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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
Mixed text, image, audio and document workloads that benefit from one model across modalities.
Qwen3.5-9B is a multimodal foundation model from the Qwen3.5 family, designed to deliver strong reasoning, coding, and visual understanding in an efficient 9B-parameter architecture. It uses a unified vision-language...
qwen3.5-9b is a Multimodal model from Alibaba Cloud · Qwen (CN). HotON.ai tracks it at $0.05 per 1M input tokens and $0.15 per 1M output tokens, with a 256K-token context window. Its composite efficiency score is 90/100 at an estimated $0.000 per successful task.
qwen3.5-9b is tracked at $0.05 per 1M input tokens and $0.15 per 1M output tokens. A typical 3:1 output-to-input workload blends to roughly $0.12 per 1M tokens. Figures are illustrative demo data.
Mixed text, image, audio and document workloads that benefit from one model across modalities.
qwen3.5-9b supports up to a 256K-token context window — large enough for long documents and extended conversations in a single request.
Within the HotON.ai tracked set, qwen3.5-9b is cheaper than 91% of models on input price and ranks #102 of 535 by overall efficiency.
Yes — gemma-3-12b-it is a lower-cost option at $0.13 per 1M output tokens, while still covering similar Multimodal use cases. Compare them side by side on HotON.ai.
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HotON.ai — qwen3.5-9b (Alibaba Cloud · Qwen): $0.05/1M input, $0.15/1M output, as of 2026-04-28. https://hoton.ai/en/models/qwen-qwen3-5-9bPricing 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.