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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 2026-05-10 · Source: qwen_model_studio_official_pricing
General-purpose text generation, chat, summarization and content workloads where broad capability and low cost matter most.
Qwen-Max, based on Qwen2.5, provides the best inference performance among Qwen models, especially for complex multi-step tasks. It's a large-scale MoE model that has been pretrained on over 20 trillion...
qwen-max is a Text model from Alibaba Cloud · Qwen (CN). HotON.ai tracks it at $1.04 per 1M input tokens and $4.16 per 1M output tokens, with a 33K-token context window. Its composite efficiency score is 87/100 at an estimated $0.004 per successful task.
qwen-max is tracked at $1.04 per 1M input tokens and $4.16 per 1M output tokens. A typical 3:1 output-to-input workload blends to roughly $3.38 per 1M tokens. Figures are illustrative demo data.
General-purpose text generation, chat, summarization and content workloads where broad capability and low cost matter most.
qwen-max supports up to a 33K-token context window — large enough for long documents and extended conversations in a single request.
Within the HotON.ai tracked set, qwen-max is cheaper than 27% of models on input price and ranks #425 of 537 by overall efficiency.
Yes — minimax-m2 is a lower-cost option at $1.00 per 1M output tokens, while still covering similar Text use cases. Compare them side by side on HotON.ai.
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HotON.ai — qwen-max (Alibaba Cloud · Qwen): $1.04/1M input, $4.16/1M output, as of 2026-05-10. https://hoton.ai/en/models/qwen-qwen-maxPricing 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.