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.
| Wan 3.0 Video alibaba/wan-3.0 | Gemini 2.5 Pro google/gemini-2.5-pro | |
|---|---|---|
| Provider | Alibaba | |
| Family | Wan | |
| Modality | video | text |
| Context window | — | 1,000,000 tok |
| Max output | — | 65,536 tok |
| Released | 2026-08-25 | 2026-05-22 |
| Input price | $0.050 /sec | $1.25 /1M |
| Output price | — | $10.00 /1M |
| Cache read | — | — |
| Tools | — | — |
| Streaming | — | yes |
| Vision | — | yes |
| JSON mode | — | — |
| Reasoning | — | — |
| Prompt caching | — | — |
Alibaba's Wan 3.0 text-to-video model. Generates cinematic videos from text prompts with adaptive aspect ratio, 480P, 720P, or 1080P resolution, and configurable duration.
Google's most capable Gemini 2.5 model with strong reasoning, thinking support, and a 1M token context window.
# 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 Wan 3.0 Video
client.chat.completions.create(
model="alibaba/wan-3.0",
messages=[{"role":"user","content":"hello"}],
)
# Try Gemini 2.5 Pro — same client, same key
client.chat.completions.create(
model="google/gemini-2.5-pro",
messages=[{"role":"user","content":"hello"}],
)