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Meta Muse Ember scores 36 on the Artificial Analysis, the cheapest to reach so

Meta's Muse Ember (max) scored 36 on the Artificial Analysis Intelligence Index at $0.14 per task, making it the cheapest model to reach that score, according to Artificial Analysis. The result matches Claude Haiku 5.5 (max), which costs nearly 3x more at $0.41 for the same score, while Muse Ember (xhigh) scores 34 at $0.12. Muse Ember (max) also scored 68.1% on AutomationBench-AA and 46 on the Artificial Analysis Coding Agent Index in Muse Code, ahead of Claude Haiku 5.5 in Claude Code (37) and GPT-6 Luna in Codex (31), though its AA-Omniscience accuracy of 21.1% was the lowest among similarly intelligent models because it declines to answer 64% of questions, holding its hallucination rate to 17.4%.

read4 min views2 publishedNov 9, 2026
Meta Muse Ember scores 36 on the Artificial Analysis, the cheapest to reach so
Image: source

November 9, 2026

See model page Muse Ember is Meta's newest efficient-tier model line, with the same input and output token prices as Claude Haiku 5.5 and GPT-6 Luna

Key Takeaways: #

➤ On the Intelligence Index vs. Cost per Task Pareto frontier at both max and xhigh effort. Muse Ember (max) is the cheapest model scoring 36 or higher, at $0.14 per task, and Muse Ember (xhigh) scores 34 for $0.12. Claude Haiku 5.5 (max) costs almost 3x more at $0.41 for the same score as Muse Ember (max). Muse Ember (max) is also about 4x cheaper than DeepSeek V4.1 Flash 1017 (max, 33, $0.60) and GLM-5.3-Flash (28, $0.58)

➤ 8 points behind Muse Wonder for about 1/50th of the Cost per Task. Muse Wonder (max) scores 44 at $6.95 per Intelligence Index task

➤ Stands out on AutomationBench-AA. Muse Ember (max) scores 68.1% on AutomationBench-AA, level with Muse Wonder (max), and beats Claude Haiku 5.5 (max) on GDP.pdf (22.8% vs 20.8%), but trails it on AA-Briefcase (1521 vs 1574 Elo)

➤ Mixed in agentic coding in our Intelligence Index evaluations. It beats Claude Haiku 5.5 (max) on Terminal-Bench 4.0 (40.9% vs 32.8%) but trails it on FrontierCode 2.0 (27.2% vs 34.9%)

➤ Ahead of similarly priced models when running in its own coding agent. In Muse Code, Muse Ember (max) scores 46 on the Artificial Analysis Coding Agent Index, ahead of Claude Haiku 5.5 in Claude Code (max, 37) and GPT-6 Luna in Codex (max, 31)

➤ Knowledge is the main weakness, but it rarely hallucinates. Its AA-Omniscience accuracy of 21.1% is the lowest of the similarly intelligent models we compared, against 34.7% for Claude Haiku 5.5 (max) and 50.5% for Gemini 3.8 Flash (high). This is mostly because it declines to answer 64% of questions, which keeps its hallucination rate at 17.4%, half of Claude Haiku 5.5’s (max)

Other details: #

➤ Pricing: $0.10 input / $0.004 cached input / $0.50 output per 1M tokens ➤ Reasoning effort: results shown at max effort, with xhigh also on the Intelligence vs. Cost chart ➤ Availability: Meta's first-party API and Muse Code

Muse Ember costs less per task than similarly priced models

Muse Ember (max) has the same input and output token prices as Claude Haiku 5.5 (max) and GPT-6 Luna (max), but its cached input, most of the cost in our agentic evaluations, is 60% cheaper. Muse Ember (max) also uses roughly a third as many output tokens as Claude Haiku 5.5 (max)

Muse Ember's standout agentic result is AutomationBench-AA, where it scores 68.1%, level with Muse Wonder and GPT-6 Astra

Agentic coding is mixed. Muse Ember beats Claude Haiku 5.5 on Terminal-Bench 4.0 (40.9% vs 32.8%) but trails it on FrontierCode 2.0 (27.2% vs 34.9%)

Muse Ember is ahead of similarly priced models as a coding agent

In Muse Code, it scores 46 on the Artificial Analysis Coding Agent Index, ahead of Claude Haiku 5.5 in Claude Code (37) and GPT-6 Luna in Codex (31). Its lead comes from SWE-Atlas-QnA-AA and Terminal-Bench 4.0, while it trails Claude Haiku 5.5 on FrontierCode, as it does in our Intelligence Index

Knowledge is Muse Ember's main weakness, but it rarely hallucinates

Its AA-Omniscience accuracy of 21.1% is the lowest of the similarly intelligent models we compared, mostly because it declines to answer 64% of questions. That keeps its hallucination rate at 17.4%, half of Claude Haiku 5.5's

Full Artificial Analysis Intelligence Index results for Muse Ember (max)

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