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DeepSeekAugust 6, 20261 sources

DeepSeek warns of 2x–10x API price hikes; resumes $8B raise at $500B valuation

AI Analysis

Chinese AI startup DeepSeek warned of a 'significant' API price increase in the near future, with founder Jun Song signaling hikes that could range from 2x to 10x — while pledging that prices will remain below Western rivals. The company cited surging global demand for its aggressively cheap models, coming just a week after the release of DeepSeek-V4-Flash-0731. V4-Flash currently costs $0.14 per million input tokens on a cache miss and $0.28 output, and topped OpenRouter's weekly usage charts at 7.22 trillion tokens — evidence of just how much load the low pricing has attracted.

Separately, DeepSeek restarted a second funding round seeking $8 billion at a $500 billion pre-investment valuation, a staggering figure that reflects investor appetite for the company that repeatedly upends per-token economics. The price-hike warning underscores the central tension: DeepSeek's growth is built on undercutting everyone, but serving 7T+ tokens a week at rock-bottom prices is economically punishing amid a fierce China price war that also features Alibaba's new Qwen3.8-Max.

Developer reaction was pointed. The vague warning drew frustration on developer forums — dataconomy and Reddit threads complained about being told to 'plan usage accordingly' with no timeline or concrete rates. Yet loyalty runs deep on cost: an r/DeepSeek post, 'I canceled Claude and coded 7 days straight with DeepSeek V4 Flash,' hit 471 upvotes with a detailed cost/quality breakdown, and a V4-Flash-vs-GPT-5.6-Luna comparison thread drew 207. DeepSeek was even reported recruiting engineers in Germany, signaling international ambitions.

The watch item is timing and magnitude: a 10x hike would fundamentally change DeepSeek's value proposition and could send price-sensitive developers back to open-weights alternatives like Qwen, while a modest bump preserves its cost lead. The episode captures the week's cost-economics theme — the cheapest models are discovering the limits of cheap.

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