Free AI and LLM tools
Use token counting, model pricing, prompt generation and tool-schema conversion utilities for Claude, GPT, Gemini and DeepSeek workflows.
What can you do with these tools?
AI and LLM utilities focus on repeatable development tasks rather than replacing the models themselves: estimate tokens and API cost, compare model pricing, structure system prompts and convert tool definitions across Claude, OpenAI and Gemini formats. Pricing and token results explain their date or estimation method; verify important production decisions with provider documentation.
7 related tools
- AI Token Counter & Cost Estimator — Estimate token counts locally and compare API costs across Claude, GPT, Gemini and DeepSeek models
- GPT Token Counter — Count GPT-4o/4/3.5 tokens exactly with OpenAI's official BPE (o200k/cl100k) locally and estimate cost
- LLM API Pricing Comparison — Compare input/output/cached prices, context windows and blended cost across Claude, GPT, Gemini and DeepSeek
- AI Prompt & System Prompt Generator — Structure and optimize system prompts for DeepSeek, Claude, and ChatGPT with code review, translation and content templates
- Tool & Function Schema Converter — Convert between Claude tool, OpenAI function, Gemini functionDeclaration and JSON Schema — with strict mode
- AI Image Ratio & Resolution Calculator — Calculate exact pixel resolution, aspect ratios and --ar parameters for Midjourney, Flux.1, and SDXL image generators
- AI Background Remover — One-click AI cutout in your browser — no upload
LLM tasks and result confidence
| Task or input | Tool | Decision criteria and limits |
|---|---|---|
| Token budgeting | AI Token Counter & Cost Estimator | Matching tokenizers can count; other models may be estimates |
| API cost | LLM API Pricing Comparison | Token count times model price; verify dates |
| Prompt structuring | AI Prompt & System Prompt Generator | Separate role, constraints, input and output |
| Tool migration | Tool & Function Schema Converter | Review schema fields after conversion |
Recommended workflow
- Choose model and tokenization method
- Estimate input, output and cache costs
- Reconcile with API usage and official prices
Frequently asked questions
Are token counts exact?
Some models use a matching tokenizer, while others may use estimation coefficients. The tool page explains its method; use API-reported usage for billing reconciliation.
How often is model pricing updated?
The pricing page identifies its review date and reference sources. Providers can change prices at any time, so check their official pricing pages before final budgeting.
Are prompts and text sent to an AI model?
Prompt structuring, token estimation and format conversion do not require calling an LLM API. Any feature that needs a network request explains it on its page.