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keys-DeepSeekV4.1-Flash-TR3-Hybrid-1M-Context-8M-KV-Four-DGX-Sparks-with-abliterated-option

DeepSeek-V4.1-Flash TR3-Hybrid: 1M context, 8M+ KV pool (9,452,923 tokens) on 4x DGX Spark, TP4, CUDA graphs + DSpark k=5 + vision + tools. Pool grown via GMU 0.83 + batch 2048. With abliterated option.

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GITHUB · launched Sep 13, 2026 · 6 upvotes (top 99%) · 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
  • Hobby / open-source project

Visit website ↗ Source listing ↗

Could you build this?

No Serving a 1M-context model with an 8M+ KV cache pool across multi-node DGX systems requires massive enterprise GPU infrastructure and deep distributed systems optimization.

What it would actually take: The stack relies on distributed inference engines (vLLM or custom TensorRT-LLM) using Tensor Parallelism (TP4), custom CUDA graph capture, and specialized KV-cache memory offloading. The hardest part is stabilizing memory bandwidth, synchronization, and latency across multi-DGX setups for nearly 10 million KV tokens. This requires hundreds of thousands of dollars in GPU hardware and elite high-performance computing (HPC) engineering skills.

Competitors

Other products that read as similar to this one : 225 launches clear the similarity bar, closest 8 shown.

Attention rank: #221 of 226 (itself plus its competitors, highest first, normalized so YC and Product Hunt are compared fairly).

Launched 299 days after the earliest competitor.

The niche, labels, vibe code rating and competitor comparison on this page are analysis by Nicheloom. If you use them, please credit nicheloom.com. How you may use our data.