Gemini 3 Flash vs Gemini 3.1 Pro: Which AI Model Should You Choose?
Pricing, context windows, latency, capabilities, and a one-line code switch — everything you need to pick the right model.
Choose Gemini 3 Flash for cost-sensitive workloads — it is roughly 4.0× cheaper on input tokens. Choose Gemini 3.1 Pro when you need its broader capabilities or stronger benchmarks.
Side-by-side specs
| Spec | Gemini 3 Flash | Gemini 3.1 Pro |
|---|---|---|
| Provider | ||
| Category | Multimodal | Multimodal |
| Input cost / 1M tokens | $0.60 | $2.40 |
| Output cost / 1M tokens | $3.60 | $14.40 |
| Context window | 1.0M tokens | 1.0M tokens |
| Max output tokens | 65,536 | 65,536 |
| Avg. latency | — | — |
| Featured | Yes | Yes |
| New | Yes | Yes |
| Capabilities | text image audio video | text image audio video |
Pricing example
A typical chat workload of 100,000 input tokens plus 50,000 output tokens.
100K in × $0.60 + 50K out × $3.60
100K in × $2.40 + 50K out × $14.40
For this workload, Gemini 3 Flash is cheaper than Gemini 3.1 Pro by $0.72 per request.
Switch in one line
Both models live behind Railwail's OpenAI-compatible endpoint. Replace the model string and you are done.
import OpenAI from "openai";
const client = new OpenAI({
apiKey: process.env.RAILWAIL_API_KEY,
baseURL: "https://railwail.com/v1",
});
// Before — using Gemini 3 Flash
let r = await client.chat.completions.create({
model: "gemini-3-flash-preview",
messages: [{ role: "user", content: "Hello" }],
});
// After — switched to Gemini 3.1 Pro
r = await client.chat.completions.create({
model: "gemini-3.1-pro-preview",
messages: [{ role: "user", content: "Hello" }],
});from openai import OpenAI
client = OpenAI(
api_key=os.environ["RAILWAIL_API_KEY"],
base_url="https://railwail.com/v1",
)
# Before — using Gemini 3 Flash
r = client.chat.completions.create(
model="gemini-3-flash-preview",
messages=[{"role": "user", "content": "Hello"}],
)
# After — switched to Gemini 3.1 Pro
r = client.chat.completions.create(
model="gemini-3.1-pro-preview",
messages=[{"role": "user", "content": "Hello"}],
)# Before — using Gemini 3 Flash
curl https://railwail.com/v1/chat/completions \
-H "Authorization: Bearer $RAILWAIL_API_KEY" \
-H "Content-Type: application/json" \
-d '{
"model": "gemini-3-flash-preview",
"messages": [{"role": "user", "content": "Hello"}]
}'
# After — switched to Gemini 3.1 Pro
curl https://railwail.com/v1/chat/completions \
-H "Authorization: Bearer $RAILWAIL_API_KEY" \
-H "Content-Type: application/json" \
-d '{
"model": "gemini-3.1-pro-preview",
"messages": [{"role": "user", "content": "Hello"}]
}'Which one wins for...
Quick verdicts derived from public specs. Always validate on your own workload.
Higher coding category match or larger context wins.
Bigger context window helps maintain long-form coherence.
The larger context window is the deciding factor.
Multimodal/vision support is required for image inputs.
Lower average latency wins for interactive UX.
The model with the lower input-token price wins.
Frequently asked questions
Try Gemini 3 Flash and Gemini 3.1 Pro side by side
One API key, one endpoint, both models. Start free — no credit card required.