Simon Willison Weblog
2026-11-10 07:28 UTC
Score 75.0
USR-0110-20261110-ai-specialis-7579b7c0
Introducing Our Smallest, Most Efficient Model: Muse Ember Meta AI just launched their entry in the Claude Haiku/GPT Luna category: Muse Ember, which they describe as: [...] our smallest and most efficient model designed for complex reasoning execution and the work agents repeat all day: tool calls, coding subtasks, routing, extraction, and long document parsing. For shorter prompts it's priced the same as GPT-6 Luna and Claude Haiku 5.5 - both are $0.10/million input tokens and $0.50/million output. Today's other big model release, Claude Fable 5.2, is 80x that price at $8/$40. The pricing is a little less straightforward as prompts get longer, though. Luna, Ember, and Haiku all support up to a million input tokens, but they also all have a threshold after which the price goes up. Taking that threshold into account Ember is priced between the two others: Model Prompt size Input ($/M) Cached input Output GPT-6 Luna ≤272k $0.10 $0.01 $0.50 >272k $0.20 $0.02 $0.75 Muse Ember 1.0 ≤200k $0.10 $0.004 $0.50 >200k $0.30 $0.012 $1.50 Claude Haiku 5.5 ≤100k $0.10 $0.01 $0.50 >100k $0.50 $0.05 $2.50 But comparing price-per-token doesn't really make sense these days, when reasoning tokens mean that different models might use dramatically different numbers of tokens to solve the same problem. For that, one measure that's useful is the Artificial Analysis. And even more useful than that is their Intelligence Index vs. Cost per Task chart, which shows the following for those three models:…