Models that run on 256 GB

1161 models with published weights that fit in 256 GB — a Mac Studio with 256. Counted at four-bit quantisation, weights only, leaving the machine about a third of its memory and a gigabyte for context: room for roughly 274 billion parameters. A mixture of experts is counted in full, because it is held in full even though only a few experts compute. 1,161 in all, a hundred to a page; this is page 12 of 12.

A Mac Studio at the top of its configuration, or a serious machine. Almost everything openly published fits, including the large mixtures of experts. At this point the constraint is no longer whether the model loads but whether it generates fast enough to be worth waiting for.

• mdeberta-v3-base-squad2timpal0l0.3B≈0.2 GB at 4-bit
• multilingual-e5-baseintfloat0.3B≈0.2 GB at 4-bit
• paraphrase-multilingual-mpnet-base-v2sentence-transformers0.3B≈0.2 GB at 4-bit
• functiongemma-270m-itGoogle0.3B≈0.2 GB at 4-bit
• gemma-3-270mGoogle0.3B≈0.2 GB at 4-bit
• gemma-3-270m-itGoogle0.3B≈0.2 GB at 4-bit
• granite-docling-258MIBM Granite0.3B≈0.2 GB at 4-bit
• NeoBERTChandar Research Lab0.2B≈0.2 GB at 4-bit
• whisper-smallOpenAI0.2B≈0.2 GB at 4-bit
• Florence-2-baseMicrosoft0.2B≈0.2 GB at 4-bit
• t5-baseT5 community0.2B≈0.1 GB at 4-bit
• chatgpt_paraphraser_on_T5_baseHumarin0.2B≈0.1 GB at 4-bit
• jina-clip-v1Jina AI0.2B≈0.1 GB at 4-bit
• BiRefNetZhengPeng70.2B≈0.1 GB at 4-bit
• RMBG-2.0BRIA AI0.2B≈0.1 GB at 4-bit
• bert-base-multilingual-casedBERT community0.2B≈0.1 GB at 4-bit
• Audio8-TTS-Preview-0.1bEdge00.2B≈0.1 GB at 4-bit
• jina-embeddings-v2-base-zhJina AI0.2B≈0.1 GB at 4-bit
• gpt-neo-125mEleutherAI0.2B≈0.1 GB at 4-bit
• ModernBERT-baseAnswer.AI0.1B≈0.1 GB at 4-bit
• gte-modernbert-baseAlibaba-NLP0.1B≈0.1 GB at 4-bit
• modernbert-embed-baseNomic AI0.1B≈0.1 GB at 4-bit
• bart-basefacebook0.1B≈0.1 GB at 4-bit
• jina-embeddings-v2-base-enJina AI0.1B≈0.1 GB at 4-bit
• MagicPrompt-Stable-DiffusionGustavosta0.1B≈0.1 GB at 4-bit
• gpt2OpenAI community0.1B≈0.1 GB at 4-bit
• nomic-embed-text-v1Nomic AI0.1B≈0.1 GB at 4-bit
• distilbert-base-multilingual-caseddistilbert0.1B≈0.1 GB at 4-bit
• distiluse-base-multilingual-cased-v2sentence-transformers0.1B≈0.1 GB at 4-bit
• SmolLM2-135MHuggingFaceTB0.1B≈0.1 GB at 4-bit
• roberta-baseFacebook AI community0.1B≈0.1 GB at 4-bit
• roberta-base-squad2deepset0.1B≈0.1 GB at 4-bit
• openjourneyprompthero0.1B≈0.1 GB at 4-bit
• paraphrase-multilingual-MiniLM-L12-v2sentence-transformers0.1B≈0.1 GB at 4-bit
• bert-base-uncasedBERT community0.1B≈0.1 GB at 4-bit
• pubmedbert-base-embeddingsNeuML0.1B≈0.1 GB at 4-bit
• bert-base-casedBERT community0.1B≈0.1 GB at 4-bit
• bert-base-chineseBERT community0.1B≈0.1 GB at 4-bit
• BEN2Prama LLC0.1B≈0.1 GB at 4-bit
• wav2vec2-base-960hAI at Meta0.1B≈0.1 GB at 4-bit
• nomic-embed-vision-v1.5Nomic AI0.1B≈0.1 GB at 4-bit
• distilgpt2DistilBERT community0.1B≈0.1 GB at 4-bit
• ast-finetuned-audioset-10-10-0.4593Massachusetts Institute of Technology0.1B≈0.1 GB at 4-bit
• dinov2-basefacebook0.1B≈0.1 GB at 4-bit
• vit-base-patch16-224Google0.1B≈0.1 GB at 4-bit
• vit-base-patch16-224-in21kGoogle0.1B≈0.1 GB at 4-bit
• nsfw_image_detectionFalcons.ai0.1B≈0.1 GB at 4-bit
• Soprano-1.1-80Mekwek0.1B≈0.1 GB at 4-bit
• distilbert-base-uncasedDistilBERT community0.1B≈0.0 GB at 4-bit
• t5-smallT5 community0.1B≈0.0 GB at 4-bit
• RMBG-1.4BRIA AI0.0B≈0.0 GB at 4-bit
• detr-resnet-50AI at Meta0.0B≈0.0 GB at 4-bit
• whisper-tinyOpenAI0.0B≈0.0 GB at 4-bit
• gte-smallthenlper0.0B≈0.0 GB at 4-bit
• table-transformer-structure-recognitionMicrosoft0.0B≈0.0 GB at 4-bit
• table-transformer-detectionMicrosoft0.0B≈0.0 GB at 4-bit
• segformer_b2_clothesmattmdjaga0.0B≈0.0 GB at 4-bit
• dinov3-vits16-pretrain-lvd1689mfacebook0.0B≈0.0 GB at 4-bit
• segformer-b0-finetuned-ade-512-512NVIDIA0.0B≈0.0 GB at 4-bit
• Ornith-1.0-9BOrnith0.0B≈0.0 GB at 4-bit
• AutoGLM-Phone-9BZ.ai0.0B≈0.0 GB at 4-bit