GPT-4o vs GPT-4o Audio
Compare pricing, context windows, and strengths for GPT-4o by OpenAI and GPT-4o Audio by OpenAI - and see how to put either to work in Appaca.
GPT-4o
A versatile, high-intelligence flagship GPT model that handles text and image inputs and produces fast, high-quality text outputs for a wide range of tasks.
View GPT-4oGPT-4o Audio
Preview multimodal model that accepts and outputs audio, optimized for natural voice interactions and real-time conversational experiences.
View GPT-4o AudioGPT-4o vs GPT-4o Audio at a glance
Specs and pricing side by side, from the Appaca AI models directory.
| Spec | GPT-4o | GPT-4o Audio |
|---|---|---|
| Provider | OpenAI | OpenAI |
| Model type | Text | Audio |
| Context window | 128K tokens | 128K tokens |
| Input price | $2.5 / 1M tokens | $2.5 / 1M tokens |
| Output price | $10 / 1M tokens | $10 / 1M tokens |
| Audio input price | - | $40 / 1M tokens |
| Audio output price | - | $80 / 1M tokens |
| Status | Current | Current |
How GPT-4o and GPT-4o Audio differ
What the numbers mean in practice when choosing between GPT-4o and GPT-4o Audio.
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Both models cost the same on input: $2.5 per million tokens.
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Both models offer the same 128K tokens context window.
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These are different kinds of model: GPT-4o is a text model while GPT-4o Audio is an audio model, so they often complement each other in a workflow rather than compete.
Strengths side by side
Where each model shines, according to benchmarks and provider positioning.
GPT-4o
1. High-intelligence, general-purpose model
- Strong reasoning, creativity, summarization, and problem-solving.
- Great balance of speed, accuracy, and cost.
2. Multimodal input support
- Accepts text + image inputs for visual reasoning, extraction, or description.
- Output is text only, making it predictable for production.
3. Excellent for structured and unstructured tasks
- Performs well on Q&A, writing, analysis, classification, chat, and planning.
- Supports Structured Outputs, making it suitable for deterministic workflows.
4. Strong tool-use capabilities
- Supports function calling, API orchestration, and tool-augmented workflows.
- Integrates well with assistants, batch operations, and automation pipelines.
5. Large context for complex tasks
- 128K context allows multi-document reasoning, multi-step conversations, and large input payloads.
6. Production-ready reliability
- Stable outputs, predictable behaviors, and broad modality coverage.
- Supported across all major API endpoints.
7. Lower latency than o-series reasoning models
- Faster responses due to no dedicated reasoning step.
- Ideal for interactive or near-real-time applications.
8. Fine-tuning and distillation supported
- Enables specialization for domain-specific tasks.
- Distillation helps create smaller, efficient custom models.
GPT-4o Audio
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.
Use GPT-4o or GPT-4o Audio - or both
Appaca is the AI workspace for operators. Build internal tools and AI co-workers powered by GPT-4o or GPT-4o Audio - connected to your real data and ready for your whole team. No code, no deployment.
Describe it, and it's built
Tell the Appaca agent the internal tool you need and it builds a working app powered by GPT-4o or GPT-4o Audio. No code, no API keys, no deployment.
Switch models without rebuilding
Start on GPT-4o, test the same tool on GPT-4o Audio, and keep whichever performs better - the rest of your app stays exactly as it is.
Automated for the whole team
Schedule tools to run on autopilot - daily digests, weekly reports, real-time triggers - and share them with your whole team from one workspace.
Describe it, and it's built
Tell the Appaca agent what your team needs and it builds a working app powered by GPT-4o or GPT-4o Audio - connected to the tools you already use.
Related comparisons
See how GPT-4o and GPT-4o Audio stack up against other models in the directory.
FAQs
They cost the same overall: both charge $2.5 per million input tokens and $10 per million output tokens.
They are equal: both GPT-4o and GPT-4o Audio support a 128K tokens context window.
It depends on the job. Compare the pricing, context window, and strengths above against your workload - and remember the choice isn't permanent. In Appaca you can build a tool on GPT-4o, test the same tool on GPT-4o Audio, and switch at any time without rebuilding anything.
Yes. Appaca is a no-code AI workspace: describe the internal tool your team needs and the Appaca agent builds it as a working app powered by GPT-4o, GPT-4o Audio, or any other model in the directory - with a built-in database, team access, and integrations. No API keys to wire up and nothing to deploy.
Build AI tools with GPT-4o or GPT-4o Audio
Describe the tool your team needs and get a working app powered by the model you choose - with a built-in database, team access, and integrations. No code, no deployment.