Gemini 3.1 Flash-Lite Image, marketed as Nano Banana 2 Lite, is Google's ultra-low-latency image generation and editing model, described as the efficiency specialist of the family and engineered for velocity and scale where speed and cost are the primary operational constraints; the model page cites sub-2-second end-to-end latency for high-volume interactive applications.
- Input
- text image $0.25/M
- Output
- image text $30/M
- Knowledge cutoff
- 2025-01
Price in context
Where the price sits among 8 comparable models
The bar shows how this model’s price compares with every other model of the same kind on Synthorai. The cheapest and the most expensive are named at each end. These are base rates; batch, region and cache-write discounts are on the pricing page.
Specs & limits
Tokens
| Max output (vendor spec) | 4,096 |
|---|---|
| Knowledge cutoff | 2025-01 |
Thinking
| Vendor control | thinkingLevel |
|---|---|
| Accepted values | minimal · high (low and medium are not supported) |
| Default | minimal applied when the request sets nothing |
| Can be turned off | No |
| Thinking behaviour | high is the dynamic setting; as a Gemini 3 image model its thinking pass is on by default and cannot be disabled in the API. |
| Parameter | reasoning_effort |
| Values | minimal · low · medium · high the gateway's parameter surface - the vendor mapping above applies |
Image
| Sizes | 1K only (1:1 = 1024x1024) |
|---|---|
| Input modes | text-to-image, interleaved generation + editing, up to 14 reference images |
| Image capabilities |
|
Model
| Modalities | text + image → image + text |
|---|
- Optimized for ultra-low-latency, high-volume interactive use
- caching and structured outputs not supported
- thinking minimal/high
One prompt, measured through the gateway
gemini-3.1-flash-lite-image
Model returned 1408×768 latency 3 s
One prompt, one request per model, no retries and no cherry-picking - the first result each model returned. Neither size nor duration was pinned: each model used its own default, because a request shaped to fit all of them would flatter none. Files here are re-encoded for the web, so judge composition and prompt adherence, not compression.
Use gemini-3.1-flash-lite-image in 30 seconds
OpenAI-compatible: swap the base_url, keep your SDK. POST /v1/images/generations
from openai import OpenAI
client = OpenAI(
base_url="https://synthorai.io/v1",
api_key="sk-syn-...",
)
resp = client.images.generate(
model="gemini-3.1-flash-lite-image",
prompt="a watercolor lighthouse at dawn",
size="1024x1024",
)
print(resp.data[0].b64_json[:80])import OpenAI from "openai";
const client = new OpenAI({
baseURL: "https://synthorai.io/v1",
apiKey: "sk-syn-...",
});
const resp = await client.images.generate({
model: "gemini-3.1-flash-lite-image",
prompt: "a watercolor lighthouse at dawn",
size: "1024x1024",
});
console.log(resp.data?.[0]?.b64_json?.slice(0, 80));curl https://synthorai.io/v1/images/generations \
-H "Authorization: Bearer sk-syn-..." \
-H "Content-Type: application/json" \
-d '{
"model": "gemini-3.1-flash-lite-image",
"prompt": "a watercolor lighthouse at dawn",
"size": "1024x1024"
}'package main
import (
"context"
"fmt"
"github.com/openai/openai-go/v3"
"github.com/openai/openai-go/v3/option"
)
func main() {
client := openai.NewClient(
option.WithBaseURL("https://synthorai.io/v1"),
option.WithAPIKey("sk-syn-..."),
)
resp, _ := client.Images.Generate(context.TODO(), openai.ImageGenerateParams{
Model: "gemini-3.1-flash-lite-image",
Prompt: "a watercolor lighthouse at dawn",
Size: "1024x1024",
})
fmt.Println(resp.Data[0].B64JSON[:80])
}import com.openai.client.OpenAIClient;
import com.openai.client.okhttp.OpenAIOkHttpClient;
import com.openai.models.images.*;
OpenAIClient client = OpenAIOkHttpClient.builder()
.baseUrl("https://synthorai.io/v1")
.apiKey("sk-syn-...")
.build();
ImagesResponse resp = client.images().generate(
ImageGenerateParams.builder()
.model("gemini-3.1-flash-lite-image")
.prompt("a watercolor lighthouse at dawn")
.size("1024x1024")
.build());
System.out.println(resp.data().orElseThrow().get(0).b64Json().orElseThrow().substring(0, 80));About gemini-3.1-flash-lite-image
- It handles interleaved text-and-image prompts and excels at localized edits such as color swaps, sticker generation, and background adjustments, while Google says it retains reliable prompt adherence, strong character consistency, and legible in-image text.
- Output is fixed at 1K resolution across ten aspect ratios, the first time the Lite tier has had ratio control, and it accepts up to fourteen object reference images, the highest count in the family.
- The trade-offs are explicit in the docs: the output budget is 4,096 tokens against 32,768 on its siblings, multi-turn editing is more limited than on Flash or Pro, and Search grounding, Image Search grounding, and video input are all absent, though function calling is supported and thinking is available at minimal or high.
- Google positions it as the upgrade path for anyone still on the original Nano Banana.
- Every image carries SynthID and C2PA watermarking.
- Synthorai exposes it through the same OpenAI-compatible API used for its text models.
FAQ
Is the gemini-3.1-flash-lite-image API free to try?
Yes: new accounts get 10 trial calls and up to $1 in free credit, no card required. That's enough to try gemini-3.1-flash-lite-image against your real workload before adding a payment method.
What is gemini-3.1-flash-lite-image best at?
Sub-2-second end-to-end latency; excels at localized edits and stickers; SynthID and C2PA watermarking on every image. See the About section for the full picture from the vendor's own release notes.
How much does gemini-3.1-flash-lite-image cost?
gemini-3.1-flash-lite-image costs $0.25 per million input tokens and $30 per million output tokens on Synthorai. That is the provider's list price, with no platform markup.
How do I generate images with the gemini-3.1-flash-lite-image API?
POST to /v1/images/generations on Synthorai with model="gemini-3.1-flash-lite-image". It follows the OpenAI images API shape, so no vendor SDK is needed. Supported sizes: 1K only (1:1 = 1024x1024).
How do I get access to gemini-3.1-flash-lite-image?
Point your existing OpenAI SDK at base_url="https://synthorai.io/v1", set model="gemini-3.1-flash-lite-image", and you're done. One API key covers every model on the gateway.
Related models
Compare
Every value on this page is transcribed from the vendor's own documentation, linked above, and carries the date it was checked. Prices are compared across the catalogue; specification values that vendors define differently are shown with the difference stated rather than charted. Nothing here is measured by us, and nothing is scored.