--- title: Qwen3.5 35B A3b — Fast Multimodal LLM | ModelsLab description: Access Qwen3.5 35B A3b API for 35B MoE model with 3B active params, 262k context, and vision-language reasoning. Try high-throughput inference now. url: https://modelslab.com/qwen35-35b-a3b canonical: https://modelslab.com/qwen35-35b-a3b type: website component: Seo/ModelPage generated_at: 2026-07-01T04:03:05.480316Z --- Available now on ModelsLab · Language Model Qwen3.5 35B A3b 35B Power, 3B Speed --- [Try Qwen3.5 35B A3b](/models/together_ai/Qwen-Qwen3.5-35B-A3B) [API Documentation](https://docs.modelslab.com) Run Qwen3.5 35B A3b --- MoE Efficiency ### 3B Active Parameters Activates 3B of 35B params per token for 5x faster throughput than dense models. Multimodal Native ### Vision-Language Unified Handles text, images, reasoning with 262k context, extensible to 1M tokens. Benchmark Leader ### Top MMLU-Pro Scores Hits 85.3% MMLU-Pro, 84.2% GPQA, strong in coding and agent tasks. Examples See what Qwen3.5 35B A3b can create --- Copy any prompt below and try it yourself in the [playground](/models/together_ai/Qwen-Qwen3.5-35B-A3B). Code Review “Review this Python function for efficiency and suggest optimizations: def fibonacci(n): if n <= 1: return n else: return fibonacci(n-1) + fibonacci(n-2)” Math Proof “Prove that the sum of the first n natural numbers is n(n+1)/2 using mathematical induction.” JSON Parser “Write a JavaScript function to safely parse JSON from user input and handle errors gracefully.” Algorithm Explain “Explain quicksort algorithm step-by-step with a small example array \[5, 2, 9, 1, 5, 6\].” For Developers A few lines of code. Qwen3.5 35B A3b. One call. --- ModelsLab handles the infrastructure: fast inference, auto-scaling, and a developer-friendly API. No GPU management needed. - **Serverless:** scales to zero, scales to millions - **Pay per token,** no minimums - **Python and JavaScript SDKs,** plus REST API [API Documentation ](https://docs.modelslab.com) PythonJavaScriptcURL Copy ```

import requests

response = requests.post(
    "https://modelslab.com/api/v7/llm/chat/completions",
    json={
  "key": "YOUR_API_KEY",
  "prompt": "",
  "model_id": ""
}
)
print(response.json())

``` FAQ Common questions about Qwen3.5 35B A3b --- [Read the docs ](https://docs.modelslab.com) ### What is Qwen3.5 35B A3b API? Qwen3.5 35B A3b API provides access to Alibaba's 35B MoE LLM with 3B active parameters. Supports multimodal inputs and 262k context. Ideal for fast reasoning and tool use. ### How fast is qwen3 5 35b a3b model? Achieves 60-100+ tokens/second on RTX 4090 due to MoE routing. Outpaces dense 27B models by 5x in throughput. Suited for real-time agents. ### Qwen3.5 35B A3b alternative to what? Serves as efficient alternative to dense 70B models with similar knowledge but lower compute. Matches Qwen3-VL in vision tasks. Open weights under Apache 2.0. ### What context length for qwen3.5 35b a3b api? Native 262,144 tokens input, up to 65k output. Extensible to 1M with config. Stable for long agent workflows. ### Qwen3.5 35B A3b LLM benchmarks? Scores 85.3% MMLU-Pro, 84.2% GPQA Diamond, 69.2% SWE-bench. Strong in coding, math, multilingual tasks across 201 languages. ### Qwen3.5 35b a3b model architecture? Uses Gated Delta Networks with 256 MoE experts, 40 layers, GQA attention. Trained on 36T tokens. Multimodal from early fusion. Ready to create? --- Start generating with Qwen3.5 35B A3b on ModelsLab. [Try Qwen3.5 35B A3b](/models/together_ai/Qwen-Qwen3.5-35B-A3B) [API Documentation](https://docs.modelslab.com) --- *This markdown version is optimized for AI agents and LLMs.* **Links:** - [Website](https://modelslab.com) - [API Documentation](https://docs.modelslab.com) - [Blog](https://modelslab.com/blog) --- *Generated by ModelsLab - 2026-07-01*