en tiempo real end-un-end voz y visión conversacional AI supporting duplex audio transmisión y instant visual fundamentación.
Technical Specifications
- Provider
- Alibaba
- Category
- flagship
- Release Date
- 2025-01
- Batch API Discount
- 50% off async batch
- Consumer Subscription
- API Pay-as-you-go
- Reasoning Effort Control
- Fixed
- Structured Outputs
- Yes
- Output Modalities
- text, audio
- Official Documentation
- Visit Official Docs ↗
Data Privacy, Licensing & Deployment Governance
Official Provider Release Intelligence, API Quotas & Agentic Specs
- Official API Model ID (SDK String)
- qwen-omni-turbo-instruct
- Supported SDK & API Protocol
- Alibaba REST API (OpenAI-Compatible)
- Lifecycle & Deprecation Status
- Active GA (Guaranteed support through 2027+)
- Production Rate Limits (RPM & TPM)
- 5,000 – 15,000 RPM (Production Tier) · 800,000 – 2,000,000 TPM
- Long-Context Pricing Tier (>128K / >200K)
- Flat rate ($0.3/1M in) across full 33K window
- Prompt Cache Write & TTL Policy
- Cached input at $0.03/1M tokens
- Computer Use & Browser GUI Agent
- Supported (Screen coordinate grounding, browser & desktop GUI action loops)
- MCP & Parallel Tool Calling
- Native MCP Client/Server ready · Parallel function calling · 100% Strict JSON Schema
- Web Search Grounding & Code Sandbox
- Supported via external Tavily/Exa Search & E2B/Docker Sandbox tools
- Fine-Tuning & Distillation Support
- API Prompt Engineering & RAG Distillation
- Multimodal Tokenization Billing
- Text BPE (~4 chars/token) · Vision (~258–765 tokens per image tile) · Audio (~25–32 tokens/sec)
- Weights Precision & Quantization
- Cloud-Hosted Proprietary (FP8 / BF16 Tensor Core Cluster)
- Minimum GPU VRAM Requirement
- Zero Local VRAM Required (100% Serverless Cloud API)
- Supported Inference Engines
- Managed Alibaba Cloud API
- System Card & Safety Framework
- Alibaba Production Safety & Alignment Verified
- Enterprise Compliance (SOC2 / HIPAA / ZDR)
- SOC2 Type II · GDPR · Zero Data Retention (ZDR) & HIPAA BAA Available on Enterprise Tier
Qwen-Omni Turbo Cost, Context, Hardware & API Integration
For single-user chat, a $20/mo subscription caps your bill below this API volume.
Break-even point: ~358 requests/day equals $20/month.
Same Monthly Workload Cost Across Popular Reference Models
Live Prompt Paste Tokenizer & Cost Counter
Paste real system instructions, JSON schemas, or code to measure BPE token counts across tokenizers.
Hybrid Prompt Routing Cascade Simulator
Route routine queries to a fast lightweight model ($0.15/1M) and escalate only complex reasoning turns to Qwen-Omni Turbo:
Benchmark Scores & 6-Axis Capability Radar
- MMLU-Pro
- 69%
- HumanEval
- 76%
- Chatbot Arena Elo
- 1235pts
Strengths
- nativo completo-duplex voz-un-voz interaction sin separate TTS canalizaciones
- sub-400ms voz response latencia para natural phone-like conversations
- Concurrent visual scene perception y vocal dialogue
Limitations & Trade-offs
- ventana de contexto limitado un 32K tokens un maintain bajo-latencia audio buffering
- complejo codificación y técnico STEM precisión es menor que texto-solo flagships
Editorial Assessment
de Alibaba direct answer un GPT-4o voz, ofreciendo nativo multimodal conversación un bajo costo.
Best for: en tiempo real voz cliente agentes, interactivo tutors, y hands-free smart devices
Compare Qwen-Omni Turbo
Frequently Asked Questions about Qwen-Omni Turbo
How much does the Qwen-Omni Turbo API cost per 1M tokens?+
Qwen-Omni Turbo by Alibaba is priced at $0.3 per 1M input tokens and $1.2 per 1M output tokens. With prompt caching enabled, cached input tokens cost $0.03 per 1M tokens, and asynchronous Batch API requests receive a 50% discount.
Should I use a $20/month subscription or the Qwen-Omni Turbo pay-as-you-go API?+
A flat $20/month consumer subscription is predictable for daily interactive chat and manual coding. However, if you are building software, running automated workflows, or sending low-to-moderate volume with prompt caching enabled, the pay-as-you-go API is typically far more cost-effective and offers higher rate limits without manual UI caps.
How many words and pages fit in Qwen-Omni Turbo's context window?+
Qwen-Omni Turbo features a 33K tokens context window, which equals approximately 24,576 English words or ~66 standard single-spaced pages in a single prompt. Its maximum output generation per turn is 8,192 tokens.
Can I run Qwen-Omni Turbo locally on my own GPU (Open Weights)?+
No, Qwen-Omni Turbo is a proprietary closed-weights model hosted by Alibaba. It cannot be downloaded for local GPU execution and must be accessed via Alibaba's official API or cloud platform.
Does Alibaba train on data sent to the Qwen-Omni Turbo API, and is commercial use allowed?+
API payloads are excluded from model training by default. License tier: Proprietary Commercial API (Alibaba Terms). Full commercial ownership of generated outputs. Supported deployment channels include: Alibaba Cloud API & Enterprise Endpoints.
How does Qwen-Omni Turbo perform on coding and reasoning benchmarks?+
Qwen-Omni Turbo achieves a composite Intelligence Index of 74/100, scoring N/A% on SWE-bench Verified, N/A% on GPQA Diamond, 69% on MMLU-Pro, and 1235 pts on Chatbot Arena Elo.
What is Qwen-Omni Turbo best used for?+
Qwen-Omni Turbo is best suited for: en tiempo real voz cliente agentes, interactivo tutors, y hands-free smart devices. Assessment: de Alibaba direct answer un GPT-4o voz, ofreciendo nativo multimodal conversación un bajo costo.
Alibaba Family Lineage, Routing Tiers & Upgrade Path
Step down to a lighter sibling for high-volume routing or step up to Alibaba's flagship reasoning tier:
Qwen3.8 Max Preview
Qwen3.7 Plus
Qwen3.7 Max
Qwen3.6 Max Preview
Qwen3.6 Plus
Qwen3.6 Flash
AI Glossary & Architecture Concepts
View full glossary →Key machine learning concepts and benchmarks relevant to Qwen-Omni Turbo:
La unidad básica de texto que procesa un modelo de lenguaje, que normalmente equivale a 3 o 4 caracteres o aproximadamente 0,75 palabras. Por ejemplo, una frase típica se divide en varios tokens.
Un conjunto estandarizado de pruebas para evaluar y comparar objetivamente las capacidades de distintos modelos de IA en tareas como programación (SWE-bench) o matemáticas avanzadas (AIME).
La cantidad máxima de tokens que un modelo puede considerar a la vez, incluyendo tanto la entrada que lee como la salida que genera. Una ventana de 1.000.000 de tokens puede procesar unas 750.000 palabras en una sola petición.
La capacidad de un modelo de detectar la necesidad de una función externa y emitir argumentos JSON estructurados para ejecutar API, búsquedas web o consultas a bases de datos.
Un protocolo abierto desarrollado por Anthropic que permite a los agentes de IA conectarse de forma estandarizada a sistemas de archivos locales, entornos de desarrollo y servicios externos.
Una optimización donde los proveedores almacenan estados de atención previos para prefijos de prompts frecuentes, reduciendo el coste de entrada hasta en un 90% y acelerando la respuesta.
Las puntuaciones de benchmarks, precios por token y límites de tasa evolucionan rápidamente. Verifique siempre las especificaciones actuales en la documentación oficial del proveedor.