Bridging the Gap Between Silicon and Intelligence.
We specialize in extracting maximum performance from GPU hardware, ensuring your AI models run faster, leaner, and more reliably on any infrastructure.
About v4r Labs
v4r Labs is an applied AI systems lab focused on performance engineering, secure compute, and deployment efficiency. The lab benchmarks and optimizes workloads across GPUs, accelerators, and inference engines in cloud and bare-metal environments. Work is grounded in real measurements and production tooling.
Capabilities
- Hardware Benchmarking: Comparative analysis across NVIDIA, AMD, and Tenstorrent.
- Model Optimization: Fine-tuning Llama and Gemma architectures for production.
- Inference Acceleration: Custom vLLM and PyTorch implementation.
- Cloud & Bare Metal: Seamless deployment on AWS, DigitalOcean, and private clusters.
Core Expertise & Technologies
Hotaisle
Consumer GPUs
PyTorch
HuggingFace
Meta
DeepSeek
Example Stacks Profiled
- Llama • PyTorch • ROCm • AMD MI300X
- Llama • PyTorch • CUDA • NVIDIA H100
- Nemotron • vLLM • CUDA • NVIDIA H100
- DeepSeek • vLLM • Neuron • AWS Inferentia2
Example Tuning
- Quantization
- Attention Variants
- KV Cache Sizing
- Batch & Concurrency
Technology Demo
Explore our real-time performance tracking for multi-GPU clusters. Optimized for high-throughput inference workloads.