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Get started freeGPT-4o mini Audio vs Claude 3.5 Sonnet
Compare GPT-4o mini Audio and Claude 3.5 Sonnet. Build AI products powered by either model on Appaca.
Model Comparison
| Feature | GPT-4o mini Audio | Claude 3.5 Sonnet |
|---|---|---|
| Provider | OpenAI | Anthropic |
| Model Type | audio | text |
| Context Window | 128,000 tokens | 200,000 tokens |
| Input Cost | $0.15/ 1M tokens | $3.00/ 1M tokens |
| Output Cost | $0.60/ 1M tokens | $15.00/ 1M tokens |
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Build your first app freeStrengths & Best Use Cases
GPT-4o mini Audio
OpenAI1. Affordable multimodal audio model
- Extremely low-cost audio + text model for production-scale usage.
- Ideal for startups and high-volume traffic apps.
2. Fast real-time performance
- Low latency suitable for responsive voice assistants, AI phone bots, IVR flows, and audio chat apps.
- Great when speed matters more than deep reasoning.
3. Audio input and audio output
- Accepts raw audio (speech, recordings, commands).
- Generates natural audio responses via the REST API.
4. Large 128K context window
- Handles long conversations, transcriptions, and extended instructions.
- Supports multi-step voice workflows or multi-part inputs.
5. Great for lightweight reasoning workloads
- Performs well for classification, instructions, Q&A, rewriting, and audio-driven tasks.
- Good for voice agents that don't need high-end reasoning like GPT-5.1.
6. Works across major endpoints
- Chat Completions, Responses API, Realtime API, Assistants, Batch.
- Supports streaming and function calling.
7. Scalable for commercial production
- Perfect for customer support hotlines, appointment bots, FAQ voice agents, or embedded voice UI in apps.
- Reliable and predictable output behavior given its price.
8. Preview model designed for experimentation
- Lets teams prototype voice-first features with minimal cost.
- Useful stepping-stone before upgrading to GPT-4o Audio or GPT-5 audio models.
Claude 3.5 Sonnet
Anthropic1. Intelligence & Reasoning
- Outperforms previous Claude models and competitor LLMs across major benchmarks.
- Excels in graduate-level reasoning (GPQA), knowledge tasks (MMLU), and coding (HumanEval).
- Handles nuance, humor, and complex instructions with human-like clarity.
2. Speed & Efficiency
- Runs 2x faster than Claude 3 Opus, making it ideal for real-time and high-volume workflows.
- Cost-effective pricing: $3/M input tokens and $15/M output tokens.
- Supports a 200K token context window, enabling rich, long-form reasoning.
3. Coding Capabilities
- Solves significantly more coding and bug-fix tasks (64% vs Opus's 38% in internal evaluations).
- Can autonomously write, edit, and execute code when tool use is enabled.
- Strong at translating and modernizing legacy codebases.
4. Vision Strength
- Best vision model in the Claude family, surpassing Opus on vision benchmarks.
- Excellent at interpreting charts, graphs, and imperfect images.
- Reliable text extraction from low-quality visuals for retail, logistics, finance, etc.
5. Agentic Workflows
- Highly capable for multi-step task orchestration.
- Performs well as the engine for agents requiring reasoning, planning, and tool-calling abilities.
6. Content Quality
- Produces natural, relatable writing with improved tone, style, and context awareness.
- Strong at long-form content creation and editing.
7. Safety & Reliability
- Rated ASL-2, meeting Anthropic's safety standards.
- Undergoes extensive red-teaming and external evaluation (UK AISI & US AISI).
- Not trained on user data without explicit permission.
Prompts to Get Started
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