1:"$Sreact.fragment"
2:I[106,["/_next/static/chunks/a1ab49af14ac3965.js"],"RootProvider"]
3:I[53113,["/_next/static/chunks/4d80e004cf4896dd.js","/_next/static/chunks/a9a3c4fe06e2de96.js"],"default"]
4:I[73211,["/_next/static/chunks/4d80e004cf4896dd.js","/_next/static/chunks/a9a3c4fe06e2de96.js"],"default"]
5:I[25838,["/_next/static/chunks/a1ab49af14ac3965.js","/_next/static/chunks/fc6384242057cf3a.js","/_next/static/chunks/102a89dfeee873be.js","/_next/static/chunks/3d6200c160d8fee0.js","/_next/static/chunks/c3337f1fa9e81806.js"],"TreeContextProvider"]
a:I[6998,["/_next/static/chunks/4d80e004cf4896dd.js","/_next/static/chunks/a9a3c4fe06e2de96.js"],"default"]
:HL["/_next/static/chunks/2fe6387a7ffef26a.css","style"]
0:{"P":null,"b":"8D_ay196DvicGYoDHN50Z","c":["","docs","getting-started","installation"],"q":"","i":false,"f":[[["",{"children":["docs",{"children":[["slug","getting-started/installation","oc"],{"children":["__PAGE__",{}]}]}]},"$undefined","$undefined",true],[["$","$1","c",{"children":[[["$","link","0",{"rel":"stylesheet","href":"/_next/static/chunks/2fe6387a7ffef26a.css","precedence":"next","crossOrigin":"$undefined","nonce":"$undefined"}],["$","script","script-0",{"src":"/_next/static/chunks/a1ab49af14ac3965.js","async":true,"nonce":"$undefined"}]],["$","html",null,{"lang":"en","suppressHydrationWarning":true,"children":["$","body",null,{"className":"antialiased","children":["$","$L2",null,{"children":["$","$L3",null,{"parallelRouterKey":"children","error":"$undefined","errorStyles":"$undefined","errorScripts":"$undefined","template":["$","$L4",null,{}],"templateStyles":"$undefined","templateScripts":"$undefined","notFound":[[["$","title",null,{"children":"404: This page could not be found."}],["$","div",null,{"style":{"fontFamily":"system-ui,\"Segoe UI\",Roboto,Helvetica,Arial,sans-serif,\"Apple Color Emoji\",\"Segoe UI Emoji\"","height":"100vh","textAlign":"center","display":"flex","flexDirection":"column","alignItems":"center","justifyContent":"center"},"children":["$","div",null,{"children":[["$","style",null,{"dangerouslySetInnerHTML":{"__html":"body{color:#000;background:#fff;margin:0}.next-error-h1{border-right:1px solid rgba(0,0,0,.3)}@media (prefers-color-scheme:dark){body{color:#fff;background:#000}.next-error-h1{border-right:1px solid rgba(255,255,255,.3)}}"}}],["$","h1",null,{"className":"next-error-h1","style":{"display":"inline-block","margin":"0 20px 0 0","padding":"0 23px 0 0","fontSize":24,"fontWeight":500,"verticalAlign":"top","lineHeight":"49px"},"children":404}],["$","div",null,{"style":{"display":"inline-block"},"children":["$","h2",null,{"style":{"fontSize":14,"fontWeight":400,"lineHeight":"49px","margin":0},"children":"This page could not be found."}]}]]}]}]],[]],"forbidden":"$undefined","unauthorized":"$undefined"}]}]}]}]]}],{"children":[["$","$1","c",{"children":[[["$","script","script-0",{"src":"/_next/static/chunks/fc6384242057cf3a.js","async":true,"nonce":"$undefined"}],["$","script","script-1",{"src":"/_next/static/chunks/102a89dfeee873be.js","async":true,"nonce":"$undefined"}],["$","script","script-2",{"src":"/_next/static/chunks/3d6200c160d8fee0.js","async":true,"nonce":"$undefined"}],["$","script","script-3",{"src":"/_next/static/chunks/c3337f1fa9e81806.js","async":true,"nonce":"$undefined"}]],["$","$L5",null,{"tree":{"$id":"root","name":"Documentation","children":[{"$id":"index.mdx","type":"page","name":"Introduction","description":"Zen LM by Hanzo AI -- 14 frontier models for code, reasoning, vision, multimodal, embeddings, and safety","icon":"$undefined","url":"/docs","$ref":{"file":"index.mdx"}},{"$id":"_0","type":"separator","icon":"$undefined","name":"Getting Started"},{"type":"folder","name":"Getting started","root":"$undefined","defaultOpen":"$undefined","description":"$undefined","collapsible":"$undefined","children":[{"$id":"getting-started/installation.mdx","type":"page","name":"Installation","description":"Install dependencies for using Zen models","icon":"$undefined","url":"/docs/getting-started/installation","$ref":{"file":"getting-started/installation.mdx"}},{"$id":"getting-started/quickstart.mdx","type":"page","name":"Quickstart","description":"Get started with Zen models in minutes","icon":"$undefined","url":"/docs/getting-started/quickstart","$ref":{"file":"getting-started/quickstart.mdx"}}],"$id":"getting-started","$ref":"$undefined","icon":"$undefined"},{"$id":"_1","type":"separator","icon":"$undefined","name":"API"},{"type":"folder","name":"API Reference","root":"$undefined","defaultOpen":"$undefined","description":"$undefined","collapsible":"$undefined","children":[{"$id":"api/chat-completions.mdx","type":"page","name":"Chat Completions","description":"Generate text with any of the 14 Zen models using the OpenAI-compatible chat completions endpoint","icon":"$undefined","url":"/docs/api/chat-completions","$ref":{"file":"api/chat-completions.mdx"}},{"$id":"api/embeddings.mdx","type":"page","name":"Embeddings","description":"Generate 3072-dimensional vector embeddings with zen3-embedding","icon":"$undefined","url":"/docs/api/embeddings","$ref":{"file":"api/embeddings.mdx"}},{"$id":"api/models.mdx","type":"page","name":"Models","description":"All 14 Zen models -- capabilities, pricing, and recommended use cases","icon":"$undefined","url":"/docs/api/models","$ref":{"file":"api/models.mdx"}},{"$id":"api/pricing.mdx","type":"page","name":"Pricing","description":"Zen LM API pricing -- transparent at 3x upstream inference cost","icon":"$undefined","url":"/docs/api/pricing","$ref":{"file":"api/pricing.mdx"}}],"$id":"api","$ref":"$undefined","index":{"$id":"api/index.mdx","type":"page","name":"API Reference","description":"Zen LM Cloud API -- OpenAI-compatible endpoints for all 14 Zen models","icon":"$undefined","url":"/docs/api","$ref":{"file":"api/index.mdx"}},"icon":"$undefined"},{"$id":"_2","type":"separator","icon":"$undefined","name":"Models"},{"type":"folder","name":"Models","root":"$undefined","defaultOpen":"$undefined","description":"$undefined","collapsible":"$undefined","children":[{"$id":"models/zen-3d.mdx","type":"page","name":"zen-3d","description":"3D generation model for text-to-3D and image-to-3D asset creation.","icon":"$undefined","url":"/docs/models/zen-3d","$ref":{"file":"models/zen-3d.mdx"}},{"$id":"models/zen-agent.mdx","type":"page","name":"zen-agent","description":"32B dense model with tool use and planning for agentic AI workflows.","icon":"$undefined","url":"/docs/models/zen-agent","$ref":{"file":"models/zen-agent.mdx"}},{"$id":"models/zen-artist-edit.mdx","type":"page","name":"zen-artist-edit","description":"Image editing model for inpainting, outpainting, and edit-by-instruction.","icon":"$undefined","url":"/docs/models/zen-artist-edit","$ref":{"file":"models/zen-artist-edit.mdx"}},{"$id":"models/zen-artist.mdx","type":"page","name":"zen-artist","description":"Image generation model supporting multiple styles and high-resolution output.","icon":"$undefined","url":"/docs/models/zen-artist","$ref":{"file":"models/zen-artist.mdx"}},{"$id":"models/zen-code.mdx","type":"page","name":"zen-code","description":"Legacy 14B dense code model for general programming tasks.","icon":"$undefined","url":"/docs/models/zen-code","$ref":{"file":"models/zen-code.mdx"}},{"$id":"models/zen-coder-flash.mdx","type":"page","name":"zen-coder-flash","description":"Lightweight 7B dense model for low-latency code completions.","icon":"$undefined","url":"/docs/models/zen-coder-flash","$ref":{"file":"models/zen-coder-flash.mdx"}},{"$id":"models/zen-coder.mdx","type":"page","name":"zen-coder","description":"32B dense code model with 131K context for multi-language development.","icon":"$undefined","url":"/docs/models/zen-coder","$ref":{"file":"models/zen-coder.mdx"}},{"$id":"models/zen-designer.mdx","type":"page","name":"zen-designer","description":"Design generation model for UI/UX, graphics, and visual layouts.","icon":"$undefined","url":"/docs/models/zen-designer","$ref":{"file":"models/zen-designer.mdx"}},{"$id":"models/zen-director.mdx","type":"page","name":"zen-director","description":"Text-to-video generation model with cinematic quality output.","icon":"$undefined","url":"/docs/models/zen-director","$ref":{"file":"models/zen-director.mdx"}},{"$id":"models/zen-dub-live.mdx","type":"page","name":"zen-dub-live","description":"Real-time voice synthesis with ultra-low latency for live applications.","icon":"$undefined","url":"/docs/models/zen-dub-live","$ref":{"file":"models/zen-dub-live.mdx"}},{"$id":"models/zen-dub.mdx","type":"page","name":"zen-dub","description":"Voice synthesis and multi-language dubbing model.","icon":"$undefined","url":"/docs/models/zen-dub","$ref":{"file":"models/zen-dub.mdx"}},{"$id":"models/zen-eco.mdx","type":"page","name":"zen-eco","description":"Efficient 4B dense model balancing capability and cost for general-purpose tasks.","icon":"$undefined","url":"/docs/models/zen-eco","$ref":{"file":"models/zen-eco.mdx"}},{"$id":"models/zen-foley.mdx","type":"page","name":"zen-foley","description":"Sound effects generation model for text-to-SFX production.","icon":"$undefined","url":"/docs/models/zen-foley","$ref":{"file":"models/zen-foley.mdx"}},{"$id":"models/zen-guard-gen.mdx","type":"page","name":"zen-guard-gen","description":"8B dense model for safe text generation with built-in guardrails.","icon":"$undefined","url":"/docs/models/zen-guard-gen","$ref":{"file":"models/zen-guard-gen.mdx"}},{"$id":"models/zen-guard-stream.mdx","type":"page","name":"zen-guard-stream","description":"4B dense model for low-latency streaming content moderation.","icon":"$undefined","url":"/docs/models/zen-guard-stream","$ref":{"file":"models/zen-guard-stream.mdx"}},{"$id":"models/zen-live.mdx","type":"page","name":"zen-live","description":"Real-time bidirectional speech translation with ultra-low latency.","icon":"$undefined","url":"/docs/models/zen-live","$ref":{"file":"models/zen-live.mdx"}},{"$id":"models/zen-max.mdx","type":"page","name":"zen-max","description":"Trillion-parameter 1.04T MoE open-weights frontier model. Same model as zen4-max.","icon":"$undefined","url":"/docs/models/zen-max","$ref":{"file":"models/zen-max.mdx"}},{"$id":"models/zen-musician.mdx","type":"page","name":"zen-musician","description":"Music generation model with multi-instrument composition and style control.","icon":"$undefined","url":"/docs/models/zen-musician","$ref":{"file":"models/zen-musician.mdx"}},{"$id":"models/zen-nano.mdx","type":"page","name":"zen-nano","description":"Ultra-compact 0.6B dense model for edge inference at 44K tokens/sec.","icon":"$undefined","url":"/docs/models/zen-nano","$ref":{"file":"models/zen-nano.mdx"}},{"$id":"models/zen-omni.mdx","type":"page","name":"zen-omni","description":"72B dense hypermodal model supporting text, vision, audio, and code.","icon":"$undefined","url":"/docs/models/zen-omni","$ref":{"file":"models/zen-omni.mdx"}},{"$id":"models/zen-pro.mdx","type":"page","name":"zen-pro","description":"Professional-grade 32B dense model with 19K tokens/sec throughput.","icon":"$undefined","url":"/docs/models/zen-pro","$ref":{"file":"models/zen-pro.mdx"}},{"$id":"models/zen-reranker.mdx","type":"page","name":"zen-reranker","description":"568M dense cross-encoder model for search result reranking.","icon":"$undefined","url":"/docs/models/zen-reranker","$ref":{"file":"models/zen-reranker.mdx"}},{"$id":"models/zen-scribe.mdx","type":"page","name":"zen-scribe","description":"Speech-to-text transcription model with multi-language support.","icon":"$undefined","url":"/docs/models/zen-scribe","$ref":{"file":"models/zen-scribe.mdx"}},{"$id":"models/zen-translator.mdx","type":"page","name":"zen-translator","description":"Context-aware translation model supporting 100+ languages.","icon":"$undefined","url":"/docs/models/zen-translator","$ref":{"file":"models/zen-translator.mdx"}},{"$id":"models/zen-video-i2v.mdx","type":"page","name":"zen-video-i2v","description":"Image-to-video animation model that brings still images to life.","icon":"$undefined","url":"/docs/models/zen-video-i2v","$ref":{"file":"models/zen-video-i2v.mdx"}},{"$id":"models/zen-video.mdx","type":"page","name":"zen-video","description":"Video understanding model for frame analysis, captioning, and temporal reasoning.","icon":"$undefined","url":"/docs/models/zen-video","$ref":{"file":"models/zen-video.mdx"}},{"$id":"models/zen-vl.mdx","type":"page","name":"zen-vl","description":"32B dense multimodal model for vision-language understanding.","icon":"$undefined","url":"/docs/models/zen-vl","$ref":{"file":"models/zen-vl.mdx"}},{"$id":"models/zen-voyager.mdx","type":"page","name":"zen-voyager","description":"World model for spatial reasoning and 3D scene understanding.","icon":"$undefined","url":"/docs/models/zen-voyager","$ref":{"file":"models/zen-voyager.mdx"}},{"$id":"models/zen-world.mdx","type":"page","name":"zen-world","description":"World simulation model for spatial reasoning and environment generation.","icon":"$undefined","url":"/docs/models/zen-world","$ref":{"file":"models/zen-world.mdx"}},{"$id":"models/zen.mdx","type":"page","name":"zen","description":"Standard 8-32B dense foundation model for general-purpose AI tasks.","icon":"$undefined","url":"/docs/models/zen","$ref":{"file":"models/zen.mdx"}},{"$id":"models/zen3-embedding.mdx","type":"page","name":"zen3-embedding","description":"High-quality text embedding model with 3072 dimensions and 8K context.","icon":"$undefined","url":"/docs/models/zen3-embedding","$ref":{"file":"models/zen3-embedding.mdx"}},{"$id":"models/zen3-guard.mdx","type":"page","name":"zen3-guard","description":"Content safety classifier with 4B dense architecture. 40K context.","icon":"$undefined","url":"/docs/models/zen3-guard","$ref":{"file":"models/zen3-guard.mdx"}},{"$id":"models/zen3-nano.mdx","type":"page","name":"zen3-nano","description":"Ultra-lightweight 4B dense model for edge deployment. 40K context.","icon":"$undefined","url":"/docs/models/zen3-nano","$ref":{"file":"models/zen3-nano.mdx"}},{"$id":"models/zen3-omni.mdx","type":"page","name":"zen3-omni","description":"Hypermodal ~200B dense model supporting text, vision, and audio. 202K context.","icon":"$undefined","url":"/docs/models/zen3-omni","$ref":{"file":"models/zen3-omni.mdx"}},{"$id":"models/zen3-vl.mdx","type":"page","name":"zen3-vl","description":"Vision-language model with 30B (3B active) MoE architecture. 131K context.","icon":"$undefined","url":"/docs/models/zen3-vl","$ref":{"file":"models/zen3-vl.mdx"}},{"$id":"models/zen4-coder-flash.mdx","type":"page","name":"zen4-coder-flash","description":"Fast 30B (3B active) MoE code model with 262K context.","icon":"$undefined","url":"/docs/models/zen4-coder-flash","$ref":{"file":"models/zen4-coder-flash.mdx"}},{"$id":"models/zen4-coder-pro.mdx","type":"page","name":"zen4-coder-pro","description":"Premium 480B full-precision BF16 code model with 262K context.","icon":"$undefined","url":"/docs/models/zen4-coder-pro","$ref":{"file":"models/zen4-coder-pro.mdx"}},{"$id":"models/zen4-coder.mdx","type":"page","name":"zen4-coder","description":"Code generation model with 480B (35B active) MoE and 262K context.","icon":"$undefined","url":"/docs/models/zen4-coder","$ref":{"file":"models/zen4-coder.mdx"}},{"$id":"models/zen4-max.mdx","type":"page","name":"zen4-max","description":"Trillion-parameter frontier MoE model. 1.04T (32B active) with 256K context.","icon":"$undefined","url":"/docs/models/zen4-max","$ref":{"file":"models/zen4-max.mdx"}},{"$id":"models/zen4-mini.mdx","type":"page","name":"zen4-mini","description":"Fast and efficient 8B dense model with 40K context.","icon":"$undefined","url":"/docs/models/zen4-mini","$ref":{"file":"models/zen4-mini.mdx"}},{"$id":"models/zen4-pro.mdx","type":"page","name":"zen4-pro","description":"High capability MoE model. 80B (3B active) with 131K context.","icon":"$undefined","url":"/docs/models/zen4-pro","$ref":{"file":"models/zen4-pro.mdx"}},{"$id":"models/zen4-thinking.mdx","type":"page","name":"zen4-thinking","description":"Deep reasoning model with 80B (3B active) MoE + chain-of-thought. 131K context.","icon":"$undefined","url":"/docs/models/zen4-thinking","$ref":{"file":"models/zen4-thinking.mdx"}},{"$id":"models/zen4-ultra.mdx","type":"page","name":"zen4-ultra","description":"Maximum reasoning model with 744B MoE (40B active) + extended chain-of-thought. 202K context.","icon":"$undefined","url":"/docs/models/zen4-ultra","$ref":{"file":"models/zen4-ultra.mdx"}},{"$id":"models/zen4.mdx","type":"page","name":"zen4","description":"Flagship 744B MoE model with 40B active parameters and 202K context window.","icon":"$undefined","url":"/docs/models/zen4","$ref":{"file":"models/zen4.mdx"}}],"$id":"models","$ref":"$undefined","icon":"$undefined"},{"$id":"_3","type":"separator","icon":"$undefined","name":"Training"},{"type":"folder","name":"Training","root":"$undefined","defaultOpen":"$undefined","description":"$undefined","collapsible":"$undefined","children":[{"$id":"training/cloud.mdx","type":"page","name":"Cloud Training","description":"Full-scale training on 8x H200 GPUs","icon":"$undefined","url":"/docs/training/cloud","$ref":{"file":"training/cloud.mdx"}},{"$id":"training/cuda.mdx","type":"page","name":"CUDA Training","description":"Train locally with NVIDIA GPUs","icon":"$undefined","url":"/docs/training/cuda","$ref":{"file":"training/cuda.mdx"}},{"$id":"training/mlx.mdx","type":"page","name":"MLX Training","description":"Train on Apple Silicon with MLX","icon":"$undefined","url":"/docs/training/mlx","$ref":{"file":"training/mlx.mdx"}},{"$id":"training/overview.mdx","type":"page","name":"Training Overview","description":"Train Zen models with multiple backend options","icon":"$undefined","url":"/docs/training/overview","$ref":{"file":"training/overview.mdx"}}],"$id":"training","$ref":"$undefined","icon":"$undefined"},{"$id":"_4","type":"separator","icon":"$undefined","name":"Datasets"},{"$id":"datasets.mdx","type":"page","name":"Datasets","description":"Zen Agentic Dataset - 8.47 billion tokens of real-world agentic programming","icon":"$undefined","url":"/docs/datasets","$ref":{"file":"datasets.mdx"}}],"fallback":{"$id":"fallback:root","name":"Docs","children":[{"$id":"fallback:models.mdx","type":"page","name":"Models","description":"Complete Zen LM model family -- 49 models across 10 modalities","icon":"$undefined","url":"/docs/models","$ref":{"file":"models.mdx"}},{"$id":"fallback:training.mdx","type":"page","name":"Training","description":"Fine-tune Zen4 models with MLX, Unsloth, or DeepSpeed","icon":"$undefined","url":"/docs/training","$ref":{"file":"training.mdx"}}]}},"children":"$L6"}]]}],{"children":["$L7",{"children":["$L8",{},null,false,false]},null,false,false]},null,false,false]},null,false,false],"$L9",false]],"m":"$undefined","G":["$a",[]],"S":true}
b:I[99924,["/_next/static/chunks/a1ab49af14ac3965.js","/_next/static/chunks/fc6384242057cf3a.js","/_next/static/chunks/102a89dfeee873be.js","/_next/static/chunks/3d6200c160d8fee0.js","/_next/static/chunks/c3337f1fa9e81806.js"],"LayoutContextProvider"]
c:I[32824,["/_next/static/chunks/a1ab49af14ac3965.js","/_next/static/chunks/fc6384242057cf3a.js","/_next/static/chunks/102a89dfeee873be.js","/_next/static/chunks/3d6200c160d8fee0.js","/_next/static/chunks/c3337f1fa9e81806.js"],"SidebarProvider"]
d:I[99924,["/_next/static/chunks/a1ab49af14ac3965.js","/_next/static/chunks/fc6384242057cf3a.js","/_next/static/chunks/102a89dfeee873be.js","/_next/static/chunks/3d6200c160d8fee0.js","/_next/static/chunks/c3337f1fa9e81806.js"],"LayoutBody"]
e:I[99924,["/_next/static/chunks/a1ab49af14ac3965.js","/_next/static/chunks/fc6384242057cf3a.js","/_next/static/chunks/102a89dfeee873be.js","/_next/static/chunks/3d6200c160d8fee0.js","/_next/static/chunks/c3337f1fa9e81806.js"],"LayoutHeader"]
f:I[48068,["/_next/static/chunks/a1ab49af14ac3965.js","/_next/static/chunks/fc6384242057cf3a.js","/_next/static/chunks/102a89dfeee873be.js","/_next/static/chunks/3d6200c160d8fee0.js","/_next/static/chunks/c3337f1fa9e81806.js","/_next/static/chunks/03fa6a72e52d2376.js","/_next/static/chunks/7cdbc484c0405193.js"],"default"]
10:I[80761,["/_next/static/chunks/a1ab49af14ac3965.js","/_next/static/chunks/fc6384242057cf3a.js","/_next/static/chunks/102a89dfeee873be.js","/_next/static/chunks/3d6200c160d8fee0.js","/_next/static/chunks/c3337f1fa9e81806.js"],"SearchToggle"]
11:I[32824,["/_next/static/chunks/a1ab49af14ac3965.js","/_next/static/chunks/fc6384242057cf3a.js","/_next/static/chunks/102a89dfeee873be.js","/_next/static/chunks/3d6200c160d8fee0.js","/_next/static/chunks/c3337f1fa9e81806.js"],"SidebarTrigger"]
12:I[80157,["/_next/static/chunks/a1ab49af14ac3965.js","/_next/static/chunks/fc6384242057cf3a.js","/_next/static/chunks/102a89dfeee873be.js","/_next/static/chunks/3d6200c160d8fee0.js","/_next/static/chunks/c3337f1fa9e81806.js"],"SidebarContent"]
13:I[32824,["/_next/static/chunks/a1ab49af14ac3965.js","/_next/static/chunks/fc6384242057cf3a.js","/_next/static/chunks/102a89dfeee873be.js","/_next/static/chunks/3d6200c160d8fee0.js","/_next/static/chunks/c3337f1fa9e81806.js"],"SidebarCollapseTrigger"]
14:I[80761,["/_next/static/chunks/a1ab49af14ac3965.js","/_next/static/chunks/fc6384242057cf3a.js","/_next/static/chunks/102a89dfeee873be.js","/_next/static/chunks/3d6200c160d8fee0.js","/_next/static/chunks/c3337f1fa9e81806.js"],"LargeSearchToggle"]
15:I[32824,["/_next/static/chunks/a1ab49af14ac3965.js","/_next/static/chunks/fc6384242057cf3a.js","/_next/static/chunks/102a89dfeee873be.js","/_next/static/chunks/3d6200c160d8fee0.js","/_next/static/chunks/c3337f1fa9e81806.js"],"SidebarViewport"]
16:I[80157,["/_next/static/chunks/a1ab49af14ac3965.js","/_next/static/chunks/fc6384242057cf3a.js","/_next/static/chunks/102a89dfeee873be.js","/_next/static/chunks/3d6200c160d8fee0.js","/_next/static/chunks/c3337f1fa9e81806.js"],"SidebarLinkItem"]
17:I[80157,["/_next/static/chunks/a1ab49af14ac3965.js","/_next/static/chunks/fc6384242057cf3a.js","/_next/static/chunks/102a89dfeee873be.js","/_next/static/chunks/3d6200c160d8fee0.js","/_next/static/chunks/c3337f1fa9e81806.js"],"SidebarPageTree"]
18:I[73332,["/_next/static/chunks/a1ab49af14ac3965.js","/_next/static/chunks/fc6384242057cf3a.js","/_next/static/chunks/102a89dfeee873be.js","/_next/static/chunks/3d6200c160d8fee0.js","/_next/static/chunks/c3337f1fa9e81806.js"],"ThemeToggle"]
19:I[80157,["/_next/static/chunks/a1ab49af14ac3965.js","/_next/static/chunks/fc6384242057cf3a.js","/_next/static/chunks/102a89dfeee873be.js","/_next/static/chunks/3d6200c160d8fee0.js","/_next/static/chunks/c3337f1fa9e81806.js"],"SidebarDrawer"]
1c:I[89923,["/_next/static/chunks/4d80e004cf4896dd.js","/_next/static/chunks/a9a3c4fe06e2de96.js"],"OutletBoundary"]
1d:"$Sreact.suspense"
1f:I[89923,["/_next/static/chunks/4d80e004cf4896dd.js","/_next/static/chunks/a9a3c4fe06e2de96.js"],"ViewportBoundary"]
21:I[89923,["/_next/static/chunks/4d80e004cf4896dd.js","/_next/static/chunks/a9a3c4fe06e2de96.js"],"MetadataBoundary"]
6:["$","$Lb",null,{"navTransparentMode":"$undefined","children":["$","$Lc",null,{"defaultOpenLevel":"$undefined","prefetch":"$undefined","children":["$","$Ld",null,{"children":[["$","$Le",null,{"id":"nd-subnav","className":"[grid-area:header] sticky top-(--fd-docs-row-1) z-30 flex items-center ps-4 pe-2.5 border-b transition-colors backdrop-blur-sm h-(--fd-header-height) md:hidden max-md:layout:[--fd-header-height:--spacing(14)] data-[transparent=false]:bg-fd-background/80","children":[["$","$Lf",null,{"href":"/","className":"inline-flex items-center gap-2.5 font-semibold","children":"⚡ Zen LM"}],["$","div",null,{"className":"flex-1","children":"$undefined"}],["$","$L10",null,{"className":"p-2","hideIfDisabled":true}],["$","$L11",null,{"className":"inline-flex items-center justify-center rounded-md text-sm font-medium transition-colors duration-100 disabled:pointer-events-none disabled:opacity-50 focus-visible:outline-none focus-visible:ring-2 focus-visible:ring-fd-ring hover:bg-fd-accent hover:text-fd-accent-foreground [&_svg]:size-4.5 p-2","children":["$","svg",null,{"ref":"$undefined","xmlns":"http://www.w3.org/2000/svg","width":24,"height":24,"viewBox":"0 0 24 24","fill":"none","stroke":"currentColor","strokeWidth":2,"strokeLinecap":"round","strokeLinejoin":"round","className":"lucide lucide-panel-left","aria-hidden":"true","children":[["$","rect","afitv7",{"width":"18","height":"18","x":"3","y":"3","rx":"2"}],["$","path","fh3hqa",{"d":"M9 3v18"}],"$undefined"]}]}]]}],[["$","$L12",null,{"children":[["$","div",null,{"className":"flex flex-col gap-3 p-4 pb-2","children":[["$","div",null,{"className":"flex","children":[["$","$Lf",null,{"href":"/","className":"inline-flex text-[0.9375rem] items-center gap-2.5 font-medium me-auto","children":"⚡ Zen LM"}],"$undefined",["$","$L13",null,{"className":"inline-flex items-center justify-center rounded-md text-sm font-medium transition-colors duration-100 disabled:pointer-events-none disabled:opacity-50 focus-visible:outline-none focus-visible:ring-2 focus-visible:ring-fd-ring hover:bg-fd-accent hover:text-fd-accent-foreground p-1.5 [&_svg]:size-4.5 mb-auto text-fd-muted-foreground","children":["$","svg",null,{"ref":"$undefined","xmlns":"http://www.w3.org/2000/svg","width":24,"height":24,"viewBox":"0 0 24 24","fill":"none","stroke":"currentColor","strokeWidth":2,"strokeLinecap":"round","strokeLinejoin":"round","className":"lucide lucide-panel-left","aria-hidden":"true","children":[["$","rect","afitv7",{"width":"18","height":"18","x":"3","y":"3","rx":"2"}],["$","path","fh3hqa",{"d":"M9 3v18"}],"$undefined"]}]}]]}],["$","$L14",null,{"hideIfDisabled":true}],false,["$","div",null,{"className":"p-3 rounded-lg bg-primary/10 text-sm","children":[["$","strong",null,{"children":"zen4-max"}]," — 1T+ MoE frontier model"]}]]}],["$","$L15",null,{"children":[[["$","$L16","0",{"item":{"text":"HuggingFace","url":"https://huggingface.co/zenlm"},"className":""}],["$","$L16","1",{"item":{"text":"GitHub","url":"https://github.com/zenlm"},"className":"mb-4"}]],["$","$L17",null,{}]]}],["$","div",null,{"className":"flex flex-col border-t p-4 pt-2 empty:hidden","children":[["$","div",null,{"className":"flex text-fd-muted-foreground items-center empty:hidden","children":[false,[],["$","$L18",null,{"className":"ms-auto p-0","mode":"$undefined"}]]}],"$undefined"]}]]}],["$","$L19",null,{"children":[["$","div",null,{"className":"flex flex-col gap-3 p-4 pb-2","children":[["$","div",null,{"className":"flex text-fd-muted-foreground items-center gap-1.5","children":[["$","div",null,{"className":"flex flex-1","children":[]}],false,["$","$L18",null,{"className":"p-0","mode":"$undefined"}],["$","$L11",null,{"className":"inline-flex items-center justify-center rounded-md text-sm font-medium transition-colors duration-100 disabled:pointer-events-none disabled:opacity-50 focus-visible:outline-none focus-visible:ring-2 focus-visible:ring-fd-ring hover:bg-fd-accent hover:text-fd-accent-foreground [&_svg]:size-4.5 p-2","children":["$","svg",null,{"ref":"$undefined","xmlns":"http://www.w3.org/2000/svg","width":24,"height":24,"viewBox":"0 0 24 24","fill":"none","stroke":"currentColor","strokeWidth":2,"strokeLinecap":"round","strokeLinejoin":"round","className":"lucide lucide-panel-left","aria-hidden":"true","children":[["$","rect","afitv7",{"width":"18","height":"18","x":"3","y":"3","rx":"2"}],["$","path","fh3hqa",{"d":"M9 3v18"}],"$undefined"]}]}]]}],false,"$6:props:children:props:children:props:children:1:0:props:children:0:props:children:3"]}],"$6:props:children:props:children:props:children:1:0:props:children:1",["$","div",null,{"className":"flex flex-col border-t p-4 pt-2 empty:hidden","children":"$undefined"}]]}]],false,"$L1a"]}]}]}]
7:["$","$1","c",{"children":[null,["$","$L3",null,{"parallelRouterKey":"children","error":"$undefined","errorStyles":"$undefined","errorScripts":"$undefined","template":["$","$L4",null,{}],"templateStyles":"$undefined","templateScripts":"$undefined","notFound":"$undefined","forbidden":"$undefined","unauthorized":"$undefined"}]]}]
8:["$","$1","c",{"children":["$L1b",[["$","script","script-0",{"src":"/_next/static/chunks/03fa6a72e52d2376.js","async":true,"nonce":"$undefined"}],["$","script","script-1",{"src":"/_next/static/chunks/7cdbc484c0405193.js","async":true,"nonce":"$undefined"}]],["$","$L1c",null,{"children":["$","$1d",null,{"name":"Next.MetadataOutlet","children":"$@1e"}]}]]}]
9:["$","$1","h",{"children":[null,["$","$L1f",null,{"children":"$L20"}],["$","div",null,{"hidden":true,"children":["$","$L21",null,{"children":["$","$1d",null,{"name":"Next.Metadata","children":"$L22"}]}]}],null]}]
1a:["$","$L3",null,{"parallelRouterKey":"children","error":"$undefined","errorStyles":"$undefined","errorScripts":"$undefined","template":["$","$L4",null,{}],"templateStyles":"$undefined","templateScripts":"$undefined","notFound":"$undefined","forbidden":"$undefined","unauthorized":"$undefined"}]
23:I[70258,["/_next/static/chunks/a1ab49af14ac3965.js","/_next/static/chunks/fc6384242057cf3a.js","/_next/static/chunks/102a89dfeee873be.js","/_next/static/chunks/3d6200c160d8fee0.js","/_next/static/chunks/c3337f1fa9e81806.js","/_next/static/chunks/03fa6a72e52d2376.js","/_next/static/chunks/7cdbc484c0405193.js"],"DocsPage"]
24:I[70258,["/_next/static/chunks/a1ab49af14ac3965.js","/_next/static/chunks/fc6384242057cf3a.js","/_next/static/chunks/102a89dfeee873be.js","/_next/static/chunks/3d6200c160d8fee0.js","/_next/static/chunks/c3337f1fa9e81806.js","/_next/static/chunks/03fa6a72e52d2376.js","/_next/static/chunks/7cdbc484c0405193.js"],"DocsTitle"]
25:I[70258,["/_next/static/chunks/a1ab49af14ac3965.js","/_next/static/chunks/fc6384242057cf3a.js","/_next/static/chunks/102a89dfeee873be.js","/_next/static/chunks/3d6200c160d8fee0.js","/_next/static/chunks/c3337f1fa9e81806.js","/_next/static/chunks/03fa6a72e52d2376.js","/_next/static/chunks/7cdbc484c0405193.js"],"DocsDescription"]
26:I[70258,["/_next/static/chunks/a1ab49af14ac3965.js","/_next/static/chunks/fc6384242057cf3a.js","/_next/static/chunks/102a89dfeee873be.js","/_next/static/chunks/3d6200c160d8fee0.js","/_next/static/chunks/c3337f1fa9e81806.js","/_next/static/chunks/03fa6a72e52d2376.js","/_next/static/chunks/7cdbc484c0405193.js"],"DocsBody"]
27:I[51504,["/_next/static/chunks/a1ab49af14ac3965.js","/_next/static/chunks/fc6384242057cf3a.js","/_next/static/chunks/102a89dfeee873be.js","/_next/static/chunks/3d6200c160d8fee0.js","/_next/static/chunks/c3337f1fa9e81806.js","/_next/static/chunks/03fa6a72e52d2376.js","/_next/static/chunks/7cdbc484c0405193.js"],"CodeBlock"]
28:I[51504,["/_next/static/chunks/a1ab49af14ac3965.js","/_next/static/chunks/fc6384242057cf3a.js","/_next/static/chunks/102a89dfeee873be.js","/_next/static/chunks/3d6200c160d8fee0.js","/_next/static/chunks/c3337f1fa9e81806.js","/_next/static/chunks/03fa6a72e52d2376.js","/_next/static/chunks/7cdbc484c0405193.js"],"Pre"]
1b:["$","$L23",null,{"toc":[{"depth":1,"url":"#installation","title":"Installation"},{"depth":2,"url":"#requirements","title":"Requirements"},{"depth":2,"url":"#install-transformers","title":"Install Transformers"},{"depth":2,"url":"#install-vllm-production","title":"Install vLLM (Production)"},{"depth":2,"url":"#install-mlx-apple-silicon","title":"Install MLX (Apple Silicon)"},{"depth":2,"url":"#install-sglang","title":"Install SGLang"},{"depth":2,"url":"#gpu-memory-requirements","title":"GPU Memory Requirements"}],"children":[["$","$L24",null,{"children":"Installation"}],["$","$L25",null,{"children":"Install dependencies for using Zen models"}],["$","$L26",null,{"children":[["$","h1",null,{"className":"flex scroll-m-28 flex-row items-center gap-2","id":"installation","children":[["$","a",null,{"data-card":"","href":"#installation","className":"peer","children":"Installation"}],["$","svg",null,{"ref":"$undefined","xmlns":"http://www.w3.org/2000/svg","width":24,"height":24,"viewBox":"0 0 24 24","fill":"none","stroke":"currentColor","strokeWidth":2,"strokeLinecap":"round","strokeLinejoin":"round","className":"lucide lucide-link size-3.5 shrink-0 text-fd-muted-foreground opacity-0 transition-opacity peer-hover:opacity-100","aria-hidden":true,"children":[["$","path","1cjeqo",{"d":"M10 13a5 5 0 0 0 7.54.54l3-3a5 5 0 0 0-7.07-7.07l-1.72 1.71"}],["$","path","19qd67",{"d":"M14 11a5 5 0 0 0-7.54-.54l-3 3a5 5 0 0 0 7.07 7.07l1.71-1.71"}],"$undefined"]}]]}],"\n",["$","h2",null,{"className":"flex scroll-m-28 flex-row items-center gap-2","id":"requirements","children":[["$","a",null,{"data-card":"","href":"#requirements","className":"peer","children":"Requirements"}],["$","svg",null,{"ref":"$undefined","xmlns":"http://www.w3.org/2000/svg","width":24,"height":24,"viewBox":"0 0 24 24","fill":"none","stroke":"currentColor","strokeWidth":2,"strokeLinecap":"round","strokeLinejoin":"round","className":"lucide lucide-link size-3.5 shrink-0 text-fd-muted-foreground opacity-0 transition-opacity peer-hover:opacity-100","aria-hidden":true,"children":[["$","path","1cjeqo",{"d":"M10 13a5 5 0 0 0 7.54.54l3-3a5 5 0 0 0-7.07-7.07l-1.72 1.71"}],["$","path","19qd67",{"d":"M14 11a5 5 0 0 0-7.54-.54l-3 3a5 5 0 0 0 7.07 7.07l1.71-1.71"}],"$undefined"]}]]}],"\n",["$","ul",null,{"children":["\n",["$","li",null,{"children":"Python 3.10+"}],"\n",["$","li",null,{"children":"PyTorch 2.2+"}],"\n",["$","li",null,{"children":"CUDA 12.1+ (for GPU inference)"}],"\n"]}],"\n",["$","h2",null,{"className":"flex scroll-m-28 flex-row items-center gap-2","id":"install-transformers","children":[["$","a",null,{"data-card":"","href":"#install-transformers","className":"peer","children":"Install Transformers"}],["$","svg",null,{"ref":"$undefined","xmlns":"http://www.w3.org/2000/svg","width":24,"height":24,"viewBox":"0 0 24 24","fill":"none","stroke":"currentColor","strokeWidth":2,"strokeLinecap":"round","strokeLinejoin":"round","className":"lucide lucide-link size-3.5 shrink-0 text-fd-muted-foreground opacity-0 transition-opacity peer-hover:opacity-100","aria-hidden":true,"children":[["$","path","1cjeqo",{"d":"M10 13a5 5 0 0 0 7.54.54l3-3a5 5 0 0 0-7.07-7.07l-1.72 1.71"}],["$","path","19qd67",{"d":"M14 11a5 5 0 0 0-7.54-.54l-3 3a5 5 0 0 0 7.07 7.07l1.71-1.71"}],"$undefined"]}]]}],"\n",["$","$L27",null,{"className":"shiki shiki-themes github-light github-dark","style":{"--shiki-light":"#24292e","--shiki-dark":"#e1e4e8","--shiki-light-bg":"#fff","--shiki-dark-bg":"#24292e"},"tabIndex":"0","icon":"<svg viewBox=\"0 0 24 24\"><path d=\"m 4,4 a 1,1 0 0 0 -0.7070312,0.2929687 1,1 0 0 0 0,1.4140625 L 8.5859375,11 3.2929688,16.292969 a 1,1 0 0 0 0,1.414062 1,1 0 0 0 1.4140624,0 l 5.9999998,-6 a 1.0001,1.0001 0 0 0 0,-1.414062 L 4.7070312,4.2929687 A 1,1 0 0 0 4,4 Z m 8,14 a 1,1 0 0 0 -1,1 1,1 0 0 0 1,1 h 8 a 1,1 0 0 0 1,-1 1,1 0 0 0 -1,-1 z\" fill=\"currentColor\" /></svg>","children":["$","$L28",null,{"children":["$","code",null,{"children":["$","span",null,{"className":"line","children":[["$","span",null,{"style":{"--shiki-light":"#6F42C1","--shiki-dark":"#B392F0"},"children":"pip"}],["$","span",null,{"style":{"--shiki-light":"#032F62","--shiki-dark":"#9ECBFF"},"children":" install"}],["$","span",null,{"style":{"--shiki-light":"#032F62","--shiki-dark":"#9ECBFF"},"children":" torch"}],["$","span",null,{"style":{"--shiki-light":"#032F62","--shiki-dark":"#9ECBFF"},"children":" transformers"}],"$L29"]}]}]}]}],"\n","$L2a","\n","$L2b","\n","$L2c","\n","$L2d","\n","$L2e","\n","$L2f","\n","$L30","\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n","$L31","\n","$L32"]}]]}]
29:["$","span",null,{"style":{"--shiki-light":"#032F62","--shiki-dark":"#9ECBFF"},"children":" accelerate"}]
2a:["$","h2",null,{"className":"flex scroll-m-28 flex-row items-center gap-2","id":"install-vllm-production","children":[["$","a",null,{"data-card":"","href":"#install-vllm-production","className":"peer","children":"Install vLLM (Production)"}],["$","svg",null,{"ref":"$undefined","xmlns":"http://www.w3.org/2000/svg","width":24,"height":24,"viewBox":"0 0 24 24","fill":"none","stroke":"currentColor","strokeWidth":2,"strokeLinecap":"round","strokeLinejoin":"round","className":"lucide lucide-link size-3.5 shrink-0 text-fd-muted-foreground opacity-0 transition-opacity peer-hover:opacity-100","aria-hidden":true,"children":[["$","path","1cjeqo",{"d":"M10 13a5 5 0 0 0 7.54.54l3-3a5 5 0 0 0-7.07-7.07l-1.72 1.71"}],["$","path","19qd67",{"d":"M14 11a5 5 0 0 0-7.54-.54l-3 3a5 5 0 0 0 7.07 7.07l1.71-1.71"}],"$undefined"]}]]}]
2b:["$","$L27",null,{"className":"shiki shiki-themes github-light github-dark","style":{"--shiki-light":"#24292e","--shiki-dark":"#e1e4e8","--shiki-light-bg":"#fff","--shiki-dark-bg":"#24292e"},"tabIndex":"0","icon":"<svg viewBox=\"0 0 24 24\"><path d=\"m 4,4 a 1,1 0 0 0 -0.7070312,0.2929687 1,1 0 0 0 0,1.4140625 L 8.5859375,11 3.2929688,16.292969 a 1,1 0 0 0 0,1.414062 1,1 0 0 0 1.4140624,0 l 5.9999998,-6 a 1.0001,1.0001 0 0 0 0,-1.414062 L 4.7070312,4.2929687 A 1,1 0 0 0 4,4 Z m 8,14 a 1,1 0 0 0 -1,1 1,1 0 0 0 1,1 h 8 a 1,1 0 0 0 1,-1 1,1 0 0 0 -1,-1 z\" fill=\"currentColor\" /></svg>","children":["$","$L28",null,{"children":["$","code",null,{"children":["$","span",null,{"className":"line","children":[["$","span",null,{"style":{"--shiki-light":"#6F42C1","--shiki-dark":"#B392F0"},"children":"pip"}],["$","span",null,{"style":{"--shiki-light":"#032F62","--shiki-dark":"#9ECBFF"},"children":" install"}],["$","span",null,{"style":{"--shiki-light":"#032F62","--shiki-dark":"#9ECBFF"},"children":" vllm"}]]}]}]}]}]
2c:["$","h2",null,{"className":"flex scroll-m-28 flex-row items-center gap-2","id":"install-mlx-apple-silicon","children":[["$","a",null,{"data-card":"","href":"#install-mlx-apple-silicon","className":"peer","children":"Install MLX (Apple Silicon)"}],["$","svg",null,{"ref":"$undefined","xmlns":"http://www.w3.org/2000/svg","width":24,"height":24,"viewBox":"0 0 24 24","fill":"none","stroke":"currentColor","strokeWidth":2,"strokeLinecap":"round","strokeLinejoin":"round","className":"lucide lucide-link size-3.5 shrink-0 text-fd-muted-foreground opacity-0 transition-opacity peer-hover:opacity-100","aria-hidden":true,"children":[["$","path","1cjeqo",{"d":"M10 13a5 5 0 0 0 7.54.54l3-3a5 5 0 0 0-7.07-7.07l-1.72 1.71"}],["$","path","19qd67",{"d":"M14 11a5 5 0 0 0-7.54-.54l-3 3a5 5 0 0 0 7.07 7.07l1.71-1.71"}],"$undefined"]}]]}]
2d:["$","$L27",null,{"className":"shiki shiki-themes github-light github-dark","style":{"--shiki-light":"#24292e","--shiki-dark":"#e1e4e8","--shiki-light-bg":"#fff","--shiki-dark-bg":"#24292e"},"tabIndex":"0","icon":"<svg viewBox=\"0 0 24 24\"><path d=\"m 4,4 a 1,1 0 0 0 -0.7070312,0.2929687 1,1 0 0 0 0,1.4140625 L 8.5859375,11 3.2929688,16.292969 a 1,1 0 0 0 0,1.414062 1,1 0 0 0 1.4140624,0 l 5.9999998,-6 a 1.0001,1.0001 0 0 0 0,-1.414062 L 4.7070312,4.2929687 A 1,1 0 0 0 4,4 Z m 8,14 a 1,1 0 0 0 -1,1 1,1 0 0 0 1,1 h 8 a 1,1 0 0 0 1,-1 1,1 0 0 0 -1,-1 z\" fill=\"currentColor\" /></svg>","children":["$","$L28",null,{"children":["$","code",null,{"children":["$","span",null,{"className":"line","children":[["$","span",null,{"style":{"--shiki-light":"#6F42C1","--shiki-dark":"#B392F0"},"children":"pip"}],["$","span",null,{"style":{"--shiki-light":"#032F62","--shiki-dark":"#9ECBFF"},"children":" install"}],["$","span",null,{"style":{"--shiki-light":"#032F62","--shiki-dark":"#9ECBFF"},"children":" mlx"}],["$","span",null,{"style":{"--shiki-light":"#032F62","--shiki-dark":"#9ECBFF"},"children":" mlx-lm"}]]}]}]}]}]
2e:["$","h2",null,{"className":"flex scroll-m-28 flex-row items-center gap-2","id":"install-sglang","children":[["$","a",null,{"data-card":"","href":"#install-sglang","className":"peer","children":"Install SGLang"}],["$","svg",null,{"ref":"$undefined","xmlns":"http://www.w3.org/2000/svg","width":24,"height":24,"viewBox":"0 0 24 24","fill":"none","stroke":"currentColor","strokeWidth":2,"strokeLinecap":"round","strokeLinejoin":"round","className":"lucide lucide-link size-3.5 shrink-0 text-fd-muted-foreground opacity-0 transition-opacity peer-hover:opacity-100","aria-hidden":true,"children":[["$","path","1cjeqo",{"d":"M10 13a5 5 0 0 0 7.54.54l3-3a5 5 0 0 0-7.07-7.07l-1.72 1.71"}],["$","path","19qd67",{"d":"M14 11a5 5 0 0 0-7.54-.54l-3 3a5 5 0 0 0 7.07 7.07l1.71-1.71"}],"$undefined"]}]]}]
2f:["$","$L27",null,{"className":"shiki shiki-themes github-light github-dark","style":{"--shiki-light":"#24292e","--shiki-dark":"#e1e4e8","--shiki-light-bg":"#fff","--shiki-dark-bg":"#24292e"},"tabIndex":"0","icon":"<svg viewBox=\"0 0 24 24\"><path d=\"m 4,4 a 1,1 0 0 0 -0.7070312,0.2929687 1,1 0 0 0 0,1.4140625 L 8.5859375,11 3.2929688,16.292969 a 1,1 0 0 0 0,1.414062 1,1 0 0 0 1.4140624,0 l 5.9999998,-6 a 1.0001,1.0001 0 0 0 0,-1.414062 L 4.7070312,4.2929687 A 1,1 0 0 0 4,4 Z m 8,14 a 1,1 0 0 0 -1,1 1,1 0 0 0 1,1 h 8 a 1,1 0 0 0 1,-1 1,1 0 0 0 -1,-1 z\" fill=\"currentColor\" /></svg>","children":["$","$L28",null,{"children":["$","code",null,{"children":["$","span",null,{"className":"line","children":[["$","span",null,{"style":{"--shiki-light":"#6F42C1","--shiki-dark":"#B392F0"},"children":"pip"}],["$","span",null,{"style":{"--shiki-light":"#032F62","--shiki-dark":"#9ECBFF"},"children":" install"}],["$","span",null,{"style":{"--shiki-light":"#032F62","--shiki-dark":"#9ECBFF"},"children":" sglang[all]"}]]}]}]}]}]
30:["$","h2",null,{"className":"flex scroll-m-28 flex-row items-center gap-2","id":"gpu-memory-requirements","children":[["$","a",null,{"data-card":"","href":"#gpu-memory-requirements","className":"peer","children":"GPU Memory Requirements"}],["$","svg",null,{"ref":"$undefined","xmlns":"http://www.w3.org/2000/svg","width":24,"height":24,"viewBox":"0 0 24 24","fill":"none","stroke":"currentColor","strokeWidth":2,"strokeLinecap":"round","strokeLinejoin":"round","className":"lucide lucide-link size-3.5 shrink-0 text-fd-muted-foreground opacity-0 transition-opacity peer-hover:opacity-100","aria-hidden":true,"children":[["$","path","1cjeqo",{"d":"M10 13a5 5 0 0 0 7.54.54l3-3a5 5 0 0 0-7.07-7.07l-1.72 1.71"}],["$","path","19qd67",{"d":"M14 11a5 5 0 0 0-7.54-.54l-3 3a5 5 0 0 0 7.07 7.07l1.71-1.71"}],"$undefined"]}]]}]
31:["$","div",null,{"className":"relative overflow-auto prose-no-margin my-6","children":["$","table",null,{"children":[["$","thead",null,{"children":["$","tr",null,{"children":[["$","th",null,{"children":"Model"}],["$","th",null,{"children":"Minimum VRAM"}],["$","th",null,{"children":"Recommended"}]]}]}],["$","tbody",null,{"children":[["$","tr",null,{"children":[["$","td",null,{"children":"zen-nano"}],["$","td",null,{"children":"2GB"}],["$","td",null,{"children":"4GB"}]]}],["$","tr",null,{"children":[["$","td",null,{"children":"zen-coder-4b"}],["$","td",null,{"children":"8GB"}],["$","td",null,{"children":"16GB"}]]}],["$","tr",null,{"children":[["$","td",null,{"children":"zen-coder-flash"}],["$","td",null,{"children":"24GB"}],["$","td",null,{"children":"48GB"}]]}],["$","tr",null,{"children":[["$","td",null,{"children":"zen-max"}],["$","td",null,{"children":"160GB"}],["$","td",null,{"children":"320GB"}]]}]]}]]}]}]
32:["$","div",null,{"className":"flex gap-2 my-4 rounded-xl border bg-fd-card p-3 ps-1 text-sm text-fd-card-foreground shadow-md","style":{"--callout-color":"var(--color-fd-info, var(--color-fd-muted))"},"children":[["$","div",null,{"role":"none","className":"w-0.5 bg-(--callout-color)/50 rounded-sm"}],["$","svg",null,{"ref":"$undefined","xmlns":"http://www.w3.org/2000/svg","width":24,"height":24,"viewBox":"0 0 24 24","fill":"none","stroke":"currentColor","strokeWidth":2,"strokeLinecap":"round","strokeLinejoin":"round","className":"lucide lucide-info size-5 -me-0.5 fill-(--callout-color) text-fd-card","aria-hidden":"true","children":[["$","circle","1mglay",{"cx":"12","cy":"12","r":"10"}],["$","path","1dtifu",{"d":"M12 16v-4"}],["$","path","e9boi3",{"d":"M12 8h.01"}],"$undefined"]}],["$","div",null,{"className":"flex flex-col gap-2 min-w-0 flex-1","children":["$undefined",["$","div",null,{"className":"text-fd-muted-foreground prose-no-margin empty:hidden","children":["$","p",null,{"children":"zen-coder-flash uses MoE architecture with 31B total params but only 3B active, making it efficient for its capability level."}]}]]}]]}]
20:[["$","meta","0",{"charSet":"utf-8"}],["$","meta","1",{"name":"viewport","content":"width=device-width, initial-scale=1"}],["$","meta","2",{"name":"theme-color","media":"(prefers-color-scheme: dark)","content":"#0A0A0A"}],["$","meta","3",{"name":"theme-color","media":"(prefers-color-scheme: light)","content":"#fff"}]]
1e:null
22:[["$","title","0",{"children":"Installation | Zen LM"}],["$","meta","1",{"name":"description","content":"Install dependencies for using Zen models"}],["$","meta","2",{"property":"og:title","content":"Zen LM - Open Foundation Models"}],["$","meta","3",{"property":"og:description","content":"Zen AI model family by Hanzo AI. 14 frontier models from 4B to 1T+ parameters for code, reasoning, vision, and multimodal tasks."}],["$","meta","4",{"property":"og:url","content":"https://zenlm.org"}],["$","meta","5",{"property":"og:site_name","content":"Zen LM"}],["$","meta","6",{"property":"og:type","content":"website"}],["$","meta","7",{"name":"twitter:card","content":"summary_large_image"}],["$","meta","8",{"name":"twitter:site","content":"@zenlmorg"}],["$","meta","9",{"name":"twitter:creator","content":"@zenlmorg"}],["$","meta","10",{"name":"twitter:title","content":"Zen LM - Open Foundation Models"}],["$","meta","11",{"name":"twitter:description","content":"Zen AI model family by Hanzo AI. 14 frontier models from 4B to 1T+ parameters for code, reasoning, vision, and multimodal tasks."}]]
