How I brought LLM costs down to zero: why parallelism is the enemy on free tiers
Summary
The article explains how to reduce LLM inference costs to near zero by coordinating multiple free-tier providers instead of relying on one model endpoint. It shows a fallback chain with circuit breakers, cooldowns, and rate-limit handling to keep requests moving when a provider hits limits. It also recommends staggering user jobs and processing prompts sequentially to avoid burst traffic and throttling. The main lesson is that parallelism can quickly exhaust free quotas, so careful scheduling and caching matter more than raw throughput.
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