How to Choose an Open Source LLM for a Product Team
A practical framework for comparing open models by quality, latency, hosting cost, licensing, safety, tooling, and maintenance burden.
Define the workload
Summarization, coding, retrieval, classification, and agentic tool use place different pressure on a model. Benchmark with your real prompts and documents.
Read the license
Licensing can affect commercial use, redistribution, fine-tuning, and customer data obligations. Treat model license review as product risk work.
Measure operations
Look beyond accuracy. Track tokens per second, cold starts, GPU availability, quantization quality, and fallback strategy.
Plan for upgrades
Models change quickly. Keep your app model-agnostic enough to swap providers, compare evals, and migrate without rewriting product logic.
Frequently asked questions
Are open source models always cheaper?
Not always. Hosting, optimization, monitoring, and operational expertise can outweigh lower inference prices.
Author
Maya Chen
Maya covers applied AI, automation, and responsible product strategy for technical teams.
