Compare Ailiverse NeuCore vs. Inkling

Effortlessly build and expand your computer vision capabilities with NeuCore, which allows you to create, train, and deploy models within minutes and scale them to millions of instances. This comprehensive platform oversees the entire model lifecycle, encompassing development, training, deployment, and ongoing maintenance. To ensure the security of your data, advanced encryption techniques are implemented at every stage of the workflow, from the initial training phase through to inference. NeuCore’s vision AI models are designed for seamless integration with your current systems and workflows, including compatibility with edge devices. The platform offers smooth scalability, meeting the demands of your growing business and adapting to changing requirements. It has the capability to segment images into distinct object parts and can convert text in images to a machine-readable format, also providing functionality for handwriting recognition. With NeuCore, crafting computer vision models is simplified to a drag-and-drop and one-click process, while experienced users can delve into customization through accessible code scripts and instructional videos. This combination of user-friendliness and advanced options empowers both novices and experts alike to harness the power of computer vision.

Inkling is Thinking Machines’ open-weights foundation model built for customization, multimodal reasoning, and agentic AI workflows. The model uses a Mixture-of-Experts architecture with 975 billion total parameters and 41 billion active parameters, making it large in capacity while activating only a subset of experts per token. Inkling supports up to a 1 million token context window and was pretrained on 45 trillion tokens spanning text, images, audio, and video. It is designed as a broad generalist model with strengths across coding, reasoning, instruction following, factuality, tool use, vision, audio understanding, forecasting, and safety. Developers can tune its thinking effort to trade off latency, cost, and performance, which is useful for production systems that need efficient reasoning at scale. Inkling can be fine-tuned on Tinker, tested in the Inkling Playground, and deployed through partners such as TogetherAI, Fireworks, Modal, Databricks, Baseten, vLLM, SGLang, llama.cpp, and Hugging Face transformers. The model can generate applications, operate tools, create styled artifacts, reason over visual and audio inputs, and support long refinement loops for collaborative work. Thinking Machines also previewed Inkling-Small, a lighter Mixture-of-Experts model with 276 billion total parameters and 12 billion active parameters for lower-cost and lower-latency workloads. By combining open weights, multimodal training, agentic capabilities, efficient reasoning, and fine-tuning support, Inkling gives builders a flexible AI foundation for specialized products and workflows.