Cerebras Inference

Cerebras InferenceSince 2024-08

Cerebras Inference is the world's fastest AI inference platform, powered by the revolutionary Cerebras CS-3 Wafer-Scale Engine (WSE-3). Delivering unprecedented speeds exceeding 2,100 tokens per second on Llama 3.1 8B and over 450 tokens per second on Llama 3.1 70B, Cerebras runs AI inference up to 20x faster than traditional NVIDIA GPU clusters. By replacing traditional GPU memory bandwidth bottlenecks with 44 Gigabytes of on-chip SRAM across a monolithic silicon wafer, Cerebras achieves instantaneous response times that transform conversational AI, real-time code synthesis, and multi-step agentic reflection loops into fluid, zero-latency interactions.

Traditional GPUs are limited by external HBM/DRAM bandwidth, forcing token generation to stall while weights are retrieved across PCIe buses. The Cerebras WSE-3 features 900,000 AI-optimized compute cores and 21 Petabytes/sec of memory bandwidth directly on a single silicon wafer. Cerebras Inference provides a 100% OpenAI-compatible API, allowing developers to switch their application endpoints with zero code modifications. It supports streaming completions, tool calling, JSON structured schemas, and massive token context lengths with guaranteed instantaneous time-to-first-token.

LlamaIndexSince 2023-01

LlamaIndex is the premier open-source data framework designed to bridge private, enterprise, and unstructured data with large language models. By providing sophisticated data connectors, automated parser modules, semantic chunking algorithms, and multi-document index structures, LlamaIndex enables developers to build context-augmented LLM applications and autonomous knowledge retrieval engines with minimal boilerplate. From parsing complex multi-page PDF documents and financial spreadsheets to orchestrating complex Agentic RAG workflows that query multiple disparate databases, LlamaIndex handles the complete data ingestion, indexing, and query evaluation lifecycle.

Architected for production scale, LlamaIndex provides seamless abstractions for 160+ vector stores, SQL databases, knowledge graphs, and data loaders through LlamaHub. Its query engine supports hybrid vector-lexical searches, sub-question query decomposition, recursive retrieval, and reranking pipelines. With native support for LlamaParse (a state-of-the-art vision-based document parser) and LlamaCloud (a managed parsing and retrieval service), enterprise engineering teams can deploy enterprise-grade RAG applications with strict accuracy evaluation benchmarks and low token consumption.