LLM Engineer's Almanac - Workloads | Modal

The three types of LLM workloads and how to serve them

LLM Engineer's Almanac - Workloads | Modal Advisor Executive Summary Benchmarking Workloads Quant Formats Block Quants Token Timing Simulator Spec Dec Roofline More Powered by Modal Advisor Executive Summary Benchmarking Workloads Quant Formats Block Quants Token Timing Simulator Spec Dec Roofline Powered by Modal The three types of LLM workloads and how to serve them We hold this truth to be self-evident: not all workloads are created equal. But for large language models, this truth is far from universally acknowledged. Most organizations building LLM applications get their AI from an API, an

saved by

• CLL

related reading

• LLM Engineer's Almanac - Advisormodal.com
• LLM Inference Performance Engineering: Best Practices | Databricks Blogdatabricks.com
• LLM Engineer's Almanac - Executive Summary | Modalmodal.com
• How To Scale Your Modeljax-ml.github.io
• What We’ve Learned From A Year of Building with LLMs – Applied LLMsapplied-llms.org
• Inside vLLM: Anatomy of a High-Throughput LLM Inference Systemvllm.ai
• Look Ma, No Bubbles! Designing a Low-Latency Megakernel for Llama-1B · Hazy Researchhazyresearch.stanford.edu
• Patterns for Building LLM-based Systems & Productseugeneyan.com
• The State of LLM Serving in 2026: Ollama, SGLang, TensorRT, Triton, and vLLM | Canteenthecanteenapp.com
• Paged Attention from First Principles: A View Inside vLLM – Hamza's Bloghamzaelshafie.bearblog.dev
• ⭐️ Fast LLM Inference From Scratchandrewkchan.dev
• Transformers Inference Optimization Toolset | AstraBlogastralord.github.io