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.
| Gemini 2.5 Pro google/gemini-2.5-pro | Wan 2.7 I2V alibaba/wan-2.7-i2v | |
|---|---|---|
| Provider | Alibaba | |
| Family | Wan | |
| Modality | text | video |
| Context window | 1,000,000 tok | — |
| Max output | 65,536 tok | — |
| Released | 2026-05-22 | 2026-05-29 |
| Input price | $1.25 /1M | $0.100 /sec |
| Output price | $10.00 /1M | — |
| Cache read | — | — |
| Tools | — | — |
| Streaming | yes | — |
| Vision | — | — |
| JSON mode | — | — |
| Reasoning | — | — |
| Prompt caching | — | — |
Google's most capable Gemini 2.5 model with strong reasoning, thinking support, and a 1M token context window.
Alibaba's Wan 2.7 image-to-video model that generates videos from a reference image with optional text prompts. Supports 720P and 1080P output with durations from 2 to 15 seconds.
# 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 Gemini 2.5 Pro
client.chat.completions.create(
model="google/gemini-2.5-pro",
messages=[{"role":"user","content":"hello"}],
)
# Try Wan 2.7 I2V — same client, same key
client.chat.completions.create(
model="alibaba/wan-2.7-i2v",
messages=[{"role":"user","content":"hello"}],
)