Overchat AI Research Reveals Q1 2026 AI Model Usage Trends Across Text, Image, and Video

Structured Digest of the Announcement

Overchat AI has released new research detailing artificial intelligence model usage patterns between May 18, 2026, and May 18, 2026. The study analyzed approximately 8.6 million AI interactions from 1,312,500 users on its platform. This research provides an overview of adoption rates for various text, image, and video generation models recently launched or updated within a 90-day period.

Key Digest

10 Essential Facts at a Glance

Overchat AI conducted research on AI model usage from May 18 to May 18, 2026.
The study encompassed 1,312,500 users and approximately 8.6 million AI interactions on the Overchat AI platform.
OpenAI's GPT-5.5 accounted for 81.2% of text model usage during the measurement period.
Anthropic's Claude Opus 4.7 and Opus 4.6 registered 5.4% and 3.6% of text model usage, respectively.
xAI's Grok 4.3 and DeepSeek V4 captured 2.9% and 1.9% of text model usage, respectively.
OpenAI's GPT-Image-2 was utilized for 43.7% of image generation interactions.
Nano Banana Pro from Google held 32.0% of image usage, while Nano Banana 2 accounted for 23.3%.
Sora 2 maintained its position as the most used video model at 64.4% of video usage.
Seedance 2.0 and Kling 3.0 recorded 28.8% and 6.8% of video model usage, respectively.
The usage share of the OpenAI GPT series on Overchat AI increased from 66% to over 80% compared to a previous report.

What This Means

The reported data indicates a notable consolidation in the text AI model landscape, with OpenAI's GPT series expanding its usage share to over 80% on the Overchat AI platform. This occurred despite numerous new model releases and updates from various developers, suggesting a strong user preference for the dominant model's generalist capabilities or specific performance. The continued significant usage of Anthropic's Claude Opus 4.6, even after its newer version's release, points to user priorities potentially extending beyond the latest iteration, possibly due to perceived quality differences or task completion reliability. This dynamic challenges expectations of market fragmentation, highlighting that user loyalty or specific functional requirements influence adoption and model version choices.

In image generation, user behavior suggests a prioritization of quality over speed and cost, as evidenced by the higher adoption of GPT-Image-2 despite its reported slower processing and higher expense. This preference indicates that for certain creative tasks, users are willing to invest more resources for superior visual output. The segmentation observed between Nano Banana Pro and Nano Banana 2, where users did not exclusively migrate to the cheaper option, further supports a quality-driven selection process. For video generation, while Sora 2 remains widely used, its declining share and the rise of Seedance 2.0 and Kling 3.0 reflect an evolving market where newer models with advanced visual capabilities are gaining traction. The eventual deprecation of older models will naturally accelerate this transition, prompting users to adopt newer alternatives offering enhanced features or broader support.

Questions Worth Watching

Will the consolidation trend in text AI models continue, or will specialized models gain more significant market share in the future?
How might developers balance new feature introductions with maintaining perceived quality and consistency across model versions to retain user base?
What impact will the increasing user preference for quality in image generation have on the development and pricing strategies of future AI models?

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