Qwen3 Coder 30B A3B Instruct API
Released 2025-07-31 | N/A context | 1.1B Params parameters
Qwen3 Coder 30B A3B Instruct API enables Repository-scale code generation / refactoring, Large codebase analysis, Multi-file transformations, Complex code-generation / writing, and Tool-calling / script / automation generation. Qwen3-Coder-30B-A3B-Instruct is a sparse Mixture-of-Experts (MoE) model with around 30.5B total parameters (3.3B active per inference), 48 layers, supporting extremely long context (native 262,144 tokens — extendable to 1M in some deployments). Standout strengths include Massive context window — handles large codebases or long instructions and Sparse-MoE architecture — efficient inference vs dense 30B models. It is a strong fit for coding copilots, repository workflows, and tool-augmented engineering assistants in production environments.
from openai import OpenAI # Initialize the OpenAI client with Qubrid base URL client = OpenAI( base_url="https://platform.qubrid.com/v1", api_key="QUBRID_API_KEY", ) stream = client.chat.completions.create( model="Qwen/Qwen3-Coder-30B-A3B-Instruct", messages=[ { "role": "user", "content": "Write a Python function to calculate fibonacci sequence" } ], max_tokens=65536, temperature=0.7, top_p=0.8, stream=True ) for chunk in stream: if chunk.choices and chunk.choices[0].delta.content: print(chunk.choices[0].delta.content, end="", flush=True) print("\n")from openai import OpenAI # Initialize the OpenAI client with Qubrid base URL client = OpenAI( base_url="https://platform.qubrid.com/v1", api_key="QUBRID_API_KEY", ) stream = client.chat.completions.create( model="Qwen/Qwen3-Coder-30B-A3B-Instruct", messages=[ { "role": "user", "content": "Write a Python function to calculate fibonacci sequence" } ], max_tokens=65536, temperature=0.7, top_p=0.8, stream=True ) for chunk in stream: if chunk.choices and chunk.choices[0].delta.content: print(chunk.choices[0].delta.content, end="", flush=True) print("\n") Enterprise
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