Qwen3 Max Instruct API
256K context · Released Apr 29, 2026 · By Alibaba · Apache 2.0
Qwen3 Max Instruct costs $0.49 per million input tokens and $1.95 per million output tokens, against an official rate of $0.85 and $3.4 — 43% below official pricing. It is a Alibaba model under the Apache 2.0 licence, with a 256K context window, callable through an OpenAI-compatible endpoint with the model id `qwen/qwen3-max-instruct`. This model is listed for reference and is not currently served by an upstream provider, so requests for it return no available channel.
Not currently available. No configured upstream serves this model, so a request for it returns no available channel. The rate below is what it will cost when it is enabled.
Input
$0.49/M
$0.85/M
Output
$1.95/M
$3.40/M
Savings
43%
off official
- No markup
- OpenAI SDK compatible
- No minimum spend
- Apache 2.0
Apache 2.0 with no strings attached, which matters if your legal team reads licenses. Strong multilingual coverage and reliable structured output.
Copy this and go
The model id is already filled in. Nothing in this snippet needs editing except your key.
from openai import OpenAI
client = OpenAI(
api_key="YOUR_API_KEY",
base_url="https://router.xark.io/api/v1" # ← the only line that changes
)
response = client.chat.completions.create(
model="qwen/qwen3-max-instruct",
messages=[{"role": "user", "content": "Hello"}]
)
Qwen3 Max Instruct pricing across providers
Rates as published by each provider. We update these when they change; if you spot one that's stale, tell us and we'll fix it.
| Provider | Input | Output |
|---|---|---|
| AI Token Router | $0.49/M | $1.95/M |
| Official (Alibaba) | $0.85/M | $3.40/M |
| OpenRouter | $0.82/M | $3.30/M |
| DeepInfra | $0.60/M | $2.40/M |
| Together AI | $0.80/M | $3.20/M |
Cached input on Qwen3 Max Instruct is billed at $0.10/M — roughly 80% below the standard input rate. For agent loops with a large fixed system prompt this is usually the number that matters most.
What it's good at
- Products shipping into regulated or licence-sensitive contexts
- Multilingual applications beyond EN/ZH
- JSON-mode and schema-constrained generation