← 트렌딩

Tangerine Index는 ChatGPT 이후 나온 프로덕트와 사람들의 반응을 싣습니다.

club-3090

github.com

Community recipes for serving LLMs on RTX 3090/4090/5090 CUDA gpus. Multi-engine (vLLM, sglang, llama.cpp and other custom engines) and model-agnostic. Currently shipping Qwen3.8-27B Qwen3.6 35B Gemma 4 26B Gemma 4 31B configs for 1×/2×/4x/8x cards.

오픈소스

github.com 방문외부 사이트GitHub2,488 스타외부 사이트

반응 (1)

비슷한 프로덕트

설명이 비슷한 순

  1. Llama 3.1 70B on a single RTX 3090 via NVMe-to-GPU bypassing the CPU

    High-efficiency LLM inference engine in C++/CUDA. Run Llama 70B on RTX 3090.

    Hacker News395점GitHub스타 469github.com오픈소스반응 2개최근 반응

  2. LLMKube

    Kubernetes for Local LLMs with GPU Acceleration

    Hacker News5점GitHub스타 255github.com셀프 호스팅오픈소스반응 2개최근 반응

  3. Can your GPU run this LLM?

    Calculate token/s & GPU memory requirement for any LLM. Supports llama.cpp/ggml/bnb/QLoRA quantization

    Hacker News15점GitHub스타 1,404github.com오픈소스반응 2개최근 반응

  4. GPTQModel

    LLM model quantization (compression) toolkit with HW acceleration support for Nvidia (CUDA), AMD (ROCm), Intel GPU (XPU), Huawei Ascent (NPU), and Intel/AMD/Apple CPU via HF, vLLM, and SGLang.

    GitHub스타 1,289github.com오픈소스최근 반응

  5. OS Megakernel that match M5 Max Tok/w at 2x the Throughput on RTX 3090

    LLM speculative inference server for heterogeneous hardware & consumer GPUs

    Hacker News6점GitHub스타 2,991github.com오픈소스반응 2개최근 반응