GPT-4o Audio vs Claude 3 Haiku

1. True multimodal audio model

• Accepts raw audio as input and produces audio or text as output.
• Enables hands-free, voice-first app experiences.

2. Natural real-time speech interaction

• Low-latency audio generation suitable for conversational agents.
• Great for voice assistants, phone bots, and interactive voice UI.

3. Large 128K context window

• Supports long conversations, call transcripts, instructions, or multi-part interactions.
• Ideal for building persistent voice agents or phone workflows.

4. High-output capacity

• Up to 16,384 max output tokens for extended responses or long explanations.
• Suitable for complex reasoning tasks in voice format.

5. Hybrid text + audio workloads

• Combine audio input/output with text prompts, instructions, or structured control.
• Useful for customer support bots, spoken form systems, IVR replacements, etc.

6. Compatible with the latest APIs

• Works with Chat Completions, Responses API, Realtime API, and Assistants.
• Supports streaming, function calling, and advanced developer tooling.

7. Strong performance for a preview model

• High reasoning and expression abilities relative to most audio-capable models.
• Designed for production-style experimentation prior to full release.

8. Ideal for next-gen voice applications

• Build lifelike AI agents, interview bots, tutoring systems, and spoken knowledge tools.
• Perfect for startups building audio-first user experiences.

1. Speed

• Fastest model in the Claude 3 family
• Near-instant responses for chat, support, and live tools

2. Efficiency

• Most affordable model
• Ideal for massive-scale applications and low-latency use cases

3. Practical Use Cases

• Customer support
• Translations
• Moderation
• Logistics, inventory systems
• Extracting insights from unstructured data

4. Vision Skills

• Handles charts, images, and diagrams quickly
• Useful for scanning large volumes of visual data