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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.
Qwen2.5-VL is proficient in recognizing common objects such as flowers, birds, fish, and insects. It is also highly capable of analyzing texts, charts, icons, graphics, and layouts within images.
qwen2.5-vl-72b-instruct is a Multimodal model from Alibaba Cloud · Qwen (CN). HotON.ai tracks it at $0.80 per 1M input tokens and $0.80 per 1M output tokens, with a 33K-token context window. Its composite efficiency score is 88/100 at an estimated $0.002 per successful task.
qwen2.5-vl-72b-instruct is tracked at $0.80 per 1M input tokens and $0.80 per 1M output tokens. A typical 3:1 output-to-input workload blends to roughly $0.80 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-72b-instruct supports up to a 33K-token context window — large enough for long documents and extended conversations in a single request.
Within the HotON.ai tracked set, qwen2.5-vl-72b-instruct is cheaper than 35% of models on input price and ranks #365 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-72b-instruct (Alibaba Cloud · Qwen): $0.80/1M input, $0.80/1M output, as of 2026-04-28. https://hoton.ai/en/models/qwen-qwen2-5-vl-72b-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.