--- license: apache-2.0 base_model: ricursiveAI/Ripple-65B-Preview tags: - dflash2 - speculative-decoding - ripple --- # Ripple-65B Preview DFlash2

**Ripple-65B Preview DFlash2** is a draft model for speculative decoding with [Ripple-65B Preview](https://huggingface.co/ricursiveAI/Ripple-65B-Preview) or [Ripple-65B Preview NVFP4](https://huggingface.co/ricursiveAI/Ripple-65B-Preview-NVFP4). **This repo contains the BF16 drafter.** It requires the target model to generate text. The drafter proposes multiple tokens at once, conditioned on intermediate hidden states from Ripple. The target then verifies the proposals. A serving implementation with correct speculative rejection sampling preserves the target model's sampling distribution. ## Model DFlash2 combines parallel block drafting, dynamic convolutions, and a candidate selector. This checkpoint drafts blocks of 16 tokens, retains 32 candidates per position, and uses a rank-256 selector. Its dynamic convolutions have kernel size 4 and group size 16. The draft has four sliding-attention layers with a 4,096-token window, followed by a full-attention layer without rotary position embeddings (NoPE). The full-attention layer can attend beyond the sliding window. The checkpoint contains **4.04B parameters** (4,037,752,064), all stored in BF16. This count is derived from the tensors in `model.safetensors`; it excludes the target model's shared token embedding and output head, which are not stored in this repository.

| Property | Value | | --- | --- | | Architecture | `DFlash2DraftModel` | | Draft layers | 5 | | Hidden size | 5,120 | | Query / KV heads | 80 / 8 | | Head dimension | 128 | | MLP | SwiGLU, intermediate size 40,960 | | Attention pattern | 4 sliding-attention layers + 1 full-attention layer | | Sliding window | 4,096 tokens | | NoPE layer | Draft layer 4 (zero-based) | | RoPE theta | 10,000 on rotary-enabled layers | | Target hidden-state layers | 1, 20, 39, 58, 77 (zero-based) | | Target depth | 80 layers | | Vocabulary size | 100,352 | | Draft block size | 16 | | Dynamic convolution | Kernel size 4, group size 16 | | Candidate selector | Top-k 32, rank 256 | | Configured maximum positions | 131,072 | | Weight precision | BF16 |

## Serve Load this repository as the **speculative draft model** alongside Ripple-65B Preview. Use the target model's tokenizer, chat template, token embeddings, and output head. The serving runtime must support Ripple and `DFlash2DraftModel`, including this checkpoint's per-layer attention pattern, NoPE layer, four-tap convolutions, and target hidden-state taps. Preserve these settings from `config.json` when loading the draft. For SGLang-based serving, the draft model settings are: ```bash --speculative-algorithm DFLASH \ --speculative-draft-model-path ricursiveAI/Ripple-65B-Preview-DFlash2 \ --speculative-draft-model-quantization unquant \ --speculative-num-draft-tokens 16 ``` These flags supplement a Ripple-compatible server launch; they are not a standalone launch command. The export's recorded validation used the `ripple-sglang` runtime on eight H100 GPUs with the RL-step-500 target checkpoint. That validation does not establish compatibility or performance for other target revisions or runtime versions. ## Citation ```bibtex @misc{ricursive2026ripple65b, title={Ripple-65B: Pushing the Frontier of Local Intelligence}, author={Ricursive Intelligence}, year={2026}, } ``` ## Contact For questions and comments, please contact us at [info@ricursive.com](mailto:info@ricursive.com). To learn more, please visit our [website](https://www.ricursive.com).