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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.
Qwen3-Coder-Next is an open-weight causal language model optimized for coding agents and local development workflows. It uses a sparse MoE design with 80B total parameters and only 3B activated per...
qwen3-coder-next is a Code model from Alibaba Cloud · Qwen (CN). HotON.ai tracks it at $0.12 per 1M input tokens and $0.75 per 1M output tokens, with a 262K-token context window. Its composite efficiency score is 90/100 at an estimated $0.001 per successful task.
qwen3-coder-next is tracked at $0.12 per 1M input tokens and $0.75 per 1M output tokens. A typical 3:1 output-to-input workload blends to roughly $0.59 per 1M tokens. Figures are illustrative demo data.
Code generation, refactoring and review, and developer-tooling workloads with large context.
qwen3-coder-next supports up to a 262K-token context window — large enough for long documents and extended conversations in a single request.
Within the HotON.ai tracked set, qwen3-coder-next is cheaper than 77% of models on input price and ranks #116 of 537 by overall efficiency.
Yes — qwen3-coder-30b-a3b-instruct is a lower-cost option at $0.27 per 1M output tokens, while still covering similar Code use cases. Compare them side by side on HotON.ai.
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HotON.ai — qwen3-coder-next (Alibaba Cloud · Qwen): $0.12/1M input, $0.75/1M output, as of 2026-04-28. https://hoton.ai/en/models/qwen-qwen3-coder-nextPricing 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.