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.
| Kimi K3 moonshot/kimi-k3 | GPT Image 2.5 Sunburst openai/gpt-image-2.5-sunburst | |
|---|---|---|
| Provider | Moonshot | OpenAI |
| Family | ||
| Modality | text | image |
| Context window | 1,048,576 tok | — |
| Max output | 32,768 tok | — |
| Released | 2026-07-16 | 2026-09-10 |
| Input price | $3.00 /1M | $0.030 /img |
| Output price | $15.00 /1M | — |
| Cache read | — | — |
| Tools | yes | — |
| Streaming | yes | — |
| Vision | yes | — |
| JSON mode | yes | — |
| Reasoning | yes | — |
| Prompt caching | — | — |
Kimi K3 is Moonshot's flagship 2.8 trillion-parameter model, built on Kimi Delta Attention (a hybrid linear attention mechanism) with Attention Residuals. It offers native visual understanding, always-on reasoning, and a 1M-token context window for long-horizon coding, knowledge work, and deep reasoning tasks.
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 Kimi K3
client.chat.completions.create(
model="moonshot/kimi-k3",
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"}],
)