{"id":9974,"date":"2026-10-05T18:25:42","date_gmt":"2026-10-05T09:25:42","guid":{"rendered":"https:\/\/localmodelwatch.tsuchitsuchi.com\/model-naiveai-naive-n0-5-en\/"},"modified":"2026-10-06T01:07:43","modified_gmt":"2026-10-05T16:07:43","slug":"model-naiveai-naive-n0-5-en","status":"publish","type":"page","link":"https:\/\/localmodelwatch.tsuchitsuchi.com\/en\/model-naiveai-naive-n0-5-en\/","title":{"rendered":"Naive-N0.5 Guide: VRAM Requirements"},"content":{"rendered":"

Everything Local Model Watch has published about the Naive-N0.5<\/strong> family: 1 article(s) covering the base model and its fine-tunes, plus converted builds we tracked after publication. Memory requirements below are computed by this site from file sizes, not quoted from model cards. Part of our model family index<\/a>.<\/p>\n

At a Glance<\/h2>\n
\n\n\n\n\n\n\n\n\n
Item<\/th>\nValue<\/th>\n<\/tr>\n<\/thead>\n
Base model(s)<\/td>\nNaiveAI\/Naive-N0.5-Flash<\/a><\/td>\n<\/tr>\n
Publisher<\/td>\nNaiveAI<\/td>\n<\/tr>\n
License (model card)<\/td>\nmit<\/td>\n<\/tr>\n
Articles<\/td>\n1<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<\/div>\n

Hardware Requirements<\/h2>\n

Estimated requirements (calculated by Local Model Watch)<\/strong><\/p>\n

\n\n\n\n\n\n
Your VRAM<\/th>\nQuantization<\/th>\nFile size<\/th>\nEst. memory needed<\/th>\n<\/tr>\n<\/thead>\n
More than 690GB of VRAM (multi-GPU or CPU offload required)<\/td>\nOriginal precision<\/td>\n575.4GB<\/td>\n690.5GB<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<\/div>\n

Memory estimates add a 20% runtime overhead (KV cache, etc.) to the actual size of the distributed files. Actual usage varies with context length, batch size and inference engine. These figures are computed by this site from file sizes, not published by the model’s authors. Compare with other models in our VRAM quick reference<\/a>. What the quantization names mean: glossary<\/a>.<\/em><\/p>\n

Can You Run It Locally?<\/h2>\n

Not usable in Ollama, LM Studio and llama.cpp yet.<\/strong><\/p>\n

The publisher ships safetensors only, and llama.cpp’s registry does not list this architecture. llama.cpp would need to add support before these tools can run it. 4 converted build(s) from other uploaders exist. Today it can be run with transformers, using the memory figures in the table above.<\/p>\n

License \u2014 mit<\/code> (Commercial use allowed):<\/strong> Permits commercial use, modification and redistribution, provided the copyright notice and license text are retained.<\/p>\n

Compiled by this site’s code from the published formats, converted builds we have found, and each engine’s own model registry. “Not found” means we have not seen such a build, not that none exists. License summaries are not legal advice \u2014 check the publisher’s original terms before relying on them.<\/em><\/p>\n

Quantized and Converted Variants<\/h2>\n
\n

\u2192 Scroll horizontally to see all columns<\/p>\n\n\n\n\n\n\n
Added<\/th>\nPublisher<\/th>\nFormat<\/th>\nRepository<\/th>\nSmallest VRAM tier (build, est. memory)<\/th>\n<\/tr>\n<\/thead>\n
2026-10-05<\/td>\nNaiveAI<\/td>\nFP8<\/td>\nNaiveAI\/Naive-N0.5-Flash-FP8-Draft<\/a><\/td>\nFP8 1.5GB (fits in 4GB VRAM)<\/td>\n<\/tr>\n
2026-10-05<\/td>\nNaiveAI<\/td>\nFP8<\/td>\nNaiveAI\/Naive-N0.5-Flash-FP8<\/a><\/td>\nFP8 352.2GB (does not fit a single consumer GPU)<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<\/div>\n

File sizes of each build:<\/p>\n