GPT-4o Audio vs Claude 3.5 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. Intelligence & Benchmark Performance

• Matches Claude 3 Opus (previous largest model) on many intelligence tasks.
• Surpasses Claude 3 Opus on multiple evaluations despite being a smaller, faster model.
• Major improvements across every skill category vs previous Haiku.

2. Coding Strength

• Scores 40.6% on SWE-bench Verified, outperforming:

  • Claude 3.5 Sonnet (original version)
  • GPT-4o
  • Many agent-driven systems

• Excellent for engineering assistants, agent coding tasks, and bug fixing.

3. Speed & Latency

• Same speed class as Claude 3 Haiku (ultra-fast).
• Ideal for real-time interactions, high request volumes, and UI responsiveness.

4. Tool Use & Instruction Following

• Better at following instructions than previous Haiku.
• Stronger at tool use accuracy, making it reliable for agents and workflows.

5. Best Use Cases

• High-volume, low-latency tasks
• User-facing products
• Sub-agent tasks in larger workflows
• Processing large structured datasets (pricing, inventory, purchase history)
• Rapid content or code generation where speed matters