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Real human-preference Elo from LMArena blind head-to-head votes. Higher is better; — means not yet ranked in that arena. This is measured, not our estimate.
Daily blended price ($/1M) — recorded each day, builds into a trend over time.
Typical 3:1 output-to-input mix, per 1M tokens
Source: litellm
General-purpose text generation, chat, summarization and content workloads where broad capability and low cost matter most.
Qwen3.7 Max is a higher-capability Qwen route tracked so the catalog matches the newest flagship naming from Model Studio.
qwen3.7-max is a Text model from Qwen (CN). HotON.ai tracks it at $2.50 per 1M input tokens and $7.50 per 1M output tokens, with a 262K-token context window. Its composite efficiency score is 87/100 at an estimated $0.009 per successful task.
qwen3.7-max is tracked at $2.50 per 1M input tokens and $7.50 per 1M output tokens. A typical 3:1 output-to-input workload blends to roughly $6.25 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.
qwen3.7-max supports up to a 262K-token context window — large enough for long documents and extended conversations in a single request.
Within the HotON.ai tracked set, qwen3.7-max is cheaper than 12% of models on input price and ranks #435 of 537 by overall efficiency.
Yes — deepseek/deepseek-v4-flash is a lower-cost option at $0.28 per 1M output tokens, while still covering similar Text use cases. Compare them side by side on HotON.ai.
Ready to paste into articles, papers or AI prompts — prices and date refresh with the live data.
HotON.ai — qwen3.7-max (Qwen): $2.50/1M input, $7.50/1M output. https://hoton.ai/en/models/qwen-qwen3-7-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.