OSS Radar
StayLameBro/backburner
Your iPhone helps your Mac run a 27B model: faster prompt reading and more context over a USB-C cable. Why it matters: useful plumbing for shipping LLM-powered features.
GitHub description: Your iPhone helps your Mac run a 27B model: faster prompt reading and more context over a USB-C cable
Stars
991
Last 24h
+85est.
Last 7 days
+595est.
Forks
104
Star history (last 1 snapshot)
Only one snapshot so far. The chart fills in as OSS Radar collects daily snapshots.
est. means the star gain is estimated, not measured: until OSS Radar has collected enough daily snapshots for a repo, we use total stars ÷ days since creation (or extrapolate from the snapshots we do have). Estimates are replaced by measured deltas automatically as history builds up.
Maintainer? Add the badge to your README
Shows your live OSS Radar rank and links back here. Updates hourly.
[](https://ossradar.net/repo/StayLameBro/backburner)<a href="https://ossradar.net/repo/StayLameBro/backburner"><img src="https://ossradar.net/badge/StayLameBro/backburner" alt="Trending on OSS Radar"></a>About backburner
StayLameBro/backburner is a Python project in the LLM tooling category, created 12 days ago. It has 991 GitHub stars and 104 forks, and gained +595 stars over the last 7 days (early estimate), ranking #70 of 167 LLM tooling repos tracked by OSS Radar this week.
See more trending LLM tooling repos or the top AI repos this week.
- Language
- Python
- Category
- LLM tooling
- Created
- Oct 1, 2026
- Last push
- Oct 11, 2026
- apple-silicon
- ios
- iphone
- llama-cpp
- llm-inference
- local-llm
- macos
- metal
- qwen
- sme2
- speculative-decoding
Similar rising repos
- syv-ai/HyperQwen+235est.
Serve large Qwen models fast on the GPUs you actually own. Qwen3.8-27B on a single 24 GB card with vLLM: 127 tok/s single-user (381 when the answer… Why it matters: useful plumbing for shipping LLM-powered features.
- drumih/turbo-fieldfare+551est.
Gemma 4 26B-A4B inference in ~2 GB of RAM on any M-series MacBook. Why it matters: useful plumbing for shipping LLM-powered features.
- jundot/omlx+658est.
LLM inference server with continuous batching & SSD caching for Apple Silicon — managed from the macOS menu bar. Why it matters: useful plumbing for shipping LLM-powered features.
- onehumanbeing/esp32-iphone-agent+1.2kest.
Let an AI model use a real iPhone with a $7 ESP32: AirPlay eyes, USB HID hands, any OpenAI-compatible vision model. No Mac, no developer account, no… Why it matters: useful plumbing for shipping LLM-powered features.
- FlashML-org/FreeToken+1.2kest.
FreeToken brings datacenter-scale model serving to your desktop. Run massive models locally, fast and efficiently. Why it matters: useful plumbing for shipping LLM-powered features.
- bojieli/ai-infra-book+863est.
《深入理解 AI Infra：量化分析与系统设计》（李博杰 著）开源书稿：从硬件约束和模型架构出发，量化推导 LLM 推理与训练系统设计。含全书正文、PDF、配套计算工具与实验. Why it matters: useful plumbing for shipping LLM-powered features.