NaiveAI/Naive-N0.5-Flash-FP8

text-generation model by NaiveAI

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Building Frontier AI with AI 🏠 Homepage · 📰 Technical Blog · 💻 GitHub Naive-N0.5-Flash is an open-weight 309B MoE model with 15.5B active parameters, built for coding and AI R&D. It supports a native 1M-token context window through a hybrid of Sliding-Window Attention (SWA) and lightweight DeepSeek Sparse Attention (DSA), with no full-attention layers. Naive-N0.5-Flash builds on the open-weight MiMo-V2.5 base model, which has a simple architecture with strong foundational capabilities in world knowledge and deep research. Most layers use Sliding-Window Attention (SWA), whose per-token decoding cost does not grow with context length, while a small number of global-attention layers preserve long-range information. At million-token context lengths, however, these global-attention layers account for much of the decoding overhead. Naive-N0.5-Flash replaces the global-attention layers with DeepSeek Sparse Attention (DSA). A lightweight indexer scores the full history, while the backbone computes attention only over a selected subset of tokens. Although the…

NaiveAI/Naive-N0.5-Flash-FP8 on Hugging Face A short preview, not the full document.

Read the full model card ↗ · Preview checked 2026-10-29T07:55:46.398Z

Inside the original model card — Document outline
  1. Introduction
  2. Key Features
  3. Model Architecture
  4. Hybrid SWA–DSA Attention
  5. Training Overview
  6. Evaluation Results
  7. Deployment
  8. Quick Start with Transformers
  9. License
  10. Citation
  11. Acknowledgments
  12. Contact

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Model overview

NaiveAI/Naive-N0.5-Flash-FP8 is a text-generation model repository published by NaiveAI on Hugging Face. A library was not reported.

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Model facts

Task
text-generation
Library
Not reported
Recent downloads (30 days)
559
Cumulative likes
64
Hugging Face trending score
51
Reported safetensors parameters
Not reported
Architecture
NaiveN05FlashForCausalLM
License
mit
Access
Not gated by Hugging Face
Created
2026-09-27T15:24:21.000Z
Last modified
2026-09-27T15:16:00.000Z

Compatibility and lineage

Language coverage was not reported.

Base-model lineage was not included.

Parameter count is not a RAM/VRAM requirement. Check precision, quantization, context length and runtime compatibility in the model card; no hardware or API-cost claim is inferred here.

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Source: Hugging Face Hub. Metadata observed 2026-10-20T06:42:37.394Z. Daily imports are snapshots, not real-time monitoring.

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