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ease
features
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support

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Description

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.

Description

Qwen3.5-Omni, an advanced multimodal AI model created by Alibaba, seamlessly integrates the understanding and generation of text, images, audio, and video within a cohesive framework, facilitating more intuitive and instantaneous interactions between humans and AI. In contrast to conventional models that analyze each modality in isolation, this innovative system is built from the ground up using vast audiovisual datasets, enabling it to effectively manage intricate inputs like lengthy audio recordings, videos, and spoken commands concurrently while excelling in all formats. It accommodates long-context inputs of up to 256K tokens and is capable of processing over ten hours of audio or extended video sequences, making it ideal for high-demand real-world scenarios. A standout characteristic of this model is its sophisticated voice interaction features, which encompass end-to-end speech dialogue, the ability to control emotional tone, and voice cloning, allowing for extraordinarily natural conversational exchanges that can vary in volume and adapt speaking styles in real-time. Furthermore, this versatility ensures that users can enjoy a truly personalized and engaging interaction experience.

API Access

Has API Yes 

API Access

Has API Yes 

Screenshots View All

Screenshots View All

Integrations

Happy Shrimp 1.0 No 
Model Context Protocol (MCP) Yes 
Tinker Yes 

Integrations

Happy Shrimp 1.0 Yes 
Model Context Protocol (MCP) No 
Tinker No 

Pricing Details

Free
Free Trial No 
Free Version Yes 

Pricing Details

No price information available.
Free Trial Yes 
Free Version No 

Deployment

Web-Based Yes 
On-Premises No 
iPhone App No 
iPad App No 
Android App No 
Windows No 
Mac No 
Linux No 
Chromebook No 

Deployment

Web-Based Yes 
On-Premises No 
iPhone App Yes 
iPad App Yes 
Android App Yes 
Windows Yes 
Mac Yes 
Linux No 
Chromebook No 

Customer Support

Business Hours No 
Live Rep (24/7) No 
Online Support No 

Customer Support

Business Hours No 
Live Rep (24/7) No 
Online Support Yes 

Types of Training

Training Docs Yes 
Webinars No 
Live Training (Online) No 
In Person No 

Types of Training

Training Docs Yes 
Webinars No 
Live Training (Online) Yes 
In Person No 

Vendor Details

Company Name

Thinking Machines Lab

Founded

2025

Country

United States

Website

thinkingmachines.ai/

Vendor Details

Company Name

Alibaba

Founded

1999

Country

China

Website

qwen.ai/blog

Alternatives

Alternatives

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