Qwen3 30B A3B
qwen3-30b-a3bQwen3 is the latest generation in the Qwen large language model series, featuring both dense and Mixture-of-Experts (MoE) architectures designed to excel in reasoning, multilingual understanding, and advanced agentic tasks. A defining capability of Qwen3 is its ability to seamlessly switch between a thinking mode for complex, multi-step reasoning and a non-thinking mode for efficient, high-quality dialogue—delivering strong versatility across use cases. Compared with earlier models such as QwQ and Qwen2.5, Qwen3 demonstrates substantial performance gains in mathematics, coding, commonsense reasoning, creative writing, and interactive conversation. The Qwen3-30B-A3B variant comprises 30.5B total parameters with 3.3B activated, 48 layers, and 128 experts (with 8 activated per task). With support for up to 131K token context lengths via YaRN, it sets a new benchmark for open-source MoE models in both capability and efficiency.
- Context
- 41.0K tokens
- Endpoint
Pricing
Quick Start
Select an endpoint and copy a working example for this model.
from openai import OpenAI client = OpenAI( api_key="YOUR_API_KEY", base_url="https://api.apertis.ai/v1") response = client.chat.completions.create( model="qwen3-30b-a3b", messages=[ {"role": "user", "content": "Hello!"} ], max_tokens=1024, temperature=0.7) print(response.choices[0].message.content) # Optional: Enable context compression to reduce token usage# response = client.chat.completions.create(# model="qwen3-30b-a3b",# messages=[{"role": "user", "content": "Hello!"}],# extra_body={"compression": {"enabled": True, "model": "gpt-4.1-mini"}}# )Supported Parameters
API docsmodelmessagesmax_tokenstemperaturetop_pstreamtoolsreasoning_effortstream_optionsthinkingextra_bodyCursor IDE Model IDs
Use these namespaced identifiers in Cursor IDE to avoid conflicts with built-in models.
Compare with Other Models
See how this model compares to others from the same provider.
Qwen3.8 27B
Qwen3.8 27B is an open-weight dense vision-language model from Qwen, designed for coding, professional knowledge work, research, and multimodal interaction. It combines strong text and visual understanding with capabilities optimized for sustained, real-world agentic tasks. The model supports flexible thinking modes that can be enabled for deeper reasoning or disabled for faster execution, making it well suited for long-running agents, multimodal workflows, coding assistants, and cost-conscious self-hosted deployments.
- Context
- 262K
- Input
- $0.45/M
- Output
- $3.20/M
Qwen3.8 2.4T A95B
Qwen3.8 2.4T A95B is Qwen's open-weight sparse Mixture-of-Experts (MoE) model and the open-weight counterpart to Qwen3.8 Max. It features 2.4T total parameters with 95B activated per token, combining frontier-scale capacity with efficient sparse inference. Designed for coding, research, complex reasoning, and agentic workflows, the model is well suited for demanding long-horizon tasks and advanced autonomous systems while providing the flexibility and customization benefits of open weights.
- Context
- 262K
- Input
- $1.80/M
- Output
- $5.40/M
Qwen3.8 Max
Qwen3.8 Max is the flagship model in Alibaba's Qwen3.8 series and the general-availability successor to Qwen3.8 Max Preview. It is a multimodal reasoning model designed for complex tasks across reasoning, visual understanding, coding, and agentic workflows. As the production-ready top tier of the Qwen3.8 family, it is well suited for advanced problem solving, multimodal analysis, software engineering, and long-running tool-driven applications.
- Context
- 1M
- Input
- $2.00/M
- Output
- $6.00/M
Qwen Plus 2025-07-28 Thinking
Qwen Plus 0728 is a hybrid reasoning model built on the Qwen3 foundation, featuring a 1M-token context window and a balanced trade-off between performance, speed, and cost.
- Context
- 1M
- Input
- $0.40/M
- Output
- $4.00/M