{"id":1283,"date":"2026-06-23T23:20:37","date_gmt":"2026-06-23T23:20:37","guid":{"rendered":"https:\/\/convly.ai\/press\/"},"modified":"2026-06-23T23:20:37","modified_gmt":"2026-06-23T23:20:37","slug":"press","status":"publish","type":"page","link":"https:\/\/convly.ai\/fr\/press\/","title":{"rendered":"Press &amp; Media Kit"},"content":{"rendered":"<p><em>Everything a journalist, newsletter, YouTuber or partner needs to feature Convly \u2014 free tools, citable data, and brand assets. Questions? Email <a href=\"mailto:hello@convly.ai\">hello@convly.ai<\/a>.<\/em><\/p>\n<h2>What is Convly?<\/h2>\n<p>Convly is an independent reference for AI models and the hardware that runs them \u2014 a structured database of 30+ models, free interactive tools, and original cost-and-performance research. Think <strong>TechPowerUp, but for AI<\/strong>. All content is available in <strong>7 languages<\/strong> (English, Arabic, French, German, Spanish, Italian, Portuguese).<\/p>\n<h2>Free tools to feature or embed<\/h2>\n<p>Our calculators are free, require no signup, and solve real problems for a technical audience \u2014 easy wins to share:<\/p>\n<ul>\n<li>\ud83d\udda5\ufe0f <strong><a href=\"\/fr\/llm-vram-calculator\/\">Can I Run This LLM? \u2014 VRAM Calculator<\/a><\/strong> \u2014 pick any model and your GPU, and instantly see what runs locally and at which quantization.<\/li>\n<li>\ud83d\udcb0 <strong><a href=\"\/fr\/ai-api-cost-calculator\/\">AI API Cost Calculator<\/a><\/strong> \u2014 enter your monthly token usage and compare the real cost of 29 models, ranked cheapest-first.<\/li>\n<\/ul>\n<p><strong>Want to embed a calculator on your own site?<\/strong> We provide free embed snippets \u2014 just <a href=\"mailto:hello@convly.ai\">demander<\/a>.<\/p>\n<h2>Original data &amp; studies \u2014 free to cite<\/h2>\n<p>We publish original analyses built on our live pricing database. Cite any figure freely (a link back is appreciated):<\/p>\n<ul>\n<li>\ud83d\udcc8 <strong><a href=\"\/fr\/ai-price-performance-index-2026\/\">The 2026 AI Price-Performance Index<\/a><\/strong> \u2014 API model prices span <strong>114\u00d7<\/strong>, yet DeepSeek V4-Flash delivers roughly <strong>37\u00d7 more intelligence per dollar<\/strong> than Claude Opus 4.8.<\/li>\n<li>\u2696\ufe0f <strong><a href=\"\/fr\/open-vs-closed-ai-cost-gap-2026\/\">Open vs Closed AI: The Real Cost Gap<\/a><\/strong> \u2014 open-weight models are <strong>~16\u00d7 cheaper on average (39\u00d7 at the median)<\/strong>; the 5 cheapest models are all open-weight, the 5 most expensive all proprietary; full spread <strong>890\u00d7<\/strong>.<\/li>\n<\/ul>\n<p>Need a custom data cut or an exclusive angle for a story? We&#8217;re happy to run the numbers \u2014 <a href=\"mailto:hello@convly.ai\">email us<\/a>.<\/p>\n<h2>The database<\/h2>\n<p><a href=\"\/fr\/models\/\">30+ AI models<\/a> with full specifications, live API pricing, and local-hardware (VRAM) requirements \u2014 plus <a href=\"\/fr\/category\/ai-comparisons\/\">data-driven head-to-head comparisons<\/a> for the models people actually compare.<\/p>\n<h2>Who reads Convly<\/h2>\n<p>AI developers and engineers, local-LLM and self-hosting enthusiasts, and hardware buyers evaluating GPUs for AI workloads \u2014 a high-intent, technical, international audience.<\/p>\n<h2>Work with us<\/h2>\n<p>Featuring a tool, citing a study, requesting data, or exploring a partnership \u2014 reach us at <strong><a href=\"mailto:hello@convly.ai\">hello@convly.ai<\/a><\/strong>. Brand assets and custom data available on request.<\/p>","protected":false},"excerpt":{"rendered":"<p>Everything a journalist, newsletter, YouTuber or partner needs to feature Convly \u2014 free tools, citable data, and brand assets. Questions? [&hellip;]<\/p>\n","protected":false},"author":0,"featured_media":0,"parent":0,"menu_order":0,"comment_status":"closed","ping_status":"closed","template":"","meta":{"site-sidebar-layout":"default","site-content-layout":"","ast-site-content-layout":"default","site-content-style":"default","site-sidebar-style":"default","ast-global-header-display":"","ast-banner-title-visibility":"","ast-main-header-display":"","ast-hfb-above-header-display":"","ast-hfb-below-header-display":"","ast-hfb-mobile-header-display":"","site-post-title":"","ast-breadcrumbs-content":"","ast-featured-img":"","footer-sml-layout":"","ast-disable-related-posts":"","theme-transparent-header-meta":"","adv-header-id-meta":"","stick-header-meta":"","header-above-stick-meta":"","header-main-stick-meta":"","header-below-stick-meta":"","astra-migrate-meta-layouts":"default","ast-page-background-enabled":"default","ast-page-background-meta":{"desktop":{"background-color":"var(--ast-global-color-5)","background-image":"","background-repeat":"repeat","background-position":"center center","background-size":"auto","background-attachment":"scroll","background-type":"","background-media":"","overlay-type":"","overlay-color":"","overlay-opacity":"","overlay-gradient":""},"tablet":{"background-color":"","background-image":"","background-repeat":"repeat","background-position":"center center","background-size":"auto","background-attachment":"scroll","background-type":"","background-media":"","overlay-type":"","overlay-color":"","overlay-opacity":"","overlay-gradient":""},"mobile":{"background-color":"","background-image":"","background-repeat":"repeat","background-position":"center center","background-size":"auto","background-attachment":"scroll","background-type":"","background-media":"","overlay-type":"","overlay-color":"","overlay-opacity":"","overlay-gradient":""}},"ast-content-background-meta":{"desktop":{"background-color":"var(--ast-global-color-4)","background-image":"","background-repeat":"repeat","background-position":"center center","background-size":"auto","background-attachment":"scroll","background-type":"","background-media":"","overlay-type":"","overlay-color":"","overlay-opacity":"","overlay-gradient":""},"tablet":{"background-color":"var(--ast-global-color-4)","background-image":"","background-repeat":"repeat","background-position":"center center","background-size":"auto","background-attachment":"scroll","background-type":"","background-media":"","overlay-type":"","overlay-color":"","overlay-opacity":"","overlay-gradient":""},"mobile":{"background-color":"var(--ast-global-color-4)","background-image":"","background-repeat":"repeat","background-position":"center center","background-size":"auto","background-attachment":"scroll","background-type":"","background-media":"","overlay-type":"","overlay-color":"","overlay-opacity":"","overlay-gradient":""}},"footnotes":""},"class_list":["post-1283","page","type-page","status-publish","hentry"],"_links":{"self":[{"href":"https:\/\/convly.ai\/fr\/wp-json\/wp\/v2\/pages\/1283","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/convly.ai\/fr\/wp-json\/wp\/v2\/pages"}],"about":[{"href":"https:\/\/convly.ai\/fr\/wp-json\/wp\/v2\/types\/page"}],"replies":[{"embeddable":true,"href":"https:\/\/convly.ai\/fr\/wp-json\/wp\/v2\/comments?post=1283"}],"version-history":[{"count":0,"href":"https:\/\/convly.ai\/fr\/wp-json\/wp\/v2\/pages\/1283\/revisions"}],"wp:attachment":[{"href":"https:\/\/convly.ai\/fr\/wp-json\/wp\/v2\/media?parent=1283"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}