Skip to content
All tags

#muse-spark

2 posts
aideep-dive

How to Decide an Agent Is Ready to Ship: Meta Muse's Behavior Checklist, Two Thresholds, and a Hands-On Check

Alexandr Wang says Meta listed 100+ behaviors a personal agent needs, built an eval for each, and set two thresholds per row: a launch-blocking floor and a bar for 'good'. They shipped after the first all-green checkpoint and a hands-on check that it was clearly better; they also ran new-user testing. The method is reusable, but post-launch safety reports show all-green is not the same as safe.

#ai-agent#evaluation#meta#muse-spark#openclaw#ai-safety
techdeep-diveAI Model Families

Muse Spark: Meta's Closed-Source Agentic Model Line, from Llama to 1.3

Muse Spark is Meta's closed-source agentic model line: version 1.3 combines a 1M-token context, multimodal inputs, and long-horizon tool loops. Standard pricing is $1.25/$4.25 per 1M input/output tokens, while Contributor drops to $0.10/$0.20 in exchange for training rights. It is not the next Llama; it is a separate product line built around models, APIs, and coding agents.

#ai-agent#llm#meta#muse-spark#model-family-muse-spark#agentic-coding#model-selection