# Ember-1 (2.8T)

> Fireworks' Kimi K3 derivative, post-trained for shorter reasoning traces. Architecture details follow the published Kimi K3 base model; the diagram focuses on its text backbone.

| Property | Value |
| --- | --- |
| Lab | Fireworks AI (United States) |
| Released | 2026-09-23 |
| Decoder type | Sparse hybrid |
| Family | Hybrid MoE |
| Scale | 2.8T total, 104B active (3.7% active) |
| Context window | 1,048,576 tokens |
| Attention | 3:1 Kimi Delta Attention and Gated MLA with NoPE |
| Layer mix | 69 KDA + 24 Gated MLA |
| KV cache / token (bf16) | 27 KiB (Low) |
| License | N/A |

**Key detail:** Inherits Kimi K3's eight Block Attention Residual groups and Stable LatentMoE, with one dense layer followed by 92 MoE layers.

## Architecture concepts

- [No Positional Embeddings (NoPE)](https://llm-atlas-7or.pages.dev/concepts/nope.md): Some or all layers drop explicit positional encodings and rely on the causal mask.
- [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.
- [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.
- [Hybrid Attention (Hybrid attention)](https://llm-atlas-7or.pages.dev/concepts/hybrid-attention.md): Mixes cheap linear-attention or state-space layers with a few full-attention layers.
- [Short Convolution (ShortConv)](https://llm-atlas-7or.pages.dev/concepts/shortconv.md): A tiny causal depthwise convolution (kernel ≈ 4) that mixes each channel over the last few tokens.
- [Attention Residuals (AttnRes)](https://llm-atlas-7or.pages.dev/concepts/attention-residuals.md): Learned, attention-style weights over earlier layer outputs replace the plain residual sum.
- [Latent MoE (Latent MoE)](https://llm-atlas-7or.pages.dev/concepts/latent-moe.md): Routed experts operate in a smaller latent space instead of the full hidden width.
- [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.

## Links

- Architecture diagram: https://sebastianraschka.com/llm-architecture-gallery/images/architectures/ember-1.webp
- Kimi K3 base config: https://huggingface.co/moonshotai/Kimi-K3/blob/main/config.json
- Tech report: https://fireworks.ai/blog/ember-1
- Source card (source of truth): https://sebastianraschka.com/llm-architecture-gallery/#card-ember-1
- Web page: https://llm-atlas-7or.pages.dev/models/ember-1/
- JSON: https://llm-atlas-7or.pages.dev/api/models/ember-1.json

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