- TESIGN / RADAR
- 2026.09.13
- colibri
colibri
Run huge MoE models on your own PC
WHO USES ITML engineer · Infra owner · Systems developer
Install to use
Runs frontier MoE models on hardware you already own.
33,753 stars · checked on GitHub GitHub check 30 h late · incl. +211 observed via GH Archive since then · 7-day +974 observed via GH Archive (as of ) · 937 Show HN points observed
RANKS All-time #185 Rising this week #7 INFRA #10
CROSS-SIGNAL Show HN + GitHubRISING +175 ★ / 24h




TESIGN TAKE
Lets you test on your own hardware whether placing a huge model across disk, RAM and VRAM actually works.
AT A GLANCE
- LICENSE
- Apache-2.0
- USAGE
- Commercial use, redistribution OK. Keep notices; mark changes.
- LANGUAGE
- C
- PLATFORM
- linux · macos · windows · cli
- ACTIVITY
- last commit 1 day ago () · latest release v1.11.0 () · 17 releases
- COMMUNITY
- 150 contributors · 117 open issues (incl. PRs) · made by: an individual
- SOURCES
- Show HN + GitHub
- OPEN SOURCE
- YES
- FIRST SEEN
- CATEGORY
- AI · INFRA
A summary, not legal advice.
WHY IT MATTERS
Large MoE models rarely fit in memory, and the usual answer is to buy different hardware. colibri streams expert weights from disk as they are needed, so the model runs on hardware you already own. It is written in pure C with no dependencies and published under Apache-2.0. Which models are supported has to be checked in the repository itself.
BUILD FROM THIS
- An in-house local-model test bench on a single server
- An inference binary built with no dependencies and shipped in a product
- A comparison run before deciding on new hardware
WHO IT'S FOR
- ML engineer
- measures local inference limits before buying hardware
- Infra owner
- trials a large model on one in-house server
- Systems developer
- wants pure-C inference code to read and change
START IN 5 MINUTES
# Get a Linux/macOS/Windows build from Releases (Python 3 needed) or build:
$ git clone https://github.com/JustVugg/colibri && cd colibri/c
$ ./setup.sh
# Download a model (GLM-5.2 int4, about 372 GB) from Hugging Face, then:
$ COLI_MODEL=/nvme/glm52_i4 ./coli chat
$ ./coli web --model /nvme/glm52_i4CAVEATS
- The reference model GLM-5.2 needs 372 GB of disk and 16 GB+ of RAM
- Speed depends on the disk; a slow drive can mean under one token per second
- A research engine that explicitly promises no SLA on speed
RECEIPT
- FIRST SEEN
- AT SOURCE
- KEPT
- STAR DELTA
- +175 ★ / 24h
- CREATED → FIRST SEEN
- 73d
- WHEN FIRST SEEN
- 28,753 ★
- SOURCES
- Show HN + GitHub
The same facts in machine-readable form — View as Markdown · JSON
SIMILAR TOOLS
Up to five from AI by ★ total: edited entries first, then repository cards; this entry is highlighted. Drawn from the same stored snapshot as the rankings — a comparison, not a recommendation.
| IMAGE | NAME | ★ TOTAL | ▲ 7d | LICENSE | PLATFORM | LAST PUSH |
|---|---|---|---|---|---|---|
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![]() | DeepSeek HarnessPlugin agent harness for developers | ★ 225k | ▲ +1,356 | MITpermissive | web · cli | |
![]() | colibriRun huge MoE models on your own PCTHIS ENTRY | ★ 33.8k | ▲ +974 | Apache-2.0permissive | linux · macos · windows · cli | |
| mattpocock/skillsCARD | ★ 261k | ▲ +872 | MITpermissive | — |
TIMELINE
- Repository created
- Show HN post ↗
- FIRST SEEN BY TESIGN
- Published on TESIGN
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