vLLM

vLLMSince 2023-06

vLLM is the industry-standard open-source LLM serving and inference engine designed for ultra-high throughput and minimal memory waste. Developed by UC Berkeley researchers, vLLM introduced PagedAttention—a revolutionary memory management algorithm that manages attention key-value (KV) cache like virtual memory in operating systems, virtually eliminating memory fragmentation. Capable of delivering 2x to 4x higher throughput than Hugging Face TGI and standard PyTorch runtimes, vLLM powers production AI inference infrastructure across enterprise cloud clusters and high-volume API providers worldwide.

vLLM features state-of-the-art inference optimizations including continuous request batching, Chunked Prefill, speculative decoding, prefix caching, and native quantization support (AWQ, GPTQ, FP8, INT4, SqueezeLLM). It provides drop-in OpenAI-compatible REST API endpoints, supports multi-GPU distributed tensor parallelism with Ray/NCCL, and serves all major model architectures including DeepSeek-V3, Llama 3.3, Mistral, Qwen 2.5, and Command R+.

HyperbolicSince 2026-01

Hyperbolic is a decentralized AI computing network and inference platform that provides high-performance, cost-effective GPU compute and open-access LLM APIs. By aggregating global GPU infrastructure with cryptographic verification of compute, Hyperbolic delivers up to 75% cost savings on frontier open-source model inference compared to traditional cloud hyperscalers. Hyperbolic serves the fastest and most affordable APIs for open-source models including DeepSeek R1/V3, Llama 3.3 70B, Qwen 2.5, and SDXL with full OpenAI-compatible API endpoints.

Hyperbolic features proprietary proof-of-sampling verification protocols to guarantee computation correctness across distributed nodes. Developers can provision on-demand and spot GPU clusters (NVIDIA H100s, H200s, and B200s) or access high-throughput serverless inference with instant autoscaling. With sub-second time-to-first-token (TTFT) and global low-latency edge routing, Hyperbolic is built for high-volume enterprise production workloads.