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LLM ComparisonGPT-5 NanoGPT-4o Audio

GPT-5 Nano vs GPT-4o Audio

Compare GPT-5 Nano and GPT-4o Audio. Build AI products powered by either model on Appaca.

Model Comparison

FeatureGPT-5 NanoGPT-4o Audio
ProviderOpenAIOpenAI
Model Typetextaudio
Context Window400,000 tokens128,000 tokens
Input Cost
$0.05/ 1M tokens
$2.50/ 1M tokens
Output Cost
$0.40/ 1M tokens
$10.00/ 1M tokens

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Strengths & Best Use Cases

GPT-5 Nano

OpenAI

1. Extremely fast performance

  • Fastest model in the GPT-5 family.
  • Great for real-time workflows, rapid responses, and high-throughput systems.

2. Most cost-efficient GPT-5 model

  • Lowest input and output token costs.
  • Suitable for large-scale or budget-sensitive applications.

3. Ideal for lightweight, well-scoped tasks

  • Excels at summarization, classification, text extraction, and simple logic tasks.
  • Best used when tasks are narrow and well-defined.

4. Multimodal input

  • Accepts text + image as input.
  • Outputs text only.

5. Broad tool support

  • Supports Web Search, File Search, Image Generation (as a tool), Code Interpreter, and MCP.
  • (Does not support Computer Use.)

GPT-4o Audio

OpenAI

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.