I didn't touch TouchDesigner myself. Hermes agent learned it from scratch and built this: → navigated my desktop with computer use → figured out how to connect to TouchDesigner → read my reference images → iterated on the art with me in a self-learning loop → then saved what it learned as a reusable skill for the next image all powered by @MiniMax_AI M3 × Hermes Desktop Agent @NousResearch Here's a full breakdown 📽️

Made some improvements on the decode path for MiniMax M3 by @MiniMax_AI on MLX-VLM Faster decode, slightly lighter footprint. Thanks to @ivanfioravanti for the PR 🚀 PR: github.com/Blaizzy/mlx-vlm/p…

MiniMax M3 support added to mlx-vlm with MSA implementation! 🚀 Tested on M3 Ultra 512GB running at 24 tps with peak memory ~240GB. Now working on optimizing performance and adding ton of tests 💪 Model is here: huggingface.co/mlx-community… PR is here: github.com/Blaizzy/mlx-vlm/p…

MiniMax M3 can now be run locally!🔥 MiniMax-M3 is a new 428B (23B active) open model with 1M context that performs on par with Gemini 3.1 Pro. Run Dynamic 2-bit GGUF on 138GB RAM/VRAM or 3-bit on 165GB. GGUF: huggingface.co/unsloth/MiniM… Guide: unsloth.ai/docs/models/minim…

The US government, citing national security authorities, has issued an export control directive to suspend all access to Fable 5 and Mythos 5 by any foreign national, whether inside or outside the United States, including foreign national Anthropic employees. The net effect of this order is that we must abruptly disable Fable 5 and Mythos 5 for all our customers to ensure compliance. Access to all other Claude models is not affected. We apologize for this disruption to our customers. We believe this is a misunderstanding and are working to restore access as soon as possible. Read our full statement: anthropic.com/news/fable-myt…

MiniMax-M3 from @MiniMax_AI is now available on Together AI. It’s an open-weight native multimodal model with 1M context, MiniMax Sparse Attention, and thinking / non-thinking modes. Together AI is MiniMax’s preferred cloud partner, with inference optimizations delivering up to 125% higher throughput across concurrency levels.

🎉 Congrats to @MiniMax_AI on releasing MiniMax M3! Frontier coding and agentic capabilities, native image and video input, computer use, and a 1M-token context window, all in a single open model. At the heart of M3 is MSA, a new sparse attention architecture: instead of attending densely over the full KV cache, each query scores 128-token KV blocks and runs attention only over the top blocks. That is what makes 1M-token context practical to serve. M3 runs in vLLM with day-0 support, verified on NVIDIA and AMD hardware: ✨ MSA sparse attention with dedicated prefill and decode kernels ✨ 1M-token context serving with prefix caching and chunked prefill ✨ BF16 and MXFP8 checkpoints, with MoE backends for both Hopper and Blackwell ✨ Native multimodal input (image video) ✨ Tool calling, reasoning parsing, and thinking-mode control for agent workloads Day-0 support like this is a true team effort. Grateful to the teams at @MiniMax_AI, @NVIDIAAI, @AIatAMD, and @inferact, and to the vLLM community for making it happen. 🙏 Deep dive into the implementation, kernel work, and deployment recipes: 🔗 vllm.ai/blog/2026-06-12-mini…

400B ? I doubt whether you have the capability to train models with 800B parameters or even 1T parameters.

Congrats to the @MiniMax_AI team on the release of MiniMax M3, a long-context multimodal model for text, image, and video reasoning. 🙌 Try it today with our free GPU-accelerated endpoint on build.nvidia.com. Details: nvda.ws/4v4BWhD

Wow. #3 on kernelbenchhard

At least the cable is included in the price! Now can it run MiniMax M3?

MiniMax M3 has arrived in Droid.

Congrats to the MiniMax team on the open-source launch of M3! There are very few <500bn parameter models that can tackle coding, agentic workloads, and multimodal all with a 1M-token context window but M3 does it all. Dig in here: baseten.co/library/minimax-m…

Congrats to our partners at @MiniMax_AI on the launch of MiniMax M3. Open-weight models continue to push the ecosystem forward, and we're excited to bring M3 to RDUs down the road. Looking forward to following what's built with it. 🚀

MiniMax M3, Open-Weight, Now On Hugging Face , with only ~428B parameters and ~23B activated parameters Weights: huggingface.co/MiniMaxAI/Min… MiniMax Sparse Attention: huggingface.co/papers/2606.1…

Congrats to the @MiniMax_AI team on the release of MiniMax M3, a long-context multimodal model for text, image, and video reasoning. 🙌 Try it today with our free GPU-accelerated endpoint on build.nvidia.com. Details: nvda.ws/4v4BWhD

MiniMax M3 is live on Fireworks. Day-0, fastest endpoint for the MiniMax series. → Top open-weight model on the Artificial Analysis index → 512K context, native image video input → MSA sparse attention: 9× faster prefill, 15× faster decode → Priced at parity with M2.7 Long-horizon agents, full-repo understanding, multimodal coding all in one model. Learn more: fireworks.ai/blog/minimax-m3…

@MiniMax_AI M3 is live on Telnyx Inference 🚀 M3 is the first open-weight model combining frontier coding & agent capabilities, 1M-token context, and native multimodal understanding. M3's 1M context Telnyx's owned GPU infrastructure = fast inference capable of processing entire codebases in one conversation. It’s time to start building telnyx.com/release-notes/min…

MiniMax M3 can now be run locally!🔥 MiniMax-M3 is a new 428B (23B active) open model with 1M context that performs on par with Gemini 3.1 Pro. Run Dynamic 2-bit GGUF on 138GB RAM/VRAM or 3-bit on 165GB. GGUF: huggingface.co/unsloth/MiniM… Guide: unsloth.ai/docs/models/minim…