NaiveAI releases Naive-N0.5-Flash, a 309B open-weight MoE model
NaiveAI has released Naive-N0.5-Flash, an open-weight Mixture-of-Experts (MoE) model with 309B total parameters and 15.5B active parameters. Designed for coding and AI research and development, the model features a native 1M-token context window achieved through a hybrid of Sliding-Window Attention (SWA) and DeepSeek Sparse Attention (DSA), eliminating the need for full-attention layers. The…
Key points
- NaiveAI released Naive-N0.5-Flash, a 309B MoE model with 15.5B active parameters under MIT license.
- The model supports a native 1M-token context window using hybrid Sliding-Window and Sparse Attention.
- API pricing is set at $0.10 per million input tokens and $0.40 per million output tokens.
The model builds on the MiMo-V2.5 base and underwent 3.25T tokens of multi-stage training to adapt to its sparse attention architecture. NaiveAI’s inference system, NaiveRT, supports FP8 mixed-precision inference on NVIDIA GPUs, delivering up to 2,000 tokens per second in Ultrafast mode. The release includes technical details on the hybrid attention stack, which uses a 128-token SWA window and DSA selecting the top 2,048 tokens for backbone attention.
Evaluations were conducted using Claude Code 2.1.207 with a 1M-token context window. The model is benchmarked against systems like GPT-5.6-Sol, Opus-5.5, and GLM-5.3 on tasks including SWE-Bench Pro, Terminal-Bench 2.1, and MLE-bench-30. NaiveAI acknowledges the contributions of the Xiaomi MiMo, DeepSeek, and SGLang teams to the development of the model and its infrastructure.
Model pages: Naive-N0.5-Flash → · Opus 5.5 →
Naive-N0.5-Flash - 309B-A15.5B
huggingface.co · 27 September 2026
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