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DeepSeek-V4

The open-source era of 1M context intelligence

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DeepSeek-V4 Preview is a new series of highly efficient MoE language models, featuring V4-Pro (1.6T params) and V4-Flash (284B params). Both models support a 1 million token context window by default, utilizing a novel hybrid attention architecture to drastically reduce compute and memory costs.

PH · launched Apr 24, 2026 · 393 upvotes (top 19%) · 0 views

Niche: large language models · 191 launches, 4 in the last 7 days ▼ -33% · Explore this niche →

Category and tags

  • Horizontal
  • Model & infra
  • Developer
  • AI-native
  • Commercial product
  • Open Source
  • Artificial Intelligence
  • Development

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Could you build this?

No Training and releasing frontier-tier 1.6T parameter MoE foundation models with custom hybrid attention architectures requires tens of millions of dollars in compute, massive GPU clusters, and world-class AI research teams.

What it would actually take: Creating frontier models like DeepSeek-V4 requires massive multi-node training infrastructure (thousands of H800/H100 GPUs interconnected via InfiniBand), proprietary distributed training frameworks (tensor/pipeline/expert parallelism), petabyte-scale curated pretraining datasets, custom CUDA/Triton kernels for hybrid attention, and an expert research team in large-scale deep learning.

Competitors

Other products that read as similar to this one : 407 launches clear the similarity bar, closest 8 shown.

Attention rank: #84 of 408 (itself plus its competitors, highest first, normalized so YC and Product Hunt are compared fairly).

Launched 175 days after the earliest competitor.

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