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Blended $/1M across tracked versions of this line.
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.
Qwen2.5-VL-32B is a multimodal vision-language model fine-tuned through reinforcement learning for enhanced mathematical reasoning, structured outputs, and visual problem-solving capabilities. It excels at visual anal...
qwen2.5-vl-32b-instruct is a Multimodal model from Alibaba Cloud · Qwen (CN). HotON.ai tracks it at $0.20 per 1M input tokens and $0.60 per 1M output tokens, with a 128K-token context window. Its composite efficiency score is 89/100 at an estimated $0.001 per successful task.
qwen2.5-vl-32b-instruct is tracked at $0.20 per 1M input tokens and $0.60 per 1M output tokens. A typical 3:1 output-to-input workload blends to roughly $0.50 per 1M tokens. Figures are illustrative demo data.
Mixed text, image, audio and document workloads that benefit from one model across modalities.
qwen2.5-vl-32b-instruct supports up to a 128K-token context window — large enough for long documents and extended conversations in a single request.
Within the HotON.ai tracked set, qwen2.5-vl-32b-instruct is cheaper than 62% of models on input price and ranks #157 of 535 by overall efficiency.
Yes — grok-4-fast is a lower-cost option at $0.50 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 — qwen2.5-vl-32b-instruct (Alibaba Cloud · Qwen): $0.20/1M input, $0.60/1M output, as of 2026-04-28. https://hoton.ai/en/models/qwen-qwen2-5-vl-32b-instructPricing 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.