Qwen3 Coder Flash
−30% vs Alibaba QwenServed by Alibaba Cloud, which may process requests in its data centres in China.
Qwen3 Coder Flash is a fast coding model for code generation and programming agents, with a 1M-token context and tool calling. It has no reasoning mode and answers directly.
The real Alibaba Qwen model
Same weights, same API, same answers. We change only how you pay for it: one key for every maker, one bill, no separate account to open. Every figure on this page comes from Alibaba Qwen’s own page — check it.
Maker's own pagePrice
input / output · per 1M tokens
Alibaba Cloud
−30%Only on FlintBeam−30% on every request
Direct on Alibaba Cloud: $0.14 / $0.57
Daily discount. Today's price can change.
More pricing details: speeds and very long prompts
Above 32,000 input tokens through Alibaba Cloud, the whole request costs here: $0.15 / $0.60 (Standard, maker's price $0.22 / $0.86)
Above 128,000 input tokens through Alibaba Cloud, the whole request costs here: $0.25 / $1.00 (Standard, maker's price $0.36 / $1.43)
Above 256,000 input tokens through Alibaba Cloud, the whole request costs here: $0.50 / $2.51 (Standard, maker's price $0.72 / $3.58)
Context
1,000,000
up to 65,536 out
65,536 by default here
Modalities
What it would cost you
1000 tokens is roughly 750 English words.
How it is served
Requests are retried automatically if a provider is unavailable.
Similar models
Models built for the same kind of work, at a similar price.
Eligible models may have a daily discount below the maker's price. Daily discounts apply to eligible models and can change from day to day.
Use it from your code
from openai import OpenAI
# Works with the official openai package (pip install openai)
client = OpenAI(
base_url="https://api.flintbeam.com/v1",
api_key="sk-live-your-api-key"
)
response = client.chat.completions.create(
model="qwen/qwen3-coder-flash",
messages=[
{"role": "system", "content": "You are an experienced software engineer."},
{"role": "user", "content": "Describe the architecture of a distributed cache."}
],
temperature=0.7,
max_tokens=1500
)
print(response.choices[0].message.content)