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 3.5 397B A17B alibaba/qwen3.5-397b-a17b | Qwen3-Embedding-0.6b qwen/qwen3-embedding-0.6b | |
|---|---|---|
| Provider | Alibaba | Alibaba Qwen |
| Family | Qwen | Qwen |
| Modality | text | embedding |
| Context window | 262,144 tok | 8,192 tok |
| Max output | 4,096 tok | — |
| Released | 2026-04-15 | 2025-06-18 |
| Input price | $0.600 /1M | $0.012 /1M |
| Output price | $3.60 /1M | — |
| Cache read | — | — |
| Tools | yes | — |
| Streaming | yes | — |
| Vision | — | — |
| JSON mode | yes | — |
| Reasoning | yes | — |
| Prompt caching | — | — |
Alibaba's Qwen 3.5 is a 397B-parameter mixture-of-experts model with 17B active parameters, offering strong reasoning capabilities with efficient inference.
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 3.5 397B A17B
client.chat.completions.create(
model="alibaba/qwen3.5-397b-a17b",
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"}],
)