How To Use Open Models Effectively

Part of AI Product Engineering

Hosted by Zach Mueller and Hamel Husain

Fri, Jul 24, 2026

7:00 PM UTC (30 minutes)

Virtual (Zoom)

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AI Evals For Engineers & PMs
Hamel Husain and Shreya Shankar
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What you'll learn

Know when open models pay off

Walk through the economics. Where open models match frontier quality, where they do not, and how the math changes as your token volume grows.

Route the right work to the right model

Run most requests on a cheaper open model and save frontier models for the hard cases. We cover the latency and throughput tradeoffs that decide what runs where.

Get started without the footguns

Which inference engine to reach for first, how to think about the serving ecosystem, and the mistakes that make teams quit on open models too early.

Why this topic matters

Frontier model prices keep climbing while open models keep getting better. For many types of production work an open model is good enough, and switching can cut your bill without hurting quality. Zach has taught thousands of engineers to run these models. He will show you when open models are the right call, and how to put them to work.

You'll learn from

Zach Mueller

Head of Developer Relations at Lambda Labs (ex-Hugging Face)

Zach Mueller is Head of Developer Relations at Lambda Labs, where he helps engineers run large-scale AI training and get more out of their infrastructure. Before Lambda he was a technical leader in the Hugging Face ecosystem, where he shipped production computer vision and regression models, built widely used training tools, and taught thousands of developers how to run distributed machine learning reliably. He is known for making hard topics approachable, from NCCL quirks to multi-node training. LinkedIn

Hamel Husain

ML Engineer with 20 years of experience

Hamel Husain is a ML Engineer with over 20 years of experience. He has worked with companies like Airbnb and GitHub, which included early LLM research used by OpenAI, for code understanding. He has also led and contributed to numerous popular open-source machine-learning tools. Hamel is currently an independent consultant helping companies build AI products.

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