15+ free tools for AI developers. Calculate costs, compare models, optimize tokens, generate schemas, and more for GPT-5, Claude Opus 4.8, Gemini 3, Grok 4, Llama 4, and other LLMs.
Count tokens for different LLM models and calculate estimated costs for your prompts and responses.
Calculate costs across different LLM providers and models to optimize your budget.
Calculate costs for generating embeddings and storing vectors in databases like Pinecone and Weaviate.
Calculate savings using the Batch API — a 50% discount across OpenAI, Anthropic, and Google models.
Estimate training and inference costs for fine-tuning custom LLM models.
Compare features, pricing, and capabilities of GPT-5, Claude, Gemini 3, Grok, and other LLMs side-by-side.
Calculate and visualize context window usage for different LLM models.
Compare API latency and response times across different LLM providers and models.
Check if your usage fits within API rate limits for different LLM providers and tiers.
Interactive visualization showing how generative AI works from query to response, including RAG, embeddings, and reranking.
Generate JSON Schema from example JSON for OpenAI function calling and Claude tool use.
Reduce token usage and API costs by optimizing your prompts without losing meaning.
Production-ready system prompts for common LLM use cases. Copy and customize for your needs.
Visualize how your text will be chunked with different settings like top-k and temperature.
Build and test prompt templates with variable substitution and formatting.
Shipping a feature on top of a large language model means making a string of practical decisions: which model to use, how many tokens your prompts consume, what the bill looks like at scale, whether your context fits the window, and how to keep latency low. LLM Forge brings those answers together in one place — a set of fast, free tools that work for every major provider, including OpenAI's GPT-5 family, Anthropic's Claude Opus 4.8 and Sonnet 4.6, Google's Gemini 3, xAI's Grok 4, Meta's Llama 4, and DeepSeek.
LLM pricing is charged per token, split between cheaper input tokens and more expensive output tokens. A prompt that looks short can be surprisingly expensive once you multiply it by thousands of daily requests. Use the token counter to see how much text a request really is, the pricing calculator to project monthly spend across models, and the batch API calculator to see where a 50% batch discount pays off.
The “best” model is rarely the most expensive one. A frontier model like Claude Opus 4.8 or GPT-5.5 is worth it for hard reasoning and long-horizon agents, but a fast, inexpensive model such as Gemini 3 Flash or Claude Haiku 4.5 often handles classification, extraction, and chat at a fraction of the cost and latency. The model comparison table lines up price, context window, max output, and capabilities so you can match the model to the job, and the response-time tool shows the speed trade-off.
If you're newer to this, the AI pipeline visualizer walks through exactly how a question becomes an answer — tokenization, embeddings, vector search, reranking, and generation — and explains retrieval-augmented generation (RAG) step by step. Every tool runs entirely in your browser, requires no signup, and is free to use.