diff --git a/api-reference/server/services/stt/moonshine.mdx b/api-reference/server/services/stt/moonshine.mdx
new file mode 100644
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@@ -0,0 +1,138 @@
+---
+title: "Moonshine"
+description: "Speech-to-text service implementation using locally-downloaded Moonshine ONNX models"
+---
+
+## Overview
+
+`MoonshineSTTService` provides offline speech recognition using Moonshine's small, fast ASR models running locally on the CPU via ONNX Runtime. No GPU required, no API key needed - models download once on first use and are cached locally for privacy-focused transcription.
+
+
+
+ Pipecat's API methods for Moonshine STT integration
+
+
+ Complete example with Moonshine STT
+
+
+ Moonshine ASR model details and research
+
+
+ Python package for Moonshine models
+
+
+
+## Installation
+
+```bash
+uv add "pipecat-ai[moonshine]"
+```
+
+## Prerequisites
+
+### Local Model Setup
+
+Before using Moonshine STT service, you need:
+
+1. **Model Selection**: Choose appropriate Moonshine model size (tiny, base, small-streaming, medium-streaming)
+2. **Storage Space**: Ensure sufficient disk space for model downloads (models are cached after first use)
+3. **CPU Resources**: Moonshine runs efficiently on CPU via ONNX Runtime
+
+### Configuration Options
+
+- **Model Size**: Balance between accuracy and performance based on your needs
+- **Language Support**: Moonshine supports English, Spanish, and other languages
+- **No API Key**: Runs entirely locally for complete privacy
+
+
+ No API keys or GPU required - Moonshine runs efficiently on CPU for complete privacy.
+
+
+## Configuration
+
+
+ Runtime-configurable settings for the STT service. See [MoonshineSTTService Settings](#moonshinesttsettings) below.
+
+
+## MoonshineSTTSettings
+
+Runtime-configurable settings passed via the `settings` constructor argument using `MoonshineSTTService.Settings(...)`. These can be updated mid-conversation with `STTUpdateSettingsFrame`. See [Service Settings](/pipecat/fundamentals/service-settings) for details.
+
+| Parameter | Type | Default | Description |
+| ---------- | ----------------- | ------------------------ | --------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
+| `model` | `str \| Model` | `Model.SMALL_STREAMING` | Moonshine model architecture. Available models: `TINY`, `BASE`, `TINY_STREAMING`, `BASE_STREAMING`, `SMALL_STREAMING` (default), `MEDIUM_STREAMING`. |
+| `language` | `Language \| str` | `Language.EN` | Language for transcription. Moonshine supports English, Spanish, and other languages. The base language code is used (e.g., "en" from "en-US"). _(Inherited from base STT settings.)_ |
+
+## Usage
+
+### Basic Setup
+
+```python
+from pipecat.services.moonshine.stt import MoonshineSTTService
+
+stt = MoonshineSTTService()
+```
+
+### With Custom Model
+
+```python
+from pipecat.services.moonshine.stt import MoonshineSTTService, Model
+
+stt = MoonshineSTTService(
+ settings=MoonshineSTTService.Settings(
+ model=Model.MEDIUM_STREAMING,
+ ),
+)
+```
+
+### With Custom Language
+
+```python
+from pipecat.services.moonshine.stt import MoonshineSTTService, Model
+from pipecat.transcriptions.language import Language
+
+stt = MoonshineSTTService(
+ settings=MoonshineSTTService.Settings(
+ model=Model.SMALL_STREAMING,
+ language=Language.ES,
+ ),
+)
+```
+
+### With Model as String
+
+```python
+from pipecat.services.moonshine.stt import MoonshineSTTService
+
+stt = MoonshineSTTService(
+ settings=MoonshineSTTService.Settings(
+ model="base",
+ ),
+)
+```
+
+## Notes
+
+- **First run downloads**: The selected model downloads from the Moonshine model hub on first use and is cached locally. Later runs load it from the cache.
+- **Segmented transcription**: `MoonshineSTTService` extends `SegmentedSTTService`, meaning it processes complete audio segments after VAD detects the user has stopped speaking.
+- **CPU-only**: Moonshine runs efficiently on CPU via ONNX Runtime, so no GPU is required. This makes it ideal for resource-constrained environments.
+- **Audio format**: Expects 16-bit mono PCM audio at 16 kHz sample rate.
+- **Model variants**: The streaming-capable models (`TINY_STREAMING`, `SMALL_STREAMING`, `MEDIUM_STREAMING`) can be run in batch mode just like the non-streaming variants. The larger streaming models (`SMALL_STREAMING`, `MEDIUM_STREAMING`) are only available in streaming form.
+- **Language support**: Moonshine supports multiple languages (English, Spanish, and others). The service uses the base language code (e.g., "en" from "en-US").
+- **No external dependencies**: Unlike API-based STT services, Moonshine requires no API keys or network connectivity after the initial model download.
diff --git a/api-reference/server/services/supported-services.mdx b/api-reference/server/services/supported-services.mdx
index a5db9f10..3b7041aa 100644
--- a/api-reference/server/services/supported-services.mdx
+++ b/api-reference/server/services/supported-services.mdx
@@ -51,6 +51,7 @@ Speech-to-Text services receive and audio input and output transcriptions.
| [Gradium](/api-reference/server/services/stt/gradium) | `uv add "pipecat-ai[gradium]"` |
| [Groq (Whisper)](/api-reference/server/services/stt/groq) | `uv add "pipecat-ai[groq]"` |
| [Mistral](/api-reference/server/services/stt/mistral) | `uv add "pipecat-ai[mistral]"` |
+| [Moonshine](/api-reference/server/services/stt/moonshine) | `uv add "pipecat-ai[moonshine]"` |
| [NVIDIA](/api-reference/server/services/stt/nvidia) | `uv add "pipecat-ai[nvidia]"` |
| [OpenAI](/api-reference/server/services/stt/openai) | `uv add "pipecat-ai[openai]"` |
| [Sarvam](/api-reference/server/services/stt/sarvam) | `uv add "pipecat-ai[sarvam]"` |
diff --git a/docs.json b/docs.json
index 79af2cf1..4530159d 100644
--- a/docs.json
+++ b/docs.json
@@ -348,6 +348,7 @@
"api-reference/server/services/stt/gradium",
"api-reference/server/services/stt/groq",
"api-reference/server/services/stt/mistral",
+ "api-reference/server/services/stt/moonshine",
"api-reference/server/services/stt/nvidia",
"api-reference/server/services/stt/openai",
"api-reference/server/services/stt/sarvam",