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DeepSeek v4 Flash launched in public beta (announced via DeepSeek tweet and…

2026-07-31 · 16:29 UTC ·@AlexFinn ·1 min read

Brief

DeepSeek v4 Flash is out in public beta and, per the DeepSeek announcement and @alexfinn (2026-07-31), claims significant benchmark gains over Fable and the v4-Pro-Preview. The post asserts some versions run on 96 GB Mac Studio or DGX Spark (≈$4,000-class hardware), pushing local AI adoption and stressing Responses API/Codex support and improved agent features.

Why it matters

DeepSeek v4 Flash launched in public beta (announced via DeepSeek tweet and reposted by @alexfinn on 2026-07-31) and reportedly outperforms Fable on some benchmarks, with the v4-Flash surpassing the v4-Pro-Preview.

Key details

  • Author claims some v4-Flash variants can run on consumer-grade hardware (96 GB Mac Studio) or a DGX Spark, arguing that ~$4,000 hardware now delivers "unlimited super intelligence" and will undercut frontier labs’ high pricing.
  • DeepSeek-V4-Flash API is live in public beta, natively supports the Responses API format and Codex, and includes major agent-capability upgrades according to DeepSeek’s official announcement.
Source evidence

You can now host frontier AI on average hardware

Deepseek v4 Flash has arrived and it BEATS Fable on some benchmarks

O and you can run some versions of it on 96gb Mac Studio or even a DGX Spark

$4,000 hardware now gives you unlimited super intellgence

This rocks the AI industry to the core. Frontier labs won't be able to get away with charging exorbitant prices for intelligence (cough Fable)

The more these labs battle, the more we as the consumer win

Never been more important to get into local AI, especially as the hardware only gets more and more unavailable

DeepSeek (@deepseek_ai)

🚀 DeepSeek-V4-Flash Official API is now LIVE in public beta!

🔷 We’ve massively upgraded its Agent capabilities—benchmark scores are now far surpassing the V4-Pro-Preview. Check out the massive performance leap below! 👇
🔷 The official V4-Flash now natively supports the Responses API format and is fully adapted for Codex!

Check out the configuration details in our official API docs: api-docs.deepseek.com/quick_…

— https://nitter.net/deepseek_ai/status/2083084415157022911#m