# slee-persis/GVS5H > A training-free method that runs five instances of one LLM in parallel, coordinating through a shared filesystem to solve hard coding problems, evaluated on LiveCodeBench. - Magnitude: 4.8 out of 10 — Breakout - Stars: 835 total · +52 stars measured 2026-10-25, 04:56–06:17 UTC, ≈ 134 by evening - Star trust: star growth looks organic - Category: Language models · Language: Python · License: MIT · Created: 2026-08-26 · Last push: 2026-09-23 - GitHub: https://github.com/slee-persis/GVS5H · Page: https://gitnova.dev/en/r/slee-persis/GVS5H ## Useful for - Run the scaffold on LiveCodeBench to measure pass@1 for a chosen model. - Compare orchestrated vs single-pass accuracy on hard coding problems. - Self-host Qwen3.8-27B to test whether orchestration raises its pass@1. ## Why it’s here - Star-counter measurements on 2026-10-25 (UTC), 04:56–06:17: 783 → 835 stars (+52). This is the change over that interval. - Estimated end-of-day forecast: about +134 stars, using observed gains and the previous day. - Before this, the repository barely got any stars — about 1 per day. - The repository is 60 days old and already has 835 stars. - Hacker News: “Five Qwen3.8-27B models match Fable 5 Using GVS5H Harness” — 112 points, 2 h ago. ## 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: 97 - Issues and pull requests: 9 - Watchers: 12 - Average over the last week: 32 per day - Usual pace: 4 per day - Stars in the last hour (measured): 38 ## Stars per day, last 30 days (oldest → newest, today is partial) 2026-09-26 … 2026-10-25: 5, 3, 2, 7, 2, 4, 0, 4, 9, 8, 3, 2, 3, 3, 1, 2, 2, 0, 1, 4, 0, 0, 0, 4, 0, 0, 0, 2, 83, 52 ## Hacker News - Five Qwen3.8-27B models match Fable 5 Using GVS5H Harness — 112 points, 33 comments: https://news.ycombinator.com/item?id=50228167 ## Spotted in now - Spotted on Hacker News ## More in this category 1. **deepseek-ai/DeepInfer** — 6.7 · Cooling · Language models · Python · +155 stars measured 2026-10-25, 00:09–06:17 UTC, ≈ 618 by evening Offline inference framework for running DeepSeek models at large scale: optimized kernels, MoE/Attention parallelism, deterministic sampling and structured outputs. Aimed at teams deploying DeepSeek-V4.1-Flash on NVIDIA SM100 or Huawei… Full card: https://gitnova.dev/en/r/deepseek-ai/DeepInfer.md 2. **routerhubSI/uncensored-ai-api** — 6.3 · Early signal · Language models · +90 stars measured 2026-10-25, 00:10–06:17 UTC, ≈ 279 by evening Gateway to AI APIs and models (Claude, GPT, Gemini, Grok, DeepSeek, GLM, Qwen) with one key, OpenAI- and Anthropic-compatible, offering uncensored and abliterated variants with pay-per-token billing. Full card: https://gitnova.dev/en/r/routerhubSI/uncensored-ai-api.md 3. **Niko1221/Strata** — 4.6 · Steady · Language models · C++ · +211 stars measured 2026-10-25, 00:10–06:17 UTC, ≈ 836 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 4. **h563k/chat-keeper** — 4.6 · Early signal · Language models · CSS · +18 stars measured 2026-10-25, 00:11–06:17 UTC, ≈ 76 by evening A third-party mirror of the Claude web interface plus API access to Claude, Gemini and OpenAI, reachable directly from China without a VPN. The repository mainly serves as a landing page and entry point for the paid service. Full card: https://gitnova.dev/en/r/h563k/chat-keeper.md 5. **Tencent/WeVisOne-VL** — 4.4 · Early signal · Language models · Jupyter Notebook · +23 stars measured 2026-10-25, 00:10–06:17 UTC, ≈ 66 by evening WeVisOne-VL is a vision-language model by the WeChat Vision Team at Tencent that unifies object-level and pixel-level perception: detection, referring localization, counting, pointing, OCR, segmentation, and alpha matting. It handles… Full card: https://gitnova.dev/en/r/Tencent/WeVisOne-VL.md --- 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 2026-10-25 06:26 UTC, updated every 30 minutes.