# Step-5 Preview (600B)

> StepFun's 92-layer MoE pairs 512-token sliding-window attention with sparse GQA for a 1M-token context window; the figure shows the text decoder.

| Property | Value |
| --- | --- |
| Lab | StepFun (China) |
| Released | 2026-09-20 |
| Decoder type | Sparse MoE |
| Family | Sparse MoE |
| Scale | 600B total, 27B active (4.5% active) |
| Context window | 1,048,576 tokens |
| Attention | Gated GQA with QK-Norm and 3:1 sliding-window/sparse attention |
| Layer mix | 69 sliding-window + 23 sparse GQA + 3 MTP layers |
| License | N/A |

**Key detail:** Uses top-512 sparse indexing with block size 8, 352 routed experts with 8 active plus one shared expert, and MTP-3. The first three and final backbone layers use dense FFNs with intermediate size 13,824.

## Architecture concepts

- [Grouped-Query Attention (GQA)](https://llm-atlas-7or.pages.dev/concepts/gqa.md): Several query heads share one key/value head, shrinking the KV cache with little quality loss.
- [Sliding Window Attention (SWA)](https://llm-atlas-7or.pages.dev/concepts/swa.md): Some layers only attend to a local window of recent tokens instead of the whole context.
- [QK-Norm (QK-Norm)](https://llm-atlas-7or.pages.dev/concepts/qk-norm.md): RMSNorm applied to queries and keys before attention to keep logits well-behaved.
- [Gated Attention (Gated attention)](https://llm-atlas-7or.pages.dev/concepts/gated-attention.md): A learned sigmoid gate scales the attention output before it re-enters the residual stream.
- [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 v5.0: total 28.5 (Knowledge Work 40.9, Coding 20.5, Science 14.4, General 38)
- AA Intelligence Index v4.3.2: total 43.7 (General 43, Scientific 33.7, Coding 46.1, Agents 49.7)

## Links

- Architecture diagram: https://sebastianraschka.com/llm-architecture-gallery/images/architectures/step-5.webp
- config.json (mirror): https://huggingface.co/SHSLab/Step-5-Preview-BF16/blob/main/config.json
- Tech report: https://www.stepfun.com/step-5-preview
- Source card (source of truth): https://sebastianraschka.com/llm-architecture-gallery/#card-step-5-preview-600b
- Web page: https://llm-atlas-7or.pages.dev/models/step-5-preview-600b/
- JSON: https://llm-atlas-7or.pages.dev/api/models/step-5-preview-600b.json

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