Awesome new security benchmarks from @AnselmPaulus@maksym_andr et al.! We (as a community) desperately need to double down on such initiatives to make future models more robust!
Excited to share these news! Was awesome to work with the folks @AIatMeta, the speed at which they are building is crazy. Looking forward to what is next!
We are proud to share that our two new benchmarks, RepoInject v1 and BrowserInject v1, were used by Meta TBD Labs to report the robustness of Muse Spark 1.3 to prompt injections.
The robustness of Muse Spark 1.3 is comparable to that of GPT-5.6 Sol—congrats to the team!
1/4
The Muse Glimmer technical report is out today! It is our 30B open-weight model (Apache 2.0) distilled from Muse Spark, built to run agentic workloads entirely on consumer hardware — one RTX 5090, 32GB.
Today we published a technical report on Muse Glimmer, our 30B open-weight model built for agentic tasks on consumer hardware.
It runs at practical speeds on a Mac or PC with a single consumer GPU at 4-bit precision, and leads comparably-sized open models on tool use and
Shipped: Muse Spark Open, the most capable US open-weight model to date — built for coding and long-horizon agentic work. 816B total, 42B active, 1M-token context. Download the weights and run it on your own machine!
1/ muse spark open is the most capable US open-weight model to date.
816B total params, 42B active. 1M-token context. natively multimodal. built for coding and agentic work like long-horizon tasks, hard software engineering, multi-step reasoning.
america! 🇺🇲
Two months after our reasoning extraction attack release, we audited mitigations introduced since then and found that we still can extract reasoning from Astra/Sol-6.1 via third-party API providers.
We disclosed our findings to OpenAI and Anthropic...
openai.com/index/disrupti…
