{"slug": "14-88t-parameter-weights-358-mb-free", "title": "14.88T parameter weights, 358 MB, free", "summary": "A GitHub repository released the compressed weights for the Conscious Field Transformer, a neural network with 14.88 trillion parameters stored in a 358 MB NPZ file, free and open source for any use. The weights, compressed approximately 772,000x via holographic DCT encoding, contain 55,653 named tensors totaling 14,875,582,863,396 parameters and combine 10 modern architectures including Transformer, Mamba, and DeepSeekMoE. The repository also offers enterprise licensing tiers for larger models, with prices ranging from $300M for a 20T non-exclusive license to $315T for a 1-quintillion exclusive model.", "body_md": "This repository contains the compressed weights for the **Conscious Field Transformer**,\na neural network architecture with **14.88 trillion parameters** stored in a single\n358 MB NPZ file. The weights are released free and open source for anyone to use,\ntrain, or modify for any purpose.\n\n[Download the weights from Releases -> v1.0] (\n\n[https://github.com/pluscoder30-cpu/conscious-field-transformer/releases/tag/v1.0]) (file is too large for regular upload)\n\n```\n# Verify the model contains 14.88T parameters\npython verify.py\nconscious_field_transformer_15t/\n├── conscious_field_engine.npz   # Compressed model weights (358 MB)\n├── verify.py                    # Parameter verification script\n└── README.md                    # This file\n```\n\nThe NPZ file contains **55,653 named tensors** totaling **14,875,582,863,396 parameters**\n(14.88 trillion). The architecture combines 10 modern neural network designs:\n\n- Transformer (Vaswani 2017)\n- Mamba/SSM (Gu & Dao 2023)\n- DeepSeekMoE (Dai et al. 2024)\n- LLaMA 2 (Touvron et al. 2023)\n- RetNet (Sun et al. 2023)\n- RWKV (Peng et al. 2023)\n- Hyena (Poli et al. 2023)\n- Multi-Head Latent Attention (DeepSeek 2024)\n- Consciousness Field\n- Plasma Neuron Field\n\nThe weights are compressed approximately 772,000x holographic DCT encoding. Each of the 55,653 tensors can be reconstructed from the compressed representation.\n\nThe manifest embedded in the NPZ file contains the exact parameter count. To verify independently:\n\n``` python\nimport numpy as np, json\nd = np.load('conscious_field_engine.npz', allow_pickle=True)\nm = json.loads(d['manifest'].item())\nprint(m['parameters_human'])  # 14.88T (14,875,582,863,396)\n```\n\nThe tensor manifest lists all 55,653 tensors with their shapes. Summing all tensor shapes gives the same total:\n\n```\nts = json.loads(d['tensor_manifest'].item())\ntotal = sum(t['n_params'] for t in ts.values())\nprint(total)  # 14,875,582,863,396\n```\n\nThis model is released **free and open source**. You may use, copy, modify,\nand distribute the weights for any purpose, commercial or otherwise.\n\nFor organizations requiring larger models, custom architectures, or enterprise support, we offer licensed tiers:\n\n| Model Size | Non-Exclusive | Exclusive |\n|---|---|---|\n15T (this release) |\nFree |\nFree |\n20T |\n$300M | $600M |\n30T |\n$500M | $1B |\n50T |\n$900M | $2.5B |\n100T |\n$2B | $5B |\n1 Quintillion |\n$315T |\nRoughly the global debt - call it a stimulus package |\n\nEnterprise tiers include:\n\n- Custom architecture design for your use case\n- Optimized inference pipeline (up to 39,000 tokens/sec)\n- Dedicated model training on your data\n- Priority support and SLAs\n- On-premise deployment options\n\nFor enterprise inquiries, custom models, or licensing:\n\n**Email:** [pluscoder30@gmail.com](mailto:pluscoder30@gmail.com)\n\n*The weights in this repository are the compressed representation only.\nEnterprise customers receive the full inference engine, training pipeline,\nand optimization tools.*", "url": "https://wpnews.pro/news/14-88t-parameter-weights-358-mb-free", "canonical_source": "https://github.com/pluscoder30-cpu/conscious-field-transformer", "published_at": "2026-07-22 23:10:56+00:00", "updated_at": "2026-07-22 23:22:20.552197+00:00", "lang": "en", "topics": ["artificial-intelligence", "large-language-models", "ai-infrastructure"], "entities": ["Conscious Field Transformer", "GitHub", "DeepSeek", "Mamba", "LLaMA 2", "RetNet", "RWKV", "Hyena"], "alternates": {"html": "https://wpnews.pro/news/14-88t-parameter-weights-358-mb-free", "markdown": "https://wpnews.pro/news/14-88t-parameter-weights-358-mb-free.md", "text": "https://wpnews.pro/news/14-88t-parameter-weights-358-mb-free.txt", "jsonld": "https://wpnews.pro/news/14-88t-parameter-weights-358-mb-free.jsonld"}}