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%.

November 9, 2026 Meta's newest model Muse Ember scores 36 on the Artificial Analysis Intelligence Index, matching Claude Haiku 5.5 max at a third of the Cost per Task See model page https://artificialanalysis.ai/models/muse-ember 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 Read the latest Introducing the Artificial Analysis Decision Index v2 Introducing the Artificial Analysis Decision Index v2: a new proprietary evaluation, updated benchmarks, and a headline metric that rewards model calibration November 8, 2026 VIALS-AA: different paths to scientific image reasoning Independent VIALS-AA results, interactive agent traces, and an analysis of how models inspect scientific images. November 6, 2026 Thinking Machines Inkling 2 Small: the highest scoring open weights model outside of China pending weights release Thinking Machines has released Inkling 2 Small, scoring 31 on the Artificial Analysis Intelligence Index - their plan to release its weights would make it the highest-scoring open weights model developed outside China based on current rankings November 5, 2026