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LLM Comparisono3-miniGrok 4

o3-mini vs Grok 4

Compare o3-mini and Grok 4. Build AI products powered by either model on Appaca.

Model Comparison

Featureo3-miniGrok 4
ProviderOpenAIxAI
Model Typetexttext
Context Window200,000 tokens256,000 tokens
Input Cost
$1.10/ 1M tokens
$3.00/ 1M tokens
Output Cost
$4.40/ 1M tokens
$15.00/ 1M tokens

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Strengths & Best Use Cases

o3-mini

OpenAI

1. High-intelligence small reasoning model

  • Delivers strong reasoning performance in a compact footprint.
  • Ideal for tasks that need intelligence but must stay cost-efficient.

2. Excellent for developer workflows

  • Supports Structured Outputs, function calling, and Batch API.
  • Reliable for backend automation, agents, and data-processing pipelines.

3. Strong text reasoning capabilities

  • Handles multi-step logic, natural language analysis, SQL translation, entity extraction, and content generation.
  • Works well for landing pages, policy summaries, and knowledge extraction (as shown in built-in examples).

4. 200K context window

  • Allows large documents, multi-step analysis, and long-running conversations.
  • Reduces the need for aggressive chunking or external retrieval systems.

5. High 100K-token output limit

  • Enables long explanations, multi-section documents, or detailed reasoning sequences.

6. Pure text-focused model

  • Input/output is text-only (no image or audio support).
  • Optimized for language-heavy reasoning and logic tasks.

7. Broad API compatibility

  • Works across Chat Completions, Responses, Realtime, Assistants, Embeddings, Image APIs (as tools), and more.
  • Supports streaming, function calling, and structured outputs.

8. Cost-efficient for production at scale

  • Same cost/performance profile as o1-mini but with higher intelligence.

Grok 4

xAI

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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