Qwen3 235B-A22B is the world's most capable openly licensed AI model — 235 billion parameters, 96.2% HumanEval, Apache 2.0. Access it entirely free on LITHOVEX AI.
Qwen3 235B-A22B (MoE) is an AI model released April 2025 by Qwen, a leading organization in large language model research. Flagship Qwen3 — 235B total, 22B active. World-class reasoning, elite coding, 100+ languages. Rivals GPT-4o on most benchmarks. With 235B total (22B active via MoE) and a 128K tokens context window, Qwen3 235B-A22B (MoE) is designed to excel across a range of demanding tasks — from software engineering and mathematical problem-solving to multilingual content generation and long-document analysis.
Qwen3 235B-A22B (MoE) employs a Mixture-of-Experts (MoE) architecture with 235B total (22B active via MoE). In a MoE design, only a subset of "expert" sub-networks activates for each token during inference — Qwen3 235B-A22B (MoE) has 235B total (22B active via MoE) total parameters but uses only a fraction per token. This allows the model to store significantly more learned knowledge than a comparably-priced dense model. MoE architectures have proven effective at reaching frontier-level capability while keeping serving costs manageable — a key reason Qwen3 235B-A22B (MoE) can be offered at the scale that platforms like LITHOVEX AI make possible.
As of 2026-10-16, Qwen3 235B-A22B (MoE) by Qwen demonstrates measurable performance on standard AI evaluation benchmarks. On MMLU — which tests world knowledge across 57 academic subjects from elementary to professional level — it achieves 93.5%. For software engineering tasks, Qwen3 235B-A22B (MoE) scores 96.2% on HumanEval, which tests ability to write correct functions from docstrings. In mathematical reasoning, Qwen3 235B-A22B (MoE) records 96.6% on MATH. Across all 6 benchmarks tracked, the model shows consistent capability in its primary task domains. These scores place Qwen3 235B-A22B (MoE) — at 235B total (22B active via MoE) of parameters — in a competitive position within its model class. Note that benchmark scores reflect controlled evaluation conditions; real-world performance varies by task, prompt design, and domain specificity.
The primary strengths of Qwen3 235B-A22B (MoE) are: World's most capable open-weight model as of April 2025 — rivals GPT-4o and Claude Sonnet; 96.2% HumanEval — elite-tier Python code generation accuracy; Extended thinking mode for multi-step proofs and complex algorithm design; MoE efficiency: 235B stored knowledge at 22B inference cost per token. These make it particularly well-suited for Frontier-level coding: production systems, open-source contributions, Leetcode hard, Competition mathematics, physics, and chemistry at graduate level, Enterprise AI applications requiring highest available open-model quality, Long-form technical writing: whitepapers, research papers, documentation. Users working on complex, multi-step problems benefit most from Qwen3 235B-A22B (MoE)'s ability to maintain coherence across long inputs and produce structured, verifiable outputs.
Like all current AI systems, Qwen3 235B-A22B (MoE) has limitations: Requires 140GB+ VRAM for full FP16 serving — needs multiple A100/H100 GPUs; Thinking mode can over-explain simple queries; Slow at full FP16 on consumer hardware even with quantization. For production deployments, validating outputs against authoritative sources — especially for domain-specific or time-sensitive information — remains best practice. Qwen continues to improve Qwen3 235B-A22B (MoE) through ongoing research.
Qwen3 235B-A22B (MoE) is available on LITHOVEX AI with a free account. Unlike direct API access — which requires billing setup, API key management, and per-token charges — LITHOVEX AI provides a seamless browser interface with no setup required, making Qwen3 235B-A22B (MoE) accessible to students, researchers, developers, and early-stage teams globally.
As of 2026-10-16, Qwen3 235B-A22B (MoE) by Qwen demonstrates measurable performance on standard AI evaluation benchmarks. On MMLU — which tests world knowledge across 57 academic subjects from elementary to professional level — it achieves 93.5%. For software engineering tasks, Qwen3 235B-A22B (MoE) scores 96.2% on HumanEval, which tests ability to write correct functions from docstrings. In mathematical reasoning, Qwen3 235B-A22B (MoE) records 96.6% on MATH. Across all 6 benchmarks tracked, the model shows consistent capability in its primary task domains. These scores place Qwen3 235B-A22B (MoE) — at 235B total (22B active via MoE) of parameters — in a competitive position within its model class. Note that benchmark scores reflect controlled evaluation conditions; real-world performance varies by task, prompt design, and domain specificity.
Mixture-of-Experts: 235B total parameters / 22B active per token, hybrid think/no-think mode
The training pipeline for Qwen3 235B-A22B (MoE) involves multiple stages: large-scale pretraining on Approximately 36 trillion tokens across 119 languages — web, code, scientific papers, books, math datasets to develop broad world knowledge, followed by supervised fine-tuning on instruction-response pairs, and alignment techniques such as RLHF or DPO. Each stage refines the model's helpfulness, accuracy, and safety. Qwen's research team — based in China — has optimized Qwen3 235B-A22B (MoE) for the specific capability profile described above.
Inference efficiency: Qwen3 235B-A22B (MoE) at 235B total (22B active via MoE) is designed to deliver quality outputs at practical serving speeds. Its 128K tokens context window enables processing entire documents, multi-file codebases, and extended conversation histories — particularly valuable for contract review, technical documentation analysis, and codebase-level AI assistance.
Getting started with Qwen3 235B-A22B (MoE) on LITHOVEX AI takes under two minutes. Follow these steps:
For best results with Qwen3 235B-A22B (MoE): provide specific, context-rich prompts; include examples when generating code; specify output format when structure matters; break complex tasks into focused sub-questions. Since Qwen3 235B-A22B (MoE) supports extended reasoning, prompting it to "think step by step" or "show your reasoning" activates deeper chain-of-thought analysis for math, logic, and complex problems.
Frontier-level research and scientific reasoning
Complex multi-step software engineering at scale
State-of-the-art mathematical problem solving
High-stakes legal and medical document analysis
Multilingual research synthesis across 119 languages
Qwen (Tongyi Qianwen) is the AI model family from Alibaba Cloud, the cloud computing arm of Alibaba Group — one of the world's largest technology companies with over $100 billion in annual revenue. Alibaba invested in AI research through its DAMO Academy starting in 2017. The Qwen3 generation, released in April 2025, represents a major leap in open-model capability: models from 8B to 235B parameters, with hybrid thinking modes and 119-language support, all released under Apache 2.0 licenses for commercial use. Qwen models consistently rank at the top of the Open LLM Leaderboard and have been widely adopted across Asia, Europe, and North America for both commercial and research applications.
Funding: Alibaba Group — $100B+ annual revenue
Founded: 1999, headquartered in China.
Qwen3 235B-A22B (MoE) by Qwen competes in a field with several strong alternatives. Below is a detailed side-by-side comparison against commonly listed alternatives, using benchmark data and capability profiles in the catalog.
Both Qwen3 235B-A22B (MoE) and the models above are available free on LITHOVEX AI — test them side by side on your real tasks before committing to a subscription with any provider.
Qwen3 235B-A22B (MoE) is released under Apache 2.0, which means you can download and run it on your own hardware. Below are the quickest ways to get started.
LITHOVEX AI runs Qwen3 235B-A22B (MoE) on cloud infrastructure, so you can use it instantly in your browser without downloading anything, configuring drivers, or managing VRAM. Create a free account and start in under 60 seconds.
Qwen3 235B-A22B is the largest open-weight model available globally, used by researchers and enterprises across every major market. Its 119-language training and MoE efficiency make it practical even at frontier scale, with particular strength in Chinese-language tasks unmatched by any Western model.
Qwen3 235B-A22B (MoE) by Qwen has the following version history and notable updates:
For the complete changelog and latest release notes, visit the official Qwen model page.