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LLM ComparisonGPT-5 Minio3-mini

GPT-5 Mini vs o3-mini

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

Model Comparison

FeatureGPT-5 Minio3-mini
ProviderOpenAIOpenAI
Model Typetexttext
Context Window400,000 tokens200,000 tokens
Input Cost
$0.25/ 1M tokens
$1.10/ 1M tokens
Output Cost
$2.00/ 1M tokens
$4.40/ 1M tokens

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Strengths & Best Use Cases

GPT-5 Mini

OpenAI

1. High reasoning performance

  • Retains strong reasoning capabilities despite being a smaller, faster model.
  • Suitable for tasks requiring accurate logic and structured thinking.

2. Fast and cost-efficient

  • Optimized for speed, making it ideal for real-time or high-volume workloads.
  • Far cheaper than GPT-5 while maintaining solid capability.

3. Great for well-defined tasks

  • Excels when prompts are precise and objectives are clearly specified.
  • More predictable and stable for deterministic workflows.

4. Multimodal input

  • Accepts text + image as input.
  • Outputs text only.

5. Tool support

  • Works with Web Search, File Search, Code Interpreter, MCP.
  • (Does not support Image Generation as a tool and does not support Computer Use.)

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.

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