Pricing, context window, capabilities, and release date — pulled from each provider's public docs. Both are available via the same AIgateway OpenAI-compatible endpoint; flip the model string to switch.
Both models stream in parallel through your own AIgateway key. Tokens, latency, and cost update as they arrive.
| Gemini 3.1 Pro google/gemini-3.1-pro | Gemini 3.1 Flash Lite google/gemini-3.1-flash-lite | |
|---|---|---|
| Provider | ||
| Family | Gemini 3 | Gemini 3 |
| Modality | text | text |
| Context window | 1,000,000 tok | 1,000,000 tok |
| Max output | 65,536 tok | 8,192 tok |
| Released | 2026-04-13 | 2026-04-13 |
| Input price | $2.00 /1M | $0.250 /1M |
| Output price | $12.00 /1M | $1.50 /1M |
| Cache read | $0.200 /1M | $0.025 /1M |
| Tools | yes | yes |
| Streaming | yes | yes |
| Vision | yes | yes |
| JSON mode | yes | yes |
| Reasoning | yes | — |
| Prompt caching | yes | yes |
Google's most intelligent Gemini model with improved reasoning, a medium thinking level, and a 1M token context window.
Google's lightest and most cost-efficient Gemini model for high-throughput tasks.
# pip install aigateway-py openai
# aigateway-py: sub-accounts, evals, replays, jobs, webhook verify.
# openai SDK: chat/embeddings/images/audio — drop-in compat per our SDK's own guidance.
from openai import OpenAI
client = OpenAI(
base_url="https://api.aigateway.sh/v1",
api_key="sk-aig-...",
)
# Try Gemini 3.1 Pro
client.chat.completions.create(
model="google/gemini-3.1-pro",
messages=[{"role":"user","content":"hello"}],
)
# Try Gemini 3.1 Flash Lite — same client, same key
client.chat.completions.create(
model="google/gemini-3.1-flash-lite",
messages=[{"role":"user","content":"hello"}],
)