# DeepSeek-V4-Flash

DeepSeek-V4-Flash is an AI model released by DeepSeek on Apr 24 2026. It has 284B parameters, a 1M context window and open weight. Tracked results include 18% on BullshitBench v2, 88.1% on GPQA Diamond and 91.6% on LiveCodeBench.

## Facts

| Field | Value |
| --- | --- |
| Model | DeepSeek-V4-Flash |
| Developer | DeepSeek |
| Release date | Friday, Apr 24 2026 |
| Licensing | Open Weight |
| Parameters | 284B |
| Context window | 1M |

## Tracked benchmark scores

| Benchmark | Score | Source | What it measures |
| --- | --- | --- | --- |
| BullshitBench v2 | 18% | [BullshitBench](https://github.com/petergpt/bullshit-benchmark) | 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. |
| LiveCodeBench | 91.6% | [BenchLM](https://benchlm.ai), retrieved 2026-07-11 | Coding problems published so recently the AI can't have seen them in training — a contamination-free test of raw programming skill. Higher is better. |
| GPQA Diamond | 88.1% | Lab | Graduate-level science questions in biology, physics, and chemistry — hard enough that subject-matter PhDs score around 65%. Higher is better. |

## About DeepSeek-V4-Flash

DeepSeek V4 Flash was introduced in the April 24, 2026 V4 preview alongside the larger V4 Pro. Flash used a mixture-of-experts design with 284 billion total parameters and about 13 billion active per token. DeepSeek positioned it as the faster, less expensive V4 option, with a one-million-token context window and thinking and non-thinking modes.

The V4 generation combined token-level compression with sparse attention to address the memory and computation costs of long contexts. Flash reached the assistant and API with downloadable weights, giving developers hosted and self-managed deployment paths. This entry records the original April preview checkpoint.

## Questions and answers

### When was DeepSeek-V4-Flash released?

DeepSeek-V4-Flash was released by DeepSeek on Friday, Apr 24 2026.

### Who made DeepSeek-V4-Flash?

DeepSeek-V4-Flash 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-V4-Flash get?

DeepSeek-V4-Flash reports 3 tracked benchmark scores — BullshitBench v2: 18%; LiveCodeBench: 91.6%; GPQA Diamond: 88.1%. Tracked scores may come from lab reports or independent benchmarks; source details accompany the benchmark data.

### What is the context window of DeepSeek-V4-Flash?

DeepSeek-V4-Flash has a context window of 1M. Providers may specify separate input and output token limits.

### How many parameters does DeepSeek-V4-Flash have?

DeepSeek-V4-Flash is reported at 284B parameters.

### Is DeepSeek-V4-Flash open source?

Partly. DeepSeek-V4-Flash 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-V4-Flash?

DeepSeek's previous tracked release was DeepSeek-V4-Pro on Apr 24 2026. It was followed by DeepSeek-V4-Flash-0731 on Jul 31 2026.


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Canonical page: https://aireleasetracker.com/model/deepseek/deepseek-v4-flash
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.