latentbrief

Model comparison

GPT-5.4 Mini vs Claude Sonnet 4.6

The most notable difference between Claude Sonnet 4.6 and GPT-5.4 Mini is their token context capacities, with Claude Sonnet 4.6 capable of handling 1,000,000 tokens versus GPT-5.4 Mini's 400,000 tokens.

Specs

MetricGPT-5.4 MiniClaude Sonnet 4.6
Context window400K tokens1M tokens
Input $/1M tokens$0.750$3.00
Output $/1M tokens$4.50$15.00
ModalitiesFile · Image · TextText · Image
Open weightsNoNo

Capability differences

CapabilityGPT-5.4 MiniClaude Sonnet 4.6
Extended thinkingNoYes

How they differ

Context handling

GPT-5.4 Mini

GPT-5.4 Mini operates with a context window of 400,000 tokens, adequate for handling moderate-length documents and interactions.

Claude Sonnet 4.6

Claude Sonnet 4.6 supports an extensive context window of 1,000,000 tokens, enabling long-form discussions and processing massive documents.

Cost profile

GPT-5.4 Mini

GPT-5.4 Mini is more economical at $0.75 per million input tokens and $4.5 per million output tokens.

Claude Sonnet 4.6

Claude Sonnet 4.6 incurs higher costs at $3.0 per million input tokens and $15.0 per million output tokens.

Vision

GPT-5.4 Mini

GPT-5.4 Mini supports text and image inputs and expands capability by accepting file uploads for enhanced flexibility.

Claude Sonnet 4.6

Claude Sonnet 4.6 supports multi-modal input with text and image capabilities but does not accept file uploads.

GPT-5.4 Mini — what sets it apart

  • +GPT-5.4 Mini's smaller token context of 400,000 trades off capacity for more streamlined and rapid processing.
  • +Its support for file-based input alongside text and image inputs enhances versatility for data-rich applications.

Claude Sonnet 4.6 — what sets it apart

  • +Claude Sonnet 4.6 features a token context size of 1,000,000, enabling handling of extensive datasets or discussions.
  • +Provides nuanced context-aware reasoning tailored for thematic coherence over longer sequences.

Differences in token context and cost profile are pivotal when choosing between Claude Sonnet 4.6 and GPT-5.4 Mini, as they directly affect scalability and operational expense.

Analysis synthesized from gpt-4o, llama-4-maverick, phi-4, etc.