GPT-4o Audio vs Grok 4

Compare GPT-4o Audio and Grok 4. Find out which one is better for your use case.

Model Comparison

FeatureGPT-4o AudioGrok 4
ProviderOpenAIxAI
Model Typeaudiotext
Context Window128,000 tokens256,000 tokens
Input Cost$2.50 / 1M tokens$3.00 / 1M tokens
Output Cost$10.00 / 1M tokens$15.00 / 1M tokens

Strengths & Best Use Cases

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.

Grok 4

1. Flagship-level reasoning and math performance

  • Designed for world-class reasoning depth, precision, and multi-step logical chains.
  • Excels at STEM, mathematics, symbolic operations, proofs, and analytical workloads.

2. Powerful multimodal understanding

  • Supports text, images, and other modalities.
  • Handles cross-modal reasoning tasks requiring context synthesis.

3. Extreme capability across diverse tasks

  • Positioned as a top-tier 'jack of all trades' model.
  • Strong in natural language, coding, knowledge retrieval, and structured generation.

4. Large 256K context window

  • Enables analysis of long documents, entire codebases, multi-document packs, and extensive agent sessions.
  • Supports workloads that require persistent reasoning across large inputs.

5. Advanced developer tooling support

  • Function calling for tool-augmented workflows.
  • Structured outputs for predictable, schema-controlled generation.
  • Integrates smoothly with agents and complex automation pipelines.

6. Efficient caching for cost reduction

  • Cached input tokens discounted to $0.75 / 1M tokens.
  • Encourages RAG, retrieval pipelines, and multi-step conversational workflows.

7. Production-ready performance

  • Stable rate limits: 480 requests per minute.
  • High token throughput: 2,000,000 tokens per minute.
  • Available across multiple xAI regional clusters.

8. Optional Live Search augmentation

  • Add-on: $25 per 1K sources.
  • Enhances factual accuracy and real-time information retrieval.

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