Models / OpenAI / / Whisper Large v3 (Streaming) API
Whisper Large v3 (Streaming) API

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Whisper Large v3 enables realtime voice agent applications with WebSocket streaming transcription on Together AI. Purpose-built infrastructure combines OpenAI's 1.55B parameter model with intelligent voice activity detection and turn detection, delivering complete transcripts 1.4 seconds faster than alternatives. Supports 99 languages with 10-20% error reduction compared to v2. Ideal for conversational AI, customer support bots, and any application requiring natural, low-latency voice interaction.
Whisper Large v3 (Streaming) API Usage
Endpoint
How to use Whisper Large v3 (Streaming)
Model details
Architecture Overview:
• Transformer-based encoder-decoder model with 1.55B parameters
• Uses 128 Mel frequency bins instead of 80 (key improvement over v2)
• Trained on 1M hours weakly labeled + 4M hours pseudo-labeled audio
• WebSocket-based streaming architecture eliminating connection overhead
• Supports 99 languages with strong zero-shot generalization
• Advanced voice activity detection (VAD) using carefully tuned detection thresholds
Streaming Methodology:
• Trained for 2.0 epochs on massive multilingual dataset
• Weakly supervised learning on large-scale noisy data
• Demonstrates 10-20% error reduction compared to Whisper Large v2
• Strong performance across diverse languages, accents, and domains
• Purpose-built infrastructure for realtime audio processing with minimal quality degradation
Streaming Performance Characteristics:
• Industry-leading 2488ms baseline response time (1.4 seconds faster than alternatives)
• Processes audio as it arrives rather than waiting for complete files
• Intelligent turn detection determining when users finish speaking
• Optimized for time-to-complete-transcript not just time-to-first-token
• 500ms silence threshold tuning for natural conversation pacing
• Minimal quality degradation compared to batch processing
• Consistent low-latency performance under production load
• WebSocket connection multiplexing for efficient resource utilization
• Geographic distribution ensuring low latency regardless of user location
Prompting Whisper Large v3 (Streaming)
Applications & Use Cases
Voice Agent Applications:
• Customer support automation with natural conversation flow
• Interactive voice response (IVR) systems with realtime understanding
• Voice-enabled chatbots and virtual assistants
• Healthcare appointment scheduling and patient intake
• Financial services customer authentication and account management
Realtime Communication:
• Live meeting transcription with immediate accessibility
• Real-time translation services for multilingual conversations
• Voice-to-text note-taking during calls and meetings
• Live captioning for broadcasts and presentations
Enterprise Contact Centers:
• AI agent handling hundreds of simultaneous customer calls
• Call routing based on realtime speech understanding
• Agent assist tools providing realtime suggestions
• Quality monitoring with live transcription and analysis
Conversational AI Platforms:
• Voice interface for LLM-powered applications
• Multi-turn dialogue systems requiring low latency
• Voice-controlled smart home and IoT devices
• Hands-free voice interfaces for accessibility
High-Volume Deployments:
• SaaS platforms offering voice capabilities to customers
• Contact center software handling enterprise-scale call volumes
• Voice agent platforms requiring consistent sub-second performance
• Applications where response latency directly impacts user satisfaction
