# NVIDIA/flare-local-inference

> Flare is a local inference server for NVIDIA SM120/SM121 GPUs aimed at long conversations, coding agents and repeated tool use. It compiles models with PyTorch and serves them from a Rust runtime to use workstation memory and compute more efficiently.

- Magnitude: 6.6 out of 10 — Early signal
- Stars: 538 total · +33 stars measured 2026-10-22, 00:37–04:07 UTC, ≈ 280 by evening
- Star trust: star growth looks organic
- Category: Language models · Language: Python · License: Apache-2.0 · Created: 2026-10-20 · Last push: 2026-10-21
- GitHub: https://github.com/NVIDIA/flare-local-inference · Page: https://gitnova.dev/en/r/NVIDIA/flare-local-inference

## Useful for

- Serve a local LLM on an NVIDIA SM120/SM121 workstation for long coding sessions
- Run repeated tool calls against a locally hosted model without a Python runtime
- Prepare and serve a supported model package with the Flare CLI

## Why it’s here

- Star-counter measurements on 2026-10-22 (UTC), 00:37–04:07: 505 → 538 stars (+33). This is the change over that interval.
- Estimated end-of-day forecast: about +280 stars, using observed gains and the previous day.
- The repository is 2 days old and already has 538 stars. With less than two weeks of history, there's no usual pace to compare the spike against yet.
- Top new repositories this week: #29.
- About 37 forks a day — people are taking the code.

## 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: 50
- Issues and pull requests: 13
- Watchers: 5
- Average over the last week: 273 per day
- Usual pace: too little history (under two weeks)
- Stars in the last hour (measured): 9

## Stars per day, last 3 days (oldest → newest, today is partial)

2026-10-20 … 2026-10-22: 213, 327, 33

## Magnitude by day, last 2 days

10-21 5.8, 10-22 6.6

## Spotted in now

- Top new repositories this week: #29

## More in this category

1. **deepseek-ai/DeepInfer** — 9.8 · Breakout · Language models · Python · +533 stars measured 2026-10-22, 00:37–04:07 UTC, ≈ 3,065 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. **vllm-project/vllm** — 7.3 · Breakout · Language models · Python · +93 stars measured 2026-10-22, 00:37–04:07 UTC, ≈ 440 by evening
   A high-throughput and memory-efficient inference and serving engine for large language models, using PagedAttention for KV-cache management. Supports 200+ model architectures and an OpenAI-compatible API.
   Full card: https://gitnova.dev/en/r/vllm-project/vllm.md
3. **google-pytorch/torch_tpu** — 6.7 · Early signal · Language models · C++ · +10 stars measured 2026-10-22, 00:37–04:07 UTC, ≈ 137 by evening
   TorchTPU is a PyTorch backend for Google TPUs that lets you run PyTorch models and operations on TPU devices, with custom ATen kernels, an XLA compilation cache, and distributed training support.
   Full card: https://gitnova.dev/en/r/google-pytorch/torch_tpu.md
4. **eagle-hq/EAGLE-4** — 6.5 · Early signal · Language models · Python · +18 stars measured 2026-10-22, 00:37–04:07 UTC, ≈ 227 by evening
   Official inference harness for EAGLE-4 speculative decoding, adding a flexible drafter plugin to SGLang, vLLM and TokenSpeed that adapts to batch size, hardware and workload. It speeds up serving of LLMs such as Qwen3.8-27B while…
   Full card: https://gitnova.dev/en/r/eagle-hq/EAGLE-4.md
5. **headroomlabs-ai/headroom** — 5.4 · Breakout · Language models · Python · +85 stars measured 2026-10-22, 00:37–04:07 UTC, ≈ 473 by evening
   A local library, proxy and MCP server that compress tool outputs, logs, files and RAG chunks before they reach the LLM, cutting token usage without changing answers.
   Full card: https://gitnova.dev/en/r/headroomlabs-ai/headroom.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 2026-10-22 04:18 UTC, updated every 30 minutes.