Simon Willison Compares Meta’s Muse Ember Pricing and Reasoning Levels

What happened

Simon Willison compares Meta’s Muse Ember 1.0 with GPT-6 Luna and Claude Haiku 5.5, showing how their input and output prices rise at different prompt length thresholds. He also reports that Ember sits on Artificial Analysis’s intelligence versus cost per task frontier. In tests generating pelican riding bicycle SVGs, the high reasoning setting failed to return a full SVG, and the other outputs did not show a clear relationship between reasoning level and visual quality.

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The story so far

Meta released Muse Ember for routine agent tasks, and Alexandr Wang said Crouton Alpha was an early version of the model. Wang said Meta fixed issues before launch and processed more than 5 trillion tokens in testing. Ember handles tasks such as tool calls, small coding jobs, routing, extraction, and long document processing. It supports text, images, audio, and video, with a context window of up to 1 million tokens. Developers can use it through Meta Model API and Muse Code for $0.10 per million input tokens and $0.50 per million output tokens. Artificial Analysis gave Ember (max) a score of 36 on its Intelligence Index at an average cost of $0.14 per task, compared with $0.41 for Claude Haiku 5.5 (max). Its coding results varied: it beat Haiku 5.5 on Terminal-Bench 4.0 but scored lower on FrontierCode 2.0.