Infera is a production-grade model inference engine designed to deliver high throughput, low latency, and efficient resource utilization for large-scale language model serving.

It focuses on optimized execution, intelligent scheduling, and memory-efficient inference, enabling scalable and cost-effective deployment of modern LLMs.

• High-Performance Inference

  • Optimized autoregressive decoding
  • Efficient batching and request coalescing
  • Designed for both low-latency and high-throughput workloads

• Intelligent Scheduling

  • Fine-grained request scheduling
  • Dynamic batching and token-level orchestration
  • Optimized for high-concurrency serving

• Memory-Efficient Execution

  • Advanced KV cache management
  • Reduced memory fragmentation
  • Maximized GPU utilization

• Production-Ready Architecture

  • Modular and extensible engine design
  • Clean separation of scheduler, executor, and runtime
  • Designed for long-running services

• Flexible Model Support

  • Native support for modern Transformer-based LLMs
  • Easy integration with existing model ecosystems