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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
Complex reasoning, analysis, planning and multi-step problem solving where answer quality matters more than raw cost.
DeepSeek R1 is here: Performance on par with OpenAI o1, but open-sourced and with fully open reasoning tokens. It's 671B parameters in size, with 37B active in an inference pass....
deepseek-r1 is a Reasoning model from DeepSeek (CN). HotON.ai tracks it at $0.70 per 1M input tokens and $2.50 per 1M output tokens, with a 64K-token context window. Its composite efficiency score is 88/100 at an estimated $0.003 per successful task.
deepseek-r1 is tracked at $0.70 per 1M input tokens and $2.50 per 1M output tokens. A typical 3:1 output-to-input workload blends to roughly $2.05 per 1M tokens. Figures are illustrative demo data.
Complex reasoning, analysis, planning and multi-step problem solving where answer quality matters more than raw cost.
deepseek-r1 supports up to a 64K-token context window — large enough for long documents and extended conversations in a single request.
Within the HotON.ai tracked set, deepseek-r1 is cheaper than 38% of models on input price and ranks #403 of 537 by overall efficiency.
Yes — grok-4-fast-reasoning is a lower-cost option at $0.50 per 1M output tokens, while still covering similar Reasoning use cases. Compare them side by side on HotON.ai.
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HotON.ai — deepseek-r1 (DeepSeek): $0.70/1M input, $2.50/1M output, as of 2026-04-28. https://hoton.ai/en/models/deepseek-deepseek-r1Pricing 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.