# DeepSeek V4-Flash (284B)

> DeepSeek's efficient V4 preview keeps the million-token architecture while reducing the MoE scale to 284B parameters and 13B active parameters.

| Property | Value |
| --- | --- |
| Lab | DeepSeek (China) |
| Released | 2026-04-24 |
| Decoder type | Sparse MoE |
| Family | Sparse MoE |
| Scale | 284B total, 13B active (4.6% active) |
| Context window | 1,048,576 tokens |
| Attention | MLA-style CSA/HCA with mHC |
| Layer mix | 43 CSA/HCA |
| KV cache / token (bf16) | 5.4 KiB (Very low) |
| License | MIT License |

**Key detail:** Uses 256 experts, 6 routed plus 1 shared expert per token, hash-based routing, compressed attention, and the V4 MTP path.

## Architecture concepts

- [Compressed Sparse & Heavily Compressed Attention (CSA / HCA)](https://llm-atlas-7or.pages.dev/concepts/csa-hca.md): Pool groups of older tokens into fewer KV entries, compressing along the sequence axis.
- [Manifold-constrained Hyper-Connections (mHC)](https://llm-atlas-7or.pages.dev/concepts/mhc.md): Several parallel residual streams with learned, constrained mixing between them.
- [Multi-Head Latent Attention (MLA)](https://llm-atlas-7or.pages.dev/concepts/mla.md): Keys and values are compressed into a small latent vector that is cached instead of full K/V.
- [DeepSeek Sparse Attention (DSA)](https://llm-atlas-7or.pages.dev/concepts/deepseek-sparse-attention.md): A lightweight indexer scores past tokens and each query attends only to its top-k picks.
- [Mixture of Experts (MoE)](https://llm-atlas-7or.pages.dev/concepts/moe.md): Many feed-forward experts, but a router sends each token to only a few of them.
- [Multi-Token Prediction (MTP)](https://llm-atlas-7or.pages.dev/concepts/mtp.md): Extra heads learn to predict several future tokens, and can draft tokens at inference.

## Benchmark (Artificial Analysis Intelligence Index)

- AA Intelligence Index v4.3.2: total 34.3 (General 31.8, Scientific 27.6, Coding 31.2, Agents 43.5)

## Links

- Architecture diagram: https://sebastianraschka.com/llm-architecture-gallery/images/architectures/deepseek-v4-flash.webp
- View in article: https://magazine.sebastianraschka.com/p/recent-developments-in-llm-architectures#%C2%A75-csahca-mhc-and-compressed-attention-caches-deepseek-v4
- config.json: https://huggingface.co/deepseek-ai/DeepSeek-V4-Flash/blob/main/config.json
- License: https://huggingface.co/deepseek-ai/DeepSeek-V4-Flash/blob/main/LICENSE
- Tech report: https://arxiv.org/abs/2606.19348
- Source card (source of truth): https://sebastianraschka.com/llm-architecture-gallery/#card-deepseek-v4-flash
- Web page: https://llm-atlas-7or.pages.dev/models/deepseek-v4-flash/
- JSON: https://llm-atlas-7or.pages.dev/api/models/deepseek-v4-flash.json

_Data from Sebastian Raschka's LLM Architecture Gallery (https://sebastianraschka.com/llm-architecture-gallery/). Synced 2026-11-04._