GPT-5 Freemium

OpenAI's GPT-5 unifies fast chat replies with deep step-by-step reasoning in one model

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GPT-5 is OpenAI’s flagship model, released in August 2025. It picks a fast answer or a long reasoning path per prompt, ships with a 400K-token context window, and costs $1.25 per million input tokens on the API.

What is GPT-5?

GPT-5 is a text and image model from OpenAI that replaced GPT-4o and GPT-4.1 as the default for ChatGPT. The headline change is not raw size but routing: one system decides whether your question needs a quick pass or extended reasoning, so you stop choosing between “4o for speed” and “o3 for thinking”.

OpenAI lists three sizes: gpt-5, gpt-5-mini and gpt-5-nano. The full model targets hard coding and analysis work, mini handles high-volume chat, and nano is built for cheap classification and extraction jobs.

GPT-5 Features

  • Automatic routing — the model decides per request whether to answer immediately or reason first; you don’t pick a mode.
  • 400K token context (128K output on the API) — roughly 300,000 words, enough for a medium codebase or a long contract set.
  • Reasoning effort control — API users set reasoning_effort to minimal, low, medium or high, trading latency for accuracy.
  • Native tool use — parallel function calling, structured JSON output and a built-in search tool.
  • Multimodal input — text and images in, text out.
  • Safety routing — a separate lighter model answers “safe completion” classes such as ambiguous medical or legal prompts to save compute.

GPT-5 Highlights

Pricing is the part worth memorising. On the API, GPT-5 runs $1.25 per million input tokens and $10 per million output tokens. Mini is $0.25/$2, nano is $0.05/$0.40. Cached input drops to $0.125 per million on the full model, which matters if you re-send the same system prompt on every call.

In ChatGPT, GPT-5 is the default for Free, Plus, Pro and Team. Free accounts get a capped number of messages before the system quietly falls back to a smaller model — an easy thing to miss when quality suddenly dips.

Benchmark-wise, OpenAI reported 74.9% on SWE-bench Verified and the model cut factual error rates “roughly 45%” versus GPT-4o in internal evals. Treat vendor numbers with a sceptical eye; independent replications have been less uniform.

What Is GPT-5 Good At?

  • Multi-file coding — refactors where the model must hold several files in context at once.
  • Long document analysis — contracts, research PDFs, transcripts that would overflow a 128K window.
  • Agentic tools — function-heavy workflows where reliable JSON output beats clever prose.
  • Customer-facing chat — mini at $0.25/M input is cheap enough to sit in front of real traffic.
  • Data extraction — nano for classifying or parsing thousands of rows where latency matters more than nuance.

    • Who Should Use GPT-5 and Who Should Not

    It fits teams already inside OpenAI’s stack, and anyone doing long-context work who wants one model instead of juggling three. It’s a harder sell if you need a specific open-weight licence — GPT-5 is closed — or if you’re cost-sensitive at scale, where Gemini 2.5 Flash and DeepSeek undercut the full model by close to an order of magnitude on output tokens.

    The real annoyance is opacity. You cannot see which path was taken, so a bad answer sometimes reflects “the router misjudged this” rather than the model’s ceiling. Turn reasoning effort up and the same prompt fixes itself — which is useful to know and also a bit of a tax.

    Quick Summary

  • GPT-5 launched in August 2025 as OpenAI’s default model, replacing GPT-4o in ChatGPT.
  • API pricing is $1.25 per million input and $10 per million output tokens for the full model.
  • Context window is 400K tokens; some ChatGPT plans cap this lower in practice.
  • Three sizes ship: gpt-5, gpt-5-mini and gpt-5-nano.
  • It’s closed-weight — no self-hosting, no public fine-tuning of the flagship tier.

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