o3 vs GPT-4o Audio
Compare pricing, context windows, and strengths for o3 by OpenAI and GPT-4o Audio by OpenAI - and see how to put either to work in Appaca.
o3
A powerful reasoning model excelling at complex, multi-step tasks across math, science, coding, and visual reasoning; succeeded by GPT-5.
View o3GPT-4o Audio
Preview multimodal model that accepts and outputs audio, optimized for natural voice interactions and real-time conversational experiences.
View GPT-4o Audioo3 vs GPT-4o Audio at a glance
Specs and pricing side by side, from the Appaca AI models directory.
| Spec | o3 | GPT-4o Audio |
|---|---|---|
| Provider | OpenAI | OpenAI |
| Model type | Text | Audio |
| Context window | 200K tokens | 128K tokens |
| Input price | $2 / 1M tokens | $2.5 / 1M tokens |
| Output price | $8 / 1M tokens | $10 / 1M tokens |
| Audio input price | - | $40 / 1M tokens |
| Audio output price | - | $80 / 1M tokens |
| Status | Current | Current |
How o3 and GPT-4o Audio differ
What the numbers mean in practice when choosing between o3 and GPT-4o Audio.
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o3 is 20% cheaper on input tokens ($2 vs $2.5 per million), which adds up quickly in document-heavy workloads.
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o3 is 20% cheaper on output tokens ($8 vs $10 per million) - the bigger factor for tools that generate long documents.
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o3's 200K tokens context window is roughly 1.6x larger than GPT-4o Audio's 128K tokens, so it can work across bigger codebases, contracts, or archives in one pass.
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These are different kinds of model: o3 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.
o3
1. Advanced reasoning capability
- Designed for multi-step thinking across text, code, and visual inputs.
- Excels at math, science, logic puzzles, and complex analytical workflows.
2. Strong performance across domains
- Highly capable in technical writing, data analysis, and structured problem-solving.
- Useful for research, engineering tasks, and intricate instruction-following.
3. Visual reasoning support
- Accepts image inputs, enabling tasks such as diagram analysis, chart interpretation, and visual logic assessments.
4. High output capacity
- Up to 100,000 output tokens, supporting long-form content, technical breakdowns, and multi-part solutions.
5. Excellent instruction following
- Produces detailed, step-by-step responses for tasks requiring precision and clarity.
- Ideal for educational explanations, system design reasoning, and code walkthroughs.
6. Large 200K context window
- Handles long documents, multi-file reasoning, or extended conversations with minimal loss of context.
7. Broad API support
- Works with Chat Completions, Responses, Realtime, Assistants, Batch, Embeddings, Image Generation, and more.
- Supports streaming and function calling for advanced workflows.
8. Positioned as a legacy reasoning model
- Remains extremely capable but formally succeeded by GPT-5, which offers stronger reasoning and performance.
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 o3 or GPT-4o Audio - or both
Appaca is the AI workspace for operators. Build internal tools and AI co-workers powered by o3 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 o3 or GPT-4o Audio. No code, no API keys, no deployment.
Switch models without rebuilding
Start on o3, 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 o3 or GPT-4o Audio - connected to the tools you already use.
Related comparisons
See how o3 and GPT-4o Audio stack up against other models in the directory.
FAQs
o3 is generally cheaper: $2 input / $8 output per million tokens, versus $2.5 / $10 for GPT-4o Audio. Actual cost depends on how many tokens your workload reads and writes.
o3 has the larger context window at 200K tokens, compared to 128K tokens for GPT-4o Audio. A larger window means the model can consider more text at once - useful for long contracts, codebases, or months of records.
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 o3, 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 o3, 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 o3 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.