LLM Token Visualizer – How big is 128k token input
Does the same job
all alternatives →- BPByte-Pair Encoding tokenizer for training LLMs on large datasets2024 · github.com · ▲5
- BSByte Size Text Visualizer2024 · unli.xyz · ▲5
- TTTokenPath – token-level citations for LLM output, read from attentionJul 2026 · tokenpath.ai · ▲5
- LLLLMStack – Low-Code Platform for Building LLM Apps with LocalAI Support2023 · github.com · ▲7
- ATA text format for UI wireframes – comparing token costs across 4 formatFeb 2026 · github.com · ▲5
I've been exploring how to describe UI layouts to LLMs efficiently. The problem: When you ask an AI to generate or modify UI, how do you describe the current state? - Natural language ("header on top, form below") is ambiguous - ASCII art breaks when edited (alignment issues) - HTML is precise but verbose I ran some measurements. For a simple login form: - Natural language: 102 tokens - ASCII art: 84 tokens - HTML: 330 tokens I experimented with a grid-based text format using Excel-like cell references: grid: 4x3 A1..D1: { type: txt, value: "Login" } A2..D2: { type: input, label: "Email" }…
- ATA tool to properly observe your LLM's context windowOct 2025 · blog.nilenso.com · ▲8
More ai this month
the category →
I trained a 125M-parameter transformer to autocomplete piano performances in real time (~108 notes/sec on an iPhone 15). The idea is basically GitHub Copilot or Tabnine, except instead of prompting it with code, you prompt it by playing a few notes on a MIDI piano. The model then continues what you played, entirely on-device. The app is free if anyone wants to try it. Happy to answer questions about the model, training, Core ML, or the many things that didn't work.
AI · 17d ago · simedw.com
Astute▲585Automate your B2B brand going viral, with new media creators
AI · 18d ago · company-app.joinastute.com
Hey HN, Henry from Cactus here! We previously released Cactus Needle, a 14MB agentic LLM for tool call, device use, and structured extraction for phones, wearables, smart homes, small robots and microcontrollers. We got really great feedback here, and have now incorporated the suggestions to release Needle 2. The whole model is a single 14MB binary that runs a full session in 28MB of RAM; 45m parameters at 2bit compression. Needle hits 500 tokens/sec decode speed on a Raspberry Pi 5, sits between 400-1,500 tokens/sec on VR devices like Meta Quest 3S and Apple Vision Pro, and ranges…
AI · 27d ago · cactuscompute.com
Launched alongside, March 2025
the whole month →
Mimic Human Research & Save Findings in AI Knowledge Base
AI · 2025 · sider.ai
