1. Affordable multimodal audio model

• Extremely low-cost audio + text model for production-scale usage.
• Ideal for startups and high-volume traffic apps.

2. Fast real-time performance

• Low latency suitable for responsive voice assistants, AI phone bots, IVR flows, and audio chat apps.
• Great when speed matters more than deep reasoning.

3. Audio input and audio output

• Accepts raw audio (speech, recordings, commands).
• Generates natural audio responses via the REST API.

4. Large 128K context window

• Handles long conversations, transcriptions, and extended instructions.
• Supports multi-step voice workflows or multi-part inputs.

5. Great for lightweight reasoning workloads

• Performs well for classification, instructions, Q&A, rewriting, and audio-driven tasks.
• Good for voice agents that don't need high-end reasoning like GPT-5.1.

6. Works across major endpoints

• Chat Completions, Responses API, Realtime API, Assistants, Batch.
• Supports streaming and function calling.

7. Scalable for commercial production

• Perfect for customer support hotlines, appointment bots, FAQ voice agents, or embedded voice UI in apps.
• Reliable and predictable output behavior given its price.

8. Preview model designed for experimentation

• Lets teams prototype voice-first features with minimal cost.
• Useful stepping-stone before upgrading to GPT-4o Audio or GPT-5 audio models.

1. State-of-the-art reasoning

• Top performance across academic reasoning, scientific knowledge, math, and complex problem-solving.
• Excels at long-horizon, multi-step workflows and deep logical interpretation.

2. World-leading multimodal capabilities

• Natively understands text, images, videos, audio, and code.
• Ranked highest on benchmarks like MMMU-Pro, Video-MMMU, ScreenSpot-Pro.

3. Exceptional coding + agentic workflows

• Strong in competitive coding and real-world agentic tasks (SWE-Bench Verified, Terminal-Bench, LiveCodeBench).
• Improved tool calling, planning, and execution for autonomous or semi-autonomous agents.

4. Powerful for long-context tasks

• Effective at 128K-1M context windows with high retrieval accuracy.
• Ideal for document-heavy workflows, research, analysis, multi-file coding, and multi-document reasoning.

5. Strong information synthesis and interpretation

• Outperforms peers in chart reasoning, OCR, structured extraction, and screen understanding.
• Excellent at combining multimodal inputs into coherent, concise answers.

6. High reliability for enterprise tasks

• Benchmarks show superior factuality, grounding, and parametric knowledge.
• Strong multilingual accuracy and global commonsense performance.

7. Optimized for production agents

• Designed for complex multi-step planning, simultaneous task execution, and improved consistency.
• Works across coding, research, creative workflows, UI generation, and data-heavy applications.