# DeepSeek releases V4 Flash model at $0.14 per million tokens

> Chinese lab DeepSeek has officially taken its V4 Flash model out of preview as of August 1, 2026, and the number that matters is the price: 14 cents per million input tokens. That undercuts frontier alternatives dramatically, continuing the aggressive discounting DeepSeek has become known for. The strategy is clear. By pricing inference at a level that makes high volume usage affordable, DeepSeek is aiming squarely at cost conscious developers who might otherwise default to pricier American models. Flash tier models trade a little peak capability for speed and economics, which is exactly what many production applications actually need. This continues a broader pattern in which Chinese labs compete less on raw benchmark supremacy and more on efficiency and accessibility. For the global market, relentless price pressure from DeepSeek keeps forcing the incumbents to justify their premiums, and it steadily lowers the cost of building on top of capable models.

_Section: [Daily AI Updates](https://www.wortins.com/daily-ai) · Source: LLM Stats · Published Sunday, August 2, 2026_

## Wortins' read

Chinese lab DeepSeek has officially taken its V4 Flash model out of preview as of August 1, 2026, and the number that matters is the price: 14 cents per million input tokens. That undercuts frontier alternatives dramatically, continuing the aggressive discounting DeepSeek has become known for. The strategy is clear. By pricing inference at a level that makes high volume usage affordable, DeepSeek is aiming squarely at cost conscious developers who might otherwise default to pricier American models. Flash tier models trade a little peak capability for speed and economics, which is exactly what many production applications actually need. This continues a broader pattern in which Chinese labs compete less on raw benchmark supremacy and more on efficiency and accessibility. For the global market, relentless price pressure from DeepSeek keeps forcing the incumbents to justify their premiums, and it steadily lowers the cost of building on top of capable models.

## Source

[Read the full story at LLM Stats](https://llm-stats.com/llm-updates)

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