# DeepSeek R1-0528

DeepSeek R1-0528 is an AI model released by DeepSeek on May 28 2025. It has open weight. At release it scored 8% on BullshitBench v2.

## Facts

| Field | Value |
| --- | --- |
| Model | DeepSeek R1-0528 |
| Developer | DeepSeek |
| Release date | Wednesday, May 28 2025 |
| Licensing | Open Weight |

## Benchmark scores published at release

| Benchmark | Score | Source | What it measures |
| --- | --- | --- | --- |
| BullshitBench v2 | 8% | Lab | Given a confidently-worded but nonsensical prompt, does the AI spot that it makes no sense and push back — instead of playing along and inventing an answer? The score is how often it clearly called out the nonsense. Higher is better. |

## Questions and answers

### When was DeepSeek R1-0528 released?

DeepSeek R1-0528 was released by DeepSeek on Wednesday, May 28 2025.

### Who made DeepSeek R1-0528?

DeepSeek R1-0528 was built by DeepSeek. Chinese AI lab known for efficient, open-weight models. Gained attention for strong performance at lower cost.

### What benchmark scores did DeepSeek R1-0528 get?

DeepSeek R1-0528 reports 1 tracked benchmark score — BullshitBench v2: 8%. Scores are the figures published at release by DeepSeek.

### Is DeepSeek R1-0528 open source?

Partly. DeepSeek R1-0528 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 DeepSeek R1-0528?

DeepSeek's previous tracked release was DeepSeek V3-0324 on Mar 24 2025, 65 days earlier. It was followed by DeepSeek V3.1 on Aug 21 2025.


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Canonical page: https://aireleasetracker.com/model/deepseek/deepseek-r1-0528
Full dataset: https://aireleasetracker.com/llms-full.txt · JSON: https://aireleasetracker.com/models.json
Source: AI Release Tracker (https://aireleasetracker.com). Benchmark scores are the figures published by the releasing lab at launch.
