# Imagen 4 API Is Dead. Here’s the Complete Migration Fix.

> Source: <https://byteiota.com/imagen-4-api-is-dead-heres-the-complete-migration-fix/>
> Published: 2026-08-18 10:21:41+00:00

Google killed three Imagen 4 API endpoints on August 17. If your production app calls `generate_images()`

with any of those model IDs, it is throwing a hard error right now — not a deprecation warning, not a graceful fallback. A hard stop. And if you migrated to `gemini-2.5-flash-image`

based on Google’s earlier guidance, you have six weeks before that one dies too. Here is the complete fix.

## What Google Shut Down

Three endpoints died on August 17, 2026:

`imagen-4.0-generate-001`

(Standard, $0.040/image)`imagen-4.0-fast-generate-001`

(Fast, $0.020/image)`imagen-4.0-ultra-generate-001`

(Ultra, $0.060/image)

Vertex AI users saw these deprecated in March. Gemini API users hit the wall yesterday. Run a codebase audit now — search for `generate_images`

, `imagen-4.0`

, and `GenerateImagesConfig`

.

## The Migration Is Not a Drop-In Swap

Three things changed at the API level. Miss any of them and you ship broken code.

**1. The method is gone.** `client.models.generate_images()`

does not exist on Gemini image models. Switch to `client.models.generate_content()`

.

**2. The response structure changed.** `response.generated_images`

is gone. Iterate over `response.candidates[0].content.parts`

and check each part for `inline_data`

.

**3. Multiple images require a loop.** There is no direct equivalent to `number_of_images=4`

in the same request shape. Call in a loop or check whether your target model supports the `n`

config parameter.

Here is a minimal before-and-after:

### Old Code (Broken as of August 17)

``` python
from google import genai
from google.genai import types

client = genai.Client()
response = client.models.generate_images(
    model='imagen-4.0-generate-001',
    prompt='A photo of a golden retriever on a beach',
    config=types.GenerateImagesConfig(number_of_images=1),
)
response.generated_images[0].image.save('output.png')
```

### New Code (Working with Gemini 3.1 Flash Image)

``` python
from google import genai
from google.genai.types import GenerateContentConfig, Modality
from PIL import Image
from io import BytesIO

client = genai.Client()
response = client.models.generate_content(
    model="gemini-3.1-flash-image",
    contents="A photo of a golden retriever on a beach",
    config=GenerateContentConfig(response_modalities=[Modality.IMAGE]),
)
for part in response.candidates[0].content.parts:
    if part.inline_data is not None:
        image = Image.open(BytesIO(part.inline_data.data))
        image.save("output.png")
```

Firebase AI Logic users have a separate migration path — check [Google’s Firebase migration guide](https://firebase.google.com/docs/ai-logic/imagen-models-migration) for the SDK-specific calls.

## Do Not Stop at Gemini 2.5 Flash Image

Google’s initial migration guidance pointed at `gemini-2.5-flash-image`

. That model retires on **October 2, 2026** — 44 days from now. If you migrate to it today, you are doing this again in six weeks.

Go directly to `gemini-3.1-flash-image`

(Nano Banana 2) or `gemini-3.1-flash-lite-image`

(Nano Banana 2 Lite). Both are GA with no announced retirement date. [Google’s model retirement tracker](https://vorplabs.com/models/google-model-retirements) is worth bookmarking if you run multiple Google AI integrations.

## Which Model Is Right for Your Workload

Two real options:

| Model | Price (1K img) | Speed | Max Res | Status |
|---|---|---|---|---|
`gemini-3.1-flash-image` | $0.067 | ~10s | 4K | GA — safe |
`gemini-3.1-flash-lite-image` | $0.034 | ~4s | 1K | GA — safe |
`gemini-3.1-flash-image` (Batch) | $0.034 | async | 4K | GA — safe |
`gemini-2.5-flash-image` | ~$0.050 | ~7s | 2K | Retires Oct 2 |

**Gemini 3.1 Flash Image** is the full-quality target. Four-K output, 14 aspect ratios, multi-subject consistency across up to five characters, native world knowledge. List price is approximately $0.067 per 1K-resolution image. Run it through the [Batch API](https://ai.google.dev/gemini-api/docs/pricing) and the price drops to $0.034 with async delivery.

**Gemini 3.1 Flash Lite Image** is the budget option. At $0.034 per image, it is cheaper than old Imagen 4 Standard ($0.040) and roughly matches what Imagen 4 Fast cost in bulk. Outputs cap at 1K resolution, text rendering is weaker on small fonts, and there is no Search grounding. For draft generation, thumbnail pipelines, or high-volume preview workflows, it earns its place.

At standard resolution, real-time, Nano Banana 2 costs 67% more than Imagen 4 Standard used to. That is the honest number. There is no GA equivalent to Imagen 4 Fast’s $0.020 price point. Nano Banana 2 Lite closes the gap and brings you a stable model in return.

## The Quick Decision

Final-quality images, full resolution, or conversational image editing: use `gemini-3.1-flash-image`

. High-volume previews, drafts, or anything where 1K is sufficient: use `gemini-3.1-flash-lite-image`

. Need full quality at Imagen 4 Standard pricing: use Nano Banana 2 through the Batch API.

Either way, migrate once to a 3.1 model and you are on GA with no announced sunset. That stability is worth the extra cost over the alternative — staying on Gemini 2.5 Flash Image and scheduling the same migration for October.

For the full list of changes in the Gemini API across all model types, the [official Gemini API changelog](https://ai.google.dev/gemini-api/docs/changelog) is the authoritative source.