About LLM Matrix Lab
LLM Matrix Lab is a high-performance, interactive multi-model tokenizer, 3D transformer visualizer, and convolutional neural network laboratory designed to give developers deep insight into how AI models process text, vision, and deep learning matrices.
Multi-Model BPE Engine
/ai-tokenizer →Real-time Byte-Pair Encoding (BPE) segmentation powered by WebAssembly (Tiktoken WASM) and HuggingFace tokenizers across OpenAI, Meta Llama 3, DeepSeek, Qwen, and Gemma models.
Vision Tile & Patch Grid
/image-tokenizer →Interactive canvas overlays demonstrating OpenAI Vision 512x512 tile scaling breakdown and Vision Transformer (ViT / CLIP) 16x16 spatial patch grid computations.
Acoustic Audio Codecs
/audio-tokenizer →Audio tokenization breakdown converting acoustic waveforms and spectrograms into multi-codebook residual vector quantization (RVQ) neural tokens.
Token Efficiency Assistant
/token-efficiency →Prompt optimization tool analyzing token waste, comparing structural data formats (JSON, YAML, Markdown, XML), and displaying side-by-side visual diffs.
Neural Network Visualizer
/neural-network →Deep learning workbench to construct topologies, step through backpropagation, draw custom digits on an MNIST canvas, and analyze step-by-step math formulas.
3D Transformer Engine
/llm-visualization →Interactive 3D WebGL visualizer rendering layer-by-layer token embeddings, self-attention QKV projections, feed-forward MLPs, and softmax probability distributions.
CNN Operations Visualizer
/cnn →Interactive 2D discrete convolution and spatial max pooling laboratory. Step through sliding filter kernels (Sobel, Prewitt, Laplacian), live Frobenius inner products, and spatial downsampling on MNIST digits and custom matrices.
Bibhu Pradhan
Creator & DeveloperBuilding Scalable Tech & AI Applications
LLM Matrix Lab was created by Bibhu to simplify prompt optimization, token cost estimation, vision model patch analysis, and deep learning mechanics like CNN convolution and max pooling. Designed with zero server telemetry and modern Vercel-inspired UI tokens, it aims to be the standard developer console for multi-model AI tokenization and neural network visualization.
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If you find these free AI tokenizer & neural visualization tools helpful, consider supporting hosting and continuous updates!
Have Questions, Ideas, or Found a Bug?
Reach out directly via email or submit a quick feedback form on our dedicated contact page.