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Veloresearch/velocity-local-services

Velocity Local Services: an app for running LLMs locally on Windows and Linux. Load any GGUF model and chat with web search, tools and schematics, let it use your computer by voice, and serve it to opencode, Hermes or any app through an OpenAI-compatible API and MCP. Context up to 32M tokens. No cloud.

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1 contributors
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Momentum

How fast Veloresearch/velocity-local-services 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 2 – Oct 26, 2026

Stars +33 in 55 days

051015
14

Forks +4 in 55 days

0123
3

Merged PRs 0 in 55 days

01

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

Not in the Trendshift top 25 in this period

Sep 2Sep 9Sep 16Sep 23Sep 30Oct 7Oct 14Oct 21
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
Wed, Sep 2, 2026+0+00
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Fri, Sep 4, 2026+0+00
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Mon, Sep 7, 2026+2+00
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Sat, Oct 10, 2026+0+00
Sun, Oct 11, 2026+0+00
Mon, Oct 12, 2026+9+00
Tue, Oct 13, 2026+14+30
Wed, Oct 14, 2026+1+00
Thu, Oct 15, 2026+2+10
Fri, Oct 16, 2026+1+00
Sat, Oct 17, 2026+2+00
Sun, Oct 18, 2026+0+00
Mon, Oct 19, 2026+0+00
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Sun, Oct 25, 2026+0+00
Mon, Oct 26, 2026+0+00
Total+33+40
  • 1#1 on the list
  • 7Rank that day
  • Not trending

Social mentions

Recent discussions about this repository across the web
  1. Oct 121 post

    • 4B model, 6 GB laptop GPU, 32M tokens of context. Fully local.

      Read full on Reddit

      r/LocalLLM

  2. 15 days earlier
  3. Sep 271 post

    • Introducing Velocity Context: a 32M-token memory for any local model. ◆ 4B model, 8K window, 6 GB laptop GPU: answers in 653 ms ◆ RULER (NVIDIA's harness): 86.9 at 128K ◆ No embeddings, no vector DB,…

      Read full on X, posted by @velo_research

      @velo_research · x.com

  4. Sep 261 post

    • In 1936, Turing imagined a machine with infinite memory. In 2026, a local model on your laptop still sees ~8K tokens. Cloud models reach 1M, and every one tested gets worse as the input grows. Meet…

      Read full on X, posted by @velo_research

      @velo_research · x.com

  5. 15 days earlier
  6. Sep 111 post

    • Big Tech says querying millions of tokens requires H100 clusters and $20k/mo cloud bills. We just ran 32,000,000 tokens of persistent context locally on an RTX 3060 laptop (6GB VRAM). Zero cloud.…

      Read full on X, posted by @velo_research

      @velo_research · x.com

  7. 7 days earlier
  8. Sep 41 post

    • VLS Mesh is live. ⚡ connect the computers you already own and make them work together for local AI. pick one as the main device. the others join in. plug & play. you probably already own more compute…

      Read full on X, posted by @velo_research

      @velo_research · x.com

  9. Sep 33 posts

    • 🚀 Velocity releases VLS Preview - a free local AI runtime with up to 32,000,000 tokens of context for the models you already use. Windows & Linux, your own hardware, no special long-context model,…

      Read full on X, posted by @velo_research

      @velo_research · x.com

    • A 4B model with an 8,192-token window answered a question about a 32,000,000-token corpus in 653 ms. On an RTX 3060 Laptop. 6 GB of VRAM. The corpus is 3,900x the window, and the answer time did not…

      Read full on X, posted by @velo_research

      @velo_research · x.com

    • this is what "a lot of context" actually means: ~1,900 pdfs ~3,200 research papers ~400 books ~2 million lines of code on your own computer. vls is free :)

      Read full on X, posted by @velo_research

      @velo_research · x.com

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