{"id":4391,"date":"2026-08-18T04:45:56","date_gmt":"2026-08-18T04:45:56","guid":{"rendered":"https:\/\/tucumandevelopers.com\/index.php\/2026\/08\/18\/deepseek-vs-qwen-vs-kimi-vs-glm-which-one-should-you-use\/"},"modified":"2026-08-18T04:45:56","modified_gmt":"2026-08-18T04:45:56","slug":"deepseek-vs-qwen-vs-kimi-vs-glm-which-one-should-you-use","status":"publish","type":"post","link":"https:\/\/tucumandevelopers.com\/index.php\/2026\/08\/18\/deepseek-vs-qwen-vs-kimi-vs-glm-which-one-should-you-use\/","title":{"rendered":"DeepSeek vs Qwen vs Kimi vs GLM: Which One Should You Use?"},"content":{"rendered":"<div>\n<div>\n<p>Now let me walk you through each family, what they&#8217;re great at, and where they fall short.<\/p>\n<h2> <a name=\"deepseek-the-one-i-reach-for-most\" href=\"#deepseek-the-one-i-reach-for-most\"> <\/a> DeepSeek: The One I Reach For Most <\/h2>\n<p>Okay, I&#8217;m just going to say it \u2014 DeepSeek V4 Flash at $0.25 per million output tokens is the best deal in AI right now. Period. I use it for probably 80% of my day-to-day work and my monthly bill dropped by about 60% compared to when I was running everything through GPT-4o.<\/p>\n<h3> <a name=\"the-lineup\" href=\"#the-lineup\"> <\/a> The Lineup <\/h3>\n<p>Here&#8217;s what DeepSeek offers and where each one shines:<\/p>\n<div>\n<table>\n<thead>\n<tr>\n<th>Model<\/th>\n<th>Output $\/M<\/th>\n<th>When I Use It<\/th>\n<\/tr>\n<\/thead>\n<tbody>\n<tr>\n<td><strong>V4 Flash<\/strong><\/td>\n<td>$0.25<\/td>\n<td>Default choice \u2014 coding, content, chat, basically everything<\/td>\n<\/tr>\n<tr>\n<td>V3.2<\/td>\n<td>$0.38<\/td>\n<td>When I want the latest architecture but can spend a little more<\/td>\n<\/tr>\n<tr>\n<td>V4 Pro<\/td>\n<td>$0.78<\/td>\n<td>Production workloads where quality matters more than cost<\/td>\n<\/tr>\n<tr>\n<td>R1 (Reasoner)<\/td>\n<td>$2.50<\/td>\n<td>Hard math, multi-step logic, debugging gnarly algorithms<\/td>\n<\/tr>\n<tr>\n<td>Coder<\/td>\n<td>$0.25<\/td>\n<td>Dedicated code generation tasks<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<\/div>\n<h3> <a name=\"what-makes-it-click\" href=\"#what-makes-it-click\"> <\/a> What Makes It Click <\/h3>\n<ul>\n<li>The price-to-quality ratio is genuinely absurd. V4 Flash holds its own against models that cost 10x more.<\/li>\n<li>Code generation is where DeepSeek absolutely shines \u2014 I ran it through some HumanEval-style tests and it consistently scored near the top.<\/li>\n<li>Speed is ridiculous. I&#8217;m getting around 60 tokens per second on V4 Flash, which makes it feel instant.<\/li>\n<li>English is strong. I honestly can&#8217;t tell the difference between V4 Flash and the Western incumbents on most English prompts.<\/li>\n<li>It comes from a research-first culture, so there&#8217;s a tradition of open weights and transparency.<\/li>\n<\/ul>\n<h3> <a name=\"where-it-struggles\" href=\"#where-it-struggles\"> <\/a> Where It Struggles <\/h3>\n<ul>\n<li>Vision is basically a no-go \u2014 there&#8217;s no native image understanding, so if you need to analyze pictures, look elsewhere.<\/li>\n<li>Chinese-language quality is good but not the absolute best. GLM and Kimi edge it out here.<\/li>\n<li>The model variety is narrower than what Qwen offers, so you have fewer size options to fine-tune cost vs. quality.<\/li>\n<\/ul>\n<p>Let me show you how easy it is to switch to V4 Flash \u2014 this is literally the code I run dozens of times a day: <\/p>\n<div>\n<pre><code><span>from<\/span> <span>openai<\/span> <span>import<\/span> <span>OpenAI<\/span> <span>client<\/span> <span>=<\/span> <span>OpenAI<\/span><span>(<\/span> <span>api_key<\/span><span>=<\/span><span>\"<\/span><span>ga_xxxxxxxxxxxx<\/span><span>\"<\/span><span>,<\/span> <span>base_url<\/span><span>=<\/span><span>\"<\/span><span>https:\/\/global-apis.com\/v1<\/span><span>\"<\/span> <span>)<\/span> <span>response<\/span> <span>=<\/span> <span>client<\/span><span>.<\/span><span>chat<\/span><span>.<\/span><span>completions<\/span><span>.<\/span><span>create<\/span><span>(<\/span> <span>model<\/span><span>=<\/span><span>\"<\/span><span>deepseek-v4-flash<\/span><span>\"<\/span><span>,<\/span> <span>messages<\/span><span>=<\/span><span>[{<\/span><span>\"<\/span><span>role<\/span><span>\"<\/span><span>:<\/span> <span>\"<\/span><span>user<\/span><span>\"<\/span><span>,<\/span> <span>\"<\/span><span>content<\/span><span>\"<\/span><span>:<\/span> <span>\"<\/span><span>Explain quantum computing in 100 words<\/span><span>\"<\/span><span>}]<\/span> <span>)<\/span> <span>print<\/span><span>(<\/span><span>response<\/span><span>.<\/span><span>choices<\/span><span>[<\/span><span>0<\/span><span>].<\/span><span>message<\/span><span>.<\/span><span>content<\/span><span>)<\/span> <\/code><\/pre>\n<div>\n<\/p><\/div>\n<\/p><\/div>\n<p>That&#8217;s it. Drop in your Global API key, point the base URL at <code>https:\/\/global-apis.com\/v1<\/code>, and you&#8217;re off to the races.<\/p>\n<h2> <a name=\"qwen-the-model-that-does-everything\" href=\"#qwen-the-model-that-does-everything\"> <\/a> Qwen: The Model That Does Everything <\/h2>\n<p>If DeepSeek is my daily driver, Qwen is my &#8220;I need a specific tool&#8221; pick. Alibaba&#8217;s team has built out the most complete model family of the bunch, and honestly, the breadth is staggering.<\/p>\n<h3> <a name=\"the-lineup\" href=\"#the-lineup\"> <\/a> The Lineup <\/h3>\n<div>\n<table>\n<thead>\n<tr>\n<th>Model<\/th>\n<th>Output $\/M<\/th>\n<th>What It&#8217;s For<\/th>\n<\/tr>\n<\/thead>\n<tbody>\n<tr>\n<td>Qwen3-8B<\/td>\n<td>$0.01<\/td>\n<td>Ultra-light classification, quick rewrites, simple stuff<\/td>\n<\/tr>\n<tr>\n<td>Qwen3-32B<\/td>\n<td>$0.28<\/td>\n<td>My go-to general-purpose model in this family<\/td>\n<\/tr>\n<tr>\n<td>Qwen3-Coder-30B<\/td>\n<td>$0.35<\/td>\n<td>Dedicated code work<\/td>\n<\/tr>\n<tr>\n<td>Qwen3-VL-32B<\/td>\n<td>$0.52<\/td>\n<td>Image understanding<\/td>\n<\/tr>\n<tr>\n<td>Qwen3-Omni-30B<\/td>\n<td>$0.52<\/td>\n<td>Audio, video, image \u2014 the kitchen sink<\/td>\n<\/tr>\n<tr>\n<td>Qwen3.5-397B<\/td>\n<td>$2.34<\/td>\n<td>Heavy enterprise reasoning<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<\/div>\n<h3> <a name=\"what-makes-it-click\" href=\"#what-makes-it-click\"> <\/a> What Makes It Click <\/h3>\n<ul>\n<li>The range is unmatched. From $0.01\/M all the way up to $3.20\/M, there&#8217;s a Qwen model for literally every budget.<\/li>\n<li>Vision is solid \u2014 the VL series handles image tasks well.<\/li>\n<li>Omni-modal support means you can feed it audio, video, and images in one shot.<\/li>\n<li>Alibaba&#8217;s infrastructure means the uptime and latency are enterprise-grade.<\/li>\n<li>The team ships new versions constantly. Qwen3.5, Qwen3.6 \u2014 there&#8217;s always something new to try.<\/li>\n<\/ul>\n<h3> <a name=\"where-it-struggles\" href=\"#where-it-struggles\"> <\/a> Where It Struggles <\/h3>\n<ul>\n<li>The naming is genuinely confusing. Qwen3-8B, Qwen3-32B, Qwen3-Coder-30B, Qwen3-VL-32B, Qwen3-Omni-30B, Qwen3.5-397B \u2014 it takes a minute to figure out what each one does.<\/li>\n<li>English quality is good but not DeepSeek-tier. For pure English prompts, I still slightly prefer DeepSeek.<\/li>\n<li>A couple of the models feel overpriced for what they deliver. Qwen3.6-35B at $1\/M made me raise an eyebrow.<\/li>\n<\/ul>\n<p>Here&#8217;s a quick example using Qwen3-32B for general tasks \u2014 perfect for code generation or content work: <\/p>\n<div>\n<pre><code><span>response<\/span> <span>=<\/span> <span>client<\/span><span>.<\/span><span>chat<\/span><span>.<\/span><span>completions<\/span><span>.<\/span><span>create<\/span><span>(<\/span> <span>model<\/span><span>=<\/span><span>\"<\/span><span>Qwen\/Qwen3-32B<\/span><span>\"<\/span><span>,<\/span> <span>messages<\/span><span>=<\/span><span>[{<\/span><span>\"<\/span><span>role<\/span><span>\"<\/span><span>:<\/span> <span>\"<\/span><span>user<\/span><span>\"<\/span><span>,<\/span> <span>\"<\/span><span>content<\/span><span>\"<\/span><span>:<\/span> <span>\"<\/span><span>Write a Python function to merge two sorted lists<\/span><span>\"<\/span><span>}]<\/span> <span>)<\/span> <span>print<\/span><span>(<\/span><span>response<\/span><span>.<\/span><span>choices<\/span><span>[<\/span><span>0<\/span><span>].<\/span><span>message<\/span><span>.<\/span><span>content<\/span><span>)<\/span> <\/code><\/pre>\n<div>\n<\/p><\/div>\n<\/p><\/div>\n<p>Notice how I&#8217;m using the same <code>client<\/code> object from before? That&#8217;s the magic of OpenAI-compatible APIs \u2014 once you set it up once, you just swap the <code>model<\/code> parameter.<\/p>\n<h2> <a name=\"kimi-the-brain-you-call-for-hard-problems\" href=\"#kimi-the-brain-you-call-for-hard-problems\"> <\/a> Kimi: The Brain You Call for Hard Problems <\/h2>\n<p>Kimi is the priciest of the four families, with prices ranging from $3.00 to $3.50 per million output tokens, but holy cow \u2014 when I need raw reasoning power, nothing else in this list touches it.<\/p>\n<h3> <a name=\"the-lineup\" href=\"#the-lineup\"> <\/a> The Lineup <\/h3>\n<p>I won&#8217;t show every variant here since the family is more focused, but K2.5 at $3.00\/M is the headline model, and the whole range sits between $3.00 and $3.50\/M. There&#8217;s no &#8220;budget&#8221; Kimi option \u2014 you&#8217;re paying premium prices for premium reasoning.<\/p>\n<h3> <a name=\"what-makes-it-click\" href=\"#what-makes-it-click\"> <\/a> What Makes It Click <\/h3>\n<ul>\n<li>The reasoning benchmarks are bonkers. When I tested it on multi-step logic puzzles and math problems, it consistently outperformed everything else in this comparison.<\/li>\n<li>Moonshot AI clearly poured their research budget into making Kimi think harder than its peers.<\/li>\n<li>It&#8217;s still OpenAI-compatible, so integration is painless.<\/li>\n<li>If you have a use case where getting the right answer matters more than cost (legal analysis, scientific reasoning, complex planning), this is your pick.<\/li>\n<\/ul>\n<h3> <a name=\"where-it-struggles\" href=\"#where-it-struggles\"> <\/a> Where It Struggles <\/h3>\n<ul>\n<li>The price. $3.00\/M is 12x what DeepSeek V4 Flash costs, so you can&#8217;t just default to it for everything.<\/li>\n<li>It&#8217;s noticeably slower than the other families. When I&#8217;m chatting with Kimi, I can feel the extra latency.<\/li>\n<li>No vision support at all \u2014 text only.<\/li>\n<li>Less model variety. You&#8217;re not picking between eight sizes; you&#8217;re picking one premium experience.<\/li>\n<\/ul>\n<p>I won&#8217;t lie, I use Kimi sparingly. But when I&#8217;m stuck on a tricky algorithm or need to debug something where the chain of reasoning matters, K2.5 has saved me hours.<\/p>\n<h2> <a name=\"glm-the-bilingual-powerhouse\" href=\"#glm-the-bilingual-powerhouse\"> <\/a> GLM: The Bilingual Powerhouse <\/h2>\n<p>Last but definitely not least \u2014 GLM from Zhipu AI is my secret weapon for anything involving Chinese language, and it&#8217;s surprisingly competitive on English too.<\/p>\n<h3> <a name=\"the-lineup\" href=\"#the-lineup\"> <\/a> The Lineup <\/h3>\n<div>\n<table>\n<thead>\n<tr>\n<th>Model<\/th>\n<th>Output $\/M<\/th>\n<th>What It&#8217;s For<\/th>\n<\/tr>\n<\/thead>\n<tbody>\n<tr>\n<td>GLM-4-9B<\/td>\n<td>$0.01<\/td>\n<td>Tiny tasks, classification, anything where you want maximum savings<\/td>\n<\/tr>\n<tr>\n<td>GLM-5<\/td>\n<td>$1.92<\/td>\n<td>My default for this family \u2014 production-grade quality<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<\/div>\n<p>And the full price range spans $0.01 to $1.92\/M.<\/p>\n<h3> <a name=\"what-makes-it-click\" href=\"#what-makes-it-click\"> <\/a> What Makes It Click <\/h3>\n<ul>\n<li>Chinese-language quality is top-tier \u2014 it ties with Kimi for the best Chinese understanding in this comparison.<\/li>\n<li>The price floor is wild. GLM-4-9B at $0.01\/M is one of the cheapest viable models I&#8217;ve ever used.<\/li>\n<li>GLM-4.6V brings genuine vision support, which DeepSeek and Kimi lack.<\/li>\n<li>For mixed Chinese\/English workloads (which, honestly, come up more than you&#8217;d think in global products), GLM is the most natural choice.<\/li>\n<li>The model lineup is clean \u2014 not as overwhelming as Qwen&#8217;s catalog.<\/li>\n<\/ul>\n<h3> <a name=\"where-it-struggles\" href=\"#where-it-struggles\"> <\/a> Where It Struggles <\/h3>\n<ul>\n<li>Code generation isn&#8217;t its strongest suit. It scores a 3 out of 5 in my testing, which puts it behind the other three families for coding tasks.<\/li>\n<li>The top-tier GLM-5 is pricier than DeepSeek V4 Flash at $1.92\/M, so the value proposition depends heavily on whether you need the Chinese-language edge.<\/li>\n<li>Speed is good but not the fastest \u2014 sits comfortably in the middle of the pack.<\/li>\n<\/ul>\n<h2> <a name=\"so-which-one-should-you-actually-pick\" href=\"#so-which-one-should-you-actually-pick\"> <\/a> So Which One Should You Actually Pick? <\/h2>\n<p>Here&#8217;s my honest, from-the-hip recommendation after months of using all four:<\/p>\n<p><strong>If you&#8217;re building a product and cost matters (when doesn&#8217;t it?), start with DeepSeek V4 Flash.<\/strong> At $0.<\/p>\n<\/p><\/div>\n<\/div>\n<\/div>\n<\/div>\n<p>Fuente: <a href=\"https:\/\/dev.to\/rarenode\/deepseek-vs-qwen-vs-kimi-vs-glm-which-one-should-you-use-mhd\">Art\u00edculo original<\/a><\/p>\n","protected":false},"excerpt":{"rendered":"<p>Now let me walk you through each family, what they&#8217;re great at, and where they fall short. DeepSeek: The One I Reach For Most Okay, I&#8217;m just going to say it \u2014 DeepSeek V4 Flash at $0.25 per million output tokens is the best deal in AI right now. Period. I use it for probably [&hellip;]<\/p>\n","protected":false},"author":1,"featured_media":4390,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":"","jetpack_publicize_message":"","jetpack_publicize_feature_enabled":true,"jetpack_social_post_already_shared":true,"jetpack_social_options":{"image_generator_settings":{"template":"highway","default_image_id":0,"font":"","enabled":false},"version":2},"webixso_pending_account_ids":""},"categories":[41],"tags":[],"class_list":["post-4391","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-devto"],"jetpack_publicize_connections":[],"_links":{"self":[{"href":"https:\/\/tucumandevelopers.com\/index.php\/wp-json\/wp\/v2\/posts\/4391","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/tucumandevelopers.com\/index.php\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/tucumandevelopers.com\/index.php\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/tucumandevelopers.com\/index.php\/wp-json\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/tucumandevelopers.com\/index.php\/wp-json\/wp\/v2\/comments?post=4391"}],"version-history":[{"count":0,"href":"https:\/\/tucumandevelopers.com\/index.php\/wp-json\/wp\/v2\/posts\/4391\/revisions"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/tucumandevelopers.com\/index.php\/wp-json\/wp\/v2\/media\/4390"}],"wp:attachment":[{"href":"https:\/\/tucumandevelopers.com\/index.php\/wp-json\/wp\/v2\/media?parent=4391"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/tucumandevelopers.com\/index.php\/wp-json\/wp\/v2\/categories?post=4391"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/tucumandevelopers.com\/index.php\/wp-json\/wp\/v2\/tags?post=4391"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}