GPT 5.4
OpenAI's frontier model with advanced reasoning and broad multimodal capabilities.
GPT 5.4 is a cloud text model from OpenAI. It is multimodal: alongside a text prompt it accepts images, then replies with generated text. Its context window handles up to 1.05M input tokens and up to 128K output tokens, and it supports adjustable reasoning effort for harder problems. Generation can be tuned with system instructions and temperature. It runs through Replicate and Runware using your own API key, from $2.50 per million input tokens.
- Pricing
- $2.50 / 1M in · $15.00 / 1M out
- Inputs
- Text, Images
- Context window
- 1.05M in · 128K out
- Reasoning
- Adjustable effort
- Controls
- System prompt, Temperature
Examples
Generated with GPT 5.4 via Replicate. The same three prompts run against every text model in the catalog, shown verbatim — so the only thing that changes between two models’ answers is the model.
Explain what an API is to someone who has never written code. Do not use a restaurant or waiter analogy. Plain prose only — no headings, bullet points, or markdown formatting. Maximum 50 words.
An API is a set of rules that lets one piece of software ask another to do something and get a response back. It’s like a shared language for apps, websites, and devices, so they can work together without needing to know each other’s inner workings.
A two-person startup is deciding whether to build their own user authentication or use a hosted provider. Give them a clear recommendation, then the single strongest argument against your own recommendation. Plain prose only — no headings, bullet points, or markdown formatting. Maximum 150 words.
Use a hosted authentication provider. For a two-person startup, auth is almost never where your advantage lives, but it is a place where small mistakes create outsized risk: account takeover, password reset flaws, session bugs, compliance headaches, and endless edge cases around social login, MFA, email deliverability, and abuse prevention. A good hosted provider lets you ship faster, reduce security risk, and keep your limited engineering time focused on the product customers will pay for. You can still revisit the decision later if auth becomes strategically important. The strongest argument against this is dependency: you are putting a critical path of your product in someone else’s hands. If pricing rises, features are missing, uptime suffers, or migration becomes painful, you may regret not owning a core part of the stack from the start.
Write a briefing for a non-technical executive explaining why their company's spending on AI is hard to predict, and what they can do about it. Cover at least three distinct causes. Plain prose only — no headings, bullet points, or markdown formatting. Write exactly 205 words.
AI spending is hard to predict because the cost drivers do not behave like traditional software licenses. First, many AI services charge by usage: every prompt, document, image, or automated action consumes tokens, compute, or API calls. If employee adoption rises suddenly, or if customers use AI-powered features more than expected, costs can jump quickly. Second, AI workloads are highly sensitive to design choices. A small change in model selection, prompt length, response length, or how often systems call the model can materially change spend. Teams may also add safety checks, monitoring, or multiple model passes to improve quality, each increasing cost in ways that are not obvious at approval time. Third, the market itself is moving fast. Vendors frequently change prices, release new models, alter performance, or shift contract terms. What was cost-effective six months ago may no longer be the best option, and new capabilities can create pressure to expand use before budgets are updated. The best response is tighter financial and operating discipline. Set usage limits, require cost estimates before launches, and track spending by team and use case. Run pilots before scaling. Standardize approved models and architectures. Review vendor contracts regularly. Most importantly, connect AI spend to measurable business outcomes, not experimentation alone.
OpenAI
OpenAI builds GPT, DALL·E, the Sora family, and the open-weight gpt-oss models, and has been a central force behind the modern wave of generative AI.
openai.com ↗