Pricing, context window, capabilities, and release date — pulled from each provider's public docs. Both are available via the same AIgateway OpenAI-compatible endpoint; flip the model string to switch.
Both models stream in parallel through your own AIgateway key. Tokens, latency, and cost update as they arrive.
| MiniMax H3 Max Text to Video minimax/h3-max | GPT Image 2.5 Sunburst openai/gpt-image-2.5-sunburst | |
|---|---|---|
| Provider | MiniMax | OpenAI |
| Family | ||
| Modality | video | image |
| Context window | — | — |
| Max output | — | — |
| Released | 2026-09-16 | 2026-09-10 |
| Input price | $0.025 /sec | $0.030 /img |
| Output price | — | — |
| Cache read | — | — |
| Tools | — | — |
| Streaming | — | — |
| Vision | — | — |
| JSON mode | — | — |
| Reasoning | — | — |
| Prompt caching | — | — |
fal's H3 Max is a post-trained variant of MiniMax H3, tuned for stronger prompt adherence and better aesthetics while co-optimized with our custom inference stack for higher throughput with no compromises on output quality
OpenAI's most capable image generation and editing model. It accepts text and image inputs and produces images with low, medium, high, xhigh, max, and auto quality settings.
# pip install aigateway-py openai
# aigateway-py: sub-accounts, evals, replays, jobs, webhook verify.
# openai SDK: chat/embeddings/images/audio — drop-in compat per our SDK's own guidance.
from openai import OpenAI
client = OpenAI(
base_url="https://api.aigateway.sh/v1",
api_key="sk-aig-...",
)
# Try MiniMax H3 Max Text to Video
client.chat.completions.create(
model="minimax/h3-max",
messages=[{"role":"user","content":"hello"}],
)
# Try GPT Image 2.5 Sunburst — same client, same key
client.chat.completions.create(
model="openai/gpt-image-2.5-sunburst",
messages=[{"role":"user","content":"hello"}],
)