Which AI Image Gen Has Best Character Consistency? OpenAI vs. Gemini vs. Flux (techstackups.com)

Recent tests conducted on AI image generation models FLUX.2, Gemini 3.1 Flash, gpt-image-2, and Runway Gen-4 have revealed significant differences in their ability to maintain character consistency when rendering images of real individuals across various scenarios. FLUX.2 and Gemini 3.1 Flash emerged as the top performers, effectively preserving distinct facial features and attributes like tattoos and hair style when placing characters in new scenes. gpt-image-2 followed closely but displayed a tendency to replicate poses too literally, resulting in somewhat unnatural images. In stark contrast, Runway Gen-4 lagged behind, struggling with character fidelity and consistency. The significance of this comparison lies in the challenge of character consistency, a key area in AI image generation that impacts user expectations, especially for projects involving human subjects. A model's ability to retain personal traits across varied situations without drifting into uncanny valley territory showcases its robustness and potential for practical applications in creative industries. The results highlight the differences in approaches among these models—ranging from multi-reference synthesis in FLUX.2 to synchronous content generation in Gemini 3.1 Flash—each offering unique advantages in accuracy and versatility for developers and artists working with AI-generated imagery.