Model comparison
GPT-5.5 vs Gemini 3.1 Flash-Lite
Compare GPT-5.5 vs Gemini 3.1 Flash-Lite API pricing: input/output token costs, cache pricing, context windows, workload estimates, and routing fit.
GPT-5.5
openai · gpt-5.5
- Input
- $5
- Output
- $30
- Context
- 1.1M
Gemini 3.1 Flash-Lite
gemini · gemini/gemini-3.1-flash-lite
- Input
- $0.25
- Output
- $1.5
- Context
- 1M
Quick take
Gemini 3.1 Flash-Lite has the lower input price at $0.25 per 1M input tokens. Gemini 3.1 Flash-Lite is cheaper for the example blended workload below. GPT-5.5 has the larger context window at 1.1M tokens.
Choose GPT-5.5 if...
- GPT-5.5 is safer for long documents, repository analysis, and RAG prompts because it has the larger context window.
- GPT-5.5 gives more room for long generated answers, reports, or code output.
Choose Gemini 3.1 Flash-Lite if...
- Gemini 3.1 Flash-Lite is the better default for cost-sensitive traffic and repeated high-volume calls.
Example workload cost
Estimates use input tokens plus 20% output tokens. They exclude provider discounts, cache hits, and tool/search surcharges.
| Workload | GPT-5.5 | Gemini 3.1 Flash-Lite | Cheaper |
|---|---|---|---|
| 1M input + 200K output | $11.00 | $0.55 | Gemini 3.1 Flash-Lite |
| 10M input + 2M output | $110.00 | $5.50 | Gemini 3.1 Flash-Lite |
| 100M input + 20M output | $1,100.00 | $55.00 | Gemini 3.1 Flash-Lite |
Context, output, and capability fit
GPT-5.5 provides the larger context window. Check max output separately when the task needs long reports, code generation, or full-document rewrites.
- GPT-5.5 max output
- 128K
- Gemini 3.1 Flash-Lite max output
- 65.5K
- GPT-5.5 features
- prompt caching, function calling, vision
- Gemini 3.1 Flash-Lite features
- prompt caching, function calling, vision
Risk notes for GPT-5.5
- High output price: cap max tokens for verbose generation workloads.
Risk notes for Gemini 3.1 Flash-Lite
- No major capability risk is flagged in this snapshot, but provider pages should still be verified before production routing.
Routing tags
frontierreasoningcodingagentslong-contextmultimodalcache-friendlyragbudgetfasthigh-volumestable