
The Decoder: Muse Spark Open is Meta's answer to Qwen, GLM, and Kimi in the open-weight race
Meta's Muse Spark Open is a new open-weight model with 816 billion parameters that processes text, images, video, and audio with up to one million tokens of context. It performs roughly on par with the most capable open-weight Chinese AI models on benchmarks and is optimized to run locally on Apple's M5 Ultra. The article Muse Spark Open is Meta's answer to Qwen, GLM, and Kimi in the open-weight race appeared first on The Decoder.
Part of a story that several outlets report: Meta releases Muse Spark Open AI model for coding
Meta has released Muse Spark Open, an open-weight AI model designed for coding and agentic tasks with 816 billion parameters and support for text, image, video, and audio inputs. The model performs well ahead of competitors like Qwen, GLM, and Kimi on several benchmark tests, though it still falls short of Meta's own paid Muse Wonder Full models. The weights are freely available on Hugging Face, though commercial providers earning over $20 million annually need a separate agreement with Meta to offer it as an API service. This release represents Meta's entry into the competitive open-weight AI model race against other major players in the field.
Explainer: Meta Muse Spark Open: The 816B Open-Weight Model Anyone Can Run
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Mistral AI launched Voxtral 3, a new family of language models built for real-time voice agents. The system combines speech-to-text, text-to-speech, and a voice agent SDK, supports more than 50 languages, and lets agents tap into external tools during live conversations. It can run on your own infrastructure or through EU-hosted APIs to keep data under your control. The article Mistral AI launches Voxtral 3, a full voice agent stack that listens, thinks, and talks in real time appeared

Voxtral 3: Mistral's voice agent SDK for real-time speech in 50+ languages — accurate transcription, emotional TTS, deep tool use. EU-hosted or self-deployed.

DeepSeek has open-sourced DeepInfer, the inference framework that runs its production services. The DeepSeek DeepInfer inference framework is the engine behind DeepSeek-V4.1-Flash. It ships under the Apache 2.0 license. DeepSeek also released deepseek-recipe, its MIT-licensed token encoding and decoding layer. For developers, this is a rare look at a frontier lab’s real serving stack. TL;DR Size / scope: 1 supported model (DeepSeek-V4.1-Flash), 1M-token context window per the model
Also reported by The Decoder and SiliconANGLE

Nvidia is leaning hard into the trend of enterprise companies wanting to run their own open models in their own data centers and also trying to make on-device, private AI agents a thing.

Cloudflare has released a preview of Clairic, a new System One extraction model on Workers AI. The Cloudflare Clairic extraction model reads text or images and returns typed values, not generated text. It targets a job developers usually give to LLMs: pulling totals, dates and IDs into JSON. Clairic answers every requested field in 1 forward pass, with no reasoning and no output tokens. TL;DR Size: Parameter count not disclosed. 65,536-token context window, up to 4 images per request.
Also reported by The Decoder

Elevenlabs' new Eleven Realtime speech-to-speech models combine speed and accuracy. The v1 Max variant scores 98.8 percent on the Big Bench Audio benchmark with a 0.57-second response time. Elevenlabs says no model on the Artificial Analysis leaderboard is both faster and more accurate. The article Elevenlabs releases two new speech-to-speech models designed for real-time AI conversations appeared first on The Decoder.