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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
General-purpose text generation, chat, summarization and content workloads where broad capability and low cost matter most.
DeepSeek-V3.1 is a large hybrid reasoning model (671B parameters, 37B active) that supports both thinking and non-thinking modes via prompt templates. It extends the DeepSeek-V3 base with a two-phase long-context...
deepseek-chat-v3.1 is a Text model from DeepSeek (CN). HotON.ai tracks it at $0.15 per 1M input tokens and $0.75 per 1M output tokens, with a 33K-token context window. Its composite efficiency score is 88/100 at an estimated $0.001 per successful task.
deepseek-chat-v3.1 is tracked at $0.15 per 1M input tokens and $0.75 per 1M output tokens. A typical 3:1 output-to-input workload blends to roughly $0.60 per 1M tokens. Figures are illustrative demo data.
General-purpose text generation, chat, summarization and content workloads where broad capability and low cost matter most.
deepseek-chat-v3.1 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, deepseek-chat-v3.1 is cheaper than 70% of models on input price and ranks #354 of 537 by overall efficiency.
Yes — deepseek/deepseek-v4-flash is a lower-cost option at $0.28 per 1M output tokens, while still covering similar Text use cases. Compare them side by side on HotON.ai.
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HotON.ai — deepseek-chat-v3.1 (DeepSeek): $0.15/1M input, $0.75/1M output, as of 2026-04-28. https://hoton.ai/en/models/deepseek-deepseek-chat-v3-1Pricing 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.