# Qwen-72B

Qwen-72B is an AI model released by Qwen on Nov 30 2023. It has 72B parameters, a 32k context window and open weight.

## Facts

| Field | Value |
| --- | --- |
| Model | Qwen-72B |
| Developer | Qwen |
| Release date | Thursday, Nov 30 2023 |
| Licensing | Open Weight |
| Parameters | 72B |
| Context window | 32k |

## About Qwen-72B

Qwen-72B was released in November 2023 alongside Qwen-1.8B, expanding the original Qwen family. Alibaba supplied base and chat checkpoints for developers choosing a larger language model for self-hosted applications.

The model documentation described three trillion pretraining tokens and a 32,000-token context window. Its custom license differed from standard permissive software licenses. The original Qwen-72B also preceded Qwen1.5-72B and Qwen2-72B, which were separate releases despite sharing a parameter count.

## Questions and answers

### When was Qwen-72B released?

Qwen-72B was released by Qwen on Thursday, Nov 30 2023.

### Who made Qwen-72B?

Qwen-72B was built by Qwen. Alibaba's AI lab, building the Qwen family. The most prolific publisher of open-weight models of any major lab, alongside a closed Max and Plus tier sold through Alibaba Cloud.

### What is the context window of Qwen-72B?

Qwen-72B has a context window of 32k. Providers may specify separate input and output token limits.

### How many parameters does Qwen-72B have?

Qwen-72B is reported at 72B parameters.

### Is Qwen-72B open source?

Partly. Qwen-72B is an open-weight model: the trained weights are free to download and run locally or on your own infrastructure, but the training data and code are not fully released and the license may restrict some commercial uses. It is not open source in the strict sense.

### What came before and after Qwen-72B?

Qwen's previous tracked release was Qwen-7B on Aug 3 2023, 119 days earlier. It was followed by Qwen1.5 on Feb 4 2024.


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Canonical page: https://aireleasetracker.com/model/qwen/qwen-72b
Site index: https://aireleasetracker.com/llms.txt
Source: AI Release Tracker (https://aireleasetracker.com). Most benchmark scores come from lab launch material; gathered results identify the leaderboard that published them.