Meta releases Muse Spark 1.2, its third model in four months
Questions this post answers
What does Muse Spark 1.2 score on the Artificial Analysis Intelligence Index and how does it compare to GPT-5.5 and Claude Opus 5?
Muse Spark 1.2 scores 54 on the Artificial Analysis Intelligence Index, up from 51 in version 1.1 and 43 in the original 1.0 release. That puts it roughly tied with GPT-5.5 (55) and Grok 4.5 (54). The current top cluster sits higher: Claude Opus 5 at 61, Claude Fable 5 at 60, GPT-5.6 Sol at 59, and Kimi K3 at 57. Developers tracking the AI coding tool landscape follow benchmark shifts like these on daily.dev.
What is the pricing for Muse Spark 1.2 per million tokens?
Muse Spark 1.2 is priced at $1.25 per million input tokens and $4.25 per million output tokens, with cache hits at $0.15 per million. The context window is 1 million tokens. The cost per Intelligence Index task rose from $0.29 to $0.40 — not from a price increase, but because the model uses roughly 53% more input tokens and 36% more output tokens per task than version 1.1. Teams budgeting for AI model usage track cost-per-task changes like these on daily.dev.
How is Meta using internal engineering workflows to generate training data for its AI models?
Meta feeds real engineer corrections from its internal coding tool MetaCode back into model training. When engineers fix MetaCode's mistakes, the original task, the AI's response, the fix, and the review are all captured as training signal for upcoming models like Watermelon. Over 7,000 weekly active users have submitted more than 800 fixes. The bet is that production correction loops are a stronger signal than synthetic benchmarks or public code repositories. Engineers building or evaluating AI coding agents find coverage of training data strategies like this on daily.dev.