repoGitHubTrust 82 · PrimaryPublished 5h agoLive · 4h ago
DaoyuanLi2816/llm-gpu-lab
One GPU. Full LLM workflow. Real benchmarks. No cloud required.
Lineage graph
Paper → model → repo connections mined from source citations (Tier-1 exact match).
Covers
newsWe'll benchmark an Open weights LLM on any GPU you choose — drop your model + hardware and we'll run it. [D]newsTop Cost-Effective Enterprise GPU Cloud Platforms for AI Workloads with H100–GB200, Elastic Scaling and Pay-as-You-Go Compute - Scott CoopnewsKicking off GPU Mode [D]newsAI Model Co-Design: Hardware-Friendly LLM Design | NVIDIA Technical Blog - NVIDIA Developer
Implements
Covers (incoming)
Related across the graph
newsAI Model Co-Design: Hardware-Friendly LLM Design | NVIDIA Technical Blog - NVIDIA DevelopernewsUltra budget 20GB vram with 448GB/s for $100 bucks.paperWattGPU: Predicting Inference Power and Latency on Unseen GPUs and LLMsnewsKicking off GPU Mode [D]newsWe'll benchmark an Open weights LLM on any GPU you choose — drop your model + hardware and we'll run it. [D]newsMeasuring PCIe transfer under dual GPU with pipeline & tensor llama.cppnewsTop Cost-Effective Enterprise GPU Cloud Platforms for AI Workloads with H100–GB200, Elastic Scaling and Pay-as-You-Go Compute - Scott Coop