Gemini 3.5 Flash vs GPT-5 Mini
The cheap-fast tier for high-volume tool calls and classification.
| Metric | Gemini 3.5 Flash | GPT-5 Mini |
|---|---|---|
| Provider | Google Gemini | OpenAI |
| Input / 1M | $1.50 | $0.25 |
| Output / 1M | $9.00 | $2.00 |
| Cache read / 1M | $0.15 (−90%) | $0.03 (−90%) |
| Reuse-adj @55% | $2.82 | $0.59 |
| Context | 1M | 400K |
| Cache capture | 81% | 85% |
| Warm TTFT | 150ms (−61%) | 150ms (−63%) |
| Quality index | 86 | 82 |
Teal marks the better value in each row. Reuse-adjusted assumes 55% prefix reuse and a 25% output share.
You need multimodal input, a very large window, and a lower input price.
You are already on OpenAI and want automatic caching with a familiar surface.
Gemini 3.5 Flash is cheaper and multimodal; GPT-5 Mini is a touch sharper on pure text tool-calling. Both are strong auto.cheapest targets.
Gemini 3.5 Flash vs GPT-5 Mini, answered.
Is Gemini 3.5 Flash or GPT-5 Mini cheaper?
At 55% prefix reuse, Gemini 3.5 Flash blends to about $2.82 per 1M tokens and GPT-5 Mini to about $0.59. GPT-5 Mini is cheaper on that basis.
Which has the larger context window?
Gemini 3.5 Flash has the larger window: 1M vs 400K tokens.
Which captures more reuse?
GPT-5 Mini shows higher measured cache capture (85% vs 81%) in the Zumik corpus.
Let an alias pick for you.
Route to whichever model wins under current policy automatically. Zumik resolves the alias to the best fit per request, so you never hard-code a loser.