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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: openrouter
General-purpose text generation, chat, summarization and content workloads where broad capability and low cost matter most.
Qwen3.7 Plus is a balanced Qwen3.7 route between flagship depth and more practical deployment cost.
qwen3.7-plus is a Text model from Qwen (CN). HotON.ai tracks it at $0.32 per 1M input tokens and $1.28 per 1M output tokens, with a 262K-token context window. Its composite efficiency score is 90/100 at an estimated $0.001 per successful task.
qwen3.7-plus is tracked at $0.32 per 1M input tokens and $1.28 per 1M output tokens. A typical 3:1 output-to-input workload blends to roughly $1.04 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-plus 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-plus is cheaper than 50% of models on input price and ranks #100 of 535 by overall efficiency.
Yes — minimax-m2.1 is a lower-cost option at $0.95 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 — qwen3.7-plus (Qwen): $0.32/1M input, $1.28/1M output. https://hoton.ai/en/models/qwen-qwen3-7-plusPricing 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.