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 Prime (Text To Video) alibaba/wan-3.0-prime | Gemini 2.5 Pro google/gemini-2.5-pro | |
|---|---|---|
| Provider | Alibaba | |
| Family | ||
| Modality | video | text |
| Context window | — | 1,000,000 tok |
| Max output | — | 65,536 tok |
| Released | 2026-09-01 | 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 | — | — |
Wan 3.0 Prime Text-to-Video transforms written prompts into polished videos with accelerated generation, fluid motion, strong scene fidelity, and coherent visual storytelling. Built for fast creative iteration, it brings complex ideas to life while preserving visual detail and cinematic consistency throughout each shot.
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 Prime (Text To Video)
client.chat.completions.create(
model="alibaba/wan-3.0-prime",
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"}],
)