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const axios = require('axios');
const api_key = "YOUR API-KEY";
const url = "https://api.segmind.com/v1/qwen3-coder-flash";
const data = {
"messages": [
{
"role": "user",
"content" : "tell me a joke on cats"
},
{
"role": "assistant",
"content" : "here is a joke about cats..."
},
{
"role": "user",
"content" : "now a joke on dogs"
},
]
};
(async function() {
try {
const response = await axios.post(url, data, { headers: { 'x-api-key': api_key } });
console.log(response.data);
} catch (error) {
console.error('Error:', error.response.data);
}
})();Attributes
An array of objects containing the role and content
Could be "user", "assistant" or "system".
A string containing the user's query or the assistant's response.
To keep track of your credit usage, you can inspect the response headers of each API call. The x-remaining-credits property will indicate the number of remaining credits in your account. Ensure you monitor this value to avoid any disruptions in your API usage.
Qwen3 Coder Flash — Fast & Affordable Code Generation AI
What is Qwen3 Coder Flash?
Qwen3 Coder Flash is Alibaba Cloud's cost-efficient, high-speed variant of the Qwen3-Coder model family — a series of code-specialized large language models built for serious software development. Part of the same lineage as the benchmark-beating Qwen3-Coder-Plus and Qwen3-Coder-480B, the Flash tier is designed for production workloads where speed and cost efficiency take priority. It delivers strong coding performance across 358+ programming languages, with a 1 million token context window that lets you pass entire codebases in a single API call.
Served via Alibaba Cloud's DashScope infrastructure, Qwen3-Coder-Flash is available through an OpenAI-compatible API, making integration into existing toolchains straightforward. It supports multi-turn conversations, tool calling, and agentic workflows — giving developers a powerful backend for building code assistants, CI/CD automation, and developer productivity tools at scale.
Key Features
- 1M Token Context Window: Process full repositories, large codebases, or lengthy documentation in a single pass — no chunking required.
- 358+ Programming Languages: Strong coverage from Python, TypeScript, and Rust to SQL, Bash, and domain-specific languages.
- Tool Calling & Agentic Support: Native function calling format compatible with Qwen Code, CLINE, and Claude Code interfaces.
- Cost-Efficient Pricing: Significantly lower cost per token than the Plus tier — ideal for high-volume or always-on applications.
- OpenAI-Compatible API: Drop-in compatible with most LLM SDKs, allowing easy integration without rewrites.
- Fast Inference: Lower latency than heavier variants, critical for real-time autocomplete and interactive developer tools.
Best Use Cases
AI Code Autocomplete & IDE Integration: Qwen3-Coder-Flash is fast enough for real-time inline suggestions in editors like VS Code or JetBrains IDEs. Its low cost makes it viable to deploy at per-keystroke frequency without ballooning infrastructure costs.
Automated Code Review: Use it as the backbone for PR review bots that check style, identify bugs, suggest refactors, and enforce patterns — processing thousands of diffs per day economically.
Documentation Generation: Point the model at entire modules or packages (thanks to the 1M context window) and generate structured API docs, README files, or inline code comments automatically.
CI/CD Quality Gates: Integrate into pipelines to auto-audit commits, detect anti-patterns, or validate test coverage logic without human review cycles.
Lightweight Agentic Backends: Power multi-step coding agents that browse files, call tools, and execute iterative tasks — all at a fraction of the cost of heavyweight models.
Prompt Tips and Output Quality
For best results, provide clear context about the programming language and desired output format. When working with large codebases, include the relevant file structure or key files in the prompt. Use system messages to set coding style conventions (e.g., PEP 8, ESLint rules). For agentic tasks, leverage the function-calling format to pass tool results back into the conversation. Avoid vague instructions — specificity dramatically improves code quality. Use temperature=0 for deterministic outputs in production pipelines, and higher temperatures for brainstorming or exploring architectural alternatives.
FAQs
Q: How does Qwen3-Coder-Flash differ from Qwen3-Coder-Plus? Flash is optimized for speed and low cost; Plus produces higher-quality outputs for complex multi-file reasoning. Use Flash for high-volume, latency-sensitive tasks and Plus when correctness is paramount.
Q: What context window does Qwen3-Coder-Flash support? It supports a 1 million token context window, allowing you to process entire repositories in a single API call.
Q: Can it be used for agentic coding workflows? Yes. It supports multi-turn tool calling and is compatible with agentic platforms like Qwen Code, CLINE, and Claude Code interfaces.
Q: Which programming languages does it support? Qwen3-Coder-Flash supports 358+ languages including Python, JavaScript/TypeScript, Java, Go, Rust, C/C++, SQL, HTML/CSS, and many more.
Q: Is the API OpenAI-compatible? Yes. The API follows OpenAI's chat completions format, making it easy to swap in as a drop-in replacement in existing integrations.
Q: When should I upgrade to Qwen3-Coder-Plus? Upgrade when tasks require deep algorithmic reasoning, complex multi-file refactoring with precise logic chains, or when output quality is more critical than cost.
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