Multimodal Models

102 summarised stories about Multimodal Models, each linking back to the original source. Browse all topics →

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Wednesday, 15 July 2026

Thinking Machines Lab Releases Inkling: A 975B-Parameter Open-Weights Multimodal MoE With 41B Active Parameters And Controllable Thinking Effort

MarkTechPost 3 months ago 41 ● 4 sources

Thinking Machines Lab released Inkling, a 975-billion-parameter open-weights multimodal mixture-of-experts model with 41 billion active parameters and a 1-million-token context window. The model was trained on 45 trillion tokens of text, images, audio, and video, and features a controllable thinking-effort mechanism that allows users to trade inference cost for performance, achieving Terminal Bench 2.1 parity with Nemotron 3 Ultra using one-third the tokens. Inkling is available on Hugging Face and hosted platforms, enabling deployment of cost-tuned agentic systems and multimodal applications across voice, vision, and text inputs.

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Multimodal Models Mixture-of-Experts

Welcome Inkling by Thinking Machines

Hugging Face 3 months ago 48 ● 2 sources

Thinking Machines released Inkling, an open-source multimodal language model with 1 trillion parameters that accepts images, text, and audio inputs natively. The model has 975 billion total parameters with 41 billion active at any time, supports a 1 million token context window, and was trained on 45 trillion tokens across multiple modalities. Inkling is available on Hugging Face with immediate support in transformers, SGLang, vLLM, and llama.cpp, enabling developers to build multimodal reasoning applications through fine-tuning or remote inference.

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Open Source Multimodal Models Mixture-of-Experts

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