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 | Qwen3-Embedding-0.6b qwen/qwen3-embedding-0.6b | |
|---|---|---|
| Provider | Alibaba | Alibaba Qwen |
| Family | Qwen | Qwen |
| Modality | image | embedding |
| Context window | — | — |
| Max output | — | — |
| Released | 2026-08-11 | 2025-06-18 |
| Input price | $0.040 /img | $0.012 /1M |
| Output price | — | $0.0000 /1M |
| Cache read | — | — |
| Tools | — | — |
| Streaming | — | — |
| Vision | — | — |
| JSON mode | — | — |
| Reasoning | — | — |
| 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.
The Qwen3 Embedding model series is the latest proprietary model of the Qwen family, specifically designed for text embedding and ranking tasks.
# 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 Qwen3-Embedding-0.6b — same client, same key
client.chat.completions.create(
model="qwen/qwen3-embedding-0.6b",
messages=[{"role":"user","content":"hello"}],
)