LLM ComparisonGPT-5.4GPT-5.1

GPT-5.4 vs GPT-5.1

Compare GPT-5.4 and GPT-5.1. Build AI products powered by either model on Appaca.

Model Comparison

FeatureGPT-5.4GPT-5.1
ProviderOpenAIOpenAI
Model Typetexttext
Context Window1,050,000 tokens400,000 tokens
Input Cost
$2.50/ 1M tokens
$1.25/ 1M tokens
Output Cost
$15.00/ 1M tokens
$10.00/ 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-5.1

OpenAI

1. Configurable Reasoning for Agentic Tasks

  • Built to excel in autonomous or semi-autonomous coding workflows, with adjustable reasoning effort for planning, refactoring and debugging.

2. Fast Multi-Modal Input with Large Output

  • Accepts both text and image inputs while producing text outputs.
  • Offers up to 128 k output tokens, allowing long responses and code generation across multiple files.

3. Large Context & Knowledge Cut-Off

  • 400 k token context window supports processing large codebases or documents.
  • Knowledge cut-off of Sep 30 2024 ensures familiarity with recent tools and frameworks.

4. Reasoning Token Support

  • Provides explicit support for reasoning tokens, enabling developers to fine-tune the balance between reasoning depth and speed.

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