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  • I have been trying to stick with a DeepSeek+ OpenCode setup for the whole week, but seems like my subsidized Claude Max is still quite relevant
    by krlx
  • Also, just talking about the raw input / output raw cost leaves out half of the equation. You also have to think about how a given providers caching strategy behaves, and how many tokens a given model actually uses to complete a task on average.

    Just because a model has a higher input / output token cost doesn't necessarily always mean it's going to be more expensive to use.

  • I don’t think you could’ve picked a shittier title.

    Don’t bother with the link, here’s a quick rundown:

    DeepSeek is raising API prices for its V4 models and introducing peak/off-peak pricing. For V4-Pro, uncached input goes from $0.435 per million tokens to $0.66 off-peak or $1.32 at peak; output rises from $0.87 to $1.98 or $3.96. The four-digit percentage increase comes from cached input, which was priced at an unusually low $0.003625 per million tokens and is rising to as much as $0.044.

    Even after the increase, DeepSeek remains cheap relative to major frontier models. Claude Sonnet 5 costs $2 per million input tokens and $10 per million output tokens; Claude Opus 5 costs $5/$25. OpenAI’s GPT-5.6 Terra is $2/$12, while GPT-5.6 Sol is $5/$30.

    So at peak rates, DeepSeek V4-Pro still costs about two-thirds as much as Sonnet on input and roughly 40% as much on output. Off-peak, the gap is wider.

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