Today's Image & Video Generation: Fastest-Growing Projects — October 15, 2026
Today's the Image & Video Generation space on GitHub, we see a strong focus on diffusion models and user-friendly setup guides for running AI models locally, particularly on Windows systems. The top-growing project, `speridlabs/iris-3b`, stands out with its innovative approach to generating high-quality images directly from pixel space without the need for VAE.
`speridlabs/iris-3b` is a diffusion transformer that generates every pixel directly and can also be fine-tuned for tasks like monocular depth estimation and image restoration. With a Growth Score of 15.15 and 177 stars, it demonstrates significant interest from the community due to its versatility and direct pixel-space generation capabilities.
Next, `ArrozDotachi/InvokeAI-Windows-Setup-Guide` provides a comprehensive guide for setting up InvokeAI on Windows 10 and 11, enabling users to run Stable Diffusion locally. This repository has seen rapid growth with a Growth Score of 14.52 and 68 stars, likely due to its detailed setup instructions that make it easier for Windows users to experiment with image generation models.
`CharlesFeng0314/JEV_sees` is an interesting project focused on real-time visual decisions from RGB, video, and RGB-D cameras. With a Growth Score of 7.67 and 86 stars, this repository shows promise in its ability to process various types of camera inputs for immediate decision-making applications.
The `apimart-66/openai-compatible-api-migration-kit` offers tools to migrate workloads between different AI API gateways while maintaining compatibility with OpenAI's standards. This kit includes examples and a checklist, making it easier for developers to switch platforms seamlessly. With 139 stars and a Growth Score of 4.05, this project is gaining traction among those looking to standardize their API interactions.
`janishar/qwen-image-2.1-studio` provides a local studio environment for Apple Silicon users to work with Qwen-Image-2.1, offering text-to-image and multi-image editing capabilities through both CLI and web UI interfaces. This project has 55 stars and a Growth Score of 3.36, reflecting its utility for macOS users who want to experiment locally without cloud dependencies.
`ejsyk3xdp3t2o/wan3.0video-wan-3.0-video-api` is an API that provides video generation services at various resolutions with clear pricing details. The project has garnered 93 stars and a Growth Score of 3.36, likely due to its straightforward pricing model and compatibility with OpenAI's interface.
`azle5biyd9td956/pixverse6-pixverse-v6-api` offers an AI API gateway that supports various services like image generation and LLM interactions at competitive rates. This repository has 93 stars but a lower Growth Score of 2.79, indicating steady interest from developers looking for comprehensive pricing information.
The `bx0idu7sqebwpgu8/grokimagine2.0-grok-imagine-2.0-prompts` project provides API examples and settings for the GrokImagine-2.0 model, which includes features like uploading images and editing regions with detailed costs outlined. With 89 stars and a Growth Score of 2.69, this repository appeals to developers seeking clear documentation and cost details.
Similarly, `cqk4s1t/gptimage2.5-gpt-image-2.5-api` offers another set of API examples for the GPTImage-2.5 model with detailed pricing information. This project has also attracted 89 stars and a Growth Score of 2.69, highlighting its value in providing clear documentation and cost breakdowns.
Lastly, `tomascupr/reelql` introduces an innovative approach to video analysis by converting any video link into JSON data through Claude skills and APIs. With 32 stars and a Growth Score of 2.67, this project is growing due to its unique ability to streamline video content processing for easy integration with other applications.
Overall, the Image & Video Generation category continues to evolve rapidly, with projects focusing on both technical innovation and user accessibility.
`speridlabs/iris-3b` is a diffusion transformer that generates every pixel directly and can also be fine-tuned for tasks like monocular depth estimation and image restoration. With a Growth Score of 15.15 and 177 stars, it demonstrates significant interest from the community due to its versatility and direct pixel-space generation capabilities.
Next, `ArrozDotachi/InvokeAI-Windows-Setup-Guide` provides a comprehensive guide for setting up InvokeAI on Windows 10 and 11, enabling users to run Stable Diffusion locally. This repository has seen rapid growth with a Growth Score of 14.52 and 68 stars, likely due to its detailed setup instructions that make it easier for Windows users to experiment with image generation models.
`CharlesFeng0314/JEV_sees` is an interesting project focused on real-time visual decisions from RGB, video, and RGB-D cameras. With a Growth Score of 7.67 and 86 stars, this repository shows promise in its ability to process various types of camera inputs for immediate decision-making applications.
The `apimart-66/openai-compatible-api-migration-kit` offers tools to migrate workloads between different AI API gateways while maintaining compatibility with OpenAI's standards. This kit includes examples and a checklist, making it easier for developers to switch platforms seamlessly. With 139 stars and a Growth Score of 4.05, this project is gaining traction among those looking to standardize their API interactions.
`janishar/qwen-image-2.1-studio` provides a local studio environment for Apple Silicon users to work with Qwen-Image-2.1, offering text-to-image and multi-image editing capabilities through both CLI and web UI interfaces. This project has 55 stars and a Growth Score of 3.36, reflecting its utility for macOS users who want to experiment locally without cloud dependencies.
`ejsyk3xdp3t2o/wan3.0video-wan-3.0-video-api` is an API that provides video generation services at various resolutions with clear pricing details. The project has garnered 93 stars and a Growth Score of 3.36, likely due to its straightforward pricing model and compatibility with OpenAI's interface.
`azle5biyd9td956/pixverse6-pixverse-v6-api` offers an AI API gateway that supports various services like image generation and LLM interactions at competitive rates. This repository has 93 stars but a lower Growth Score of 2.79, indicating steady interest from developers looking for comprehensive pricing information.
The `bx0idu7sqebwpgu8/grokimagine2.0-grok-imagine-2.0-prompts` project provides API examples and settings for the GrokImagine-2.0 model, which includes features like uploading images and editing regions with detailed costs outlined. With 89 stars and a Growth Score of 2.69, this repository appeals to developers seeking clear documentation and cost details.
Similarly, `cqk4s1t/gptimage2.5-gpt-image-2.5-api` offers another set of API examples for the GPTImage-2.5 model with detailed pricing information. This project has also attracted 89 stars and a Growth Score of 2.69, highlighting its value in providing clear documentation and cost breakdowns.
Lastly, `tomascupr/reelql` introduces an innovative approach to video analysis by converting any video link into JSON data through Claude skills and APIs. With 32 stars and a Growth Score of 2.67, this project is growing due to its unique ability to streamline video content processing for easy integration with other applications.
Overall, the Image & Video Generation category continues to evolve rapidly, with projects focusing on both technical innovation and user accessibility.