GPT-image-2.5 / 2: официальный или реверс-инжиниринговый

# Universal pattern: detect the prefix before processing — works for all official and reverse models
b64 = resp["data"][0]["b64_json"]
if b64.startswith("data:"):          # handles historical prefixed responses
    b64 = b64.split(",", 1)[1]
with open("out.png", "wb") as f:
    f.write(base64.b64decode(b64))   # ✅ write file
img_tag = f'<img src="data:image/png;base64,{b64}">'  # ✅ browser render

"Landscape 16:9 cinematic, old lighthouse at sunset"   → ~1672×941
"Portrait 9:16 phone wallpaper, cyberpunk city"        → ~941×1672
"1024×1024 square logo, minimalist cat line art"        → ~1254×1254

client.images.generate(
    model="gpt-image-2.5-vip",   # alias = gpt-image-2.5-sunburst-vip; swap in gpt-image-2.5-flare-vip / gpt-image-2-vip on this line only
    prompt="...",
    size="3840x2160",   # ✅ one of the 30 presets; images endpoints only (not chat)
    quality="max"       # optional; all six tiers on the 2.5 models, gpt-image-2-vip stops at high; flat $0.03 regardless of tier
)

client.images.generate(
    model="gpt-image-2.5-flare",
    prompt="...",
    size="2048x1152",   # ✅ output exactly this
    quality="max"       # all six tiers; xhigh / max on the two 2.5 models only; 2.5 high only equals gpt-image-2 medium
)