GPT-5 Is Here — And It’s Built for Devs Who Build with Tools

OpenAI just dropped GPT‑5 — and while the headlines will focus on benchmarks and "billion-token" context windows, the real story is this: GPT‑5 is built for developers who build with tools.

Whether you're working on AI agents, coding copilots, or multi-step task automation, GPT‑5 brings the flexibility, control, and reliability we've been waiting for. It’s not just smarter — it’s more usable for real workflows.

In this post, we’ll break down why GPT‑5 stands out, what’s new for agentic and tool-using systems, and how you can start building with it today.

Why GPT-5 Matters

GPT-5 isn’t just “faster” or “bigger.” It's a step-change in agentic reasoning, tool calling, and coding performance. Key highlights:

Best-in-class coding performance: 74.9% on SWE-bench Verified, 88% on Aider polyglot
Smarter tool use: Chains complex actions in sequence or parallel with fewer errors
More steerable: Control verbosity, reasoning effort, and tool interaction granularity
Agent-first mindset: Designed to handle multi-step, long-context, and autonomous workflows

New Capabilities That Matter for Agent Builders

1. Tool Calling Just Got an Upgrade

GPT-5 can:

Follow tool schemas more precisely
Handle tool failures better
Run preambles between tool calls to communicate progress to the user
Call custom tools with plaintext (not just JSON) — using regex or grammar constraints

For those using MCP or building agent frameworks, this is huge.

2. Smarter Agentic Behavior

GPT-5 achieves:

96.7% on τ2-bench telecom, a new benchmark for real-world agent tasks
Better chaining of tool calls without supervision
Improved understanding of complex environments

It doesn’t just call tools. It reasons through them — with more robustness and less handholding.

3. Fine-Tuned for Code Collaboration

Built in collaboration with tools like Cursor and Copilot:

Can edit, debug, and explain large codebases
Generates smaller outputs with fewer tool calls than previous models
More helpful in multi-turn developer workflows

It’s not just smart — it’s efficient.

4. New API Parameters: Control, Not Complexity

reasoning_effort: from minimal to high
verbosity: from low to high
custom_tools: plain-text tool inputs, context-free grammars supported
These features give you more control over latency, verbosity, and format — critical for UX in AI agents.

5. Massive Context Window

400K token total context length (272k input + 128k output)
Outperforms GPT-4 and GPT-4o on long-context tasks like MRCR and BrowseComp

Perfect for memory-heavy workflows and information synthesis agents.

6. Try GPT-5 in Action — Right Now on Agent Playground

Want to test GPT‑5 (or its smaller siblings) before it even lands in your ChatGPT UI?

You can try it right now with your OpenAI API key using Agent Playground — our prototyping tool for building and testing AI agents in minutes.

Supports GPT‑5, GPT‑5 Mini, and GPT‑5 Nano
Connect to 1,000+ MCP servers like Notion, GitHub, Slack, or Web Search
No setup required — just drop your key and start building
Build & test tool-using agents without writing any integration code

It’s perfect for:

Prototyping ideas with the latest models
Validating workflows before writing code
Creating your own assistant powered by GPT‑5

Here’s a preview of a conversation with a GPT‑5 Mini agent connected to Notion and Web Search:

Chat with GPT-5 Mini on Agent Playground

Example of an agent using GPT‑5 Mini with tool access in Agent Playground

Try the new GPT‑5 models in seconds → Launch Agent Playground

No waiting. No boilerplate. Just fast, flexible prototyping — powered by the best model OpenAI has released so far.

Pricing & Sizes

GPT-5 comes in 3 sizes:

Model	Input (per 1M tokens)	Output (per 1M tokens)
gpt-5	$1.25	$10.00
gpt-5-mini	$0.25	$2.00
gpt-5-nano	$0.05	$0.40

All support:

reasoning_effort and verbosity parameters
Streaming, tool-calling, prompt caching, and long context (400K tokens)

See GPT‑5 pricing and model docs for full details.

Final Thoughts: A Model Built for Agents

For years, developers building AI agents had to compromise:

Between accuracy and tool use
Between fast answers and deep reasoning
Between rigid JSON formats and more natural inputs

GPT-5 changes the game.

If you're prototyping AI agents, exploring long-context applications, or just want more control over model behavior — GPT-5 might be your new default.

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