
Inkling
Open weights 975B multimodal model built for fine-tuning
About Inkling
Inkling by Thinking Machines is an advanced open-weights multimodal AI model designed for fine-tuning and versatile AI applications. Boasting a massive 975 billion parameters in a mixture-of-experts (MoE) architecture with 41 billion active parameters, it is capable of understanding and reasoning across text, images, and audio within a 1 million token context. Its open weights allow developers and researchers to customize and optimize the model for specific tasks using tools like Tinker, or to deploy directly with Apache 2.0 licensing. The integration of native reasoning and controllable thinking effort makes Inkling a powerful tool for building sophisticated, multimodal AI solutions. Its open nature and high capacity position it as a significant advancement for those seeking a customizable, high-performance AI model in development, research, or enterprise settings.
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Pros
- ✓Massive 975B parameter size enabling deep understanding and reasoning
- ✓Supports multimodal inputs: text, images, and audio
- ✓Open weights for customization and fine-tuning
- ✓Controllable thinking effort for tailored AI responses
- ✓Native reasoning capabilities across multiple data types
Cons
- ✗Likely high computational resource requirements
- ✗Complex setup and fine-tuning process may require advanced expertise
- ✗Limited user interface or out-of-the-box integrations
Use Cases
Pricing
Likely a custom or enterprise pricing model, possibly based on usage, licensing, or support. As an open model, it may be free to download, but operational costs for deployment could vary significantly.
Quick Info
Topics
Makers
Tianyi Zhang
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