Every AI provider prices its models differently — per token, per image, per minute of audio — and those prices change often, sometimes several times a month. If you're choosing which model to build on, comparing OpenAI, Anthropic, Google, and a dozen smaller providers by hand means digging through scattered pricing pages that go stale the moment you bookmark them. indextkn keeps a live, comparable table of what things actually cost right now. It tracks 976 models across 17 providers, updated in real time, categorized by type (text, image, video, speech, transcription, audio, embedding, rerank), with input/output cost per 1M tokens, context window size, and a confidence indicator showing how recently each price was verified. It's free to browse and offers free API access, so you can pull the same pricing data into your own cost-estimation tooling instead of scraping provider pages yourself.
| # | Tool | Best for | Price |
|---|---|---|---|
| 1 | Équipes d'ingénierie et entreprises produit voulant intégrer des agents de codage autonomes sans perdre le contrôle de leurs données, identifiants ou infrastructure. | — | |
| 2 | Développeurs et ingénieurs ML sur Mac Apple Silicon voulant exécuter localement de gros modèles de langage sans matériel cloud ni GPU dédié. | — | |
| 3 | Entreprises de secteurs réglementés (défense, secteur public, finance) ayant des exigences strictes de résidence des données et ne pouvant pas utiliser d'API tierces. | — | |
| 4 | Développeurs construisant des agents IA nécessitant un support multi-fournisseurs LLM et une intégration éditeur | — | |
| 5 | Équipes et développeurs individuels utilisant plusieurs harnais d'agents IA (Claude Code, Cursor, Gemini CLI, GitHub Copilot CLI...) | — | |
| 6 | Entreprises B2B avec un produit établi cherchant à être citées par les IA génératives (ChatGPT, Perplexity, Gemini, Claude) plutôt que par Google | — | |
| 7 | Équipes de développement et utilisateurs d'agents de codage IA qui évaluent des frameworks de spec-driven development. | — | |
| 8 | Équipes de développement standardisant des règles de code entre plusieurs agents de codage IA. | — | |
| 9 | Développeurs et équipes utilisant des agents de codage IA sur plusieurs sessions | — | |
| 10 | Développeurs d'agents IA, équipes évaluant la qualité du code généré par IA | — | |
| 11 | Agents de codage IA et développeurs construisant des outils basés sur des agents | — | |
| 12 | Développeurs intégrant des modèles fine-tunés spécialisés, créateurs de modèles cherchant à monétiser leurs fine-tunes | — |
An open-source conversational API that enables autonomous AI agents to execute coding work in isolated sandboxes with access to repositories, tools, and credentials. Self-hosted platform for agent orchestration with streaming output and multi-turn convers
A Swift-based inference engine that enables running the 125-billion parameter Qwen 3.8-Flash-Next model on Apple Silicon Macs with limited memory by streaming expert weights from storage. Achieves approximately 12 tokens/second on 48GB M-series Macs.
Self-hosted AI platform for distributed, multi-model LLM inference on Kubernetes clusters with single-command installation and air-gapped deployment support.
Open-source Rust runtime for building AI agents that can call multiple LLM providers, run tools safely, and plug into terminals, CLIs, or editors like Zed and Claude Code.
A shared home for AI coding agent sessions, prompts, and tool calls, so teams can search, share, and pick up each other's agent work across different harnesses.
Done-for-you optimization service that helps B2B companies get cited and recommended by AI systems like ChatGPT, Perplexity, Gemini, and Claude.
Open, community-maintained directory tracking spec-driven development frameworks and real-world projects to evaluate their practical effectiveness.
Define coding rules once as version-controlled Markdown, then auto-generate the config files Cursor, Claude, GitHub Copilot, and other AI coding agents expect.
A free, open-source local memory system for AI coding agents that stores project decisions and context in SQLite, so you don't have to re-explain the same project to your agent every session.
A free Python tool that catches AI-generated code hallucinations — invented packages, fabricated APIs, wrong call signatures — using deterministic analysis instead of asking another AI model to check.
A free, open-source local code-graph engine that lets AI coding agents query symbol relationships and code structure directly, instead of guessing from repeated grep-style searches.
Marketplace where developers can discover, A/B test, and deploy fine-tuned LLM adapters with one click, and where model creators can host and monetize their own fine-tunes with a 70/30 revenue split.
