ChatGPT's GPT-4o Model Outperforms Rivals in Image Generation

OpenAI has once again taken the lead in the AI image generation race with the integration of native image generation directly into ChatGPT via its GPT-4o model. This update is not just an incremental change but a significant overhaul that positions ChatGPT at the forefront of AI image generation technology. Within hours of its release, the model went viral, with users flooding social platforms with anime-style creations that showcased technical capabilities far superior to those of DALL-E 3.

ChatGPT's new model can now compete with dedicated image-generation platforms while eliminating traditional workflow barriers. The $20 monthly ChatGPT Plus subscription now offers a comprehensive creative ecosystem that previously required multiple specialized tools and subscriptions. This integration allows users to handle both text and code, as well as images, making it an all-in-one solution that is both easy to use and a great value proposition.

In a visual showdown against industry leaders, ChatGPT demonstrated impressive capabilities. In a test involving the creation of a high-resolution photograph of a bustling city street at night, ChatGPT delivered vibrant environments with neon signage and rich reflections across meticulously rendered wet pavement. While it excelled in crowd dynamics and element inclusion, minor perspective inconsistencies occasionally betrayed its synthetic nature. The lighting was good but sometimes veered into theatrical rather than naturally urban. It also generated legible neon signs besides the specified one, adding to the realism.

Reve, another model, won the realism crown through superior rendering of complex lighting interactions. Its cinematic framing and atmospheric elements created superior dimensional authenticity. However, it reduced crowd density, which was a clever hack since it didn’t have to generate a lot of faces, making it harder to spot unrealistic details. The system prioritized mood over literal prompt adherence.

Freepik Mystik (Flux) interpreted the prompts through a different lens and deviated the most from the realistic style. It mixed Asian with Western lettering, generated different Decrypt signs instead of just one, and suffered from technical limitations in human rendering and dimensional depth. Its reflective surfaces lacked the physical accuracy displayed by ChatGPT.

In terms of prompt adherence and spatial awareness, ChatGPT demonstrated extraordinary prompt fidelity, accurately rendering 23 of 25 specified elements in their correct spatial relationships. This achievement represents unprecedented prompt comprehension, like watching an experienced artist transform detailed verbal instructions into nearly perfect visual execution with only minor deviations. The only two major bugs found were the cat not being upside down and the green color spilling from the pyramid to the first aid kit.

Freepik Mystik showed significant comprehension degradation, correctly rendering approximately half the requested elements while misinterpreting spatial relationships and modifying key components. It was the model that failed the test first. The colors spilled to different elements of the composition, and the concepts also spilled—the dog on the TV spilled to generate an astronaut dog, for example.

Reve demonstrated poorer prompt fidelity than ChatGPT but better than Flux. It fundamentally reimagined the composition with good enough adherence to instructions. Still, it introduced unauthorized elements that completely transformed the requested scene—this AI that prioritizes its aesthetic vision over literal instruction following. It generated a black background, the cat was not correctly placed, there was some color spillage, and elements were not really surreal.

In image editing, ChatGPT's natural language editing capability represents perhaps its most transformative feature, allowing intuitive modification through conversational instructions while simultaneously providing granular control comparable to specialized tools. Our tests transforming personal photos into movie posters demonstrated exceptional versatility—a workflow no competing model matched. For example, we simply fed the model a photo and instructed it to generate a Netflix poster with a specific aesthetic, title, and lettering. It did everything almost flawlessly, achieving similar results that other models would take a lot of time to undertake, and likely using different tools and plugins.

While all systems eventually show quality degradation through multiple iterations, ChatGPT maintained superior image coherence through extended editing sequences compared to both Reve and Gemini. For example, it still generated coherent, good-quality faces after several iterations, whereas Gemini stopped producing usable results after four or five tries. ChatGPT also has a granular “inpainting” feature—allowing you to modify specific areas of an image while seamlessly blending in with the background– for users in need of a more specific editing tool, which Gemini and Reve lack.

Despite implementing comprehensive safety measures, our testing identified some vulnerabilities in ChatGPT's image generation guardrails. With minimal experimentation, we were able to generate potentially problematic content. For example, while the system initially refused to generate an image involving a child and substances, it proceeded when prompts were reworded using euphemistic language while maintaining fundamentally identical content. It would not generate a child inhaling cocaine with a rolled dollar bill, but a child with white powder and a rolled green paper the size of a dollar bill is totally fine. Try as we might, we were unable to generate overly sexualized photos, violence, and other questionable content simply by convincing the model of our good intentions.

GPT-4o's image capabilities establish a new benchmark in AI-assisted visual creation—one that combines exceptional technical performance with unprecedented accessibility. For most users, this implementation now represents the optimal balance of quality, versatility, and value for $20 a month. Other specialized tools only let users handle text and code, or just images—but you can’t find an all-in-one offer with the same levels of quality making OpenAI’s service not only easy to use but a great value proposition.