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Feed-forward & experts · MoE

Mixture of Experts

Many feed-forward experts, but a router sends each token to only a few of them.

The single feed-forward block is replaced by many expert blocks. A router picks a small number (often 8) per token, so the model has a huge total parameter count while each token only touches a fraction of them, the active parameters.

Many designs add a shared expert that every token uses, and keep the first few layers dense. DeepSeek V3 is the template much of the 2025–2026 wave followed.

Mixture-of-Experts module compared with a standard feed-forward block. Figure from Sebastian Raschka’s explainer.

Adoption over time

Models in the atlas using MoE, per half-year of release.

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Models using MoE

  • Architecture diagram of Mistral Large 4 (1T)

    Mistral AI, released 2026-10-29. Sparse MoE decoder, 1T total, 52B active, 1M context. Attention: MLA with modified DeepSeek Sparse Attention, index reuse, and KV sharing.

  • Architecture diagram of MiniMax M3.1-Flash (428B)

    MiniMax, released 2026-10-19. Sparse MoE decoder, 428B total, 23B active, 1M context. Attention: GQA with QK-Norm and MiniMax Sparse Attention.

  • Architecture diagram of Recursive Flint (40B-A2.5B)

    Recursive, released 2026-10-18. Sparse MoE decoder, 40B total, 2.5B active, 256K context. Attention: GQA with QK-Norm, learned attention sinks, and sliding-window/global attention.

  • Architecture diagram of Reflection Beam (501B)

    Reflection, released 2026-10-16. Sparse MoE decoder, 501B total, 23B active, 1M context. Attention: Gated GQA with QK-Norm and sliding-window/global attention.

  • Architecture diagram of Muse Spark Open (816B-A42B)

    Meta, released 2026-10-15. Sparse MoE decoder, 816B total, 42B active, 1M context. Attention: Gated GQA with scaleless QK-Norm, local-only RoPE, global NoPE, and 3:1 sliding-window/global attention.

  • Architecture diagram of Nemotron 3.5 Super VL (120B-A12B)

    NVIDIA, released 2026-10-15. Hybrid MoE decoder, 120B total, 12B active, 1M context. Attention: Mostly Mamba-2 with eight GQA layers.

  • Architecture diagram of Ling 3.1 Flash (560B)

    InclusionAI, released 2026-10-13. Hybrid MoE decoder, 560B total, 25B active, 1M context. Attention: 7:1 Kimi Delta Attention and gated MLA.

  • Architecture diagram of Kolibri-1 (78B)

    Aleph Alpha, released 2026-10-03. Sparse MoE decoder, 78B total, 3.5B active, 256K context. Attention: GQA with QK-Norm and 4:1 sliding-window/global attention.

  • Architecture diagram of Naive-N0.5-Flash (309B)

    NaiveAI, released 2026-09-27. Sparse MoE decoder, 309B total, 16B active, 1M context. Attention: GQA with sliding-window attention and DeepSeek Sparse Attention.

  • Architecture diagram of Ember-1 (2.8T)

    Fireworks AI, released 2026-09-23. Hybrid MoE decoder, 2.8T total, 104B active, 1M context. Attention: 3:1 Kimi Delta Attention and Gated MLA with NoPE.

  • Architecture diagram of Xiaomi MiMo-V2.6-Flash-RL (309B)

    Xiaomi, released 2026-09-21. Sparse MoE decoder, 309B total, 15B active, 1M context. Attention: GQA with sliding-window/global attention.

  • Architecture diagram of Xiaomi MiMo-V2.6-Pro-RL (1.02T)

    Xiaomi, released 2026-09-21. Sparse MoE decoder, 1.02T total, 42B active, 1M context. Attention: GQA with 6:1 sliding-window/global attention.

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