Footer

Your go-to destination for discovering trending open-source projects and uncovering the insights that matter

Legal

  • Terms and conditions
  • Privacy policy

More

  • Pricing
  • Advertise
  • onedump
  • gosnakego
  • Contact us

Social

  • X (Twitter)
  • GitHub
Trendshift owl
What they build speaks louder than words
© 2026 Trendshift, created by Julian Li with ❤️
SignalAdvertise
Trendshift
SignalAdvertise
Sign in
Trendshift owl

Discover trends that matter

SignalAdvertise
DailyWeeklyMonthlyYearly
Live mentionsTopics
RepositoriesDevelopers
InsightsStats
Bifrost
Bifrost

bodhi37/Qwen3.8-Flash-12GBRAM-32GBVRAM-SSD-Recipe

Qwen3.8-Flash-Next IQ3_S on 12 GB VRAM + 32 GB RAM + NVMe: ~45-50 tok/s decode, 131k context, Strata unify fork

#LLM inference
Visit GitHub
Shell
19
1 contributors
MIT License
FeaturedAdvertise to 180K+ monthly visitors
Bifrost

Fastest Enterprise AI Gateway for Routing, Governing, and Securing all your AI Traffic

Momentum

How fast bodhi37/Qwen3.8-Flash-12GBRAM-32GBVRAM-SSD-Recipe is gaining stars, and where it lands on Trendshift and GitHub Trending

Activity and trending

Stars, forks and merged pull requests each day or month, lined up with the repository's rank on Trendshift Trending

Oct 8 – Nov 5, 2026

Stars +21 in 29 days

0246
5

Forks +0 in 29 days

01

Merged PRs 0 in 29 days

01

Trendshift Trendingwhere the repository ranked each day it made the top 25

Not in the Trendshift top 25 in this period

Oct 8Oct 12Oct 16Oct 20Oct 24Oct 28Nov 1Nov 5
The left and right arrow keys step from day to day; Home and End go to the first and the last

Stars, forks, merged pull requests and Trendshift Trending rank, by day
DayStars gainedForks gainedMerged PRs
Thu, Oct 8, 2026+0+00
Fri, Oct 9, 2026+5+00
Sat, Oct 10, 2026+2+00
Sun, Oct 11, 2026+1+00
Mon, Oct 12, 2026+0+00
Tue, Oct 13, 2026+0+00
Wed, Oct 14, 2026+0+00
Thu, Oct 15, 2026+0+00
Fri, Oct 16, 2026+0+00
Sat, Oct 17, 2026+5+00
Sun, Oct 18, 2026+1+00
Mon, Oct 19, 2026+1+00
Tue, Oct 20, 2026+1+00
Wed, Oct 21, 2026+1+00
Thu, Oct 22, 2026+0+00
Fri, Oct 23, 2026+0+00
Sat, Oct 24, 2026+1+00
Sun, Oct 25, 2026+0+00
Mon, Oct 26, 2026+0+00
Tue, Oct 27, 2026+1+00
Wed, Oct 28, 2026+1+00
Thu, Oct 29, 2026+0+00
Fri, Oct 30, 2026+0+00
Sat, Oct 31, 2026+0+00
Sun, Nov 1, 2026+1+00
Mon, Nov 2, 2026+0+00
Tue, Nov 3, 2026+0+00
Wed, Nov 4, 2026+0+00
Thu, Nov 5, 2026+0+00
Total+21+00
  • 1#1 on the list
  • 7Rank that day
  • Not trending

Social mentions

Recent discussions about this repository across the web
  1. Oct 91 post

    • Qwen3.8-Flash-Next-GSQ-RCO (IQ3_S): ~20-30 tok/sec decode & 300-90k tok/sec prefill on 12GB VRAM + 32GB RAM + NVME

      Read full on Reddit

      r/LocalLLaMA

You might also like

Repositories close to bodhi37/Qwen3.8-Flash-12GBRAM-32GBVRAM-SSD-Recipe
FeaturedAdvertise to 180K+ monthly visitors
Bifrost

Fastest Enterprise AI Gateway for Routing, Governing, and Securing all your AI Traffic

Apolog1ze-Dev/QwFNfer

C++

A custom inference engine tuned for Qwen4 architecture. Currently runs Qwen3.8-Flash-Next at 15+ tok/s on 16GB of VRAM and 30 GB of RAM

647

0xBakeer/qwen38-flash-next-spark

Shell

Run Qwen3.8-Flash-Next (180B) on a single DGX Spark by keeping its 51B n-gram embedding table on NVMe

12512

yxhpy/qwen3.8-flash-next-local-deploy

Python

Qwen3.8-Flash-Next (125B MoE) 单卡 16G 本地部署实测：Strata + GSQ-RCO IQ3_XXS，Ubuntu 24.04

4617

DominikBucko/qwen38-flash-next-2x3090

Python

Qwen3.8-Flash-Next on 2× RTX 3090: with 128 GB RAM up to 4,191 tok/s prefill · 111.5 tok/s decode (131K prompt), full 256K window at 2,865 tok/s; with 64 GB RAM 3,410 tok/s prefill · 84 tok/s decode. New: opt-in uncensored mode (runtime abliteration, no new weights).

13417

tpurtell/sm12x-exl3-qwen3.8-flash-next

Python

RTX 6000 96GB/Spark 128GB vLLM Recipe for Qwen 3.8 Flash Next

233

myllmbox/qwen38-flash-next-recipe

Shell

qwen38-flash-next recipe for solo GB10

17012

azampatti/Qwen3.8-Flash-Next-Int4-FAST

Shell

Recipe for the fastest 4bit qwen3.8FlashNext

709

sergqwer/strata-nvfp4

C++

Strata fork: Qwen3.8-Flash-Next 125B MoE in NVFP4 on one RTX 20-50 card (12 GB+) and 64 GB of RAM or more. Setup installs our GPTQ quants (huihui abliterated, OrcaRouter) from Hugging Face. CPU experts on AVX-512 or AVX2 (+AVX-VNNI), all experts in RAM from 92 GB, a low-RAM mode below, vision, W4A8 prompts. Windows / CUDA 13.

22126

myllmbox/qwen38-flash-next-cluster-recipe

Shell

qwen38-flash-next recipe for tp=2 GB10

13417