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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
Code generation, refactoring and review, and developer-tooling workloads with large context.
Qwen2.5-Coder-7B-Instruct is a 7B parameter instruction-tuned language model optimized for code-related tasks such as code generation, reasoning, and bug fixing. Based on the Qwen2.5 architecture, it incorporates enha...
qwen2.5-coder-7b-instruct is a Code model from Alibaba Cloud · Qwen (CN). HotON.ai tracks it at $0.03 per 1M input tokens and $0.09 per 1M output tokens, with a 33K-token context window. Its composite efficiency score is 89/100 at an estimated $0.000 per successful task.
qwen2.5-coder-7b-instruct is tracked at $0.03 per 1M input tokens and $0.09 per 1M output tokens. A typical 3:1 output-to-input workload blends to roughly $0.08 per 1M tokens. Figures are illustrative demo data.
Code generation, refactoring and review, and developer-tooling workloads with large context.
qwen2.5-coder-7b-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-coder-7b-instruct is cheaper than 95% of models on input price and ranks #190 of 535 by overall efficiency.
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HotON.ai — qwen2.5-coder-7b-instruct (Alibaba Cloud · Qwen): $0.03/1M input, $0.09/1M output, as of 2026-04-28. https://hoton.ai/en/models/qwen-qwen2-5-coder-7b-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.