AI Model Profile
GPT-5.4
GPT-5.4 is an OpenAI API model described in official docs as a more affordable model for coding and professional work.
Verification & Sources
- Status
- Verified
- Source links
- 3
- Freshness
- Verified June 18, 2026
- Last verified
- June 18, 2026
- Last updated
- June 17, 2026
Key source checks
Suggest a correction
Benchmark Caveat
Provider documentation and provider-published capability notes are directional, not universal rankings. Real results depend on prompts, tools, latency targets, pricing tier, safety filters, context length, and workload mix.
Best for
Candidate for coding and professional workflows that need lower cost than GPT-5.5 while staying in the OpenAI API stack.
Skip if
Skip if your team needs independently benchmarked performance claims or contractual guarantees not present in the official provider documentation.
Strengths
Official docs list large context, tool support, and lower listed API price than GPT-5.5.
Weaknesses
Still proprietary and API-hosted in this profile; teams should test cost, latency, and output quality on their own tasks.
Agent suitability
Candidate for tool-using agents where OpenAI Responses API integrations are already in place.
Kingy AI take
Use this profile as a source-backed reference point, not a ranking. Re-check official provider docs before making production or budget decisions.
Full Model Notes
GPT-5.4 is an OpenAI API model described in official docs as a more affordable model for coding and professional work.
Coding notes
Official docs describe it as suitable for coding and professional work.
Reasoning notes
Reasoning controls are listed in OpenAI model docs, but this profile does not rank it against other models.
Creative notes
Supports text and image input according to OpenAI model docs.
Research notes
Evaluate for research and document workflows that need tool use and larger context.
API pricing notes
$2.50 input MTok and $15 output MTok in OpenAI model docs as checked on 2026-06-18.
License notes
Review the official provider terms and model documentation before relying on license or redistribution assumptions.

