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.
| Qwen Image 3.0 Pro alibaba/qwen-image-3.0-pro | Qwen 3.5 397B A17B alibaba/qwen3.5-397b-a17b | |
|---|---|---|
| Provider | Alibaba | Alibaba |
| Family | Qwen | Qwen |
| Modality | image | text |
| Context window | — | 256,000 tok |
| Max output | — | 32,768 tok |
| Released | 2026-08-11 | 2026-05-14 |
| Input price | $0.040 /img | $0.600 /1M |
| Output price | — | $3.60 /1M |
| Cache read | — | — |
| Tools | — | yes |
| Streaming | — | yes |
| Vision | — | — |
| JSON mode | — | yes |
| Reasoning | — | yes |
| Prompt caching | — | — |
Alibaba's Qwen Image 3.0 Pro generates images from text prompts with a focus on complex layout generation, small-text precision, and multilingual font rendering. Supports up to 6 image variants per call, negative prompts, seed control, and optional prompt rewriting.
Alibaba's Qwen 3.5 is a 397B-parameter mixture-of-experts model with 17B active parameters, offering strong reasoning capabilities with efficient inference.
# 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 Qwen Image 3.0 Pro
client.chat.completions.create(
model="alibaba/qwen-image-3.0-pro",
messages=[{"role":"user","content":"hello"}],
)
# Try Qwen 3.5 397B A17B — same client, same key
client.chat.completions.create(
model="alibaba/qwen3.5-397b-a17b",
messages=[{"role":"user","content":"hello"}],
)