#multimodal

The discussion moved quickly from sample quality to the larger claim: one multimodal backbone for visual generation and action prediction.

Open-weight multimodal models just gained a serious new entrant. Thinking Machines released Inkling with full weights, 64K and 256K context options, and a direct fine-tuning path through Tinker.

HN readers focused less on leaderboard dominance and more on the package: Thinking Machines Lab is offering a multimodal MoE with controllable reasoning effort and Tinker-based fine-tuning as an open-weight base.

MiniMax has moved M3 from model teaser to open-weight distribution. The Hugging Face card lists about 428B total parameters, 23B activated parameters, and a 1M-token context window.

The thread’s energy centered on the architecture claim: what does “encoder-free” really mean for a 12B multimodal model?

Local multimodal AI is moving into the 12B class. Google Gemma introduced Gemma 4 12B under Apache 2.0, describing a unified encoder-free design for image, audio, and text inputs.

Google’s I/O 2026 AI story is about distribution as much as models. Gemini 3.5 Flash is now generally available across API, Antigravity, Android Studio, enterprise tools, Search, and the Gemini app, while Gemini Omni Flash brings video generation into the same push.

At Google I/O 2026, Google DeepMind unveiled Gemini Omni — its first model capable of generating video from any input including text, images, audio, and video. Combining Gemini's intelligence with Google's generative media systems, it is available now through the Gemini app and YouTube Shorts.

ByteDance Research has open-sourced Lance, a 3B-parameter unified multimodal model that handles image and video generation, editing, and understanding in a single framework. It achieves top-tier benchmark scores, matching or outperforming models twice its size.

Google has updated the Gemini API File Search tool to support multimodal content including images, audio, and video, making it easier for developers to build efficient, verifiable RAG systems.

IBM Research has published MAMMAL, a multi-modal model that unifies proteins, molecules, and gene data. It achieves state-of-the-art results on 9 of 11 biological benchmarks and outperforms AlphaFold 3 on several drug-discovery tasks.

The r/singularity community found that Claude Mythos can generate image outputs, reportedly marking Anthropic's first foray into image generation models.