Alibaba/Qwen’s flagship MoE model (2025): 235B/22B active, 128 experts, 128K context, hybrid reasoning mode, 119 languages. Open weights (Apache 2.0).
Context window
128K
tokens
Parameters
235B (22B aktywnych, MoE; 128 ekspertów)
parameters
Release date
29 April 2025
Access:DownloadAPIHostedDeployment:💻 Local☁ Cloud
Overview
Access & deployment
DownloadAPIHosted
LocalCloud
Weights: Open source
Key parameters
📏 Context: 128K
🧩 Parameters: 235B (22B aktywnych, MoE; 128 ekspertów)
✓ Tools · ✓ Fine-tuning
📥 Input: text
Platforms
Technical specification
Context window
128K
tokens
Parameters
235B (22B aktywnych, MoE; 128 ekspertów)
parameters
License
Apache 2.0
Features:✓ Tool use✓ Fine-tuning
Modalities
⬇ Input
text
⬆ Output
textcode
Capabilities and applications
Native model capabilities
Reasoning
The model's ability to reason logically and solve complex problems.
Category: reasoning
Multi-step reasoning
Carrying out multi-step chains of reasoning across long, complex tasks.
Category: reasoning
Mathematical reasoning
The model's ability to solve mathematical tasks requiring multi-step reasoning — equations, proofs, combinatorics, geometry, calculus and competition-level problems.
Category: reasoning
Coding
Generating, analysing and modifying code in many programming languages. Covers writing functions, debugging, refactoring, code review, and creating tests. Measured by benchmarks such as HumanEval and SWE-bench.
Category: coding
Agentic coding
Multi-hour, multi-step programming tasks performed autonomously by the model: cloning a repository, running tests, iterating on fixes, integrating with CLI tools. Characteristic of Codex variants (GPT-5.1-Codex-Mini, Codex-Max).
Category: coding
Agentic capability
The model's ability to autonomously plan and execute multi-step tasks by sequentially using tools, maintaining context, and adapting to intermediate results.
Category: planning
Tool use
The model's ability to call external functions, APIs and tools during a conversation: calculator, search engine, code editor, database. The model decides when and how to use a tool and interprets its result.
Category: planning
MCP support
Native support for the Model Context Protocol - the model can integrate with external MCP servers, invoke their tools, and use their data sources without a dedicated wrapper.
Category: other
Long context
Support for large context windows — tens to hundreds of thousands (or millions) of input tokens. Enables analysis of entire codebases, long documents, and many parallel conversations without losing earlier information. GPT-5.1 supports 400,000 tokens.
Category: language
Multilingual
Competence in many natural languages (from a few to over a hundred): understanding, generation, translation, and code-switching within a single conversation. Frontier models support a wide range of languages with comparable quality.
Category: language
Structured output
Producing data in structured formats such as JSON.
Category: structured_generation
Extended thinking mode
A reasoning-model variant with a larger inference budget: more thinking cycles, higher answer precision at the cost of response time. Choice between 'standard' and 'extended' thinking is left to the user (e.g. the selector in GPT-5.2 Pro).
Category: reasoning
Adaptive reasoning effort
The model decides how much 'thinking' to allocate to a given query: simple questions are answered quickly, complex problems receive more inference cycles. A GPT-5.1 feature (both Instant and Thinking) that shortens time on easy tasks and extends it for hard ones.
Category: reasoning
Language modeling
Ability to predict subsequent tokens and generate coherent natural-language text based on the preceding context.
Category: language
Application domains
Technical architecture
Core Architecture
Model Form
Training Techniques
Deployment and security
☁ Available on platforms