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DeepSeek-V4.1-Flash-vLLM-DGX-Spark

DeepSeek-V4.1-Flash (552B MoE, MXFP4 experts, 1M ctx) on four NVIDIA DGX Sparks with vLLM TP4: Engram-on-disk patch, sm121 kernel build, launchers, measured numbers

Details

External ID
1363702538
Source
GITHUB
Company
—
Product
DeepSeek-V4.1-Flash-vLLM-DGX-Spark
Website domain
github.com
Launched
Sept. 10, 2026
Cohort
—
Upvotes
65
Upvotes percentile
0.8747117601844735
Tags
—
Fetched at
Sept. 14, 2026, 5:28 p.m.
Updated at
Sept. 14, 2026, 5:28 p.m.

Enrichment

Theme
DeepSeek model deployment and inference
Vertical
Horizontal
Function
Model & infra
Audience
Developer
AI stance
AI-native
Project type
Hobby / open-source project
Normalized one-liner
vllm deployment scripts for deepseek-v4.1-flash on dgx spark
Manually corrected
False

Could you build this?

No Deploying and optimizing a 552B MoE model across multi-node DGX hardware requires custom sm121 GPU kernels, distributed inference tuning, and massive hardware infrastructure.

What it would actually take: Building this requires low-level CUDA and C++ expertise to write and optimize sm121 MXFP4 kernels, alongside deep modifications to vLLM's tensor-parallel distributed runtime and page cache management. Developing and testing this setup necessitates access to multi-node enterprise NVIDIA DGX clusters and high-speed InfiniBand networking.

Competitors

Other products that read as similar to this one — 121 launches clear the similarity bar, closest 8 shown.

Attention rank: #22 of 122 (itself plus its competitors, highest first — normalized so YC and Product Hunt are compared fairly).

Launched 263 days after the earliest competitor.

Other launches for this product

Same idea, different domain

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