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LLM ComparisonGPT-5o3-mini

GPT-5 vs o3-mini

Compare GPT-5 and o3-mini. Build AI products powered by either model on Appaca.

Model Comparison

FeatureGPT-5o3-mini
ProviderOpenAIOpenAI
Model Typetexttext
Context Window400,000 tokens200,000 tokens
Input Cost
$1.25/ 1M tokens
$1.10/ 1M tokens
Output Cost
$10.00/ 1M tokens
$4.40/ 1M tokens

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Strengths & Best Use Cases

GPT-5

OpenAI

1. High reasoning capability

  • Designed for intelligent reasoning across complex domains.
  • Supports reasoning tokens and adjustable reasoning effort.

2. Strong coding and agentic performance

  • Optimized for multi-step coding tasks, tool-use chains, and agent workflows.
  • Handles complex logic, planning, and structured problem solving reliably.

3. Multimodal input

  • Accepts text + image as input.
  • Produces text outputs with strong instruction following.

4. Extensive tool support

  • Works with Web Search, File Search, Image Generation (as a tool), Code Interpreter, MCP, and more.
  • Integrated across Chat Completions, Responses API, Realtime, Assistants, Batch, Embeddings, etc.

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.