| name | groq-core-workflow-b |
| description | Use when you need Groq's non-chat endpoints — transcribing or translating
audio with Whisper, understanding images with Llama 4 vision, generating
speech (TTS), or benchmarking models for speed vs quality.
Trigger with phrases like "groq whisper", "groq transcription",
"groq audio", "groq vision", "groq TTS", "groq speech".
|
| allowed-tools | Read, Bash(npm:*) |
| version | 1.11.0 |
| license | MIT |
| author | Jeremy Longshore <jeremy@intentsolutions.io> |
| tags | ["saas","groq","workflow","audio","vision"] |
| compatibility | Designed for Claude Code, also compatible with Codex and OpenClaw |
Groq Core Workflow B: Audio, Vision & Speech
Overview
Beyond chat completions, Groq offers ultra-fast Whisper transcription (216x real-time), Llama 4 vision, and text-to-speech — all on the same groq-sdk client. This skill covers transcription/translation, vision, TTS, and model benchmarking, with full runnable code in references/implementation.md and worked scripts in references/examples.md.
Prerequisites
groq-sdk installed, GROQ_API_KEY set (the SDK reads it from the environment automatically)- For audio: audio files in a supported format
- For vision: image URLs or base64-encoded images
Audio Models
| Model ID | Languages | Speed | Best For |
|---|
whisper-large-v3 | 100+ | 164x real-time | Best accuracy, multilingual |
whisper-large-v3-turbo | 100+ | 216x real-time | Best speed/accuracy balance |
Supported audio formats: flac, mp3, mp4, mpeg, mpga, m4a, ogg, wav, webm
Instructions
Each workflow is a single SDK call on the shared groq client. Pick the endpoint for your task, then follow the full walkthrough in references/implementation.md for the complete, copy-pasteable version of each.
- Transcription —
groq.audio.transcriptions.create({ file, model: "whisper-large-v3-turbo", response_format }). Use response_format: "verbose_json" with timestamp_granularities: ["segment"] to get per-segment start/end times.
- Translation —
groq.audio.translations.create({ file, model: "whisper-large-v3" }) transcribes any-language audio directly to English text.
- Vision — a normal
groq.chat.completions.create call where content is an array mixing { type: "text" } and { type: "image_url" } parts. Accepts up to 5 images (URL or data: base64) with meta-llama/llama-4-scout-17b-16e-instruct.
- Text-to-Speech — , then write to a file.
