{"id":79,"date":"2026-08-06T10:07:25","date_gmt":"2026-08-06T10:07:25","guid":{"rendered":"https:\/\/www.graveiensai.com\/blog\/?p=79"},"modified":"2026-08-06T10:12:34","modified_gmt":"2026-08-06T10:12:34","slug":"what-is-an-llm","status":"publish","type":"post","link":"https:\/\/www.graveiensai.com\/blog\/what-is-an-llm\/","title":{"rendered":"What Is an LLM? A Complete 2026 Guide to Large Language Models"},"content":{"rendered":"\n<figure class=\"wp-block-table\"><table class=\"has-fixed-layout\"><thead><tr><th><strong>TL;DR Key take\u00adaways<\/strong><\/th><\/tr><\/thead><tbody><tr><td>1.<strong>What is an LLM?<\/strong> A deep-learn\u00ading sys\u00adtem trained to pre\u00addict the next token in a sequence using the trans\u00adformer archi\u00adtec\u00adture.<br>2. <strong>LLM vs. Gen\u00ader\u00ada\u00adtive AI<\/strong>: LLMs are a spe\u00adcif\u00adic sub\u00adset of gen\u00ader\u00ada\u00adtive AI focused on text, where\u00adas gen\u00ader\u00ada\u00adtive AI broad\u00adly cov\u00aders audio, video, images, and code.<br>3.<strong>The Best LLMs<\/strong>: High-per\u00adform\u00ading options include pro\u00adpri\u00adetary mod\u00adels like Ope\u00adnAI (GPT\u20115) and Anthrop\u00adic (Claude), as well as open-weight mod\u00adels like Lla\u00adma, DeepSeek, and Qwen.<br>4. <strong>Built on Human Data<\/strong>: Every capa\u00adble mod\u00adel relies heav\u00adi\u00adly on human data col\u00adlec\u00adtion, anno\u00adta\u00adtion, and feed\u00adback to ensure accu\u00adra\u00adcy and align\u00adment.<\/td><\/tr><\/tbody><tfoot><tr><td><\/td><\/tr><\/tfoot><\/table><\/figure>\n\n\n\n<p class=\"wp-block-paragraph\"><strong>Who this arti\u00adcle is for:&nbsp;<\/strong>founders, ML engi\u00adneers, prod\u00aduct man\u00adagers and data lead\u00aders who want a clear, accu\u00adrate def\u00adi\u00adn\u00adi\u00adtion of large lan\u00adguage mod\u00adels plus a prac\u00adti\u00adcal view of the best LLMs, LLM archi\u00adtec\u00adture and how LLMs dif\u00adfer from gen\u00ader\u00ada\u00adtive AI.<\/p>\n\n\n\n<h2 class=\"wp-block-heading\"><strong>What is an LLM?<\/strong><\/h2>\n\n\n\n<p class=\"wp-block-paragraph\"><strong>A large lan\u00adguage mod\u00adel (LLM) is a type of arti\u00adfi\u00adcial intel\u00adli\u00adgence trained on enor\u00admous amounts of text so it can under\u00adstand, sum\u00adma\u00adrize, trans\u00adlate and gen\u00ader\u00adate human lan\u00adguage.<\/strong>&nbsp;At its core, an LLM does one decep\u00adtive\u00adly sim\u00adple thing: giv\u00aden a sequence of words, it pre\u00addicts the most prob\u00ada\u00adble next unit of text. Repeat that pre\u00addic\u00adtion bil\u00adlions of times over tril\u00adlions of words, and the mod\u00adel learns gram\u00admar, facts, rea\u00adson\u00ading pat\u00adterns and style.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">The word \u201clarge\u201d is lit\u00ader\u00adal. Mod\u00adern LLMs con\u00adtain any\u00adwhere from a few bil\u00adlion to well over a tril\u00adlion para\u00adme\u00adters the inter\u00adnal weights the mod\u00adel adjusts dur\u00ading train\u00ading and are trained on datasets mea\u00adsured in tril\u00adlions of tokens drawn from books, web\u00adsites, code and licensed human data.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">If you have used Chat\u00adG\u00adPT, Claude, Gem\u00adi\u00adni or Microsoft Copi\u00adlot, you have already used an LLM. These sys\u00adtems pow\u00ader chat\u00adbots, cod\u00ading assis\u00adtants, search sum\u00admaries and enter\u00adprise&nbsp;<a href=\"https:\/\/www.graveiensai.com\/conversational-ai\">con\u00adver\u00adsa\u00adtion\u00adal AI<\/a>&nbsp;tools. The glob\u00adal LLM mar\u00adket reflects that adop\u00adtion: ana\u00adlysts esti\u00admate it at rough\u00adly&nbsp;<strong>$10\u201313 bil\u00adlion in 2026<\/strong>, with dou\u00adble-dig\u00adit annu\u00adal growth fore\u00adcast into the 2030s.<\/p>\n\n\n\n<h2 class=\"wp-block-heading\"><strong>How LLMs work: from tokens to answers<\/strong><\/h2>\n\n\n\n<p class=\"wp-block-paragraph\">Under\u00adstand\u00ading what an LLM is becomes clear\u00ader once you see the four stages behind every response.<\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li><strong>Tok\u00adeniza\u00adtion.&nbsp;Your input is bro\u00adken into tokens words or word frag\u00adments.<\/strong><\/li>\n\n\n\n<li><strong>Embed\u00adding.&nbsp;<\/strong>Each token becomes a vec\u00adtor of num\u00adbers that cap\u00adtures mean\u00ading, so \u201cking\u201d and \u201cqueen\u201d sit near each oth\u00ader math\u00ade\u00admat\u00adi\u00adcal\u00adly.<\/li>\n\n\n\n<li><strong>Atten\u00adtion &amp; pre\u00addic\u00adtion.&nbsp;<\/strong>The mod\u00adel weighs how much each token relates to every oth\u00ader token, then pre\u00addicts the next one.<\/li>\n\n\n\n<li><strong>Decod\u00ading.&nbsp;<\/strong>The mod\u00adel repeats pre\u00addic\u00adtion token by token until it pro\u00adduces a com\u00adplete answer.<\/li>\n<\/ul>\n\n\n\n<p class=\"wp-block-paragraph\">The qual\u00adi\u00adty of this pipeline depends on the train\u00ading data behind it. That is why teams invest in struc\u00adtured&nbsp;<a href=\"https:\/\/www.graveiensai.com\/data-collection\">data col\u00adlec\u00adtion<\/a>&nbsp;and rig\u00ador\u00adous&nbsp;<a href=\"https:\/\/www.graveiensai.com\/data-annotation\">data anno\u00adta\u00adtion and label\u00ading<\/a>&nbsp;before a sin\u00adgle train\u00ading run begins the mod\u00adel can only learn from the sig\u00adnal it is giv\u00aden.<\/p>\n\n\n\n<h2 class=\"wp-block-heading\"><strong>LLM architecture explained<\/strong><\/h2>\n\n\n\n<p class=\"wp-block-paragraph\">The dom\u00adi\u00adnant LLM archi\u00adtec\u00adture is the&nbsp;<strong>trans\u00adformer<\/strong>, first described by researchers at Google in the 2017 paper \u201cAtten\u00adtion Is All You Need.\u201d Near\u00adly every lead\u00ading mod\u00adel today GPT, Claude, Gem\u00adi\u00adni, Lla\u00adma is a trans\u00adformer vari\u00adant.<\/p>\n\n\n\n<h3 class=\"wp-block-heading\"><strong>Self-attention<\/strong><\/h3>\n\n\n\n<p class=\"wp-block-paragraph\">Self-atten\u00adtion lets the mod\u00adel look at an entire sequence at once and decide which words mat\u00adter most to each oth\u00ader, cap\u00adtur\u00ading long-range con\u00adtext that old\u00ader left-to-right net\u00adworks missed.<\/p>\n\n\n\n<h3 class=\"wp-block-heading\"><strong>Layers and parameters<\/strong><\/h3>\n\n\n\n<p class=\"wp-block-paragraph\">A trans\u00adformer stacks dozens or hun\u00addreds of iden\u00adti\u00adcal lay\u00aders. The para\u00adme\u00adters the tun\u00adable weights inside those lay\u00aders are what the mod\u00adel \u201clearns.\u201d More para\u00adme\u00adters mean more capac\u00adi\u00adty, though data qual\u00adi\u00adty now mat\u00adters as much as raw size.<\/p>\n\n\n\n<h3 class=\"wp-block-heading\"><strong>Mixture of Experts (MoE)<\/strong><\/h3>\n\n\n\n<p class=\"wp-block-paragraph\">Many 2026 fron\u00adtier mod\u00adels use a Mix\u00adture of Experts design, where only a frac\u00adtion of the net\u00adwork acti\u00advates per token keep\u00ading the mod\u00adel pow\u00ader\u00adful while cut\u00adting the com\u00adpute cost of each response.<\/p>\n\n\n\n<figure class=\"wp-block-table\"><table class=\"has-fixed-layout\"><tbody><tr><td><strong>Pro tip<\/strong>Archi\u00adtec\u00adture sets the ceil\u00ading on what a mod\u00adel&nbsp;<em>can<\/em>&nbsp;learn. Human feed\u00adback sets how well it&nbsp;<em>actu\u00adal\u00adly<\/em>&nbsp;behaves. The best teams treat&nbsp;<a href=\"https:\/\/www.graveiensai.com\/llm-fine\">LLM fine-tun\u00ading with RLHF and SFT<\/a>&nbsp;as a first-class part of the archi\u00adtec\u00adture con\u00adver\u00adsa\u00adtion, and val\u00adi\u00addate behav\u00adior through&nbsp;<a href=\"https:\/\/www.graveiensai.com\/llm-evaluation\">LLM eval\u00adu\u00ada\u00adtion and red-team\u00ading<\/a>.<\/td><\/tr><\/tbody><\/table><\/figure>\n\n\n\n<h2 class=\"wp-block-heading\"><strong>LLM vs generative AI: what\u2019s the difference?<\/strong><\/h2>\n\n\n\n<p class=\"wp-block-paragraph\"><strong>Gen\u00ader\u00ada\u00adtive AI<\/strong>&nbsp;is any AI sys\u00adtem that cre\u00adates new con\u00adtent text, images, audio, video or code.&nbsp;<strong>An LLM is a spe\u00adcif\u00adic kind of gen\u00ader\u00ada\u00adtive AI that spe\u00adcial\u00adizes in lan\u00adguage.<\/strong>&nbsp;Every LLM is gen\u00ader\u00ada\u00adtive AI, but not all gen\u00ader\u00ada\u00adtive AI is an LLM.<\/p>\n\n\n\n<figure class=\"wp-block-table\"><table class=\"has-fixed-layout\"><thead><tr><th class=\"has-text-align-left\" data-align=\"left\"><strong>Aspect<\/strong><\/th><th class=\"has-text-align-left\" data-align=\"left\"><strong>Large lan\u00adguage mod\u00adel (LLM)<\/strong><\/th><th class=\"has-text-align-left\" data-align=\"left\"><strong>Gen\u00ader\u00ada\u00adtive AI (broad\u00ader field)<\/strong><\/th><\/tr><\/thead><tbody><tr><td><strong>Pri\u00adma\u00adry out\u00adput<\/strong><\/td><td>Text and lan\u00adguage tasks<\/td><td>Text, images, audio, video, code<\/td><\/tr><tr><td><strong>Core archi\u00adtec\u00adture<\/strong><\/td><td>Trans\u00adformer<\/td><td>Trans\u00adform\u00aders, dif\u00adfu\u00adsion, GANs<\/td><\/tr><tr><td><strong>Exam\u00adple sys\u00adtems<\/strong><\/td><td>GPT\u20115, Claude, Gem\u00adi\u00adni, Lla\u00adma<\/td><td>LLMs plus image &amp; video gen\u00ader\u00ada\u00adtors<\/td><\/tr><tr><td><strong>Typ\u00adi\u00adcal use<\/strong><\/td><td>Chat, sum\u00adma\u00adriza\u00adtion, trans\u00adla\u00adtion<\/td><td>Con\u00adtent of any modal\u00adi\u00adty<\/td><\/tr><tr><td><strong>Rela\u00adtion\u00adship<\/strong><\/td><td>A sub\u00adset of gen\u00ader\u00ada\u00adtive AI<\/td><td>The umbrel\u00adla cat\u00ade\u00adgo\u00adry<\/td><\/tr><\/tbody><\/table><\/figure>\n\n\n\n<p class=\"wp-block-paragraph\">The line is blur\u00adring: top mod\u00adels are now&nbsp;<strong>mul\u00adti\u00admodal<\/strong>. Build\u00ading them requires&nbsp;<a href=\"https:\/\/www.graveiensai.com\/voice-speech\">voice and speech data<\/a>,&nbsp;<a href=\"https:\/\/www.graveiensai.com\/transcription\">audio tran\u00adscrip\u00adtion,<\/a>&nbsp;and&nbsp;<a href=\"https:\/\/www.graveiensai.com\/computer-vision\">com\u00adput\u00ader vision<\/a>&nbsp;anno\u00adta\u00adtion feed\u00ading the same mod\u00adel. Our overview of&nbsp;<a href=\"https:\/\/www.graveiensai.com\/generative-ai\">gen\u00ader\u00ada\u00adtive AI and LLM ser\u00advices<\/a>&nbsp;maps how these modal\u00adi\u00adties come togeth\u00ader.<\/p>\n\n\n\n<h2 class=\"wp-block-heading\"><strong>The best LLMs in 2026<\/strong><\/h2>\n\n\n\n<p class=\"wp-block-paragraph\">There is no sin\u00adgle win\u00adner the leader\u00adboard for the best LLMs shifts month\u00adly, and the right mod\u00adel depends on your task, bud\u00adget and laten\u00adcy needs. As of mid-2026 the fron\u00adtier is led by a rec\u00adog\u00adniz\u00adable short list.<\/p>\n\n\n\n<figure class=\"wp-block-table\"><table class=\"has-fixed-layout\"><thead><tr><th class=\"has-text-align-left\" data-align=\"left\"><strong>Provider<\/strong><\/th><th class=\"has-text-align-left\" data-align=\"left\"><strong>Flag\u00adship fam\u00adi\u00adly<\/strong><\/th><th class=\"has-text-align-left\" data-align=\"left\"><strong>Known strengths<\/strong><\/th><\/tr><\/thead><tbody><tr><td><strong>Ope\u00adnAI<\/strong><\/td><td>GPT\u20115 series<\/td><td>Struc\u00adtured rea\u00adson\u00ading, agen\u00adtic tool use<\/td><\/tr><tr><td><strong>Anthrop\u00adic<\/strong><\/td><td>Claude Opus \/ Son\u00adnet<\/td><td>Cod\u00ading depth, long-con\u00adtext reli\u00ada\u00adbil\u00adi\u00adty<\/td><\/tr><tr><td><strong>Google Deep\u00adMind<\/strong><\/td><td>Gem\u00adi\u00adni 3<\/td><td>Native mul\u00adti\u00admodal, sci\u00aden\u00adtif\u00adic rea\u00adson\u00ading<\/td><\/tr><tr><td><strong>xAI<\/strong><\/td><td>Grok 4<\/td><td>Rea\u00adson\u00ading on hard exam-style bench\u00admarks<\/td><\/tr><tr><td><strong>Meta<\/strong><\/td><td>Lla\u00adma<\/td><td>Most-deployed open-weight mod\u00adel in enter\u00adprise<\/td><\/tr><\/tbody><\/table><\/figure>\n\n\n\n<p class=\"wp-block-paragraph\">Mod\u00adels are com\u00adpared on bench\u00admarks such as&nbsp;<strong>SWE-bench Ver\u00adi\u00adfied<\/strong>,&nbsp;<strong>GPQA Dia\u00admond<\/strong>,&nbsp;<strong>MMLU<\/strong>&nbsp;and&nbsp;<strong>ARC-AGI<\/strong>. No mod\u00adel tops every chart, so many pro\u00adduc\u00adtion sys\u00adtems route each request to whichev\u00ader mod\u00adel best fits the task. That is where inde\u00adpen\u00addent&nbsp;<a href=\"https:\/\/www.graveiensai.com\/llm-evaluation\">LLM eval\u00adu\u00ada\u00adtion<\/a>&nbsp;earns its keep, espe\u00adcial\u00adly in reg\u00adu\u00adlat\u00aded fields like&nbsp;<a href=\"https:\/\/www.graveiensai.com\/healthcare\">health\u00adcare<\/a>&nbsp;and&nbsp;<a href=\"https:\/\/www.graveiensai.com\/banking-finance\">bank\u00ading and finance<\/a>.<\/p>\n\n\n\n<h2 class=\"wp-block-heading\"><strong>Best LLM for coding<\/strong><\/h2>\n\n\n\n<p class=\"wp-block-paragraph\">Soft\u00adware devel\u00adop\u00adment is the most pop\u00adu\u00adlar pro\u00adfes\u00adsion\u00adal use of LLMs. In 2026 the lead\u00aders are Anthropic\u2019s Claude Opus-class mod\u00adels and OpenAI\u2019s GPT\u20115 cod\u00ading vari\u00adants, with fast Gem\u00adi\u00adni tiers close behind and open-weight GLM and Qwen cod\u00ading series rival\u00ading them on SWE-bench.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\"><strong>What sep\u00ada\u00adrates a strong cod\u00ading mod\u00adel:<\/strong><\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li><strong>Agen\u00adtic abil\u00adi\u00adty<\/strong>&nbsp;plan\u00adning mul\u00adti-step edits across a whole repos\u00adi\u00adto\u00adry, not just auto\u00adcom\u00adplet\u00ading a line.<\/li>\n\n\n\n<li><strong>Long con\u00adtext<\/strong>&nbsp;hold\u00ading an entire code\u00adbase in mem\u00ado\u00adry to rea\u00adson about depen\u00adden\u00adcies.<\/li>\n\n\n\n<li><strong>Test-and-fix loops<\/strong>&nbsp;run\u00adning code, read\u00ading the error, and cor\u00adrect\u00ading itself.<\/li>\n<\/ul>\n\n\n\n<p class=\"wp-block-paragraph\">Cod\u00ading mod\u00adels are made reli\u00adable through vast amounts of human-grad\u00aded exam\u00adples. This pref\u00ader\u00adence data is exact\u00adly what our&nbsp;<a href=\"https:\/\/www.graveiensai.com\/generative-ai\">RLHF and gen\u00ader\u00ada\u00adtive AI<\/a>&nbsp;teams pro\u00adduce, backed by a&nbsp;<a href=\"https:\/\/www.graveiensai.com\/workforce\">spe\u00adcial\u00adized STEM and engi\u00adneer\u00ading work\u00adforce<\/a>&nbsp;that can judge whether a model\u2019s code is actu\u00adal\u00adly cor\u00adrect.<\/p>\n\n\n\n<h2 class=\"wp-block-heading\"><strong>Best open source LLMs<\/strong><\/h2>\n\n\n\n<p class=\"wp-block-paragraph\">Open mod\u00adels have closed most of the gap with pro\u00adpri\u00adetary sys\u00adtems. One dis\u00adtinc\u00adtion first: most \u201copen-source\u201d mod\u00adels are real\u00adly&nbsp;<strong>open-weight<\/strong>&nbsp;you get the weights, but not always the train\u00ading data or code, and the license may restrict use. The lead\u00ading open fam\u00adi\u00adlies in 2026:<\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li><strong>Meta Lla\u00adma<\/strong>&nbsp;the most wide\u00adly deployed open-weight fam\u00adi\u00adly in enter\u00adprise.<\/li>\n\n\n\n<li><strong>DeepSeek<\/strong>&nbsp;strong rea\u00adson\u00ading and math, under a per\u00admis\u00adsive MIT license.<\/li>\n\n\n\n<li><strong>Aliba\u00adba Qwen<\/strong>&nbsp;com\u00adpet\u00adi\u00adtive on rea\u00adson\u00ading and cod\u00ading, much of it Apache 2.0.<\/li>\n\n\n\n<li><strong>Zhipu GLM<\/strong>&nbsp;cod\u00ading per\u00adfor\u00admance that rivals top pro\u00adpri\u00adetary mod\u00adels.<\/li>\n\n\n\n<li><strong>Mis\u00adtral<\/strong>&nbsp;strong mul\u00adti\u00adlin\u00adgual mod\u00adels, now ship\u00adping under Apache 2.0.<\/li>\n\n\n\n<li><strong>Google Gem\u00adma<\/strong>&nbsp;opti\u00admized for on-device and edge deploy\u00adment.<\/li>\n<\/ul>\n\n\n\n<p class=\"wp-block-paragraph\">An open base mod\u00adel still needs adap\u00adta\u00adtion to your domain: task-spe\u00adcif\u00adic&nbsp;<a href=\"https:\/\/www.graveiensai.com\/llm-fine\">LLM fine-tun\u00ading<\/a>, mul\u00adti\u00adlin\u00adgual&nbsp;<a href=\"https:\/\/www.graveiensai.com\/language-services\">lan\u00adguage and local\u00adiza\u00adtion<\/a>, and&nbsp;<a href=\"https:\/\/www.graveiensai.com\/content-moderation\">con\u00adtent mod\u00ader\u00ada\u00adtion<\/a>&nbsp;data to keep out\u00adputs safe.<\/p>\n\n\n\n<h2 class=\"wp-block-heading\"><strong>How LLMs are actually built: the human-data layer<\/strong><\/h2>\n\n\n\n<p class=\"wp-block-paragraph\">An LLM\u2019s archi\u00adtec\u00adture is pub\u00adlic and its com\u00adpute is buyable but its behav\u00adior is shaped by human data that is hard to source well. Three ingre\u00addi\u00adents define a usable LLM:<\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li><strong>Pre\u00adtrain\u00ading data&nbsp;clean, diverse, well-sourced text and mul\u00adti\u00admodal data, gov\u00aderned by&nbsp;<a href=\"https:\/\/www.graveiensai.com\/data-validation\">data val\u00adi\u00adda\u00adtion<\/a>&nbsp;and&nbsp;<a href=\"https:\/\/www.graveiensai.com\/nlp\">nat\u00adur\u00adal lan\u00adguage pro\u00adcess\u00ading<\/a>&nbsp;anno\u00adta\u00adtion.<\/strong><\/li>\n\n\n\n<li><strong>Super\u00advised fine-tun\u00ading (SFT)<\/strong>&nbsp;human-writ\u00adten exam\u00adples that teach the mod\u00adel how to respond to instruc\u00adtions.<\/li>\n\n\n\n<li><strong>RLHF human<\/strong>&nbsp;raters rank\u00ading respons\u00ades so the mod\u00adel learns what \u201cgood\u201d looks like.<\/li>\n<\/ul>\n\n\n\n<figure class=\"wp-block-table\"><table class=\"has-fixed-layout\"><tbody><tr><td><strong>Build a bet\u00adter mod\u00adel with Graveiens AI<\/strong>We deliv\u00ader this lay\u00ader for AI teams: con\u00adsent-backed data col\u00adlec\u00adtion, mul\u00adti\u00admodal anno\u00adta\u00adtion, tran\u00adscrip\u00adtion, RLHF pref\u00ader\u00adence data and expert eval\u00adu\u00ada\u00adtion run through a four-stage QA work\u00adflow and cer\u00adti\u00adfied to ISO 9001:2017. See&nbsp;<a href=\"https:\/\/www.graveiensai.com\/process\">how our process works<\/a>, read&nbsp;<a href=\"https:\/\/www.graveiensai.com\/why-choose-us\">why AI teams choose Graveiens AI<\/a>, or&nbsp;<a href=\"https:\/\/www.graveiensai.com\/contact-us\">book a low-risk pilot<\/a>&nbsp;and pay only for deliv\u00ader\u00adables you approve.<\/td><\/tr><\/tbody><\/table><\/figure>\n\n\n\n<h2 class=\"wp-block-heading\"><strong>Frequently asked questions<\/strong><br><br><\/h2>\n\n\n<div id=\"rank-math-faq\" class=\"rank-math-block\">\n<div class=\"rank-math-list \">\n<div id=\"faq-question-1786008438718\" class=\"rank-math-list-item\">\n<h3 class=\"rank-math-question \"><strong>Q.&nbsp; What does LLM stand for?<\/strong><\/h3>\n<div class=\"rank-math-answer \">\n\n<p><strong>A.&nbsp; <\/strong>LLM stands for large lan\u00adguage mod\u00adel \u2014 a deep-learn\u00ading AI trained on mas\u00adsive text datasets to under\u00adstand and gen\u00ader\u00adate human lan\u00adguage by pre\u00addict\u00ading the next token in a sequence.<\/p>\n\n<\/div>\n<\/div>\n<div id=\"faq-question-1786008612623\" class=\"rank-math-list-item\">\n<h3 class=\"rank-math-question \"><strong>Q.&nbsp; What is an LLM in simple terms?<\/strong><\/h3>\n<div class=\"rank-math-answer \">\n\n<p><strong>A.&nbsp; <\/strong>An LLM is a very advanced auto\u00adcom\u00adplete. It reads your text, pre\u00addicts the most like\u00adly next words one at a time, and strings those pre\u00addic\u00adtions into coher\u00adent answers.<\/p>\n\n<\/div>\n<\/div>\n<div id=\"faq-question-1786008704332\" class=\"rank-math-list-item\">\n<h3 class=\"rank-math-question \"><strong>Q.&nbsp; Is ChatGPT an LLM?<\/strong><\/h3>\n<div class=\"rank-math-answer \">\n\n<p><strong>A.&nbsp; <\/strong>Yes. Chat\u00adG\u00adPT is a chat\u00adbot inter\u00adface pow\u00adered by OpenAI\u2019s GPT fam\u00adi\u00adly of large lan\u00adguage mod\u00adels. The LLM is the under\u00adly\u00ading mod\u00adel; Chat\u00adG\u00adPT is the prod\u00aduct that lets you talk to it.<\/p>\n\n<\/div>\n<\/div>\n<div id=\"faq-question-1786009179449\" class=\"rank-math-list-item\">\n<h3 class=\"rank-math-question \"><strong>Q.&nbsp; What is the difference between an LLM and generative AI?<\/strong><\/h3>\n<div class=\"rank-math-answer \">\n\n<p><strong>A.&nbsp; <\/strong>An LLM is a type of gen\u00ader\u00ada\u00adtive AI that spe\u00adcial\u00adizes in lan\u00adguage. Gen\u00ader\u00ada\u00adtive AI is the broad\u00ader cat\u00ade\u00adgo\u00adry that also cre\u00adates images, audio and video. Every LLM is gen\u00ader\u00ada\u00adtive AI, but not all gen\u00ader\u00ada\u00adtive AI is an LLM.<\/p>\n\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n\n\n<h2 class=\"wp-block-heading\"><strong>Conclusion<\/strong><\/h2>\n\n\n\n<p class=\"wp-block-paragraph\"><strong>So, what is an LLM?<\/strong>&nbsp;It is a large lan\u00adguage mod\u00adel a trans\u00adformer-based AI trained on mas\u00adsive human data to pre\u00addict and gen\u00ader\u00adate lan\u00adguage, and the engine behind today\u2019s most use\u00adful AI prod\u00aducts. Mod\u00adels are only as good as the human data behind them: the col\u00adlec\u00adtion, anno\u00adta\u00adtion and feed\u00adback lay\u00ader is what deter\u00admines suc\u00adcess.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\"><strong>Ready to build a bet\u00adter mod\u00adel?<\/strong><\/p>\n\n\n\n<figure class=\"wp-block-table\"><table class=\"has-fixed-layout\"><tbody><tr><td><strong>Ready to build a bet\u00adter mod\u00adel?<\/strong>Talk to the Graveiens AI team about a pilot \u2014 anno\u00adta\u00adtion, voice data, tran\u00adscrip\u00adtion or an RLHF run \u2014 and pay only for the deliv\u00ader\u00adables you approve.&nbsp; <a href=\"https:\/\/www.graveiensai.com\/contact-us\"><strong>graveiensai.com\/contact-us<\/strong><\/a><\/td><\/tr><\/tbody><\/table><\/figure>\n\n\n\n<p class=\"wp-block-paragraph\"><em>Sources: Vaswani et al., \u201cAtten\u00adtion Is All You Need\u201d (2017); Arti\u00adfi\u00adcial Analy\u00adsis and SWE-bench Ver\u00adi\u00adfied pub\u00adlic leader\u00adboards (2026); Mor\u00addor Intel\u00adli\u00adgence and Straits Research LLM mar\u00adket fore\u00adcasts (2026).<\/em><br><\/p>\n","protected":false},"excerpt":{"rendered":"<p>TL;DR Key take\u00adaways 1.What is an LLM? A deep-learn\u00ading sys\u00adtem trained to pre\u00addict the next token in a sequence using the trans\u00adformer archi\u00adtec\u00adture.2. LLM vs. Gen\u00ader\u00ada\u00adtive AI: LLMs\u2026<\/p>\n","protected":false},"author":1,"featured_media":80,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"wp_typography_post_enhancements_disabled":false,"footnotes":""},"categories":[1],"tags":[],"class_list":["post-79","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-blog"],"_links":{"self":[{"href":"https:\/\/www.graveiensai.com\/blog\/wp-json\/wp\/v2\/posts\/79","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/www.graveiensai.com\/blog\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/www.graveiensai.com\/blog\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/www.graveiensai.com\/blog\/wp-json\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/www.graveiensai.com\/blog\/wp-json\/wp\/v2\/comments?post=79"}],"version-history":[{"count":3,"href":"https:\/\/www.graveiensai.com\/blog\/wp-json\/wp\/v2\/posts\/79\/revisions"}],"predecessor-version":[{"id":83,"href":"https:\/\/www.graveiensai.com\/blog\/wp-json\/wp\/v2\/posts\/79\/revisions\/83"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/www.graveiensai.com\/blog\/wp-json\/wp\/v2\/media\/80"}],"wp:attachment":[{"href":"https:\/\/www.graveiensai.com\/blog\/wp-json\/wp\/v2\/media?parent=79"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/www.graveiensai.com\/blog\/wp-json\/wp\/v2\/categories?post=79"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/www.graveiensai.com\/blog\/wp-json\/wp\/v2\/tags?post=79"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}