ampere 话题在 GitHub 上没有填写简介，这里按 Star 数汇总最相关的热门仓库。
llama.cpp fork for significantly improved performance on Ampere generation Nvidia cards (especially RTX 3090 / 3090 Ti): example: 110+ tok/s over a 100K-token generation at temperature 1 for qwen3.8, supporting full 262K ctx. Supports low memory (12gb) configs for 200k+ ctx. 120+ TPS, 3300+ prefill for QFN 3.8.
Kindi 0.5: local LLM inference on low-cost NVIDIA GPUs (Kepler to the RTX 50 series and the CMP 170HX), AMD Radeon 780M, 840M and 8060S, and CPUs. Bonsai 2B-27B, AH-Nanbeige4.3-33B and experimental Nemotron, with an OpenAI-compatible server.
Arduino library for INA226 power sensor
GLM-5.3-Flash on 4× NVIDIA CMP 170HX with vLLM: up to 482.6 tok/s single-user, up to 943.7 tok/s at 8 users, 262K context, TP4 or PP4, one-command container install
适用于跨平台和CUDA版本的llama-cpp-python预制轮子
Enable NVIDIA Smooth Motion on RTX 30-series / Ampere SM86 - one-click Windows utility, no per-game DLSS-FG integration required.
Ampere optimized llama.cpp
llama.cpp speculative decoding measured on one RTX 3090, Qwen3.6-35B-A3B UD-Q4_K_XL, commit 3737e4137. Published figures are re-derived from the committed data by a checker that fails on drift, a coverage probe reports how many of them it actually covers, and ERRATA.md lists this study's own retracted claims.
Cross-platform FlashAttention-2 Triton implementation for Turing+ GPUs with custom configuration mode
vLLM for NVIDIA CMP 170HX (Ampere sm_80): fast, repeatable model serving on one card or several
Setup instructions for running Valheim on Oracle Cloud Infrastructure using Arm also available at https://codeberg.org/husjon/valheim_server_oci_setup
DeepSeek-V4.1-Flash on 4× NVIDIA CMP 170HX with vLLM: up to 297 tok/s for one user, up to 868 tok/s at eight, 262K context, one-command container install
Grab an Oracle Cloud ARM Ampere A1 Free Tier instance in saturated regions — calibrated timing, FD rotation, 429 backoff, Telegram notifications
DACAN (Дацан): Qwen3.8-Flash-Next (125B MoE) on any NVIDIA RTX 20/30/40/50 card and any x86-64 CPU with AVX2, AVX-512 not required. One or two cards, one or two sockets, context up to 1M (1,048,576 tokens).
AML's goal is to make benchmarking of various AI architectures on Ampere CPUs a pleasurable experience :)
Pre-driver FMLA32 Tensor Core unlocker and PTX benchmark console for GeForce RTX 40-series, RTX 30-series and RTX 20-series on Windows 10/11 (UEFI USB) and Linux (gpu_unlock.ko), with friendly UI for Win/Linux. Restores full 2x FP16/BF16/TF32->FP32 accumulate rate with automatic hardware profiling, pre-flight ROM checks, and zero VBIOS flashing.
One-command installer + terminal control panel for a modded Project Zomboid Build 42 dedicated server on ARM64 (Oracle Cloud Ampere / box64).
Arduino energy monitor, using SCT-013-030 current sensors
Performance characterization and analysis tool for Ampere CPUs
GPTQ optimized for Ampere (RTX 3090/3060) — Marlin JIT nvcc compatibility fixes included