GPT-5.4 Nano vs Gemini 2.5 Flash-Lite: ultra-cheap high-frequency endpoints
Gemini 2.5 Flash-Lite is cheaper on standard transactional runs. GPT-5.4 Nano wins when you can leverage its 90% prompt caching discount to drop inputs to $0.02 per million.
High-frequency entry-level endpoints comparison.
For ultra-high-frequency simple tasks like sentiment analysis and router checks, entry-level models are incredibly cheap. Let's compare GPT-5.4 Nano and Gemini 2.5 Flash-Lite.
By TechCompare · Updated
Cost Comparison
Based on 100,000 input tokens (50% cached), 5,000 output tokens, and 100 requests.
Side-by-side specs
| Spec | GPT-5.4 Nano | Gemini 2.5 Flash-Lite |
|---|---|---|
| Input Cost (per M) | $0.20 | $0.10 (better on this spec) |
| Output Cost (per M) | $1.25 | $0.40 (better on this spec) |
| Cached Input (per M) | $0.02 (better on this spec) | $0.10 |
| Batch Discount | 50% | 50% |
How they differ
GPT-5.4 Nano costs $0.20 per million input tokens and $1.25 per million output tokens, with a 90% caching discount. Gemini 2.5 Flash-Lite is priced at $0.10 per million input tokens and $0.40 per million output tokens, without caching discounts.
Verdict
Flash-Lite wins the base rows at $0.10/M input against $0.20 and $0.40/M output against $1.25. The single row where Nano overtakes is cached input at $0.02/M against Flash-Lite's uncached $0.10/M, which only matters on workloads with high prompt reuse and exact-prefix matches. Both apply 50% batch discounts, preserving the Flash-Lite lead in batch mode by roughly 2x on every row. Treat Nano as the cached-prompt pick and Flash-Lite as the one-shot default.
Which should you pick?
Choose GPT-5.4 Nano
Repetitive long-context classification, high-caching search sorting.
Choose Gemini 2.5 Flash-Lite
Low-cost high-speed simple completions, basic chatbots, and data transformations.