Fastest AI image model API: what the October 2026 claims say

Three vendors claim speed this autumn, and each uses a different baseline. fal describes GPT Image 2.5 Flare as 'higher quality than GPT Image 2 with half the latency'. Microsoft says MAI-Image-2.6-Flash generates images 2.8x faster than GPT-Image-2-Medium. Google positions Nano Banana 2 as bringing Gemini Flash speed to image generation, with no number. You cannot rank these against each other, because the baselines, sizes and quality settings differ. To pick the fastest model for your prompts, time them yourself through one API.

On Sume, a synchronous call waits up to 30 seconds and returns the image with 200, or returns 202 with a job if it runs longer. That makes the 30-second line a practical speed bar for interactive use.

What does each vendor claim?

Claims are vendor statements read on the dates below; none are Sume measurements.

How do I time models on Sume?

Run the same prompt, size and quality through each model id a few times and compare medians. This script times three models; a 202 means the call passed 30 seconds, which is itself a result:

import os
import time
import requests

H = {"Authorization": f"Bearer {os.environ['SUME_API_KEY']}"}
MODELS = ["openai/gpt-image-2.5", "google/nano-banana-2",
          "bytedance-seed/seedream-5-lite"]

for model in MODELS:
    for _ in range(3):
        t0 = time.perf_counter()
        r = requests.post("https://api.sume.com/v1/images", headers=H,
            json={"model": model, "prompt": "red teapot on a white table"},
            timeout=60)
        print(model, r.status_code, round(time.perf_counter() - t0, 1), "s")

Which Sume model is the default for speed?

The Image API docs say Auto routing continues to use Flare for ChatGPT Image 2.5, and that Flare and Sunburst share pricing. If you want the quicker of the two for a draft, use Flare; reserve Sunburst for final art where detail matters. See Flare vs Sunburst.

Limits

A timing run measures your prompt, size, quality and the moment you ran it; it is not a benchmark. Higher quality and bigger sizes take longer on every model. Each request in the script bills when it completes, so keep the run small. MAI-Image-2.6 is not in Sume's image list as of this post, so it cannot be part of the script.