# sybil-solutions/dsv41-flash-offload

> Serves DeepSeek-V4.1-Flash (EXL3 3.0 bpw) on a single 24 GB RTX 3090 by offloading experts to DDR4 and NVMe, exposing an OpenAI-compatible API. Aimed at running a large MoE model locally on consumer hardware.

- Magnitude: 2.6 out of 10 — Early signal
- Stars: 102 total · +4 stars measured 2026-10-07, 00:21–12:43 UTC, ≈ 9 by evening
- Star trust: star growth looks organic
- Category: Language models · Language: Python · License: MIT · Created: 2026-10-02 · Last push: 2026-10-07
- GitHub: https://github.com/sybil-solutions/dsv41-flash-offload · Page: https://gitnova.dev/en/r/sybil-solutions/dsv41-flash-offload

## Useful for

- Run a local OpenAI-compatible DeepSeek-V4.1-Flash server on a single RTX 3090
- Process long contexts up to 262k tokens for retrieval and coding tasks
- Build the pinned-digest Docker image for reproducible deployment

## Why it’s here

- Star-counter measurements on 2026-10-07 (UTC), 00:21–12:43: 98 → 102 stars (+4). This is the change over that interval.
- Estimated end-of-day forecast: about +9 stars, using observed gains and the previous day.
- The repository is 5 days old and already has 102 stars. With less than two weeks of history, there's no usual pace to compare the spike against yet.
- Top new repositories this week: #130.
- Recent forks include notable developers: @0xSojalSec (1,007 followers).

## Star trust

Star growth looks organic.

Star-trust labels are heuristics based on the repository’s behavior, not a check of every stargazer.

## Numbers

- Forks: 12
- Issues and pull requests: 1
- Watchers: 0
- Average over the last week: 18 per day
- Usual pace: too little history (under two weeks)
- Stars in the last hour (measured): 0

## Stars per day, last 11 days (oldest → newest, today is partial)

2026-09-27 … 2026-10-07: 0, 0, 0, 0, 0, 19, 8, 5, 54, 15, 4

## Magnitude by day, last 3 days

10-05 1.8, 10-06 4.1, 10-07 2.8

## Spotted in now

- Top new repositories this week: #130

## More in this category

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   CUDA tensor core kernel library: GEMM (FP8, FP4, BF16), fused MoE, MQA scoring for the indexer. Kernels compile at runtime via DeepJIT, no CUDA build at install time.
   Full card: https://gitnova.dev/en/r/deepseek-ai/DeepGEMM.md
2. **Niko1221/Strata** — 6.3 · Peaking · Language models · C++ · +749 stars measured 2026-10-07, 00:19–12:38 UTC, ≈ 1,454 by evening
   A C++ local inference engine that runs the 125B MoE model Qwen3.8-Flash-Next on a regular PC with one NVIDIA GPU (12-24 GB) and 64 GB RAM, exposing an OpenAI/Anthropic-compatible API on localhost.
   Full card: https://gitnova.dev/en/r/Niko1221/Strata.md
3. **Edge0-AI/Edge0** — 4.7 · Breakout · Language models · Python · +215 stars measured 2026-10-07, 00:20–12:39 UTC, ≈ 362 by evening
   An open-source streaming MoE inference framework: expert weights are offloaded from SSD on demand while a trained prerouter predicts routing ahead of time. Runs on Apple Silicon via MLX and ships with two ready-to-run model tiers (35B and…
   Full card: https://gitnova.dev/en/r/Edge0-AI/Edge0.md
4. **StayLameBro/backburner** — 4.5 · Early signal · Language models · Python · +50 stars measured 2026-10-07, 00:20–12:39 UTC, ≈ 95 by evening
   A llama.cpp fork that plugs an iPhone into a Mac over USB-C and splits the work: the Mac runs layers 1-40, the iPhone runs 41-64 on its GPU, speeding up prefill and allowing context up to 196k-229k tokens. Aimed at people running…
   Full card: https://gitnova.dev/en/r/StayLameBro/backburner.md
5. **Hiteater-wzm/eeo** — 4.3 · Early signal · Language models · JavaScript · +10 stars measured 2026-10-07, 00:20–12:39 UTC, ≈ 24 by evening
   An open community and toolkit for "Everything Engine Optimization": brands publish machine-readable cards about themselves, and the tooling measures how visible a brand is in AI engine answers.
   Full card: https://gitnova.dev/en/r/Hiteater-wzm/eeo.md

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Magnitude (0–10) measures how fast and how unusually interest in a repository is growing right now. It is not a quality score.
Days are UTC. “So far today” is a fact; “expected by the end of the day” is a forecast.
Summaries and use cases are written by an LLM (DeepSeek V4.1 Flash) from the README and may be inaccurate: verify specific claims (benchmarks, speed, hardware) in the repository itself.
Data as of 2026-10-07 12:58 UTC, updated every 30 minutes.