GPT-5 Unleashed for Developers: Explore Enhanced Code and New API Features!

The much-anticipated GPT-5 was finally launched by OpenAI on Thursday, August 7, after a series of teasers. Notable changes include simplified models, interface modifications, and upcoming access to Gmail and Google Calendar. However, it is primarily the enhancement of overall performance that sparks the most interest.

Here, we will explore a number of significant improvements made for developers by OpenAI.

AI Coding: GPT-5 Shifts Into High Gear

Simply put: GPT-5 has significantly improved coding capabilities, according to OpenAI. In their statement, they claim it is the “best model to date for coding and agentic tasks”. As usual, the startup has relied on internal benchmarks to support its claims:

• SWE-bench Verified: GPT-5 scored 74.9%. This benchmark assesses the model’s ability to debug real code repositories. GPT-5 outperforms its predecessor while generating less text and making fewer calls to tools.
• Polyglot Helper: GPT-5 achieves a success rate of 88%. This task involves altering code in multiple languages based on a prompt from the Exercism platform. GPT-5 reduces errors by one-third compared to its predecessor.
• Front-End Development: GPT-5 is preferred in 70% of cases. Internal testers compared the front-end output of the model to that of its predecessor, with GPT-5 showing superior code quality and a better sense of aesthetics.
• τ2-bench telecom: GPT-5 scores 96.7%. This recent benchmark evaluates the execution of lengthy tasks involving sequences of tools. GPT-5 shows an enhanced ability to follow complex instructions without losing track.

GPT-5: A Development Partner

Beyond raw results, GPT-5 introduces a more natural form of collaboration between AI and developers. The model has been trained to act as a genuine “code collaborator”, engaging at every stage of the development cycle: writing, reviewing, debugging, refactoring, documenting, or exploring complex codebases.

“The model is directive and collaborative: it can follow highly detailed instructions with great accuracy and provide clear explanations of its actions before and between tool calls,” explains OpenAI.

It also excels in diving into complex projects, understanding internal dependencies, and addressing specific questions about how different components interact.

GPT-5 also stands out for its ability to follow complex instructions across multiple interactions and handle very long contexts: the API allows for up to 400,000 tokens (approximately 300 pages of text), a record to date. This advancement enables the model to better understand complex projects, extract relevant information from large documents, and respond more coherently, even across hundreds of lines of code. For instance, GPT-5 has been able to analyze its own reinforcement learning stack to assist its teams in reasoning more effectively about their code.

Front-End Development: A Leap Forward?

In terms of front-end development, benchmarks thus indicate a notable improvement in the performance of GPT-5. Specifically, the model produces not only functional but also better-structured, more readable code that adheres more closely to current aesthetic standards.

In its statement, OpenAI also shares some web interfaces created with GPT-5. Visually, the results are impressive and markedly better than those produced by previous models, particularly given the conciseness of the prompts.

The prompt for the image below is: “Please create an attractive and realistic homepage for a service offering coffee enthusiasts a $200 monthly subscription that includes equipment rental and advice on roasting coffee and making the best possible espresso. The target audience consists of middle-aged people living in the San Francisco Bay Area, working in the tech sector, highly educated, with disposable income, and passionate about the art and science of coffee. Optimize for a 6-month subscription conversion.”

For the page below, the prompt is:

“Create a single-page application in a single HTML file with the following requirements:”

• Name: Audio Step Sequencer
• Stack: WebAudio API.
• Objective: 16-step drum grid.
• Features: tempo, swing, pattern save/load, WAV export (simple buffer rendering).

The user interface should be futuristic and make the experience fun!”

API: GPT-5 More Aligned with Developer Needs

In the API, GPT-5 is available in three sizes: gpt-5, gpt-5-mini, and gpt-5-nano. All three are based on the same reasoning model, but they differ in latency, cost, and performance. These are distinct from gpt-5-chat-latest, used in ChatGPT, which combines several models and adjusts their use automatically based on the query.

OpenAI has also introduced new options to finely tune the model’s behavior, depending on the context or technical constraints. Here are the main parameters now accessible:

• Verbosity parameter: adjusts the level of detail in the responses (short, medium, long).
• Reasoning effort parameter: allows for reduced reasoning for quicker responses.
• Custom tools: enables the invocation of tools in plain text, with constraints defined by custom grammars.

Another useful innovation: GPT-5 can now generate preambles, i.e., visible messages before or between tool calls. This helps the model better clarify its ongoing actions, indicate its progress in complex tasks, and enhance readability for end users.