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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 2026-04-28 · Source: legacy_model_catalog
Complex reasoning, analysis, planning and multi-step problem solving where answer quality matters more than raw cost.
QwQ is the reasoning model of the Qwen series. Compared with conventional instruction-tuned models, QwQ, which is capable of thinking and reasoning, can achieve significantly enhanced performance in downstream tasks,...
qwq-32b is a Reasoning model from Alibaba Cloud · Qwen (CN). HotON.ai tracks it at $0.15 per 1M input tokens and $0.58 per 1M output tokens, with a 131K-token context window. Its composite efficiency score is 89/100 at an estimated $0.001 per successful task.
qwq-32b is tracked at $0.15 per 1M input tokens and $0.58 per 1M output tokens. A typical 3:1 output-to-input workload blends to roughly $0.47 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.
qwq-32b 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, qwq-32b is cheaper than 70% of models on input price and ranks #177 of 535 by overall efficiency.
Yes — grok-4-1-fast-reasoning is a lower-cost option at $0.50 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 — qwq-32b (Alibaba Cloud · Qwen): $0.15/1M input, $0.58/1M output, as of 2026-04-28. https://hoton.ai/en/models/qwen-qwq-32bPricing 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.