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LLM ComparisonGPT-5.4GPT-4.1 Mini

GPT-5.4 vs GPT-4.1 Mini

Compare GPT-5.4 and GPT-4.1 Mini. Build AI products powered by either model on Appaca.

Model Comparison

FeatureGPT-5.4GPT-4.1 Mini
ProviderOpenAIOpenAI
Model Typetexttext
Context Window1,050,000 tokens1,047,576 tokens
Input Cost
$2.50/ 1M tokens
$0.40/ 1M tokens
Output Cost
$15.00/ 1M tokens
$1.60/ 1M tokens

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Strengths & Best Use Cases

GPT-5.4

OpenAI

1. Best Intelligence at Scale

  • OpenAI positions GPT-5.4 as its frontier model for agentic, coding, and professional workflows.
  • Built for complex professional work where stronger reasoning and higher answer quality matter.

2. Configurable Reasoning + Multimodal Input

  • Supports configurable reasoning effort from none to xhigh, letting teams balance speed and depth.
  • Accepts both text and image inputs while producing text output.

3. Massive Context for Long-Running Work

  • 1.05M token context window supports very large codebases, documents, and multi-step workflows.
  • Allows up to 128 k output tokens for long-form answers and larger generations.

4. Updated Knowledge & Broad Tool Support

  • Knowledge cut-off of Aug 31 2025 keeps it current for newer frameworks and business context.
  • Supports tools like web search, file search, code interpreter, hosted shell, computer use, and MCP in the Responses API.

GPT-4.1 Mini

OpenAI

1. Fast, Lightweight, and Cost-Efficient

  • Designed for speed with low latency, making it ideal for high-volume, real-time applications.
  • More affordable than larger GPT-4.1 and GPT-5 models, enabling scalable deployments.

2. Strong Instruction Following

  • Excels at following structured instructions and producing concise, deterministic outputs.
  • Suitable for assistants, command-style interfaces, and tools that require stable, predictable behavior.

3. Reliable Tool Calling & Structured Outputs

  • Built with strong support for:
    • Function calling
    • Structured outputs (JSON, typed objects)
    • Systematic workflows
  • Ideal for automation, reasoning over parameters, and multi-step tool pipelines.

4. Multimodal Input (Text + Image)

  • Accepts both text and image as input.
  • Useful for tasks such as:
    • Image captioning
    • UI element reading
    • Visual question answering

5. Text-Only Output for Clarity

  • Outputs text only, ensuring clean and consistent results for:
    • Data extraction
    • Summaries
    • Code comments
    • Chat responses

6. Massive 1M-Token Context Window

  • Supports 1,047,576 tokens, enabling:
    • Long documents or books
    • Large codebases
    • Extensive conversation memory
  • Great for long-context reasoning without requiring chunking.

7. Practical for Everyday AI Applications

  • Sweet spot for:
    • Customer support agents
    • Content rewriting
    • Lightweight analysis
    • Classification and tagging
    • Workflow assistants
  • Recommended primarily for simpler use cases, with GPT-5 Mini suggested for more complex tasks.

8. Broad API Support

  • Available across:
    • Chat Completions
    • Responses
    • Realtime
    • Assistants
    • Other major API endpoints
  • Compatible with long-context modes for large-scale retrieval and processing.

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