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MiaAI-Lab/Qwen3.6-35B-A3B-NVFP4-vLLM

Self-hosted vLLM inference for Qwen3.6-35B-A3B-NVFP4

#LLM inference
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Momentum

How fast MiaAI-Lab/Qwen3.6-35B-A3B-NVFP4-vLLM 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

Sep 5 – Oct 26, 2026

Stars +2 in 52 days

01
1

Forks +0 in 52 days

01

Merged PRs 0 in 52 days

01

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

Top 25 in Jinja

7
Sep 5Sep 12Sep 19Sep 26Oct 3Oct 10Oct 17Oct 24
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 PRsJinja
Sat, Sep 5, 2026+1+00#7
Sun, Sep 6, 2026+0+00Not trending
Mon, Sep 7, 2026+0+00Not trending
Tue, Sep 8, 2026+0+00Not trending
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Sat, Sep 12, 2026+0+00Not trending
Sun, Sep 13, 2026+0+00Not trending
Mon, Sep 14, 2026+0+00Not trending
Tue, Sep 15, 2026+0+00Not trending
Wed, Sep 16, 2026+0+00Not trending
Thu, Sep 17, 2026+0+00Not trending
Fri, Sep 18, 2026+0+00Not trending
Sat, Sep 19, 2026+0+00Not trending
Sun, Sep 20, 2026+0+00Not trending
Mon, Sep 21, 2026+0+00Not trending
Tue, Sep 22, 2026+0+00Not trending
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Thu, Sep 24, 2026+0+00Not trending
Fri, Sep 25, 2026+0+00Not trending
Sat, Sep 26, 2026+0+00Not trending
Sun, Sep 27, 2026+0+00Not trending
Mon, Sep 28, 2026+0+00Not trending
Tue, Sep 29, 2026+0+00Not trending
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Thu, Oct 1, 2026+0+00Not trending
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Sat, Oct 3, 2026+0+00Not trending
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Tue, Oct 6, 2026+0+00Not trending
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Sat, Oct 10, 2026+0+00Not trending
Sun, Oct 11, 2026+0+00Not trending
Mon, Oct 12, 2026+0+00Not trending
Tue, Oct 13, 2026+0+00Not trending
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Thu, Oct 15, 2026+0+00Not trending
Fri, Oct 16, 2026+0+00Not trending
Sat, Oct 17, 2026+0+00Not trending
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Mon, Oct 26, 2026+0+00Not trending
Total+2+00
  • 1#1 on the list
  • 7Rank that day
  • Not trending
  • Mentions and achievements

    Where people are talking about MiaAI-Lab/Qwen3.6-35B-A3B-NVFP4-vLLM, and every badge it has earned
    1. Jun 221 post
      • FYI the best Qwen 3.6 35b nvfp4 to run is the @NVIDIAAI nvfp4. Do not use unsloth nvfp4, it performs worse. Here's how it compares to bf16 👇

        Read full on X, posted by @MiaAI_lab

        @MiaAI_lab · x.com

    2. Jun 191 post
      • Did you know Qwen 3.6 35B NVFP4 with 256k context, MTP, kv cache fp16 & image support takes around 68gb of VRAM? My @NVIDIAAI DGX Spark can do 110 tok/s 👇

        Read full on X, posted by @MiaAI_lab

        @MiaAI_lab · x.com

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