# Hyperstitioncc/Hyperkernel

> Public implementations of the megakernels generated by Hyperkernel: an OpenAI-compatible LLM server plus inference for driving, DNA generation, world models, robotics and protein folding on NVIDIA B300 GPUs.

- Magnitude: 1.4 out of 10 — Cooling
- Stars: 183 total · +0 stars measured 2026-11-09, 00:04–02:15 UTC, ≈ 1 by evening
- Star trust: star growth looks organic
- Category: Language models · Language: Rust · License: MIT · Created: 2026-11-05 · Last push: 2026-11-07
- GitHub: https://github.com/Hyperstitioncc/Hyperkernel · Page: https://gitnova.dev/en/r/Hyperstitioncc/Hyperkernel

## Useful for

- Run an OpenAI-compatible DeepSeek-V4.1-Flash server on 4 GPUs with 1M-token context
- Run openpilot's driving model over camera frames and get per-frame outputs
- Fold a protein with ESMFold from a sequence and save the structure to PDB

## Why it’s here

- Star-counter measurements on 2026-11-09 (UTC), 00:04–02:15: 183 → 183 stars (+0). This is the change over that interval.
- The repository is 4 days old and already has 183 stars. With less than two weeks of history, there's no usual pace to compare the spike against yet.
- About 9 forks a day — people are taking the code.
- Recent forks include notable developers: @johndpope (1,339 followers), @zapabob (298 followers).

## Star trust

Star growth looks organic.

Star-trust labels are heuristics based on the repository’s behavior, not a check of every stargazer.

## Numbers

- Forks: 21
- Issues and pull requests: 0
- Watchers: 3
- Average over the last week: 37 per day
- Usual pace: too little history (under two weeks)
- Stars in the last hour (measured): 0

## Stars per day, last 5 days (oldest → newest, today is partial)

2026-11-05 … 2026-11-09: 78, 83, 21, 1, 0

## Magnitude by day, last 4 days

11-06 5.1, 11-07 5.5, 11-08 3.5, 11-09 1.4

## More in this category

1. **synchopate/llama-modchip** — 6.8 · Early signal · Language models · Python · +36 stars measured 2026-11-09, 00:02–02:08 UTC, ≈ 414 by evening
   Tool for running large MoE models (DeepSeek-V4-Flash 284B, Nemotron-30B) on pure CPU with 64 GB RAM and no GPU, using a custom Fractal-64 compression format and speculative decoding.
   Full card: https://gitnova.dev/en/r/synchopate/llama-modchip.md
2. **NVIDIA/auto-ontology** — 5.4 · Peaking · Language models · Python · +86 stars measured 2026-11-09, 00:02–02:09 UTC, ≈ 633 by evening
   NVIDIA's Python framework that builds a semantic ontology graph over enterprise metadata, giving LLM agents trusted metric and entity definitions for reliable text-to-SQL.
   Full card: https://gitnova.dev/en/r/NVIDIA/auto-ontology.md
3. **neuml/txtai** — 4.7 · Breakout · Language models · Python · +8 stars measured 2026-11-09, 00:03–02:09 UTC, ≈ 63 by evening
   Python framework for semantic search, LLM orchestration and language model workflows. Combines vector indexes, graphs and relational databases into an embeddings database for RAG, agents and multimodal search.
   Full card: https://gitnova.dev/en/r/neuml/txtai.md
4. **JustVugg/colibri** — 4.0 · Steady · Language models · C · +30 stars measured 2026-11-09, 00:03–02:09 UTC, ≈ 306 by evening
   A pure-C, zero-dependency inference engine for running large MoE models (744B–2.8T parameters) on consumer hardware by treating VRAM, RAM, and storage as a single multitier hierarchy and streaming experts from disk.
   Full card: https://gitnova.dev/en/r/JustVugg/colibri.md
5. **Niko1221/Strata** — 3.8 · Steady · Language models · C++ · +37 stars measured 2026-11-09, 00:03–02:10 UTC, ≈ 401 by evening
   A C++ local inference engine that runs the 125B MoE model Qwen3.8-Flash-Next on a regular PC with one NVIDIA GPU (12-24 GB) and 64 GB RAM, exposing an OpenAI/Anthropic-compatible API on localhost.
   Full card: https://gitnova.dev/en/r/Niko1221/Strata.md

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Magnitude (0–10) measures how fast and how unusually interest in a repository is growing right now. It is not a quality score.
Days are UTC. “So far today” is a fact; “expected by the end of the day” is a forecast.
Summaries and use cases are written by an LLM (DeepSeek V4.1 Flash) from the README and may be inaccurate: verify specific claims (benchmarks, speed, hardware) in the repository itself.
Data as of 2026-11-09 02:18 UTC, updated every 30 minutes.