0xBakeer/deepseek-v41-flash-spark

DeepSeek-V4.1-Flash on a single DGX Spark (GB10): resident hot experts + NVMe streaming, DSpark, OpenAI API. Work in progress.

Language modelsPython

2.4 Early signal Magnitude out of 10. Star growth looks organic. Data as of September 14, 2026.

Open on Seismograph Open on GitHub

About the project

A recipe for serving DeepSeek-V4.1-Flash (510 GB, 15,360 FP4 experts) on a single NVIDIA DGX Spark: a hot set of experts stays resident while the rest stream from NVMe via O_DIRECT, plus DSpark speculative decoding and an OpenAI-compatible API. Work in progress.

Useful for

Run an OpenAI-compatible DeepSeek-V4.1-Flash server on a single DGX Spark without tensor parallelism
Run bench/bench.py to compare tok/s, expert hit rate and NVMe read volume across configurations
Connect Open WebUI to the server and check reasoning_content streaming

README summarized by DeepSeek V4.1 Flash. Details may be inaccurate.

Why it’s trending

5 stars today.
The spike has held for 3 days in a row — not a one-off blip.
The repository is 3 days old and already has 71 stars.
Recent forks include notable developers: @mrpmorris (290 followers).

Stars per day

Bars are daily stars, the line is the usual pace. Red marks spike days.

Numbers

Total stars: 71
Stars in a day: 5
Forks: 10
Issues and pull requests: 4
Watchers: 3
Language: Python
License: MIT
Created: September 10, 2026
Last push: September 12, 2026

Star trust

Growth looks organic: forks and discussion are in line with active projects, and stars arrive unevenly, the way people give them.

These are heuristics, not a verdict: we judge by the repository’s behavior, not by a list of stargazers.

Spotted in

September 13, 2026Top new repositories this week: #195

README badge

Paste it into your README — the badge shows the current magnitude and links to this page.

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