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Daily blended price ($/1M) — recorded each day, builds into a trend over time.
Typical 3:1 output-to-input mix, per 1M tokens
Price as of 2026-05-11 · Source: arcee_ai_reference_catalog
Complex reasoning, analysis, planning and multi-step problem solving where answer quality matters more than raw cost.
Maestro Reasoning is Arcee's flagship analysis model: a 32 B‑parameter derivative of Qwen 2.5‑32 B tuned with DPO and chain‑of‑thought RL for step‑by‑step logic. Compared to the earlier 7 B...
maestro-reasoning is a Reasoning model from Arcee Ai (US). HotON.ai tracks it at $0.90 per 1M input tokens and $3.30 per 1M output tokens, with a 131K-token context window. Its composite efficiency score is 88/100 at an estimated $0.003 per successful task.
maestro-reasoning is tracked at $0.90 per 1M input tokens and $3.30 per 1M output tokens. A typical 3:1 output-to-input workload blends to roughly $2.70 per 1M tokens. Figures are illustrative demo data.
Complex reasoning, analysis, planning and multi-step problem solving where answer quality matters more than raw cost.
maestro-reasoning supports up to a 131K-token context window — large enough for long documents and extended conversations in a single request.
Within the HotON.ai tracked set, maestro-reasoning is cheaper than 32% of models on input price and ranks #310 of 535 by overall efficiency.
Yes — qwen-plus-2025-07-28:thinking is a lower-cost option at $0.78 per 1M output tokens, while still covering similar Reasoning use cases. Compare them side by side on HotON.ai.
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HotON.ai — maestro-reasoning (Arcee Ai): $0.90/1M input, $3.30/1M output, as of 2026-05-11. https://hoton.ai/en/models/arcee-ai-maestro-reasoningPricing is real (via the TestKey catalog, updated daily). Quality (Arena Elo) is real where the model is ranked on LMArena. Efficiency is a modeled composite of real price and context.