Qwen3 235B
Qwen3 235B is a 235-billion-parameter mixture-of-experts text generation model from Qwen with a 262,144-token context window.
Qwen
DeepInfraLarge mixture-of-experts model for complex tasks
Qwen3 235B is a large language model developed by Qwen, the AI research team at Alibaba Cloud. It uses a mixture-of-experts (MoE) architecture with 235 billion total parameters and 22 billion active parameters per forward pass, released in July 2025 under the model identifier Qwen3-235B-A22B-Instruct-2507. The model is served through DeepInfra and supports a context window of up to 262,144 tokens, making it suitable for tasks involving long documents or extended conversations.
Qwen3 235B is designed for instruction-following tasks including reasoning, coding, summarization, and multilingual text generation. The MoE design activates only 22 billion parameters at inference time, which allows the model to handle complex tasks while keeping compute requirements lower than a dense model of equivalent total parameter count. It is well suited for developers and researchers working on applications that require long-context understanding or nuanced instruction following.
What Qwen3 235B supports
Long Context Window
Supports up to 262,144 tokens of context, enabling processing of long documents, codebases, or extended multi-turn conversations in a single pass.
Mixture-of-Experts Architecture
Uses a sparse MoE design with 235B total parameters but only 22B active per forward pass, reducing per-token compute relative to a dense model of the same size.
Instruction Following
Fine-tuned as an instruct model to follow complex, multi-step user instructions across a wide range of task types.
Code Generation
Capable of writing, explaining, and debugging code across multiple programming languages as part of its general instruction-following training.
Multilingual Text Generation
Supports text generation across multiple languages, consistent with the broader Qwen3 model family's multilingual training scope.
Reasoning Tasks
Handles multi-step reasoning problems in areas such as mathematics, logic, and analytical question answering.
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Get Started FreeBenchmark scores
Scores represent accuracy — the percentage of questions answered correctly on each test.
| Benchmark | What it tests | Score |
|---|---|---|
| MMLU-Pro | Expert knowledge across 14 academic disciplines | 76.2% |
| GPQA Diamond | PhD-level science questions (biology, physics, chemistry) | 61.3% |
| MATH-500 | Undergraduate and competition-level math problems | 90.2% |
| AIME 2024 | American math olympiad problems | 32.7% |
| LiveCodeBench | Real-world coding tasks from recent competitions | 34.3% |
| HLE | Questions that challenge frontier models across many domains | 4.7% |
| SciCode | Scientific research coding and numerical methods | 29.9% |
Common questions about Qwen3 235B
What is the context window size for Qwen3 235B?
Qwen3 235B supports a context window of 262,144 tokens, which also matches its maximum response size.
How many parameters does Qwen3 235B have?
The model has 235 billion total parameters. Due to its mixture-of-experts architecture, only 22 billion parameters are active during each forward pass.
Who developed Qwen3 235B and when was it released?
Qwen3 235B was developed by Qwen, the AI team at Alibaba Cloud, and released in July 2025.
What provider serves Qwen3 235B on MindStudio?
Qwen3 235B is served through DeepInfra on MindStudio.
Does Qwen3 235B support image or video inputs?
Based on the available metadata, Qwen3 235B is a text generation model and image or video input support is not confirmed for this version.
What is the pricing for Qwen3 235B?
Pricing information for Qwen3 235B is not published in the current metadata. Check MindStudio or DeepInfra directly for current pricing details.
What people think about Qwen3 235B
Community reception on r/LocalLLaMA has been broadly positive, with the original Qwen3 release thread accumulating nearly 2,000 upvotes and over 430 comments. Users frequently highlight the model's coding and reasoning benchmark scores, as well as the efficiency of its MoE architecture that activates only 22B parameters at inference time.
A notable discussion thread from August 2025 focused on the addition of 1M token context support for the 2507 variants, which generated significant interest among users working with long documents. Some community members also noted the distinction between the instruct and thinking variants, with discussion around which version to use for different task types.
Qwen added 1M support for Qwen3-30B-A3B-Instruct-2507 and Qwen3-235B-A22B-Instruct-2507
Qwen 3 !!!
Qwen released Qwen3-Next-80B-A3B — the FUTURE of efficient LLMs is here!
Qwen released Qwen3-235B-A22B-2507!
Qwen/Qwen3-235B-A22B-Thinking-2507
Parameters & options
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