/whisper/entrypoint.sh /usr/local/bin/mike-ai-whisper-entrypoint
+RUN chmod 0755 /usr/local/bin/mike-ai-whisper-entrypoint
+
+ENV WHISPER_HOST=0.0.0.0 \
+    WHISPER_PORT=8084 \
+    WHISPER_CLI=/opt/whisper.cpp/build/bin/whisper-cli \
+    WHISPER_MODEL=/models/ggml-large-v3-turbo.bin \
+    WHISPER_THREADS=8 \
+    WHISPER_LANGUAGE=de \
+    FFMPEG_BIN=/usr/bin/ffmpeg
+
+VOLUME ["/models"]
+EXPOSE 8084
+ENTRYPOINT ["/usr/local/bin/mike-ai-whisper-entrypoint"]
diff --git a/platform/docker/whisper/entrypoint.sh b/platform/docker/whisper/entrypoint.sh
new file mode 100644
index 0000000..2bf53eb
--- /dev/null
+++ b/platform/docker/whisper/entrypoint.sh
@@ -0,0 +1,25 @@
+#!/bin/sh
+set -eu
+
+model=${WHISPER_MODEL:-/models/ggml-large-v3-turbo.bin}
+model_url=${WHISPER_MODEL_URL:-https://huggingface.co/ggerganov/whisper.cpp/resolve/main/ggml-large-v3-turbo.bin}
+model_dir=$(dirname "$model")
+
+mkdir -p "$model_dir"
+chown 10004:10004 "$model_dir"
+
+if [ ! -s "$model" ]; then
+  partial="${model}.part"
+  echo "Downloading Whisper model to persistent storage"
+  # All writes below must use the volume owner. The container deliberately
+  # drops CAP_DAC_OVERRIDE, so even uid 0 cannot rename a file in the
+  # whisper-owned directory after capabilities have been removed.
+  if [ ! -s "$partial" ]; then
+    gosu whisper rm -f "$partial"
+    gosu whisper curl --fail --location --retry 5 --retry-delay 5 \
+      --output "$partial" "$model_url"
+  fi
+  gosu whisper mv "$partial" "$model"
+fi
+
+exec gosu whisper python /app/stt_worker.py
diff --git a/scripts/speech-roundtrip.py b/scripts/speech-roundtrip.py
new file mode 100644
index 0000000..4ac63c8
--- /dev/null
+++ b/scripts/speech-roundtrip.py
@@ -0,0 +1,70 @@
+#!/usr/bin/env python3
+"""End-to-end smoke test for Athena's OpenAI-compatible TTS and STT APIs."""
+
+import json
+import os
+import sys
+import urllib.request
+import uuid
+
+
+BASE_URL = os.environ.get("ROUTER_URL", "http://127.0.0.1:8081/v1").rstrip("/")
+API_KEY = os.environ.get("ROUTER_API_KEY", "")
+TEST_TEXT = "Dies ist ein lokaler Test der Spracherkennung auf Athena."
+
+
+def request(path: str, data: bytes, content_type: str) -> bytes:
+    req = urllib.request.Request(
+        f"{BASE_URL}{path}",
+        data=data,
+        headers={
+            "Authorization": f"Bearer {API_KEY}",
+            "Content-Type": content_type,
+        },
+        method="POST",
+    )
+    with urllib.request.urlopen(req, timeout=360) as response:
+        return response.read()
+
+
+def main() -> int:
+    if not API_KEY:
+        print("ROUTER_API_KEY is required", file=sys.stderr)
+        return 2
+
+    speech = request(
+        "/audio/speech",
+        json.dumps({
+            "model": "piper",
+            "voice": "alloy",
+            "response_format": "wav",
+            "input": TEST_TEXT,
+        }).encode(),
+        "application/json",
+    )
+
+    boundary = f"speech-{uuid.uuid4().hex}"
+    body = (
+        f"--{boundary}\r\n"
+        'Content-Disposition: form-data; name="model"\r\n\r\n'
+        "whisper-1\r\n"
+        f"--{boundary}\r\n"
+        'Content-Disposition: form-data; name="language"\r\n\r\n'
+        "de\r\n"
+        f"--{boundary}\r\n"
+        'Content-Disposition: form-data; name="file"; filename="test.wav"\r\n'
+        "Content-Type: audio/wav\r\n\r\n"
+    ).encode() + speech + f"\r\n--{boundary}--\r\n".encode()
+
+    result = json.loads(request(
+        "/audio/transcriptions",
+        body,
+        f"multipart/form-data; boundary={boundary}",
+    ))
+    transcript = result.get("text", "").strip()
+    print(transcript)
+    return 0 if transcript else 1
+
+
+if __name__ == "__main__":
+    raise SystemExit(main())