How to choose an LLM API? Developers weigh cost, speed, and reliability
Puzzleheaded-Fig1589 · reddit · 2026-08-17
A developer discusses criteria for selecting an LLM API for new projects, noting a shift from focusing solely on intelligence to balancing cost, speed, reliability, and quality. Key evaluation factors listed include token pricing, latency, context window, coding performance, structured output/tool calling, rate limits, reliability, API compatibility, and total cost at scale. The post seeks insights into how practitioners benchmark models and what drives provider switches in production.
More from Infra
- Omarchy: DHH-endorsed, agent-first Linux operating system — vista8 · 2026-08-17
- Llama-3.0-Flash Leaked to Run End-to-End on a Single DGX Spark — Affectionate-File-26 · 2026-08-17
- AWS Trainium 4 Projected to Deploy 5M Units by 2H27, 12M by 2028 — zephyr_z9 · 2026-08-17
- IBM Open Sources Docling-Graph: Converting PDFs to Knowledge Graphs — aigleeson · 2026-08-17
- Open-source ETL Duckle loads 20M rows in 15.69s, beats Airbyte — JafarNajafov · 2026-08-17
- llama.cpp Adds Support for Ling 3.0 Models — parepeg · 2026-08-17