# OmniJev/Flide

> Inference engine for Jev-style decision models that serves the /v1/systemone API and answers choice and yes/no questions with exact state forking, reported up to 9.5x faster than vLLM and SGLang.

- Magnitude: 6.9 out of 10 — Early signal
- Stars: 299 total · +27 stars measured 2026-11-10, 00:26–06:03 UTC, ≈ 192 by evening
- Star trust: star growth looks organic
- Category: Language models · Language: Python · License: Apache-2.0 · Created: 2026-10-24 · Last push: 2026-11-09
- GitHub: https://github.com/OmniJev/Flide · Homepage: https://flide.org · Page: https://gitnova.dev/en/r/OmniJev/Flide

## Useful for

- Serve a decision model over HTTP with flide serve and query it via /v1/systemone
- Batch several decision model requests in one body for document or support triage
- Keep per-session state cache so an agent reads only newly added context

## Why it’s here

- Star-counter measurements on 2026-11-10 (UTC), 00:26–06:03: 272 → 299 stars (+27). This is the change over that interval.
- Estimated end-of-day forecast: about +192 stars, using observed gains and the previous day.
- Before this, the repository barely got any stars — about 2 per day.
- The repository is 17 days old and already has 299 stars.
- Hacker News: “Show HN: Flide: Make Jev-like decision models up to 9.5x faster” — 121 points, 1 day ago.
- Recent forks include notable developers: @millette (311 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: 10
- Issues and pull requests: 1
- Watchers: 0
- Average over the last week: 68 per day
- Usual pace: 1 per day
- Stars in the last hour (measured): 4
- Latest release: v0.1.11 (2026-11-09)

## Stars per day, last 18 days (oldest → newest, today is partial)

2026-10-24 … 2026-11-10: 1, 0, 0, 1, 2, 0, 3, 1, 0, 0, 12, 2, 2, 4, 1, 8, 265, 27

## Magnitude by day, last 2 days

11-09 6.4, 11-10 6.9

## Hacker News

- Show HN: Flide: Make Jev-like decision models up to 9.5x faster — 121 points, 29 comments: https://news.ycombinator.com/item?id=50421155

## Spotted in now

- Spotted on Hacker News

## More in this category

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   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** — 4.6 · Peaking · Language models · Python · +128 stars measured 2026-11-10, 00:26–06:03 UTC, ≈ 497 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** — 4.5 · Breakout · Language models · Python · +7 stars measured 2026-11-10, 00:26–06:03 UTC, ≈ 50 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** — 4.3 · Steady · Language models · C · +85 stars measured 2026-11-10, 00:27–06:04 UTC, ≈ 326 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** — 3.9 · Steady · Language models · C++ · +103 stars measured 2026-11-10, 00:27–06:04 UTC, ≈ 418 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 2026-11-10 06:13 UTC, updated every 30 minutes.